WorldWideScience

Sample records for learning methods aimed

  1. Conversational Analysis as a Method for Research on Intercultural Learning: A Report on a Project with the Aim of "Learning by Undertaking Research"

    Directory of Open Access Journals (Sweden)

    Gabriele Berkenbusch

    2009-01-01

    Full Text Available Conversational analysis—situated between pragmatic linguistics and qualitative empirical research—is a complex method, which needs a lot of time and dedication. It is necessary to develop a so-called “analytical mentality”. The aim of the project presented in this paper was to develop the theoretical insights and the practical skills of a group of students for this kind of research. They worked together throughout the duration of the project, especially in the collec¬tion of empiric material: i.e. the recording of conversations between foreign and German stu¬dents, the transcription of the material, a group discussion on the data and finally its analysis. This articles aims at showing what students can learn by doing this kind of work, based on examples of the collected empirical material: (1 they will be introduced to the different levels and stages of the research process and have the chance to develop a methodical and methodological competence; (2 their general communicative competences and their special competences of the foreign language will increase, as well as (3 their knowledge of intercultural learning by working with authentic data of intercultural communication. So, for instance, stereotypes and how they have been constructed during the interaction may be analysed and precisely described on a micro-analytical level. URN: urn:nbn:de:0114-fqs0901335

  2. LCoMotion - Learning, Cognition and Motion; a multicomponent cluster randomized school-based intervention aimed at increasing learning and cognition - rationale, design and methods

    DEFF Research Database (Denmark)

    Bugge, Anna; Tarp, Jakob; Ostergaard, Lars

    2014-01-01

    BACKGROUND: The aim of the study; LCoMotion - Learning, Cognition and Motion was to develop, document, and evaluate a multi-component physical activity (PA) intervention in public schools in Denmark. The primary outcome was cognitive function. Secondary outcomes were academic skills, body composi...

  3. LCoMotion - Learning, Cognition and Motion; a multicomponent cluster randomized school-based intervention aimed at increasing learning and cognition - rationale, design and methods.

    Science.gov (United States)

    Bugge, Anna; Tarp, Jakob; Østergaard, Lars; Domazet, Sidsel Louise; Andersen, Lars Bo; Froberg, Karsten

    2014-09-18

    The aim of the study; LCoMotion - Learning, Cognition and Motion was to develop, document, and evaluate a multi-component physical activity (PA) intervention in public schools in Denmark. The primary outcome was cognitive function. Secondary outcomes were academic skills, body composition, aerobic fitness and PA. The primary aim of the present paper was to describe the rationale, design and methods of the LCoMotion study. LCoMotion was designed as a cluster-randomized controlled study. Fourteen schools from all five regions in Denmark participated. All students from 6th and 7th grades were invited to participate (n = 869) and consent was obtained for 87% (n = 759). Baseline measurements were obtained in November/December 2013 and follow-up measurements in May/June 2014. The intervention lasted five months and consisted of a "package" of three main components: PA during academic lessons, PA during recess and PA homework. Furthermore a cycling campaign was conducted during the intervention period. Intervention schools should endeavor to ensure that students were physically active for at least 60 min every school day. Cognitive function was measured by a modified Eriksen flanker task and academic skills by a custom made mathematics test. PA was objectively measured by accelerometers (ActiGraph, GT3X and GT3X+) and aerobic fitness assessed by an intermittent shuttle-run test (the Andersen intermittent running test). Furthermore, compliance with the intervention was assessed by short message service (SMS)-tracking and questionnaires were delivered to students, parents and teachers. LCoMotion has ability to provide new insights on the effectiveness of a multicomponent intervention on cognitive function and academic skills in 6th and 7th grade students. Clinicaltrials.gov: NCT02012881 (10/10/2013).

  4. An Experiential-Based Learning Method Aiming to Improve Spatial Awareness Utilizing GPS, Geocaching, and Geo-Selfies

    Science.gov (United States)

    Flynn, K. Colton; Popp, Jennie

    2016-01-01

    Many educators have suggested that spatial awareness is vital in the foundation of geography curricula, as well as the ability to utilize geospatial technologies (National Research Council 2006; Kerski 2008; Lee and Bednarz 2009; Favier and Van der Schee 2014). The purpose of this research was to identify a low-cost and effective method to improve…

  5. Aims and methods of nuclear materials management

    International Nuclear Information System (INIS)

    Leven, D.; Schier, H.

    1979-05-01

    Whilst international safeguarding of fissile materials against abuse has been the subject of extensive debate, little public attention has so far been devoted to the internal security of these materials. All countries using nuclear energy for peaceful purposes have laid down appropriate regulations. In the Federal Republic of Germany safeguards are required, for instance, by the Atomic Energy Act, and are therefore a prerequisite for licensing. The aims and methods of national nuclear materials management are contrasted with viewpoints on international safeguards

  6. Aims and methods of education: A recapitulation

    Directory of Open Access Journals (Sweden)

    Pantić Nataša

    2007-01-01

    Full Text Available This paper gives an overview of principal distinction between the aims of the so-called "traditional" and "progressive" education and respective pedagogies associated with each. The term "traditional" education is used to denote the kind of education that prepares people for their role in society as it is, while the term "progressive" is used for education that aspires to equip mankind with capacity to shape the change of society. The paper raises some critical questions about the role of pedagogy in achieving the aims of the progressive model, arguing that the employment of "progressive" methods does not necessarily guarantee the achievement of the commonly professed purposes of progressive education. This is illustrated in the paper by the results of a study in English schools showing how despite the claim of progressive methods, teachers tend to retain traditional attitudes and on the other hand, how even traditional teaching methods can serve the progressive purpose. This is not to advocate for the traditional pedagogy, but to suggest that it might be something other than pedagogy that makes a critical difference in educating liberal-minded citizens of the future. In this sense the paper explores the role of other factors that make a difference towards progressive education, such as democratization of human relations in school ethos and respect for children's freedom.

  7. The AI&M procedure for learning from incomplete data

    DEFF Research Database (Denmark)

    Jaeger, Manfred

    2006-01-01

    We investigate methods for parameter learning from incomplete data that is not missing at random. Likelihood-based methods then require the optimization of a profile likelihood that takes all possible missingness mechanisms into account. Optimizing this profile likelihood poses two main difficult......We investigate methods for parameter learning from incomplete data that is not missing at random. Likelihood-based methods then require the optimization of a profile likelihood that takes all possible missingness mechanisms into account. Optimizing this profile likelihood poses two main...... by operations in the space of data completions, rather than directly in the parameter space of the profile likelihood. We apply the AI\\&M method to learning parameters for Bayesian networks. The method is compared against conservative inference, which takes into account each possible data completion......, and against EM. The results indicate that likelihood-based inference is still feasible in the case of unknown missingness mechanisms, and that conservative inference is unnecessarily weak. On the other hand, our results also provide evidence that the EM algorithm is still quite effective when the data...

  8. Learning object for teacher training aimed to develop communication skills

    Directory of Open Access Journals (Sweden)

    Norma Esmeralda RODRÍGUEZ RAMÍREZ

    2014-06-01

    Full Text Available This article presents the results and reflections obtained across a research aimed to analyze the quality criteria of an opened learning object oriented to develop communication skills in order to be able to report and validate it according to its content, pedagogic structure, technological structure, graphical and textual language and usability to teacher training, in order to base it theoretically, pedagogically and technologically. The research question was: Which are the quality criteria that a learning object aimed to develop communication skills must cover? Under a quantitative approach, there were electronic questionnaires applied to: 34 Technological University teachers, eight experts about of communicative competence, teaching, technology and graphic design. The results indicated that some of the quality criteria of learning object are: the effective managing of the learning content, the balanced composition of his pedagogic structure, the technological structure efficiency and the proper managing of graphical and textual language.

  9. AN ADAPTIVE ACO-DRIVEN SCHEME FOR LEARNING AIM ORIENTED PERSONALIZED E-LEARNING

    Directory of Open Access Journals (Sweden)

    Sushma Hans

    2014-10-01

    Full Text Available The e-learning paradigm is now a well-established vehicle of modern education. It caters to a wide spectrum of students with diverse backgrounds who enroll with their own learning aims. A core challenge under this scenario is to generate personalized learning paths so that each student can achieve her learning aim most effectively. Prior works used static attributes such as prior knowledge level, learning ability, browsing preferences, learning style etc. to generate personalized learning paths. In this paper, we take an entirely new route by taking into account the continuous improvement of a learner in the light of her own learning aim, to redefine her learning path at each level of the course. We introduce the concept of personalized examination system that systematically evaluates the dynamic learning ability of every student according to her pre-set goals. The proposed intelligent e-learning system uses Ant Colony Optimization to iteratively optimize the forward learning paths. Experimental results reveal that the system is able to tap a student’s improved learning ability to choose more difficult paths that contribute highly towards her own aims. We demonstrate that the overall learning success of weaker students doubles as compared to statically generated paths while there is considerable improvement of 50% in the learning success for average students as well. This clearly indicates that our approach gives realistic benefits to initially weak students who gradually evolve as the course progresses.

  10. Linking aims, paradigm and method in nursing research.

    Science.gov (United States)

    Houghton, Catherine; Hunter, Andrew; Meskell, Pauline

    2012-01-01

    To explore the use of paradigms as ontological and philosophical guides for conducting PhD research. A paradigm can help to bridge the aims of a study and the methods to achieve them. However, choosing a paradigm can be challenging for doctoral researchers: there can be ambiguity about which paradigm is suitable for a particular research question and there is a lack of guidance on how to shape the research process for a chosen paradigm. The authors discuss three paradigms used in PhD nursing research: post-positivism, interpretivism and pragmatism. They compare each paradigm in relation to its ontology, epistemology and methodology, and present three examples of PhD nursing research studies to illustrate how research can be conducted using these paradigms in the context of the research aims and methods. The commonalities and differences between the paradigms and their uses are highlighted. Creativity and flexibility are important when deciding on a paradigm. However, consistency and transparency are also needed to ensure the quality and rigour necessary for conducting nursing research. When choosing a suitable paradigm, the researcher should ensure that the ontology, epistemology and methodology of the paradigm are manifest in the methods and research strategies employed.

  11. Qualitative methods in workplace learning

    OpenAIRE

    Fabritius, Hannele

    2015-01-01

    Methods of learning in the workplace will be introduced. The methods are connect to competence development and to the process of conducting development discussions in a dialogical way. The tools developed and applied are a fourfold table, a cycle of work identity, a plan of personal development targets, a learning meeting and a learning map. The methods introduced will aim to better learning at work.

  12. Internet Use with Learning Aim: Views of German Language Pre-Service Teachers

    Directory of Open Access Journals (Sweden)

    Mukadder Seyhan Yücel

    2011-10-01

    Full Text Available The aim of this study is to indicate the views of teacher candidates of German Language Department at Education Faculty, Trakya University about the use of internet with the aim of learning. This study has designed as phenomenology which is one of the qualitative research methods. The study data were obtained via semi-constructed interview technique and the content analysis technique was used in the data analysis. In the research, the findings gathered from the interviews with the teacher candidates are presented in themes, and then interpreted. Considering findings of the study, it has been seen that Internet should be used for learning-teaching purpose. Teacher candidates of German Language support the fact that Internet has a crucial role in education, and particularly it is useful and essential as Internet provides lots of opportunities for German Language Teaching such as authentic study samples, rich materials and exercises on skills, contemporary videos reflecting German culture or film sections. Internet is also a good material which provides accessing various information and also realizing and sharing many goals. If the information is gathered via audio and visual ways, it will be retentive. Thus, German Language teacher candidates can have opportunity to study on the foreign language and its culture through Internet. Furthermore, they have met the contemporary approaches like realizing self-directed learning individually. That’s why, the views of German Language pre-service teacher about the use of Internet with the aim of learning are very important.

  13. Internet Use with Learning Aim: Views of German Language Pre-Service Teachers

    Directory of Open Access Journals (Sweden)

    Mukadder Seyhan Yücel

    2011-04-01

    Full Text Available The aim of this study is to indicate the views of teacher candidates of German Language Department at Education Faculty, Trakya University about the use of internet with the aim of learning. This study has designed as phenomenology which is one of the qualitative research methods. The study data were obtained via semi-constructed interview technique and the content analysis technique was used in the data analysis. In the research, the findings gathered from the interviews with the teacher candidates are presented in themes, and then interpreted. Considering findings of the study, it has been seen that Internet should be used for learning-teaching purpose. Teacher candidates of German Language support the fact that Internet has a crucial role in education, and particularly it is useful and essential as Internet provides lots of opportunities for German Language Teaching such as authentic study samples, rich materials and exercises on skills, contemporary videos reflecting German culture or Şlm sections. Internet is also a good material which provides accessing various information and also realizing and sharing many goals. If the information is gathered via audio and visual ways, it will be retentive. Thus, German Language teacher candidates can have opportunity to study on the foreign language and its culture through Internet. Furthermore, they have met the contemporary approaches like realizing self-directed learning individually. That’s why, the views of German Language pre-service teacher about the use of Internet with the aim of learning are very important

  14. Qualitative approaches to use of the RE-AIM framework: rationale and methods.

    Science.gov (United States)

    Holtrop, Jodi Summers; Rabin, Borsika A; Glasgow, Russell E

    2018-03-13

    There have been over 430 publications using the RE-AIM model for planning and evaluation of health programs and policies, as well as numerous applications of the model in grant proposals and national programs. Full use of the model includes use of qualitative methods to understand why and how results were obtained on different RE-AIM dimensions, however, recent reviews have revealed that qualitative methods have been used infrequently. Having quantitative and qualitative methods and results iteratively inform each other should enhance understanding and lessons learned. Because there have been few published examples of qualitative approaches and methods using RE-AIM for planning or assessment and no guidance on how qualitative approaches can inform these processes, we provide guidance on qualitative methods to address the RE-AIM model and its various dimensions. The intended audience is researchers interested in applying RE-AIM or similar implementation models, but the methods discussed should also be relevant to those in community or clinical settings. We present directions for, examples of, and guidance on how qualitative methods can be used to address each of the five RE-AIM dimensions. Formative qualitative methods can be helpful in planning interventions and designing for dissemination. Summative qualitative methods are useful when used in an iterative, mixed methods approach for understanding how and why different patterns of results occur. In summary, qualitative and mixed methods approaches to RE-AIM help understand complex situations and results, why and how outcomes were obtained, and contextual factors not easily assessed using quantitative measures.

  15. Armed To Learn: Aiming At California K 12 School Gun Policy

    Science.gov (United States)

    2016-03-01

    AIMING AT CALIFORNIA K-12 SCHOOL GUN POLICY by Catherine Wilson Jones March 2016 Thesis Co-Advisors: Kathleen Kiernan John Rollins...Master’s thesis 4. TITLE AND SUBTITLE ARMED TO LEARN: AIMING AT CALIFORNIA K-12 SCHOOL GUN POLICY 5. FUNDING NUMBERS 6. AUTHOR(S) Catherine...gap in viewpoints between gun control advocates who want tighter gun control and constitutionalists who believe as strongly in the Second Amendment

  16. Listen, live and learn: A review of the application process, aiming to ...

    African Journals Online (AJOL)

    The Listen, Live and Learn (LLL) initiative at Stellenbosch University (SU) is a senior student housing model with the aim of providing an experiential opportunity for students to make contact with 'the other'. It is posited on the social contact theory assumption that if people of different genders, races, ethnicities, and/or ...

  17. Dental Faculty Members' Pedagogic Beliefs and Curriculum Aims in Problem-Based Learning: An Exploratory Study.

    Science.gov (United States)

    von Bergmann, HsingChi; Walker, Judith; Dalrymple, Kirsten R; Shuler, Charles F

    2017-08-01

    The aims of this exploratory study were to explore dental faculty members' views and beliefs regarding knowledge, the dental profession, and teaching and learning and to determine how these views related to their problem-based learning (PBL) instructional practices. Prior to a PBL in dental education conference held in 2011, all attendees were invited to complete a survey focused on their pedagogical beliefs and practices in PBL. Out of a possible 55 participants, 28 responded. Additionally, during the conference, a forum was held in which preliminary survey findings were shared and participants contributed to focus group data collection. The forum results served to validate and bring deeper understanding to the survey findings. The conference participants who joined the forum (N=32) likely included some or many of the anonymous respondents to the survey, along with additional participants interested in dental educators' beliefs. The findings of the survey and follow-up forum indicated a disconnect between dental educators' reported views of knowledge and their pedagogical practices in a PBL environment. The results suggested that the degree of participants' tolerance of uncertainty in knowledge and the discrepancy between their epistemological and ontological beliefs about PBL pedagogy influenced their pedagogical choices. These findings support the idea that learner-centered, inquiry-based pedagogical approaches such as PBL may create dissonance between beliefs about knowledge and pedagogical practice that require the building of a shared understanding of and commitment to curricular goals prior to implementation to ensure success. The methods used in this study can be useful tools for faculty development in PBL programs in dental education.

  18. Characterizing the Learning Effect in Response to Biofeedback Aimed at Reducing Tibial Acceleration during Running

    Directory of Open Access Journals (Sweden)

    Linda M. A. van Gelder

    2018-02-01

    Full Text Available Increased tibial acceleration has been found to be an important risk factor for tibial stress fractures. Interventions aimed at reducing this variable which found a beneficial effect include the use of biofeedback in gait retraining. However, no studies have focused on the time participants take to modify tibial acceleration, therefore we aimed to find the start of a learning plateau in this study. Six participants ran on a treadmill while multisensory feedback was given. A single-subject analysis was used to characterise the learning effects. All participants changed peak tibial acceleration within the first step of running in the feedback condition. Two participants further reduced tibial acceleration to reach a plateau within 120 steps. In four of the six participants a strong effect of the feedback was still present after a week. Further research is needed to optimise the use of biofeedback in reducing the prevalence of tibial stress fractures.

  19. The method of quick satellite aiming with 3-Steps on the mobile satellite station

    Directory of Open Access Journals (Sweden)

    Sheng Liang

    2017-02-01

    Full Text Available The study analyses and concludes the technology of the satellite aiming during real-time broadcast of mobile video.We conclude a method of quick satellite aiming with 3-steps according to practical exercises and users' requirement to meet situation of facts and standardized operation,which can improve efficiency and quality of service.

  20. Cooperative Learning as a Democratic Learning Method

    Science.gov (United States)

    Erbil, Deniz Gökçe; Kocabas, Ayfer

    2018-01-01

    In this study, the effects of applying the cooperative learning method on the students' attitude toward democracy in an elementary 3rd-grade life studies course was examined. Over the course of 8 weeks, the cooperative learning method was applied with an experimental group, and traditional methods of teaching life studies in 2009, which was still…

  1. Machine learning methods for planning

    CERN Document Server

    Minton, Steven

    1993-01-01

    Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credi

  2. Strategies for Effective Faculty Involvement in Online Activities Aimed at Promoting Critical Thinking and Deep Learning

    Science.gov (United States)

    Abdul Razzak, Nina

    2016-01-01

    Highly-traditional education systems that mainly offer what is known as "direct instruction" usually result in graduates with a surface approach to learning rather than a deep one. What is meant by deep-learning is learning that involves critical analysis, the linking of ideas and concepts, creative problem solving, and application…

  3. Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies

    Science.gov (United States)

    Tjalla, Awaluddin; Sofiah, Evi

    2015-01-01

    This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…

  4. Active Learning Methods

    Science.gov (United States)

    Zayapragassarazan, Z.; Kumar, Santosh

    2012-01-01

    Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…

  5. Learning Method, Facilities And Infrastructure, And Learning Resources In Basic Networking For Vocational School

    OpenAIRE

    Pamungkas, Bian Dwi

    2017-01-01

    This study aims to examine the contribution of learning methods on learning output, the contribution of facilities and infrastructure on output learning, the contribution of learning resources on learning output, and the contribution of learning methods, the facilities and infrastructure, and learning resources on learning output. The research design is descriptive causative, using a goal-oriented assessment approach in which the assessment focuses on assessing the achievement of a goal. The ...

  6. Evaluation of a faculty development program aimed at increasing residents' active learning in lectures.

    Science.gov (United States)

    Desselle, Bonnie C; English, Robin; Hescock, George; Hauser, Andrea; Roy, Melissa; Yang, Tong; Chauvin, Sheila W

    2012-12-01

    Active engagement in the learning process is important to enhance learners' knowledge acquisition and retention and the development of their thinking skills. This study evaluated whether a 1-hour faculty development workshop increased the use of active teaching strategies and enhanced residents' active learning and thinking. Faculty teaching in a pediatrics residency participated in a 1-hour workshop (intervention) approximately 1 month before a scheduled lecture. Participants' responses to a preworkshop/postworkshop questionnaire targeted self-efficacy (confidence) for facilitating active learning and thinking and providing feedback about workshop quality. Trained observers assessed each lecture (3-month baseline phase and 3-month intervention phase) using an 8-item scale for use of active learning strategies and a 7-item scale for residents' engagement in active learning. Observers also assessed lecturer-resident interactions and the extent to which residents were asked to justify their answers. Responses to the workshop questionnaire (n  =  32/34; 94%) demonstrated effectiveness and increased confidence. Faculty in the intervention phase demonstrated increased use of interactive teaching strategies for 6 items, with 5 reaching statistical significance (P ≤ .01). Residents' active learning behaviors in lectures were higher in the intervention arm for all 7 items, with 5 reaching statistical significance. Faculty in the intervention group demonstrated increased use of higher-order questioning (P  =  .02) and solicited justifications for answers (P  =  .01). A 1-hour faculty development program increased faculty use of active learning strategies and residents' engagement in active learning during resident core curriculum lectures.

  7. Geometrical methods in learning theory

    International Nuclear Information System (INIS)

    Burdet, G.; Combe, Ph.; Nencka, H.

    2001-01-01

    The methods of information theory provide natural approaches to learning algorithms in the case of stochastic formal neural networks. Most of the classical techniques are based on some extremization principle. A geometrical interpretation of the associated algorithms provides a powerful tool for understanding the learning process and its stability and offers a framework for discussing possible new learning rules. An illustration is given using sequential and parallel learning in the Boltzmann machine

  8. Computational study of formamide-water complexes using the SAPT and AIM methods

    International Nuclear Information System (INIS)

    Parreira, Renato L.T.; Valdes, Haydee; Galembeck, Sergio E.

    2006-01-01

    In this work, the complexes formed between formamide and water were studied by means of the SAPT and AIM methods. Complexation leads to significant alterations in the geometries and electronic structure of formamide. Intermolecular interactions in the complexes are intense, especially in the cases where the solvent interacts with the carbonyl and amide groups simultaneously. In the transition states, the interaction between the water molecule and the lone pair on the amide nitrogen is also important. In all the complexes studied herein, the electrostatic interactions between formamide and water are the main attractive force, and their contribution may be five times as large as the corresponding contribution from dispersion, and twice as large as the contribution from induction. However, an increase in the resonance of planar formamide with the successive addition of water molecules may suggest that the hydrogen bonds taking place between formamide and water have some covalent character

  9. General and Specific Culture Learning in EFL Textbooks Aimed at Adult Learners in Spain

    Directory of Open Access Journals (Sweden)

    Rodríguez Antonio R. Raigón

    2015-03-01

    Full Text Available Since language teaching in modern-day society is closely linked to cultural instruction, this study employs the model of a cultural learning analysis based on the earlier work of Paige and Lee. Using this model, the authors analysed the cultural content of six B1 and B2-level textbooks for teaching English to adults in Spain, and carried out a comparative study of the results, contrasting the two levels. Findings show that the subjective aspects of culture receive less coverage in textbooks, despite being fundamental to an understanding of the values of a society. Regarding the comparison between B1 and B2 levels, the data indicate that the number of big “C” Culture occurrences is similar for both levels, although there are differences in other cultural aspects. So, for example, culture in general is dealt with more at the B1 level, whereas small “c” culture is dealt with more at the B2 level.

  10. Beyond existence and aiming outside the laboratory: estimating frequency-dependent and pay-off-biased social learning strategies.

    Science.gov (United States)

    McElreath, Richard; Bell, Adrian V; Efferson, Charles; Lubell, Mark; Richerson, Peter J; Waring, Timothy

    2008-11-12

    The existence of social learning has been confirmed in diverse taxa, from apes to guppies. In order to advance our understanding of the consequences of social transmission and evolution of behaviour, however, we require statistical tools that can distinguish among diverse social learning strategies. In this paper, we advance two main ideas. First, social learning is diverse, in the sense that individuals can take advantage of different kinds of information and combine them in different ways. Examining learning strategies for different information conditions illuminates the more detailed design of social learning. We construct and analyse an evolutionary model of diverse social learning heuristics, in order to generate predictions and illustrate the impact of design differences on an organism's fitness. Second, in order to eventually escape the laboratory and apply social learning models to natural behaviour, we require statistical methods that do not depend upon tight experimental control. Therefore, we examine strategic social learning in an experimental setting in which the social information itself is endogenous to the experimental group, as it is in natural settings. We develop statistical models for distinguishing among different strategic uses of social information. The experimental data strongly suggest that most participants employ a hierarchical strategy that uses both average observed pay-offs of options as well as frequency information, the same model predicted by our evolutionary analysis to dominate a wide range of conditions.

  11. Students' Ideas on Cooperative Learning Method

    Science.gov (United States)

    Yoruk, Abdulkadir

    2016-01-01

    Aim of this study is to investigate students' ideas on cooperative learning method. For that purpose students who are studying at elementary science education program are distributed into two groups through an experimental design. Factors threaten the internal validity are either eliminated or reduced to minimum value. Data analysis is done…

  12. The multinational birth cohort of EuroPrevall: background, aims and methods

    NARCIS (Netherlands)

    Keil, T.; McBride, D.; Grimshaw, K.; Niggemann, B.; Xepapadaki, P.; Zannikos, K.; Sigurdardottir, S. T.; Clausen, M.; Reche, M.; Pascual, C.; Stanczyk, A. P.; Kowalski, M. L.; Dubakiene, R.; Drasutiene, G.; Roberts, G.; Schoemaker, A.-F. A.; Sprikkelman, A. B.; Fiocchi, A.; Martelli, A.; Dufour, S.; Hourihane, J.; Kulig, M.; Wjst, M.; Yazdanbakhsh, M.; Szépfalusi, Z.; van Ree, R.; Willich, S. N.; Wahn, U.; Mills, E. N. C.; Beyer, K.

    2010-01-01

    P>Background/aim: The true prevalence and risk factors of food allergies in children are not known because estimates were based predominantly on subjective assessments and skin or serum tests of allergic sensitization to food. The diagnostic gold standard, a double-blind placebo-controlled food

  13. BIBLIOGRAPHIC STUDY IN RISK MANAGEMENT AIMED TO IDENTIFY MORE REFERENCED TOOLS, METHODS AND RELATIONSHIPS

    Directory of Open Access Journals (Sweden)

    Alamir Costa Louro

    2015-06-01

    Full Text Available The objective of this paper is to identify and discuss trends in tools and methods used in project risk management and its relationship to other matters, using current scientific articles. The focus isn´t in understanding how they work in technical terms, but think about the possibilities of deepening in academic studies, including making several suggestions for future research. Adjacent to the article there is a discussion about an alleged "one best way" imperative normativity approach. It was answered the following research questions: what subjects and theories are related to project risk management tools and methods? The first contribution is related to the importance of the academic Chris Chapman as an author who has more published and also more referenced in the survey. There are several contributions on various subjects such as: the perception of the existence of many conceptual papers; papers about construction industry, problematization of contracts according to agency theory, IT and ERPs issues. Other contributions came from the bibliometric method that brings lot of consolidated information about terms, topics, authors, references, periods and, of course, methods and tools about Project Risk Management.

  14. A Method for User Centering Systematic Product Development Aimed at Industrial Design Students

    Science.gov (United States)

    Coelho, Denis A.

    2010-01-01

    Instead of limiting the introduction and stimulus for new concept creation to lists of specifications, industrial design students seem to prefer to be encouraged by ideas in context. A new method that specifically tackles human activity to foster the creation of user centered concepts of new products was developed and is presented in this article.…

  15. The LIFE Project “Monitoring of insects with public participation” (MIPP: aims, methods and conclusions

    Directory of Open Access Journals (Sweden)

    Giuseppe Maria Carpaneto

    2017-08-01

    Full Text Available The Life Project “Monitoring of insects with public participation” (LIFE11 NAT/IT/000252 had as the main objective to develop and test methods for the monitoring of five beetle species listed in the Annexes of the Habitats Directive (92/43/EEC: Osmoderma eremita (hermit beetle, Scarabaeidae, Lucanus cervus (European stag beetle, Lucanidae, Cerambyx cerdo (great capricorn beetle, Cerambycidae, Rosalia alpina (rosalia longicorn, Cerambycidae and Morimus asper/funereus (morimus longicorn, Cerambycidae. The data gathered represent an important contribution to the monitoring of these target species in Italy. The methods developed for monitoring of the target species are intended for use by the local management authorities and staff of protected areas. These developed methods are the result of extensive fieldwork and ensure scientific validity, ease of execution and limited labour costs. The detailed description of methods and the results for each species are published in separate articles of this special issue of Nature Conservation. A second objective of the project was to gather faunistic data with a Citizen Science approach, using the web and a mobile application software (app specifically built for mobile devices. The validation of the records collected by the citizens was carried out by experts, based on photographs, which were obligatory for all records. Dissemination activities represented the principal way to contact and engage citizens for the data collection and also offered the possibility of providing information on topics such as Natura 2000, the Habitats Directive, the role of monitoring in nature conservation, the importance of forest ecosystems and the ecological role of the saproxylic insects. An innovative method tested during the project was the training of a dog for searching and monitoring the elusive hermit beetle; the trained dog also added a “curiosity” factor to attract public attention towards this rare insect and

  16. Reflexive Learning through Visual Methods

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2014-01-01

    What. This chapter concerns how visual methods and visual materials can support visually oriented, collaborative, and creative learning processes in education. The focus is on facilitation (guiding, teaching) with visual methods in learning processes that are designerly or involve design. Visual...... methods are exemplified through two university classroom cases about collaborative idea generation processes. The visual methods and materials in the cases are photo elicitation using photo cards, and modeling with LEGO Serious Play sets. Why. The goal is to encourage the reader, whether student...... or professional, to facilitate with visual methods in a critical, reflective, and experimental way. The chapter offers recommendations for facilitating with visual methods to support playful, emergent designerly processes. The chapter also has a critical, situated perspective. Where. This chapter offers case...

  17. Validation of the analytical method for sodium dichloroisocyanurate aimed at drinking water disinfection

    International Nuclear Information System (INIS)

    Martinez Alvarez, Luis Octavio; Alejo Cisneros, Pedro; Garcia Pereira, Reynaldo; Campos Valdez, Doraily

    2014-01-01

    Cuba has developed the first effervescent 3.5 mg sodium dichloroisocyanurate tablets as a non-therapeutic active principle. This ingredient releases certain amount of chlorine when dissolved into a litre of water and it can cause adequate disinfection of drinking water ready to be taken after 30 min. Developing and validating an analytical iodometric method applicable to the quality control of effervescent 3.5 mg sodium dichloroisocyanurate tablets

  18. The Evaluation Method of the Lightning Strike on Transmission Lines Aiming at Power Grid Reliability

    Science.gov (United States)

    Wen, Jianfeng; Wu, Jianwei; Huang, Liandong; Geng, Yinan; Yu, zhanqing

    2018-01-01

    Lightning protection of power system focuses on reducing the flashover rate, only distinguishing by the voltage level, without considering the functional differences between the transmission lines, and being lack of analysis the effect on the reliability of power grid. This will lead lightning protection design of general transmission lines is surplus but insufficient for key lines. In order to solve this problem, the analysis method of lightning striking on transmission lines for power grid reliability is given. Full wave process theory is used to analyze the lightning back striking; the leader propagation model is used to describe the process of shielding failure of transmission lines. The index of power grid reliability is introduced and the effect of transmission line fault on the reliability of power system is discussed in detail.

  19. Investigations on pelagic food webs in mountain lakes - aims and methods

    Directory of Open Access Journals (Sweden)

    Jirí NEDOMA

    1999-08-01

    Full Text Available A methodical approach for the assessment of pelagic biomass and the main carbon fluxes in remote and hardly accessible mountain lakes was elaborated and tested. Number and biomass of bacteria (BAC, autotrophic picoplankton (APP, heterotrophic nanoflagellates (HNF, ciliates (CIL, phytoplankton (PHY, zooplankton smaller than 40 μm (ZOOS and zooplankton larger than 40 μm (ZOOL were investigated regularly during two ice-free periods in 13 European mountain lakes (1st level approach – fixed samples elaborated in specialized laboratories. Carbon fluxes measured in 9 lakes included: primary production, exudation by PHY and BAC uptake of exudates, BAC production, elimination of BAC. These processes were measured in the field by specialized teams (2nd level approach. The ranges of values found in mountain lakes were evaluated and possible methodical and interpretative errors discussed. BAC were a significant component of pelagic biomass. The intercomparison between different partners showed differences in bacterial counts lower than 10%, whereas the mean cell volumes measured fluctuated by more than 40%. APP was never found in a significant quantity, except in one lake. HNF and CIL, though regularly found, were usually scarce and only occasionally significant in terms of biomass. The main components of pelagic biomass were BAC, PHY and ZOOL+ZOOS, except for acidified lakes, where zooplankton was very low. In oligotrophic mountain lakes, the percentage of extracellular production in the total primary production was considerable. Bacterial abundance and production often reached values quite comparable with the situation found in lowland mesotrophic lakes during winter.

  20. Control methods for cattle feedstuffs aimed at prevention of Bovine spongiform encephalopathy (BSE

    Directory of Open Access Journals (Sweden)

    Nešić Ksenija

    2006-01-01

    Full Text Available In the course of the last decades of the twentieth century, more than 30 new diseases were determined for the first time in history. Bovine spongiform encephalopathy (BSE, or "mad cow disease" is one of them. The disease implies the subacute neurodegenerative transmission of spongiform encephalopathy and it was diagnosed and described for the first time in Great Britain in 1986. A theory has been established that BSE is spread through feedstuffs, more precisely, meat-bone flour which contains infective proteins of ruminants, and legislature has been passed throughout the world with the objective of preventing the entry of meat-bone flour into the food chain. The complete ban of the use of meat-bone flour for all farm animals (with the exception of fish flour for non-ruminants and an adequate thermal treatment in the production of meat-bone flour (133ºC, 3 bar, 20 min are the elements on which the European Union (EU legislature is based. The regulations in our country include a ban on the use of meat-bone flour in cattle feedstuffs and a ban on imports of beef proteins. The implementation of this legislature throughout the world requires the corresponding analytical means. At the present time, there are several available possibilities: optic microscopy, PCR, immunoprobes, spectroscopic methods, and several others which are still being examined for use for this purpose. All the analytical methods are being applied with the objective of controlling the implementation of the current regulations, but also in order to discover possible cross contamination that could take place in factories of animal feedstuffs, during transportation, storage, or on farms, in particular when there are no separate lines for feedstuffs that contains meat-bone flour and others in which even its traces are banned. In order to secure the successful control and prevention of bovine spongiform encephalopathy in our country, as well as to secure the unhindered continuation of

  1. Do students’ styles of learning affect how they adapt to learning methods and to the learning environment?

    OpenAIRE

    Topal, Kenan; Sarıkaya, Özlem; Basturk, Ramazan; Buke, Akile

    2015-01-01

    Objectives: The process of development and evaluation of undergraduate medical education programs should include analysis of learners’ characteristics, needs, and perceptions about learning methods. This study aims to evaluate medical students’ perceptions about problem-based learning methods and to compare these results with their individual learning styles.Materials and Methods: The survey was conducted at Marmara University Medical School where problem-based learning was implemented in the...

  2. The Tobacco Deposition and Trial Testimony Archive (DATTA) project: origins, aims, and methods.

    Science.gov (United States)

    Davis, Ronald M; Douglas, Clifford E; Beasley, John K

    2006-12-01

    Research on previously secret tobacco industry documents has grown substantially during the past decade, since these documents first became available as the result of private and governmental litigation and investigations by the US Congress and the US Food and Drug Administration. Complementary research on tobacco litigation testimony is now being conducted through the Tobacco Deposition and Trial Testimony Archive (DATTA) project. We obtained transcripts of depositions and trial testimony, deposition and trial exhibits, expert reports, and other litigation documents from law firms, court reporter firms, individual lawyers and witnesses, tobacco company websites, and other sources. As of 3 March 2006, the publicly available collection of DATTA (http://tobaccodocuments.org/datta) contained 4850 transcripts of depositions and trial testimony, including a total of about 820,000 transcript pages. Transcripts covered testimony from 1957 to 2005 (85% were for testimony from 1990 to 2005) given by more than 1500 witnesses in a total of 232 lawsuits. Twelve research teams were established to study the transcripts, with each team covering a particular topic (for example, the health consequences of tobacco use, addiction and pharmacology, tobacco advertising and promotion, tobacco-product design and manufacture, economic impact of tobacco use, youth initiation of tobacco use, and public understanding of the risks of tobacco use and exposure to second-hand smoke). The teams used qualitative research methods to analyse the documents, and their initial findings are published throughout this journal supplement.

  3. METHODS FOR MULTITEMPORAL ANALYSIS OF SATELLITE DATA AIMED AT ENVIRONMENTAL RISK MONITORING

    Directory of Open Access Journals (Sweden)

    M. Caprioli

    2012-08-01

    Full Text Available In the last years the topic of Environmental monitoring has raised a particular importance, also according to minor short-term stability and predictability of climatic events. Facing this situation, often in terms of emergency, involves high and unpredictable costs for public Agencies. Prevention of damages caused by natural disasters does not regard only weather forecasts, but requires constant attention and practice of monitoring and control of human activity on territory. Practically, the problem is not knowing if and when an event will affect a determined area, but recognizing the possible damages if this event happened, by adopting the adequate measures to reduce them to a minimum, and requiring the necessary tools for a timely intervention. On the other hand, the surveying technologies should be the most possible accurate and updatable in order to guarantee high standards, involving the analysis of a great amount of data. The management of such data requires the integration and calculation systems with specialized software and fast and reliable connection and communication networks. To solve such requirements, current satellite technology, with recurrent data acquisition for the timely generation of cartographic products updated and coherent to the territorial investigation, offers the possibility to fill the temporal gap between the need of urgent information and official reference information. Among evolved image processing techniques, Change detection analysis is useful to facilitate individuation of environmental temporal variations, contributing to reduce the users intervention by means of the processes automation and improving in a progressive way the qualitative and quantitative accuracy of results. The research investigate automatic methods on land cover transformations by means of "Change detection" techniques executable on satellite data that are heterogeneous for spatial and spectral resolution with homogenization and

  4. The Collaborative Lithium Trials (CoLT: specific aims, methods, and implementation

    Directory of Open Access Journals (Sweden)

    Hooper Stephen R

    2008-08-01

    Full Text Available Abstract Background Lithium is a benchmark treatment for bipolar illness in adults. However, there has been relatively little methodologically stringent research regarding the use of lithium in youth suffering from bipolarity. Methods Under the auspices of the Best Pharmaceuticals for Children Act (BPCA, a Written Request (WR pertaining to the study of lithium in pediatric mania was issued by the United States Food and Drug Administration (FDA to the National Institute of Child Health and Human Development (NICHD in 2004. Accordingly, the NICHD issued a Request for Proposals (RFP soliciting submissions to pursue this research. Subsequently, the NICHD awarded a contract to a group of investigators in order to conduct these studies. Results The Collaborative Lithium Trials (CoLT investigators, the BPCA-Coordinating Center, and the NICHD developed protocols to provide data that will: (1 establish evidence-based dosing strategies for lithium; (2 characterize the pharmacokinetics and biodisposition of lithium; (3 examine the acute efficacy of lithium in pediatric bipolarity; (4 investigate the long-term effectiveness of lithium treatment; and (5 characterize the short- and long-term safety of lithium. By undertaking two multi-phase trials rather than multiple single-phase studies (as was described in the WR, the feasibility of the research to be undertaken was enhanced while ensuring all the data outlined in the WR would be obtained. The first study consists of: (1 an 8-week open-label, randomized, escalating dose Pharmacokinetic Phase; (2 a 16-week Long-Term Effectiveness Phase; (3 a 28-week double-blind Discontinuation Phase; and (4 an 8-week open-label Restabilization Phase. The second study consists of: (1 an 8-week, double-blind, parallel-group, placebo-controlled Efficacy Phase; (2 an open-label Long-Term Effectiveness lasting either 16 or 24 weeks (depending upon blinded treatment assignment during the Efficacy Phase; (3 a 28-week double

  5. Decomposition methods for unsupervised learning

    DEFF Research Database (Denmark)

    Mørup, Morten

    2008-01-01

    This thesis presents the application and development of decomposition methods for Unsupervised Learning. It covers topics from classical factor analysis based decomposition and its variants such as Independent Component Analysis, Non-negative Matrix Factorization and Sparse Coding...... methods and clustering problems is derived both in terms of classical point clustering but also in terms of community detection in complex networks. A guiding principle throughout this thesis is the principle of parsimony. Hence, the goal of Unsupervised Learning is here posed as striving for simplicity...... in the decompositions. Thus, it is demonstrated how a wide range of decomposition methods explicitly or implicitly strive to attain this goal. Applications of the derived decompositions are given ranging from multi-media analysis of image and sound data, analysis of biomedical data such as electroencephalography...

  6. Learning Method and Its Influence on Nutrition Study Results Throwing the Ball

    Science.gov (United States)

    Samsudin; Nugraha, Bayu

    2015-01-01

    This study aimed to know the difference between playing and learning methods of exploratory learning methods to learning outcomes throwing the ball. In addition, this study also aimed to determine the effect of nutritional status of these two learning methods mentioned above. This research was conducted at SDN Cipinang Besar Selatan 16 Pagi East…

  7. A Comparison between the Effect of Cooperative Learning Teaching Method and Lecture Teaching Method on Students' Learning and Satisfaction Level

    Science.gov (United States)

    Mohammadjani, Farzad; Tonkaboni, Forouzan

    2015-01-01

    The aim of the present research is to investigate a comparison between the effect of cooperative learning teaching method and lecture teaching method on students' learning and satisfaction level. The research population consisted of all the fourth grade elementary school students of educational district 4 in Shiraz. The statistical population…

  8. A case-based, small-group cooperative learning course in preclinical veterinary science aimed at bridging basic science and clinical literacy

    Directory of Open Access Journals (Sweden)

    J.P. Schoeman

    2009-05-01

    Full Text Available In 1999 a dedicated problem-based learning course was introduced into the lecture-based preclinical veterinary curriculum of the University of Pretoria. The Introduction to Clinical Studies Course combines traditional lectures, practical sessions, student self-learning and guided tutorials. The self-directed component of the course utilises case-based, small group cooperative learning as an educational vehicle to link basic science with clinical medicine. The aim of this article is to describe the objectives and structure of the course and to report the results of the assessment of the students' perceptions on some aspects of the course. Students reacted very positively to the ability of the course to equip them with problem-solving skills. Students indicated positive perceptions about the workload of the course. There were, however, significantly lower scores for the clarity of the course objectives. Although the study guide for the course is very comprehensive, the practice regarding the objectives is still uncertain. It is imperative to set clear objectives in non-traditional, student-centred courses. The objectives have to be explained at the outset and reiterated throughout the course. Tutors should also communicate the rationale behind problem based learning as a pedagogical method to the students. Further research is needed to verify the effectiveness of this course in bridging the gap between basic science and clinical literacy in veterinary science. Ongoing feedback and assessment of the management and content are important to refine this model for integrating basic science with clinical literacy.

  9. A case-based, small-group cooperative learning course in preclinical veterinary science aimed at bridging basic science and clinical literacy.

    Science.gov (United States)

    Schoeman, J P; van Schoor, M; van der Merwe, L L; Meintjes, R A

    2009-03-01

    In 1999 a dedicated problem-based learning course was introduced into the lecture-based preclinical veterinary curriculum of the University of Pretoria. The Introduction to Clinical Studies Course combines traditional lectures, practical sessions, student self-learning and guided tutorials. The self-directed component of the course utilises case-based, small-group cooperative learning as an educational vehicle to link basic science with clinical medicine. The aim of this article is to describe the objectives and structure of the course and to report the results of the assessment of the students' perceptions on some aspects of the course. Students reacted very positively to the ability of the course to equip them with problem-solving skills. Students indicated positive perceptions about the workload of the course. There were, however, significantly lower scores for the clarity of the course objectives. Although the study guide for the course is very comprehensive, the practice regarding the objectives is still uncertain. It is imperative to set clear objectives in non-traditional, student-centred courses. The objectives have to be explained at the outset and reiterated throughout the course. Tutors should also communicate the rationale behind problem-based learning as a pedagogical method to the students. Further research is needed to verify the effectiveness of this course in bridging the gap between basic science and clinical literacy in veterinary science. Ongoing feedback and assessment of the management and content are important to refine this model for integrating basic science with clinical literacy.

  10. Statistical learning methods: Basics, control and performance

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de

    2006-04-01

    The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.

  11. Statistical learning methods: Basics, control and performance

    International Nuclear Information System (INIS)

    Zimmermann, J.

    2006-01-01

    The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms

  12. Moving Forwards with the Aim of Going Backwards Fast: High-Performance Rowing as a Learning Environment

    Science.gov (United States)

    Rossi, Tony; Rynne, Steven B.; Rabjohns, Martin

    2016-01-01

    Background and purpose: This paper focuses on the learning culture within the high-performance levels of rowing. In doing so, we explore the case of an individual's learning as he moves across athletic, coaching and administrative functions. This exploration draws on a cultural learning framework and complementary theorisings related to…

  13. Parallelization of the ROOT Machine Learning Methods

    CERN Document Server

    Vakilipourtakalou, Pourya

    2016-01-01

    Today computation is an inseparable part of scientific research. Specially in Particle Physics when there is a classification problem like discrimination of Signals from Backgrounds originating from the collisions of particles. On the other hand, Monte Carlo simulations can be used in order to generate a known data set of Signals and Backgrounds based on theoretical physics. The aim of Machine Learning is to train some algorithms on known data set and then apply these trained algorithms to the unknown data sets. However, the most common framework for data analysis in Particle Physics is ROOT. In order to use Machine Learning methods, a Toolkit for Multivariate Data Analysis (TMVA) has been added to ROOT. The major consideration in this report is the parallelization of some TMVA methods, specially Cross-Validation and BDT.

  14. Development and application of the RE-AIM QuEST mixed methods framework for program evaluation.

    Science.gov (United States)

    Forman, Jane; Heisler, Michele; Damschroder, Laura J; Kaselitz, Elizabeth; Kerr, Eve A

    2017-06-01

    To increase the likelihood of successful implementation of interventions and promote dissemination across real-world settings, it is essential to evaluate outcomes related to dimensions other than Effectiveness alone. Glasgow and colleagues' RE-AIM framework specifies four additional types of outcomes that are important to decision-makers: Reach, Adoption, Implementation (including cost), and Maintenance. To further strengthen RE-AIM, we propose integrating qualitative assessments in an expanded framework: RE-AIM Qualitative Evaluation for Systematic Translation (RE-AIM QuEST), a mixed methods framework. RE-AIM QuEST guides formative evaluation to identify real-time implementation barriers and explain how implementation context may influence translation to additional settings. RE-AIM QuEST was used to evaluate a pharmacist-led hypertension management intervention at 3 VA facilities in 2008-2009. We systematically reviewed each of the five RE-AIM dimensions and created open-ended companion questions to quantitative measures and identified qualitative and quantitative data sources, measures, and analyses. To illustrate use of the RE-AIM QuEST framework, we provide examples of real-time, coordinated use of quantitative process measures and qualitative methods to identify site-specific issues, and retrospective use of these data sources and analyses to understand variation across sites and explain outcomes. For example, in the Reach dimension, we conducted real-time measurement of enrollment across sites and used qualitative data to better understand and address barriers at a low-enrollment site. The RE-AIM QuEST framework may be a useful tool for improving interventions in real-time, for understanding retrospectively why an intervention did or did not work, and for enhancing its sustainability and translation to other settings.

  15. Pre-School Education--Aims, Methods and Problems. Report of a Symposium (Venice, Italy, October 11-16, 1971).

    Science.gov (United States)

    Council of Europe, Strasbourg (France). Committee for General and Technical Education.

    This report provides a summary of the proceedings and recommendations of the Council of Europe symposium on preschool education held in Venice, Italy in 1971. The report is divided into three major areas: (1) historical background information; (2) summaries of general lectures, especially dealing with the functions, aims, methods, and problems of…

  16. Comparing different methods for fast screening of microbiological quality of beach sand aimed at rapid-response remediation.

    Science.gov (United States)

    Testolin, Renan C; Almeida, Tito C M; Polette, Marcus; Branco, Joaquim O; Fischer, Larissa L; Niero, Guilherme; Poyer-Radetski, Gabriel; Silva, Valéria C; Somensi, Cleder A; Corrêa, Albertina X R; Corrêa, Rogério; Rörig, Leonardo R; Itokazu, Ana Gabriela; Férard, Jean-François; Cotelle, Sylvie; Radetski, Claudemir M

    2017-05-15

    There is scientific evidence that beach sands are a significant contributor to the pathogen load to which visitors are exposed. To develop beach quality guidelines all beach zones must be included in microbiological evaluations, but monitoring methods for beach sand quality are relatively longstanding, expensive, laborious and require moderate laboratory infrastructure. This paper aimed to evaluate the microorganism activity in different beach zones applying and comparing a classical method of membrane filtration (MF) with two colorimetric screening methods based on fluorescein (FDA) and tetrazolium (TTC) salt biotransformation to evaluate a new rapid and low-cost method for beach sand microbiological contamination assessments. The colorimetric results can help beach managers to evaluate rapidly and at low cost the microbiological quality of different beach zones in order to decide whether remedial actions need to be adopted to prevent exposure of the public to microbes due to beach sand and/or water contamination. Copyright © 2017. Published by Elsevier Ltd.

  17. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  18. Development of Experience-based Learning about Atmospheric Environment with Quantitative Viewpoint aimed at Education for Sustainable Development

    Science.gov (United States)

    Saitoh, Y.; Tago, H.

    2014-12-01

    The word "ESD (Education for Sustainable Development)" has spread over the world in UN decade (2005 - 2014), and the momentum of the educational innovation aimed at ESD also has grown in the world. Especially, environmental educations recognized as one of the most important ESD have developed in many countries including Japan, but most of those are still mainly experiences in nature. Those could develop "Respect for Environment" of the educational targets of ESD, however we would have to take a further step in order to enhance "Ability of analysis and thinking logically about the environment" which are also targets of ESD.Thus, we developed experienced-learning program about atmospheric particulate matter (PM2.5), for understanding the state of the environment objectively based on quantitative data. PM2.5 is known for harmful, and various human activities are considered a source of it, therefore environmental standards for PM2.5 have been established in many countries. This program was tested on junior high school students of 13 - 15 years old, and the questionnaire survey also was conducted to them before and after the program for evaluating educational effects. Students experienced to measure the concentration of PM2.5 at 5 places around their school in a practical manner. The measured concentration of PM2.5 ranged from 19 to 41 μg/m3/day, that value at the most crowded roadside exceeded Japan's environmental standard (35 μg/m3/day). Many of them expressed "Value of PM2.5 is high" in their individual discussion notes. As a consistent with that, the answer "Don't know" to the question "What do you think about the state of the air?" markedly decreased after the program, on the other hand the answer "Pollution" to the same question increased instead. From above-mentioned, it was considered that they could judge the state of the air objectively. Consequently, the questionnaire result "Concern about Air Pollution" increased significantly after the program compared

  19. Using a Mixed-Methods RE-AIM Framework to Evaluate Community Health Programs for Older Latinas.

    Science.gov (United States)

    Schwingel, Andiara; Gálvez, Patricia; Linares, Deborah; Sebastião, Emerson

    2017-06-01

    This study used the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework to evaluate a promotora-led community health program designed for Latinas ages 50 and older that sought to improve physical activity, nutrition, and stress management. A mixed-methods evaluation approach was administered at participant and organizational levels with a focus on the efficacy, adoption, implementation, and maintenance components of the RE-AIM theoretical model. The program was shown to be effective at improving participants' eating behaviors, increasing their physical activity levels, and lowering their depressive symptoms. Promotoras felt motivated and sufficiently prepared to deliver the program. Some implementation challenges were reported. More child care opportunities and an increased focus on mental well-being were suggested. The promotora delivery model has promise for program sustainability with both promotoras and participants alike expressing interest in leading future programs.

  20. New e-learning method using databases

    Directory of Open Access Journals (Sweden)

    Andreea IONESCU

    2012-10-01

    Full Text Available The objective of this paper is to present a new e-learning method that use databases. The solution could pe implemented for any typeof e-learning system in any domain. The article will purpose a solution to improve the learning process for virtual classes.

  1. New Educational Environments Aimed at Developing Intercultural Understanding While Reinforcing the Use of English in Experience-Based Learning

    Directory of Open Access Journals (Sweden)

    Leonard R. Bruguier

    2012-07-01

    Full Text Available New learning environments with communication and information tools are increasingly accessible with technology playing a crucial role in expanding and reconceptualizing student learning experiences. This paper reviews the outcome of an innovative course offered by four universities in three countries: Canada, the United States, and Mexico. Course objectives focused on broadening the understanding of indigenous and non-indigenous peoples primarily in relation to identity as it encouraged students to reflect on their own identity while improving their English skills in an interactive and experiential manner and thus enhancing their intercultural competence.

  2. Mixed method evaluation of the Virtual Traveller physically active lesson intervention: An analysis using the RE-AIM framework.

    Science.gov (United States)

    Norris, E; Dunsmuir, S; Duke-Williams, O; Stamatakis, E; Shelton, N

    2018-02-02

    Physically active lessons integrating movement into academic content are a way to increase children's physical activity levels. Virtual Traveller was a physically active lesson intervention set in Year 4 (aged 8-9) primary school classes in Greater London, UK. Implemented by classroom teachers, it was a six-week intervention providing 10-min physically active Virtual Field Trips three times a week. The aim of this paper is to report the process evaluation of the Virtual Traveller randomized controlled trial according to RE-AIM framework criteria (Reach, Effectiveness, Adoption, Implementation and Maintenance). A mixed methods approach to evaluation was conducted with five intervention group classes. Six sources of data were collected via informed consent logs, teacher session logs, teacher and pupil questionnaires, teacher interviews and pupil focus groups. High participation and low attrition rates were identified (Reach) alongside positive evaluations of Virtual Traveller sessions from pupil and teachers (Effectiveness). Participants were from more deprived and ethnic backgrounds than local and national averages, with Virtual Traveller having the potential to be a free intervention (Adoption). 70% of sessions were delivered overall (Implementation) but no maintenance of the programme was evident at three month follow-up (Maintenance). Mixed method evaluation of Virtual Traveller showed potential for it to be implemented as a low-cost physically active lesson intervention in UK primary schools. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Qualitative and Quantitative Features Evaluation of Two Methods of Sugarcane Harvesting (with aim of Energy and Sugar Production

    Directory of Open Access Journals (Sweden)

    K Andekaeizadeh

    2018-03-01

    Full Text Available Introduction Sugarcane is an important plant in the world that cultivate for the production of sugar and energy. For this purpose, evaluation of Sugarcane (SC and Energycane (EC methods is necessary. Energy is vital for economic and social development and the demand for it is rising. The international community look toward alternative to fossil fuels is the aim of using liquid fuel derived from agricultural resources. According to calculations, about 47% from renewable energy sources in Brazil comes from sugarcane so as, the country is known the second largest source of renewable energy. Sugarcane in Brazil provides about 17.5% of primary energy sources. Material such as bagasse and ethanol are derived from sugarcane that provide 4.2% and 11.2 % consumed energy, respectively . In developing countries, the use of this product increase in order to achieve self-sufficiency in the production of starch and sugar and thus independence in bioethanol production. Evaluation of energy consumption in manufacturing systems, show the measurement method of yield conversion to the amount of energy. Many of products of Sugarcane have ability to produce bioenergy. Many materials obtain from sugarcane such as, cellulosic ethanol, biofuels and other chemical materials. Hence, Energycane is introduced as a new method of sugarcane harvesting. But, one of the problems of this method is high cost and high energy consumption of harvester. So that the total cost of Energycane method is 38.4 percent of production total costs, whereas, this cost, in Sugarcane method is 5.32 percent of production total costs. In a study that was conducted by Matanker et al (2014 with title “Power requirements and field performance in harvesting EC and SC”, the power requirements of some components of sugarcane harvester and its field capacity, in Sugarcane and Energycane methods were examined. The consumed power by basecutter, elevator and chopper was measured in terms of Mega grams

  4. Listen, live and learn: A review of the application process, aiming to enhance diversity within the Listen, Live and Learn senior student housing initiative, at Stellenbosch University

    Directory of Open Access Journals (Sweden)

    Mathew Smorenburg

    2014-07-01

    Full Text Available The Listen, Live and Learn (LLL initiative at Stellenbosch University (SU is a senior student housing model with the aim of providing an experiential opportunity for students to make contact with ‘the other’. It is posited on the social contact theory assumption that if people of different genders, races, ethnicities, and/or religion make contact and interact with one another on an equal level, then less stereotyping by them will occur.The initiative therefore aims to enhance interaction between diverse students and to enable social integration. However, as diversity is a core element of LLL, an application and selection process had to be developed in order to provide a holistic, transparent, unbiased and scaleable tool. The present results suggest that the application and selection process, specifically developed for the enhancement of diversity within the LLL initiative, maintained the distribution of race and gender, as constructs of diversity throughout the process. The conclusion can be drawn that the process is holistic, transparent, unbiased and scaleable while providing a practical example of a standardised alternative selection process for programmes seeking to increase diversity.

  5. Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

    Science.gov (United States)

    Hodson, Derek

    2014-01-01

    This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

  6. Methods for control over learning individual trajectory

    Science.gov (United States)

    Mitsel, A. A.; Cherniaeva, N. V.

    2015-09-01

    The article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects.

  7. The Guided Autobiography Method: A Learning Experience

    Science.gov (United States)

    Thornton, James E.

    2008-01-01

    This article discusses the proposition that learning is an unexplored feature of the guided autobiography method and its developmental exchange. Learning, conceptualized and explored as the embedded and embodied processes, is essential in narrative activities of the guided autobiography method leading to psychosocial development and growth in…

  8. Active teaching methods, studying responses and learning

    DEFF Research Database (Denmark)

    Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain

    2010-01-01

    Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed....

  9. A Review on Different Virtual Learning Methods in Pharmacy Education

    Directory of Open Access Journals (Sweden)

    Amin Noori

    2015-10-01

    Full Text Available Virtual learning is a type of electronic learning system based on the web. It models traditional in- person learning by providing virtual access to classes, tests, homework, feedbacks and etc. Students and teachers can interact through chat rooms or other virtual environments. Web 2.0 services are usually used for this method. Internet audio-visual tools, multimedia systems, a disco CD-ROMs, videotapes, animation, video conferencing, and interactive phones can all be used to deliver data to the students. E-learning can occur in or out of the classroom. It is time saving with lower costs compared to traditional methods. It can be self-paced, it is suitable for distance learning and it is flexible. It is a great learning style for continuing education and students can independently solve their problems but it has its disadvantages too. Thereby, blended learning (combination of conventional and virtual education is being used worldwide and has improved knowledge, skills and confidence of pharmacy students.The aim of this study is to review, discuss and introduce different methods of virtual learning for pharmacy students.Google scholar, Pubmed and Scupus databases were searched for topics related to virtual, electronic and blended learning and different styles like computer simulators, virtual practice environment technology, virtual mentor, virtual patient, 3D simulators, etc. are discussed in this article.Our review on different studies on these areas shows that the students are highly satisfied withvirtual and blended types of learning.

  10. Effectiveness of adolescent suicide prevention e-learning modules that aim to improve knowledge and self-confidence of gatekeepers: study protocol for a randomized controlled trial

    OpenAIRE

    Ghoncheh, Rezvan; Kerkhof, Ad JFM; Koot, Hans M

    2014-01-01

    Background Providing e-learning modules can be an effective strategy for enhancing gatekeepers’ knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12–20 years). The primary outcomes of this study are par...

  11. Effectiveness of adolescent suicide prevention e-learning modules that aim to improve knowledge and self-confidence of gatekeepers: Study protocol of a randomized controlled trial

    OpenAIRE

    Ghoncheh, R.; Kerkhof, A.J.F.M.; Koot, H.M.

    2014-01-01

    Background: Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12-20 years). The primary outcomes of this study are pa...

  12. Choosing Learning Methods Suitable for Teaching and Learning in Computer Science

    Science.gov (United States)

    Taylor, Estelle; Breed, Marnus; Hauman, Ilette; Homann, Armando

    2013-01-01

    Our aim is to determine which teaching methods students in Computer Science and Information Systems prefer. There are in total 5 different paradigms (behaviorism, cognitivism, constructivism, design-based and humanism) with 32 models between them. Each model is unique and states different learning methods. Recommendations are made on methods that…

  13. Teaching learning methods of an entrepreneurship curriculum

    Directory of Open Access Journals (Sweden)

    KERAMAT ESMI

    2015-10-01

    Full Text Available Introduction: One of the most significant elements of entrepreneurship curriculum design is teaching-learning methods, which plays a key role in studies and researches related to such a curriculum. It is the teaching method, and systematic, organized and logical ways of providing lessons that should be consistent with entrepreneurship goals and contents, and should also be developed according to the learners’ needs. Therefore, the current study aimed to introduce appropriate, modern, and effective methods of teaching entrepreneurship and their validation Methods: This is a mixed method research of a sequential exploratory kind conducted through two stages: a developing teaching methods of entrepreneurship curriculum, and b validating developed framework. Data were collected through “triangulation” (study of documents, investigating theoretical basics and the literature, and semi-structured interviews with key experts. Since the literature on this topic is very rich, and views of the key experts are vast, directed and summative content analysis was used. In the second stage, qualitative credibility of research findings was obtained using qualitative validation criteria (credibility, confirmability, and transferability, and applying various techniques. Moreover, in order to make sure that the qualitative part is reliable, reliability test was used. Moreover, quantitative validation of the developed framework was conducted utilizing exploratory and confirmatory factor analysis methods and Cronbach’s alpha. The data were gathered through distributing a three-aspect questionnaire (direct presentation teaching methods, interactive, and practical-operational aspects with 29 items among 90 curriculum scholars. Target population was selected by means of purposive sampling and representative sample. Results: Results obtained from exploratory factor analysis showed that a three factor structure is an appropriate method for describing elements of

  14. Teaching learning methods of an entrepreneurship curriculum.

    Science.gov (United States)

    Esmi, Keramat; Marzoughi, Rahmatallah; Torkzadeh, Jafar

    2015-10-01

    One of the most significant elements of entrepreneurship curriculum design is teaching-learning methods, which plays a key role in studies and researches related to such a curriculum. It is the teaching method, and systematic, organized and logical ways of providing lessons that should be consistent with entrepreneurship goals and contents, and should also be developed according to the learners' needs. Therefore, the current study aimed to introduce appropriate, modern, and effective methods of teaching entrepreneurship and their validation. This is a mixed method research of a sequential exploratory kind conducted through two stages: a) developing teaching methods of entrepreneurship curriculum, and b) validating developed framework. Data were collected through "triangulation" (study of documents, investigating theoretical basics and the literature, and semi-structured interviews with key experts). Since the literature on this topic is very rich, and views of the key experts are vast, directed and summative content analysis was used. In the second stage, qualitative credibility of research findings was obtained using qualitative validation criteria (credibility, confirmability, and transferability), and applying various techniques. Moreover, in order to make sure that the qualitative part is reliable, reliability test was used. Moreover, quantitative validation of the developed framework was conducted utilizing exploratory and confirmatory factor analysis methods and Cronbach's alpha. The data were gathered through distributing a three-aspect questionnaire (direct presentation teaching methods, interactive, and practical-operational aspects) with 29 items among 90 curriculum scholars. Target population was selected by means of purposive sampling and representative sample. Results obtained from exploratory factor analysis showed that a three factor structure is an appropriate method for describing elements of teaching-learning methods of entrepreneurship curriculum

  15. European network for promoting the physical health of residents in psychiatric and social care facilities (HELPS: background, aims and methods

    Directory of Open Access Journals (Sweden)

    Marginean Roxana

    2009-08-01

    Full Text Available Abstract Background People with mental disorders have a higher prevalence of physical illnesses and reduced life expectancy as compared with the general population. However, there is a lack of knowledge across Europe concerning interventions that aim at reducing somatic morbidity and excess mortality by promoting behaviour-based and/or environment-based interventions. Methods and design HELPS is an interdisciplinary European network that aims at (i gathering relevant knowledge on physical illness in people with mental illness, (ii identifying health promotion initiatives in European countries that meet country-specific needs, and (iii at identifying best practice across Europe. Criteria for best practice will include evidence on the efficacy of physical health interventions and of their effectiveness in routine care, cost implications and feasibility for adaptation and implementation of interventions across different settings in Europe. HELPS will develop and implement a "physical health promotion toolkit". The toolkit will provide information to empower residents and staff to identify the most relevant risk factors in their specific context and to select the most appropriate action out of a range of defined health promoting interventions. The key methods are (a stakeholder analysis, (b international literature reviews, (c Delphi rounds with experts from participating centres, and (d focus groups with staff and residents of mental health care facilities. Meanwhile a multi-disciplinary network consisting of 15 European countries has been established and took up the work. As one main result of the project they expect that a widespread use of the HELPS toolkit could have a significant positive effect on the physical health status of residents of mental health and social care facilities, as well as to hold resonance for community dwelling people with mental health problems. Discussion A general strategy on health promotion for people with mental

  16. European network for promoting the physical health of residents in psychiatric and social care facilities (HELPS): background, aims and methods

    Science.gov (United States)

    Weiser, Prisca; Becker, Thomas; Losert, Carolin; Alptekin, Köksal; Berti, Loretta; Burti, Lorenzo; Burton, Alexandra; Dernovsek, Mojca; Dragomirecka, Eva; Freidl, Marion; Friedrich, Fabian; Genova, Aneta; Germanavicius, Arunas; Halis, Ulaş; Henderson, John; Hjorth, Peter; Lai, Taavi; Larsen, Jens Ivar; Lech, Katarzyna; Lucas, Ramona; Marginean, Roxana; McDaid, David; Mladenova, Maya; Munk-Jørgensen, Povl; Paziuc, Alexandru; Paziuc, Petronela; Priebe, Stefan; Prot-Klinger, Katarzyna; Wancata, Johannes; Kilian, Reinhold

    2009-01-01

    Background People with mental disorders have a higher prevalence of physical illnesses and reduced life expectancy as compared with the general population. However, there is a lack of knowledge across Europe concerning interventions that aim at reducing somatic morbidity and excess mortality by promoting behaviour-based and/or environment-based interventions. Methods and design HELPS is an interdisciplinary European network that aims at (i) gathering relevant knowledge on physical illness in people with mental illness, (ii) identifying health promotion initiatives in European countries that meet country-specific needs, and (iii) at identifying best practice across Europe. Criteria for best practice will include evidence on the efficacy of physical health interventions and of their effectiveness in routine care, cost implications and feasibility for adaptation and implementation of interventions across different settings in Europe. HELPS will develop and implement a "physical health promotion toolkit". The toolkit will provide information to empower residents and staff to identify the most relevant risk factors in their specific context and to select the most appropriate action out of a range of defined health promoting interventions. The key methods are (a) stakeholder analysis, (b) international literature reviews, (c) Delphi rounds with experts from participating centres, and (d) focus groups with staff and residents of mental health care facilities. Meanwhile a multi-disciplinary network consisting of 15 European countries has been established and took up the work. As one main result of the project they expect that a widespread use of the HELPS toolkit could have a significant positive effect on the physical health status of residents of mental health and social care facilities, as well as to hold resonance for community dwelling people with mental health problems. Discussion A general strategy on health promotion for people with mental disorders must take into

  17. Think Pair Share (TPS as Method to Improve Student’s Learning Motivation and Learning Achievement

    Directory of Open Access Journals (Sweden)

    Hetika Hetika

    2018-03-01

    Full Text Available This research aims to find out the application of Think Pair Share (TPS learning method in improving learning motivation and learning achievement in the subject of Introduction to Accounting I of the Accounting Study Program students of Politeknik Harapan Bersama. The Method of data collection in this study used observation method, test method, and documentation method. The research instruments used observation sheet, questionnaire and test question. This research used Class Action Research Design which is an action implementation oriented research, with the aim of improving quality or problem solving in a group by carefully and observing the success rate due to the action. The method of analysis used descriptive qualitative and quantitative analysis method. The results showed that the application of Think Pair Share Learning (TPS Method can improve the Learning Motivation and Achievement. Before the implementation of the action, the obtained score is 67% then in the first cycle increases to 72%, and in the second cycle increasws to 80%. In addition, based on questionnaires distributed to students, it also increases the score of Accounting Learning Motivation where the score in the first cycle of 76% increases to 79%. In addition, in the first cycle, the score of pre test and post test of the students has increased from 68.86 to 76.71 while in the second cycle the score of pre test and post test of students has increased from 79.86 to 84.86.

  18. Effectiveness of adolescent suicide prevention e-learning modules that aim to improve knowledge and self-confidence of gatekeepers: Study protocol of a randomized controlled trial

    NARCIS (Netherlands)

    Ghoncheh, R.; Kerkhof, A.J.F.M.; Koot, H.M.

    2014-01-01

    Background: Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of

  19. Kernel methods for deep learning

    OpenAIRE

    Cho, Youngmin

    2012-01-01

    We introduce a new family of positive-definite kernels that mimic the computation in large neural networks. We derive the different members of this family by considering neural networks with different activation functions. Using these kernels as building blocks, we also show how to construct other positive-definite kernels by operations such as composition, multiplication, and averaging. We explore the use of these kernels in standard models of supervised learning, such as support vector mach...

  20. Cerebellar anodal tDCS increases implicit learning when strategic re-aiming is suppressed in sensorimotor adaptation.

    Science.gov (United States)

    Leow, Li-Ann; Marinovic, Welber; Riek, Stephan; Carroll, Timothy J

    2017-01-01

    Neurophysiological and neuroimaging work suggests that the cerebellum is critically involved in sensorimotor adaptation. Changes in cerebellar function alter behaviour when compensating for sensorimotor perturbations, as shown by non-invasive stimulation of the cerebellum and studies involving patients with cerebellar degeneration. It is known, however, that behavioural responses to sensorimotor perturbations reflect both explicit processes (such as volitional aiming to one side of a target to counteract a rotation of visual feedback) and implicit, error-driven updating of sensorimotor maps. The contribution of the cerebellum to these explicit and implicit processes remains unclear. Here, we examined the role of the cerebellum in sensorimotor adaptation to a 30° rotation of visual feedback of hand position during target-reaching, when the capacity to use explicit processes was manipulated by controlling movement preparation times. Explicit re-aiming was suppressed in one condition by requiring subjects to initiate their movements within 300ms of target presentation, and permitted in another condition by requiring subjects to wait approximately 1050ms after target presentation before movement initiation. Similar to previous work, applying anodal transcranial direct current stimulation (tDCS; 1.5mA) to the right cerebellum during adaptation resulted in faster compensation for errors imposed by the rotation. After exposure to the rotation, we evaluated implicit remapping in no-feedback trials after providing participants with explicit knowledge that the rotation had been removed. Crucially, movements were more adapted in these no-feedback trials following cerebellar anodal tDCS than after sham stimulation in both long and short preparation groups. Thus, cerebellar anodal tDCS increased implicit remapping during sensorimotor adaptation, irrespective of preparation time constraints. The results are consistent with the possibility that the cerebellum contributes to the

  1. Activating teaching methods, studying responses and learning

    OpenAIRE

    Christensen, Hans Peter; Vigild, Martin E.; Thomsen, Erik; Szabo, Peter; Horsewell, Andy

    2009-01-01

    Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed. Peer Reviewed

  2. Science Learning Cycle Method to Enhance the Conceptual Understanding and the Learning Independence on Physics Learning

    Science.gov (United States)

    Sulisworo, Dwi; Sutadi, Novitasari

    2017-01-01

    There have been many studies related to the implementation of cooperative learning. However, there are still many problems in school related to the learning outcomes on science lesson, especially in physics. The aim of this study is to observe the application of science learning cycle (SLC) model on improving scientific literacy for secondary…

  3. Study Protocol - Accurate assessment of kidney function in Indigenous Australians: aims and methods of the eGFR Study

    Directory of Open Access Journals (Sweden)

    Panagiotopoulos Sianna

    2010-02-01

    Full Text Available Abstract Background There is an overwhelming burden of cardiovascular disease, type 2 diabetes and chronic kidney disease among Indigenous Australians. In this high risk population, it is vital that we are able to measure accurately kidney function. Glomerular filtration rate is the best overall marker of kidney function. However, differences in body build and body composition between Indigenous and non-Indigenous Australians suggest that creatinine-based estimates of glomerular filtration rate derived for European populations may not be appropriate for Indigenous Australians. The burden of kidney disease is borne disproportionately by Indigenous Australians in central and northern Australia, and there is significant heterogeneity in body build and composition within and amongst these groups. This heterogeneity might differentially affect the accuracy of estimation of glomerular filtration rate between different Indigenous groups. By assessing kidney function in Indigenous Australians from Northern Queensland, Northern Territory and Western Australia, we aim to determine a validated and practical measure of glomerular filtration rate suitable for use in all Indigenous Australians. Methods/Design A cross-sectional study of Indigenous Australian adults (target n = 600, 50% male across 4 sites: Top End, Northern Territory; Central Australia; Far North Queensland and Western Australia. The reference measure of glomerular filtration rate was the plasma disappearance rate of iohexol over 4 hours. We will compare the accuracy of the following glomerular filtration rate measures with the reference measure: Modification of Diet in Renal Disease 4-variable formula, Chronic Kidney Disease Epidemiology Collaboration equation, Cockcroft-Gault formula and cystatin C- derived estimates. Detailed assessment of body build and composition was performed using anthropometric measurements, skinfold thicknesses, bioelectrical impedance and a sub-study used dual

  4. Arabic Supervised Learning Method Using N-Gram

    Science.gov (United States)

    Sanan, Majed; Rammal, Mahmoud; Zreik, Khaldoun

    2008-01-01

    Purpose: Recently, classification of Arabic documents is a real problem for juridical centers. In this case, some of the Lebanese official journal documents are classified, and the center has to classify new documents based on these documents. This paper aims to study and explain the useful application of supervised learning method on Arabic texts…

  5. Life With and Without Coding: Two Methods for Early-Stage Data Analysis in Qualitative Research Aiming at Causal Explanations

    NARCIS (Netherlands)

    Gläser, Jochen; Laudel, Grit

    2013-01-01

    Qualitative research aimed at "mechanismic" explanations poses specific challenges to qualitative data analysis because it must integrate existing theory with patterns identified in the data. We explore the utilization of two methods—coding and qualitative content analysis—for the first steps in the

  6. Development and application of the RE-AIM QuEST mixed methods framework for program evaluation

    Directory of Open Access Journals (Sweden)

    Jane Forman

    2017-06-01

    The RE-AIM QuEST framework may be a useful tool for improving interventions in real-time, for understanding retrospectively why an intervention did or did not work, and for enhancing its sustainability and translation to other settings.

  7. Active learning methods for interactive image retrieval.

    Science.gov (United States)

    Gosselin, Philippe Henri; Cord, Matthieu

    2008-07-01

    Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

  8. Deep Learning and Bayesian Methods

    Directory of Open Access Journals (Sweden)

    Prosper Harrison B.

    2017-01-01

    Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.

  9. Learning styles: The learning methods of air traffic control students

    Science.gov (United States)

    Jackson, Dontae L.

    In the world of aviation, air traffic controllers are an integral part in the overall level of safety that is provided. With a number of controllers reaching retirement age, the Air Traffic Collegiate Training Initiative (AT-CTI) was created to provide a stronger candidate pool. However, AT-CTI Instructors have found that a number of AT-CTI students are unable to memorize types of aircraft effectively. This study focused on the basic learning styles (auditory, visual, and kinesthetic) of students and created a teaching method to try to increase memorization in AT-CTI students. The participants were asked to take a questionnaire to determine their learning style. Upon knowing their learning styles, participants attended two classroom sessions. The participants were given a presentation in the first class, and divided into a control and experimental group for the second class. The control group was given the same presentation from the first classroom session while the experimental group had a group discussion and utilized Middle Tennessee State University's Air Traffic Control simulator to learn the aircraft types. Participants took a quiz and filled out a survey, which tested the new teaching method. An appropriate statistical analysis was applied to determine if there was a significant difference between the control and experimental groups. The results showed that even though the participants felt that the method increased their learning, there was no significant difference between the two groups.

  10. Pragmatics of Contemporary Teaching and Learning Methods

    Directory of Open Access Journals (Sweden)

    Ryszard Józef Panfil

    2013-09-01

    Full Text Available The dynamics of the environment in which educational institutions operate have a significant influence on the basic activity of these institutions, i.e. the process of educating, and particularly teaching and learning methods used during that process: traditional teaching, tutoring, mentoring and coaching. The identity of an educational institution and the appeal of its services depend on how flexible, diverse and adaptable is the educational process it offers as a core element of its services. Such a process is determined by how its pragmatism is displayed in the operational relativism of methods, their applicability, as well as practical dimension of achieved results and values. Based on the above premises, this publication offers a pragmatic-systemic identification of contemporary teaching and learning methods, while taking into account the differences between them and the scope of their compatibility. Secondly, using the case of sport coaches’ education, the author exemplifies the pragmatic theory of perception of contemporary teaching and learning methods.

  11. e-Learning Business Research Methods

    Science.gov (United States)

    Cowie, Jonathan

    2004-01-01

    This paper outlines the development of a generic Business Research Methods course from a simple name in a box to a full e-Learning web based module. It highlights particular issues surrounding the nature of the discipline and the integration of a large number of cross faculty subject specific research methods courses into a single generic module.…

  12. Deep Learning and Bayesian Methods

    OpenAIRE

    Prosper Harrison B.

    2017-01-01

    A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such meth...

  13. RESULTS OF ANALYSIS OF BENCHMARKING METHODS OF INNOVATION SYSTEMS ASSESSMENT IN ACCORDANCE WITH AIMS OF SUSTAINABLE DEVELOPMENT OF SOCIETY

    Directory of Open Access Journals (Sweden)

    A. Vylegzhanina

    2016-01-01

    Full Text Available In this work, we introduce results of comparative analysis of international ratings indexes of innovation systems for their compliance with purposes of sustainable development. Purpose of this research is defining requirements to benchmarking methods of assessing national or regional innovation systems and compare them basing on assumption, that innovation system is aligned with sustainable development concept. Analysis of goal sets and concepts, which underlie observed international composite innovation indexes, comparison of their metrics and calculation techniques, allowed us to reveal opportunities and limitations of using these methods in frames of sustainable development concept. We formulated targets of innovation development on the base of innovation priorities of sustainable socio-economic development. Using comparative analysis of indexes with these targets, we revealed two methods of assessing innovation systems, maximally connected with goals of sustainable development. Nevertheless, today no any benchmarking method, which meets need of innovation systems assessing in compliance with sustainable development concept to a sufficient extent. We suggested practical directions of developing methods, assessing innovation systems in compliance with goals of societal sustainable development.

  14. Energy market and reserve market modeling in simultaneous and serial implementation methods with the aim of reducing electricity costs

    Directory of Open Access Journals (Sweden)

    Ramin Ghoraba

    2012-01-01

    Full Text Available In competitive electricity markets, power needed for the network’s reserve is purchased from the ancillary service market. In this market, producing units and buyers alike announce their offers. As will be seen, energy market and reserve market implementation is possible with simultaneous method and serial method by choosing each of the methods based on the type of market and other conditions. In this paper, the energy market and the active power reserve market are simulated in two formations as serial and simultaneous for a uniform pricing system. In each method, limitations of transferring power over the lines, based on available transfer capacity (ATC, is considered alongside the other constraints in the energy market and the active power reserve market. Then, during network overload, economic dispatch is accomplished between winner units in the reserve market by using a linear optimization problem, and needed power is provided from these units at a minimal cost. Finally, our proposed methods are implemented on an IEEE 39-bus test system and results are analyzed.

  15. FLIPPED CLASSROOM LEARNING METHOD TO IMPROVE CARING AND LEARNING OUTCOME IN FIRST YEAR NURSING STUDENT

    Directory of Open Access Journals (Sweden)

    Ni Putu Wulan Purnama Sari

    2017-08-01

    Full Text Available Background and Purpose: Caring is the essence of nursing profession. Stimulation of caring attitude should start early. Effective teaching methods needed to foster caring attitude and improve learning achievement. This study aimed to explain the effect of applying flipped classroom learning method for improving caring attitude and learning achievement of new student nurses at nursing institutions in Surabaya. Method: This is a pre-experimental study using the one group pretest posttest and posttest only design. Population was all new student nurses on nursing institutions in Surabaya. Inclusion criteria: female, 18-21 years old, majoring in nursing on their own volition and being first choice during students selection process, status were active in the even semester of 2015/2016 academic year. Sample size was 67 selected by total sampling. Variables: 1 independent: application of flipped classroom learning method; 2 dependent: caring attitude, learning achievement. Instruments: teaching plan, assignment descriptions, presence list, assignment assessment rubrics, study materials, questionnaires of caring attitude. Data analysis: paired and one sample t test. Ethical clearance was available. Results: Most respondents were 20 years old (44.8%, graduated from high school in Surabaya (38.8%, living with parents (68.7% in their homes (64.2%. All data were normally distributed. Flipped classroom learning method could improve caring attitude by 4.13%. Flipped classroom learning method was proved to be effective for improving caring attitude (p=0.021 and learning achievement (p=0.000. Conclusion and Recommendation: Flipped classroom was effective for improving caring attitude and learning achievement of new student nurse. It is recommended to use mix-method and larger sample for further study.

  16. Characterizing Reinforcement Learning Methods through Parameterized Learning Problems

    Science.gov (United States)

    2011-06-03

    extraneous. The agent could potentially adapt these representational aspects by applying methods from feature selection ( Kolter and Ng, 2009; Petrik et al...611–616. AAAI Press. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature selection in least-squares temporal difference learning. In A. P

  17. Tracking by Machine Learning Methods

    CERN Document Server

    Jofrehei, Arash

    2015-01-01

    Current track reconstructing methods start with two points and then for each layer loop through all possible hits to find proper hits to add to that track. Another idea would be to use this large number of already reconstructed events and/or simulated data and train a machine on this data to find tracks given hit pixels. Training time could be long but real time tracking is really fast Simulation might not be as realistic as real data but tacking has been done for that with 100 percent efficiency while by using real data we would probably be limited to current efficiency.

  18. Psychological Benefits of Nonpharmacological Methods Aimed for Improving Balance in Parkinson’s Disease: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Rastislav Šumec

    2015-01-01

    Full Text Available Parkinson’s disease (PD is a serious condition with a major negative impact on patient’s physical and mental health. Postural instability is one of the cardinal difficulties reported by patients to deal with. Neuroanatomical, animal, and clinical studies on nonparkinsonian and parkinsonian subjects suggest an important correlation between the presence of balance dysfunction and multiple mood disorders, such as anxiety, depression, and apathy. Considering that balance dysfunction is a very common symptom in PD, we can presume that by its management we could positively influence patient’s state of mind too. This review is an analysis of nonpharmacological methods shown to be effective and successful for improving balance in patients suffering from PD. Strategies such as general exercise, robotic assisted training, Tai Chi, Qi Gong, Yoga, dance (such as tango or ballet, box, virtual reality-based, or neurofeedback-based techniques and so forth can significantly improve the stability in these patients. Beside this physical outcome, many methods have also shown effect on quality of life, depression level, enjoyment, and motivation to continue in practicing the method independently. The purpose of this review is to provide information about practical and creative methods designed to improve balance in PD and highlight their positive impact on patient’s psychology.

  19. Aiming for the Singing Teacher: An Applied Study on Preservice Kindergarten Teachers' Singing Skills Development within a Music Methods Course

    Science.gov (United States)

    Neokleous, Rania

    2015-01-01

    This study examined the effects of a music methods course offered at a Cypriot university on the singing skills of 33 female preservice kindergarten teachers. To systematically measure and analyze student progress, the research design was both experimental and descriptive. As an applied study which was carried out "in situ," the normal…

  20. COMMUNITTY HEALTH II – SUBJECT THAT PROMOTES THE LEARNING- SERVING-COMUNITTY INTERACTION AIMING THE PROMOTION OF HEALTH, CARE AND COMFORT

    Directory of Open Access Journals (Sweden)

    Onã Silva

    2013-09-01

    Full Text Available Introduction: In the context of the teaching and learning process, the communication between the fields of study and their subjects is important, once such integration reflects on the formation and the learning-serving-community triad. This pedagogical basis figures in the syllabi of the subjects Community Health II and its Training Course, offered by the Nursing Program. Objective: Reporting the teaching and learning process for the academic subject Community Health II, as being an inclusive part of learning-serving-community triad, with regards of developing care for the health of individuals, family and community, according to the reports of the experiences of this author during the training course. Methodological Description: It was reported the events dealing with the data experienced by the author over the second term of 2012. The following places were used in that report. In the academic environment and in the training course which took place in one of the administrative regions of Distrito Federal. The pedagogical theoretical basis was made on Paulo Freire. Data were collected from the studied subjects, legislation, theoretical and practical meetings, communication materials on the virtual environment among other sources. Results and discussion: this experience revealed that the subject CH-II presents an interdisciplinary, multiprofessional and inclusive view of learning-serving-community triad. The participants mediated by the problematization contributed for the construction of theoretical and practical knowledge using reflections, debates, and discussions according to the Pedagogy of Autonomy. The teaching and learning methods permitted the development of independence, competencies and abilities contained in the political project. Conclusion: The training course experienced in the environment of CH-II was an unique experience, generating benefits to all the people involved in the process, besides the resignification of their practices

  1. Application of machine learning methods in bioinformatics

    Science.gov (United States)

    Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

    2018-05-01

    Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

  2. Measurement and Analysis of Olfactory Responses with the Aim of Establishing an Objective Diagnostic Method for Central Olfactory Disorders

    Science.gov (United States)

    Uno, Tominori; Wang, Li-Qun; Miwakeichi, Fumikazu; Tonoike, Mitsuo; Kaneda, Teruo

    In order to establish a new diagnostic method for central olfactory disorders and to identify objective indicators, we measured and analyzed brain activities in the parahippocampal gyrus and uncus, region of responsibility for central olfactory disorders. The relationship between olfactory stimulation and brain response at region of responsibility can be examined in terms of fitted responses (FR). FR in these regions may be individual indicators of changes in brain olfactory responses. In the present study, in order to non-invasively and objectively measure olfactory responses, an odor oddball task was conducted on four healthy volunteers using functional magnetic resonance imaging (fMRI) and a odorant stimulator with blast-method. The results showed favorable FR and activation in the parahippocampal gyrus or uncus in all subjects. In some subjects, both the parahippocampal gyrus and uncus were activated. Furthermore, activation was also confirmed in the cingulate gyrus, middle frontal gyrus, precentral gyrus, postcentral gyrus, superior temporal gyrus and insula. The hippocampus and uncus are known to be involved in the olfactory disorders associated with early-stage Alzheimer's disease and other olfactory disorders. In the future, it will be necessary to further develop the present measurement and analysis method to clarify the relationship between central olfactory disorders and brain activities and establish objective indicators that are useful for diagnosis.

  3. SMALL GROUP LEARNING METHODS AND THEIR EFFECT ON LEARNERS’ RELATIONSHIPS

    Directory of Open Access Journals (Sweden)

    Radka Borůvková

    2016-04-01

    Full Text Available Building relationships in the classroom is an essential part of any teacher's career. Having healthy teacher-to-learner and learner-to-learner relationships is an effective way to help prevent pedagogical failure, social conflict and quarrelsome behavior. Many strategies are available that can be used to achieve good long-lasting relationships in the classroom setting. Successful teachers’ pedagogical work in the classroom requires detailed knowledge of learners’ relationships. Good understanding of the relationships is necessary, especially in the case of teenagers’ class. This sensitive period of adolescence demands attention of all teachers who should deal with the problems of their learners. Special care should be focused on children that are out of their classmates’ interest (so called isolated learners or isolates in such class and on possibilities to integrate them into the class. Natural idea how to do it is that of using some modern non-traditional teaching/learning methods, especially the methods based on work in small groups involving learners’ cooperation. Small group education (especially problem-based learning, project-based learning, cooperative learning, collaborative learning or inquire-based learning as one of these methods involves a high degree of interaction. The effectiveness of learning groups is determined by the extent to which the interaction enables members to clarify their own understanding, build upon each other's contributions, sift out meanings, ask and answer questions. An influence of this kind of methods (especially cooperative learning (CL on learners’ relationships was a subject of the further described research. Within the small group education, students work with their classmates to solve complex and authentic problems that help develop content knowledge as well as problem-solving, reasoning, communication, and self-assessment skills. The aim of the research was to answer the question: Can the

  4. A Scale Development for Teacher Competencies on Cooperative Learning Method

    Science.gov (United States)

    Kocabas, Ayfer; Erbil, Deniz Gokce

    2017-01-01

    Cooperative learning method is a learning method studied both in Turkey and in the world for long years as an active learning method. Although cooperative learning method takes place in training programs, it cannot be implemented completely in the direction of its principles. The results of the researches point out that teachers have problems with…

  5. Effectiveness of adolescent suicide prevention e-learning modules that aim to improve knowledge and self-confidence of gatekeepers: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Ghoncheh, Rezvan; Kerkhof, Ad J F M; Koot, Hans M

    2014-02-08

    Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12-20 years). The primary outcomes of this study are participant's ratings on perceived knowledge, perceived self-confidence, and actual knowledge regarding adolescent suicidality. A randomized controlled trial will be carried out among 154 gatekeepers. After completing the first assessment (pre-test), participants will be randomly assigned to either the experimental group or the waitlist control group. One week after completing the first assessment the experimental group will have access to the website Mental Health Online containing the eight e-learning modules and additional information on adolescent suicide prevention. Participants in both conditions will be assessed 4 weeks after completing the first assessment (post-test), and 12 weeks after completing the post-test (follow-up). At post-test, participants from the experimental group are asked to complete an evaluation questionnaire on the modules. The waitlist control group will have access to the modules and additional information on the website after completing the follow-up assessment. Gatekeepers can benefit from e-learning modules on adolescent suicide prevention. This approach allows them to learn about this sensitive subject at their own pace and from any given location, as long as they have access to the Internet. Given the flexible nature of the program, each participant can compose his/her own training creating an instant customized course with the required steps in adolescent suicide prevention. Netherlands Trial Register NTR3625.

  6. Enriching behavioral ecology with reinforcement learning methods.

    Science.gov (United States)

    Frankenhuis, Willem E; Panchanathan, Karthik; Barto, Andrew G

    2018-02-13

    This article focuses on the division of labor between evolution and development in solving sequential, state-dependent decision problems. Currently, behavioral ecologists tend to use dynamic programming methods to study such problems. These methods are successful at predicting animal behavior in a variety of contexts. However, they depend on a distinct set of assumptions. Here, we argue that behavioral ecology will benefit from drawing more than it currently does on a complementary collection of tools, called reinforcement learning methods. These methods allow for the study of behavior in highly complex environments, which conventional dynamic programming methods do not feasibly address. In addition, reinforcement learning methods are well-suited to studying how biological mechanisms solve developmental and learning problems. For instance, we can use them to study simple rules that perform well in complex environments. Or to investigate under what conditions natural selection favors fixed, non-plastic traits (which do not vary across individuals), cue-driven-switch plasticity (innate instructions for adaptive behavioral development based on experience), or developmental selection (the incremental acquisition of adaptive behavior based on experience). If natural selection favors developmental selection, which includes learning from environmental feedback, we can also make predictions about the design of reward systems. Our paper is written in an accessible manner and for a broad audience, though we believe some novel insights can be drawn from our discussion. We hope our paper will help advance the emerging bridge connecting the fields of behavioral ecology and reinforcement learning. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  7. Early Language Learning: Complexity and Mixed Methods

    Science.gov (United States)

    Enever, Janet, Ed.; Lindgren, Eva, Ed.

    2017-01-01

    This is the first collection of research studies to explore the potential for mixed methods to shed light on foreign or second language learning by young learners in instructed contexts. It brings together recent studies undertaken in Cameroon, China, Croatia, Ethiopia, France, Germany, Italy, Kenya, Mexico, Slovenia, Spain, Sweden, Tanzania and…

  8. Keystone Method: A Learning Paradigm in Mathematics

    Science.gov (United States)

    Siadat, M. Vali; Musial, Paul M.; Sagher, Yoram

    2008-01-01

    This study reports the effects of an integrated instructional program (the Keystone Method) on the students' performance in mathematics and reading, and tracks students' persistence and retention. The subject of the study was a large group of students in remedial mathematics classes at the college, willing to learn but lacking basic educational…

  9. Suggestology as an Effective Language Learning Method.

    Science.gov (United States)

    MaCoy, Katherine W.

    The methods used and the results obtained by means of the accelerated language learning techniques developed by Georgi Lozanov, Director of the Institute of Suggestology in Bulgaria, are discussed. The following topics are included: (1) discussion of hypermnesia, "super memory," and the reasons foreign languages were chosen for purposes…

  10. MAGIC Study: Aims, Design and Methods using SystemCHANGE™ to Improve Immunosuppressive Medication Adherence in Adult Kidney Transplant Recipients.

    Science.gov (United States)

    Russell, Cynthia L; Moore, Shirley; Hathaway, Donna; Cheng, An-Lin; Chen, Guoqing; Goggin, Kathy

    2016-07-16

    Among adult kidney transplant recipients, non-adherence to immunosuppressive medications is the leading predictor of poor outcomes, including rejection, kidney loss, and death. An alarming one-third of kidney transplant patients experience medication non-adherence even though the problem is preventable. Existing adherence interventions have proven marginally effective for those with acute and chronic illnesses and ineffective for adult kidney transplant recipients. Our purpose is to describe the design and methods of the MAGIC (Medication Adherence Given Individual SystemCHANGE™) trial We report the design of a randomized controlled trial with an attention-control group to test an innovative 6-month SystemCHANGE™ intervention designed to enhance immunosuppressive medication adherence in adult non-adherent kidney transplant recipients from two transplant centers. Grounded in the Socio-Ecological Model, SystemCHANGE™ seeks to systematically improve medication adherence behaviors by identifying and shaping routines, involving supportive others in routines, and using medication taking feedback through small patient-led experiments to change and maintain behavior. After a 3-month screening phase of 190 eligible adult kidney transplant recipients, those who are adherent as measured by electronic monitoring, will be randomized into a 6-month SystemCHANGE™ intervention or attention-control phase, followed by a 6-month maintenance phase without intervention or attention. Differences in adherence between the two groups will be assessed at baseline, 6 months (intervention phase) and 12 months (maintenance phase). Adherence mediators (social support, systems-thinking) and moderators (ethnicity, perceived health) are examined. Patient outcomes (creatinine/blood urea nitrogen, infection, acute/chronic rejection, graft loss, death) and cost effectiveness are to be examined. Based on the large effect size of 1.4 found in our pilot study, intervention shows great promise

  11. Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn

    OpenAIRE

    Dwi Nur Rachmah

    2017-01-01

    Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas La...

  12. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  13. Project Oriented Immersion Learning: Method and Results

    DEFF Research Database (Denmark)

    Icaza, José I.; Heredia, Yolanda; Borch, Ole M.

    2005-01-01

    A pedagogical approach called “project oriented immersion learning” is presented and tested on a graduate online course. The approach combines the Project Oriented Learning method with immersion learning in a virtual enterprise. Students assumed the role of authors hired by a fictitious publishing...... house that develops digital products including e-books, tutorials, web sites and so on. The students defined the problem that their product was to solve; choose the type of product and the content; and built the product following a strict project methodology. A wiki server was used as a platform to hold...

  14. The method of global learning in teaching foreign languages

    Directory of Open Access Journals (Sweden)

    Tatjana Dragovič

    2001-12-01

    Full Text Available The authors describe the method of global learning of foreign languages, which is based on the principles of neurolinguistic programming (NLP. According to this theory, the educator should use the method of the so-called periphery learning, where students learn relaxation techniques and at the same time they »incidentally « or subconsciously learn a foreign language. The method of global learning imitates successful strategies of learning in early childhood and therefore creates a relaxed attitude towards learning. Global learning is also compared with standard methods.

  15. AIMES Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Jha, Shantenu [Rutgers Univ., New Brunswick, NJ (United States)

    2017-01-31

    Many important advances in science and engineering are due to large-scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scienti c distributed applications [1]. The survey established, arguably for the rst time, the relationship between infrastructure and scienti c distributed applications. It examined well known contributors to the complexity associated with infrastructure, such as inconsistent internal and external interfaces, and demonstrated the correlation with application brittleness. It discussed how infrastructure complexity reinforces the challenges inherent in developing distributed applications.

  16. Project-Based Learning Using Discussion and Lesson-Learned Methods via Social Media Model for Enhancing Problem Solving Skills

    Science.gov (United States)

    Jewpanich, Chaiwat; Piriyasurawong, Pallop

    2015-01-01

    This research aims to 1) develop the project-based learning using discussion and lesson-learned methods via social media model (PBL-DLL SoMe Model) used for enhancing problem solving skills of undergraduate in education student, and 2) evaluate the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student.…

  17. Machine Learning Methods for Production Cases Analysis

    Science.gov (United States)

    Mokrova, Nataliya V.; Mokrov, Alexander M.; Safonova, Alexandra V.; Vishnyakov, Igor V.

    2018-03-01

    Approach to analysis of events occurring during the production process were proposed. Described machine learning system is able to solve classification tasks related to production control and hazard identification at an early stage. Descriptors of the internal production network data were used for training and testing of applied models. k-Nearest Neighbors and Random forest methods were used to illustrate and analyze proposed solution. The quality of the developed classifiers was estimated using standard statistical metrics, such as precision, recall and accuracy.

  18. AIMES Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Katz, Daniel S [Univ. of Illinois, Urbana-Champaign, IL (United States). National Center for Supercomputing Applications (NCSA); Jha, Shantenu [Rutgers Univ., New Brunswick, NJ (United States); Weissman, Jon [Univ. of Minnesota, Minneapolis, MN (United States); Turilli, Matteo [Rutgers Univ., New Brunswick, NJ (United States)

    2017-01-31

    This is the final technical report for the AIMES project. Many important advances in science and engineering are due to large-scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). This is evidenced by missing design principles for DCI, and an absence of generally acceptable and usable distributed computing abstractions. The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scientific distributed applications. AIMES laid the foundations to address the tripartite challenge of dynamic resource management, integrating information, and portable and interoperable distributed applications. Four abstractions were defined and implemented: skeleton, resource bundle, pilot, and execution strategy. The four abstractions were implemented into software modules and then aggregated into the AIMES middleware. This middleware successfully integrates information across the application layer (skeletons) and resource layer (Bundles), derives a suitable execution strategy for the given skeleton and enacts its execution by means of pilots on one or more resources, depending on the application requirements, and resource availabilities and capabilities.

  19. Learners with learning difficulties in mathematics : attitudes, curriculum and methods of teaching mathematics

    OpenAIRE

    2012-01-01

    D.Ed. The aim of this theses is to find out whether there is any relationship between learners' attitudes and learning difficulties in mathematics: To investigate whether learning difficulties in mathematics are associated with learners' gender. To establish the nature of teachers' perceptions of the learning problem areas in the mathematics curriculum. To find out about the teachers' views on the methods of teaching mathematics, resources, learning of mathematics, extra curricular activit...

  20. Smoking Cessation Counseling for Asian Immigrants With Serious Mental Illness: Using RE-AIM to Understand Challenges and Lessons Learned in Primary Care–Behavioral Health Integration

    Science.gov (United States)

    Saw, Anne; Kim, Jin; Lim, Joyce; Powell, Catherine; Tong, Elisa K.

    2016-01-01

    Engagement in modifiable risk behaviors, such as tobacco use, substantially contributes to early mortality rates in individuals with serious mental illness (SMI). There is an alarmingly high prevalence of tobacco use among subgroups of Asian Americans, such as immigrants and individuals with SMI, yet there are no empirically supported effective smoking cessation interventions that have been tailored to meet the unique cultural, cognitive, and psychological needs of Asian immigrants with SMI. In this article, we share the experiences of clinicians in the delivery of smoking cessation counseling to Asian American immigrants with SMI, in the context of an Asian-focused integrated primary care and behavioral health setting. Through a qualitative analysis of clinician perspectives organized with the RE-AIM framework, we outline challenges, lessons learned, and promising directions for delivering smoking cessation counseling to Asian American immigrant clients with SMI. PMID:23667056

  1. Smoking cessation counseling for Asian immigrants with serious mental illness: using RE-AIM to understand challenges and lessons learned in primary care-behavioral health integration.

    Science.gov (United States)

    Saw, Anne; Kim, Jin; Lim, Joyce; Powell, Catherine; Tong, Elisa K

    2013-09-01

    Engagement in modifiable risk behaviors, such as tobacco use, substantially contributes to early mortality rates in individuals with serious mental illness (SMI). There is an alarmingly high prevalence of tobacco use among subgroups of Asian Americans, such as immigrants and individuals with SMI, yet there are no empirically supported effective smoking cessation interventions that have been tailored to meet the unique cultural, cognitive, and psychological needs of Asian immigrants with SMI. In this article, we share the experiences of clinicians in the delivery of smoking cessation counseling to Asian American immigrants with SMI, in the context of an Asian-focused integrated primary care and behavioral health setting. Through a qualitative analysis of clinician perspectives organized with the RE-AIM framework, we outline challenges, lessons learned, and promising directions for delivering smoking cessation counseling to Asian American immigrant clients with SMI.

  2. Decentralized indirect methods for learning automata games.

    Science.gov (United States)

    Tilak, Omkar; Martin, Ryan; Mukhopadhyay, Snehasis

    2011-10-01

    We discuss the application of indirect learning methods in zero-sum and identical payoff learning automata games. We propose a novel decentralized version of the well-known pursuit learning algorithm. Such a decentralized algorithm has significant computational advantages over its centralized counterpart. The theoretical study of such a decentralized algorithm requires the analysis to be carried out in a nonstationary environment. We use a novel bootstrapping argument to prove the convergence of the algorithm. To our knowledge, this is the first time that such analysis has been carried out for zero-sum and identical payoff games. Extensive simulation studies are reported, which demonstrate the proposed algorithm's fast and accurate convergence in a variety of game scenarios. We also introduce the framework of partial communication in the context of identical payoff games of learning automata. In such games, the automata may not communicate with each other or may communicate selectively. This comprehensive framework has the capability to model both centralized and decentralized games discussed in this paper.

  3. Implementing Collaborative Learning Methods in the Political Science Classroom

    Science.gov (United States)

    Wolfe, Angela

    2012-01-01

    Collaborative learning is one, among other, active learning methods, widely acclaimed in higher education. Consequently, instructors in fields that lack pedagogical training often implement new learning methods such as collaborative learning on the basis of trial and error. Moreover, even though the benefits in academic circles are broadly touted,…

  4. Exploring the dynamic relationship between the Accelerative Integrated Method (AIM and the core French teachers who use it: Why agency and experience matter.

    Directory of Open Access Journals (Sweden)

    Stephanie Arnott

    2011-12-01

    Full Text Available Abstract Over the last decade, almost 4,000 Canadian schools have moved to using the Accelerative Integrated Method (AIM for core French (CF instruction. Following researchers’ recommendations (Brumfit, 1984; Lapkin, Mady, & Arnott, 2009; Larsen-Freeman, 1996, 2000; Prahbu, 1990, I am shifting the focus in this case study from product to process. In other words, investigating how AIM teachers use and shape the method during implementation instead of comparing AIM and non-AIM student outcomes (Bourdages & Vignola, 2009; Carr, 2001; Mady, Arnott, & Lapkin, 2009; Maxwell, 2001; Michels, 2008;. Four interviews and observation sessions were conducted with eight elementary-level CF teachers. Findings showed that while some AIM routines and strategies were used by all, teachers exercised their agency in supplementing recommended AIM activities and materials, especially those with more AIM and CF teaching experience. Establishing that using AIM engaged teachers’ senses of plausibility (Prahbu, 1990 also exposed important implications for future AIM research and board-level policy. Résumé Depuis les années 2000, plus de 4000 écoles canadiennes ont decidé d’utiliser une forme d’enseignement qui s’appelle AIM (Accelerative Integrated Method pour leurs programmes de français de base (Core French. Selon les recommandations des chercheurs suivants (Brumfit, 1984; Lapkin, Mady, & Arnott, 2009; Larsen-Freeman, 1996, 2000; Prahbu, 1990, au lieu d’étudier les résultats, l’objectif de cette étude de cas était d’examiner la mise en œuvre de AIM. Huit enseignants de français de base ont passé quatre entrevues individuelles. Ils ont eu quatre sessions d’observation de pratique de AIM . Selon les résultats, quoiqu’ils aient employé des stratégies et routines de AIM de la même façon, tous les enseignants ont aussi décidé d’ajouter leurs propres activités et ressources à AIM, surtout ceux experts dans l’enseignement du fran

  5. Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods.

    Science.gov (United States)

    Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

    2018-01-01

    Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.

  6. The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods

    NARCIS (Netherlands)

    Verpoorten, Dominique; Poumay, M; Leclercq, D

    2006-01-01

    Please, cite this publication as: Verpoorten, D., Poumay, M., & Leclercq, D. (2006). The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence

  7. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

    OpenAIRE

    Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal, Ginsburg, & Schau, 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof, Ceroni, Jeong, & Moghaddam, 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to...

  8. Statistical learning methods in high-energy and astrophysics analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)

    2004-11-21

    We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.

  9. Statistical learning methods in high-energy and astrophysics analysis

    International Nuclear Information System (INIS)

    Zimmermann, J.; Kiesling, C.

    2004-01-01

    We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application

  10. [Aiming for zero blindness].

    Science.gov (United States)

    Nakazawa, Toru

    2015-03-01

    -independent factors, as well as our investigation of ways to improve the clinical evaluation of the disease. Our research was prompted by the multifactorial nature of glaucoma. There is a high degree of variability in the pattern and speed of the progression of visual field defects in individual patients, presenting a major obstacle for successful clinical trials. To overcome this, we classified the eyes of glaucoma patients into 4 types, corresponding to the 4 patterns of glaucomatous optic nerve head morphology described: by Nicolela et al. and then tested the validity of this method by assessing the uniformity of clinical features in each group. We found that in normal tension glaucoma (NTG) eyes, each disc morphology group had a characteristic location in which the loss of circumpapillary retinal nerve fiber layer thickness (cpRNFLT; measured with optical coherence tomography: OCT) was most likely to occur. Furthermore, the incidence of reductions in visual acuity differed between the groups, as did the speed of visual field loss, the distribution of defective visual field test points, and the location of test points that were most susceptible to progressive damage, measured by Humphrey static perimetry. These results indicate that Nicolela's method of classifying eyes with glaucoma was able to overcome the difficulties caused by the diverse nature of the disease, at least to a certain extent. Building on these findings, we then set out to identify sectors of the visual field that correspond to the distribution of retinal nerve fibers, with the aim of detecting glaucoma progression with improved sensitivity. We first mapped the statistical correlation between visual field test points and cpRNFLT in each temporal clock-hour sector (from 6 to 12 o'clock), using OCT data from NTG patients. The resulting series of maps allowed us to identify areas containing visual field test points that were prone to be affected together as a group. We also used a similar method to identify visual

  11. Learning phacoemulsification. Results of different teaching methods.

    Directory of Open Access Journals (Sweden)

    Hennig Albrecht

    2004-01-01

    Full Text Available We report the learning curves of three eye surgeons converting from sutureless extracapsular cataract extraction to phacoemulsification using different teaching methods. Posterior capsule rupture (PCR as a per-operative complication and visual outcome of the first 100 operations were analysed. The PCR rate was 4% and 15% in supervised and unsupervised surgery respectively. Likewise, an uncorrected visual acuity of > or = 6/18 on the first postoperative day was seen in 62 (62% of patients and in 22 (22% in supervised and unsupervised surgery respectively.

  12. Subsampled Hessian Newton Methods for Supervised Learning.

    Science.gov (United States)

    Wang, Chien-Chih; Huang, Chun-Heng; Lin, Chih-Jen

    2015-08-01

    Newton methods can be applied in many supervised learning approaches. However, for large-scale data, the use of the whole Hessian matrix can be time-consuming. Recently, subsampled Newton methods have been proposed to reduce the computational time by using only a subset of data for calculating an approximation of the Hessian matrix. Unfortunately, we find that in some situations, the running speed is worse than the standard Newton method because cheaper but less accurate search directions are used. In this work, we propose some novel techniques to improve the existing subsampled Hessian Newton method. The main idea is to solve a two-dimensional subproblem per iteration to adjust the search direction to better minimize the second-order approximation of the function value. We prove the theoretical convergence of the proposed method. Experiments on logistic regression, linear SVM, maximum entropy, and deep networks indicate that our techniques significantly reduce the running time of the subsampled Hessian Newton method. The resulting algorithm becomes a compelling alternative to the standard Newton method for large-scale data classification.

  13. Influence on Learning of a Collaborative Learning Method Comprising the Jigsaw Method and Problem-based Learning (PBL).

    Science.gov (United States)

    Takeda, Kayoko; Takahashi, Kiyoshi; Masukawa, Hiroyuki; Shimamori, Yoshimitsu

    2017-01-01

    Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.

  14. COOPERATIVE LEARNING IN DISTANCE LEARNING: A MIXED METHODS STUDY

    Directory of Open Access Journals (Sweden)

    Lori Kupczynski

    2012-07-01

    Full Text Available Distance learning has facilitated innovative means to include Cooperative Learning (CL in virtual settings. This study, conducted at a Hispanic-Serving Institution, compared the effectiveness of online CL strategies in discussion forums with traditional online forums. Quantitative and qualitative data were collected from 56 graduate student participants. Quantitative results revealed no significant difference on student success between CL and Traditional formats. The qualitative data revealed that students in the cooperative learning groups found more learning benefits than the Traditional group. The study will benefit instructors and students in distance learning to improve teaching and learning practices in a virtual classroom.

  15. Machine learning methods for metabolic pathway prediction

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2010-01-01

    Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

  16. Machine learning methods for metabolic pathway prediction

    Science.gov (United States)

    2010-01-01

    Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML) methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations. PMID:20064214

  17. Student Achievement in Basic College Mathematics: Its Relationship to Learning Style and Learning Method

    Science.gov (United States)

    Gunthorpe, Sydney

    2006-01-01

    From the assumption that matching a student's learning style with the learning method best suited for the student, it follows that developing courses that correlate learning method with learning style would be more successful for students. Albuquerque Technical Vocational Institute (TVI) in New Mexico has attempted to provide students with more…

  18. Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods

    Science.gov (United States)

    Soroush, Masoud; Weinberger, Charles B.

    2010-01-01

    This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…

  19. The Method of High School English Word Learning

    Institute of Scientific and Technical Information of China (English)

    吴博涵

    2016-01-01

    Most Chinese students are not interested in English learning, especially English words. In this paper, I focus on English vocabulary learning, for example, the study of high school students English word learning method, and also introduce several ways to make vocabulary memory becomes more effective. The purpose is to make high school students grasp more English word learning skills.

  20. Motivations, aims and communication around advance directives A mixed-methods study into the perspective of their owners and the influence of a current illness

    NARCIS (Netherlands)

    van Wijmen, M.P.S.; Pasman, H.R.W.; Widdershoven, G.A.M.; Onwuteaka-Philipsen, B.D.

    2014-01-01

    Objective: What are motivations of owners of an advance directive (AD) to draft an AD, what do they aim for with their AD and do they communicate about their AD? Methods: Written questionnaires were sent to a cohort of people owning different types of ADs (n= 5768). A purposive sample of people

  1. Exploring the Dynamic Relationship between the Accelerative Integrated Method (AIM) and the Core French Teachers Who Use It: Why Agency and Experience Matter

    Science.gov (United States)

    Arnott, Stephanie

    2011-01-01

    Over the last decade, almost 4,000 Canadian schools have moved to using the Accelerative Integrated Method (AIM) for core French (CF) instruction. Following researchers' recommendations (Brumfit, 1984; Lapkin, Mady, & Arnott, 2009; Larsen-Freeman, 1996, 2000; Prahbu, 1990), I am shifting the focus in this case study from product to process. In…

  2. E-learning as new method of medical education.

    Science.gov (United States)

    Masic, Izet

    2008-01-01

    status and level of tele-education development in Bosnia and Herzegovina outlining its components, faculty development needs for implementation and the possibility of its integration as official learning standard in biomedical curricula in Bosnia and Herzegovina. Tele-education refers to the use of information and communication technologies (ICT) to enhance knowledge and performance. Tele-education in biomedical education is widely accepted in the medical education community where it is mostly integrated into biomedical curricula forming part of a blended learning strategy. There are many biomedical digital repositories of e-learning materials worldwide, some peer reviewed, where instructors or developers can submit materials for widespread use. First pilot project with the aim to introduce tele-education in biomedical curricula in Bosnia and Herzegovina was initiated by Department for Medical Informatics at Medical Faculty in Sarajevo in 2002 and has been developing since. Faculty member's skills in creating tele-education differ from those needed for traditional teaching and faculty rewards must recognize this difference and reward the effort. Tele-education and use of computers will have an impact of future medical practice in a life long learning. Bologna process, which started last years in European countries, provide us to promote and introduce modern educational methods of education at biomedical faculties in Bosnia and Herzegovina. Cathedra of Medical informatics and Cathedra of Family medicine at Medical Faculty of University of Sarajevo started to use Web based education as common way of teaching of medical students. Satisfaction with this method of education within the students is good, but not yet suitable for most of medical disciplines at biomedical faculties in Bosnia and Herzegovina.

  3. Enhancing the Pronunciation of English Suprasegmental Features through Reflective Learning Method

    Science.gov (United States)

    Suwartono

    2014-01-01

    Suprasegmental features are of paramount importance in spoken English. Yet, these pronunciation features are marginalised in EFL/ESL teaching-learning. This article reported a study that was aimed at improving the students' mastery of English suprasegmental features through the use of reflective learning method. The study adopted Kemmis and…

  4. Machine Learning and Data Mining Methods in Diabetes Research.

    Science.gov (United States)

    Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

    2017-01-01

    The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

  5. Teaching and learning methods in IVET

    DEFF Research Database (Denmark)

    Aarkrog, Vibe

    The cases deals about learner centered learning in a commercial program and a technical program.......The cases deals about learner centered learning in a commercial program and a technical program....

  6. The Implementation of Discovery Learning Method to Increase Learning Outcomes and Motivation of Student in Senior High School

    Directory of Open Access Journals (Sweden)

    Nanda Saridewi

    2017-11-01

    Full Text Available Based on data from the observation of high school students grade XI that daily low student test scores due to a lack of role of students in the learning process. This classroom action research aims to improve learning outcomes and student motivation through discovery learning method in colloidal material. This study uses the approach developed by Lewin consisting of planning, action, observation, and reflection. Data collection techniques used the questionnaires and ability tests end. Based on the research that results for students received a positive influence on learning by discovery learning model by increasing the average value of 74 students from the first cycle to 90.3 in the second cycle and increased student motivation in the form of two statements based competence (KD categories (sometimes on the first cycle and the first statement KD category in the second cycle. Thus the results of this study can be used to improve learning outcomes and student motivation

  7. Building Customer Churn Prediction Models in Fitness Industry with Machine Learning Methods

    OpenAIRE

    Shan, Min

    2017-01-01

    With the rapid growth of digital systems, churn management has become a major focus within customer relationship management in many industries. Ample research has been conducted for churn prediction in different industries with various machine learning methods. This thesis aims to combine feature selection and supervised machine learning methods for defining models of churn prediction and apply them on fitness industry. Forward selection is chosen as feature selection methods. Support Vector ...

  8. Analysis of D Dimensional Dirac equation for q -deformed Posch-Teller combined with q -deformed trigonometric Manning Rosen Non-Central potential using Asymptotic Iteration Method (AIM)

    International Nuclear Information System (INIS)

    Alam, Y.; Suparmi; Cari; Anwar, F.

    2016-01-01

    In this study, we used asymptotic iteration method (AIM) to obtain the relativistic energy spectra and wavefunctions for D Dimensional Dirac equation. Solution of the D Dimensional Dirac equation using asymptotic iteration method was done by four steps. The first step, we substitutied q deformed Poschl-Teller potential plus q-deformed Manning Rosen Non-Central potential into D dimensional Dirac equation. And then, general term of D dimensioanl Dirac equation for q deformed Poschl-Teller potential plus q-deformed Manning Rosen Non-Central potential was reduced into one dimensioanal Dirac equation, consist of radial part and angular part. The second step, both of one dimensional part must be reduced to hypergeometric type differential equation by suitable parameter change. And then, hypergeometric type differential equation was transformed into AIM type differential equation. For the last step, AIM type differential equation can be solved to obtain the relativistic energy and wavefunctions of Dirac equation. Relativistic energy and wavefunctions were visualized by using Matlab software. (paper)

  9. Deep learning versus traditional machine learning methods for aggregated energy demand prediction

    NARCIS (Netherlands)

    Paterakis, N.G.; Mocanu, E.; Gibescu, M.; Stappers, B.; van Alst, W.

    2018-01-01

    In this paper the more advanced, in comparison with traditional machine learning approaches, deep learning methods are explored with the purpose of accurately predicting the aggregated energy consumption. Despite the fact that a wide range of machine learning methods have been applied to

  10. Preparing Students for Flipped or Team-Based Learning Methods

    Science.gov (United States)

    Balan, Peter; Clark, Michele; Restall, Gregory

    2015-01-01

    Purpose: Teaching methods such as Flipped Learning and Team-Based Learning require students to pre-learn course materials before a teaching session, because classroom exercises rely on students using self-gained knowledge. This is the reverse to "traditional" teaching when course materials are presented during a lecture, and students are…

  11. Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn

    Directory of Open Access Journals (Sweden)

    Dwi Nur Rachmah

    2017-12-01

    Full Text Available Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas Lambung Mangkurat. The method used in the study is the experimental method using one group pre-test and post-test design. The results of the measurements before and after the use of jigsaw learning method were compared using paired samples t-test. The results showed that there is a difference in students’ self-efficacy and motivation to learn before and after subjected to the treatments; therefore, it can be said that jigsaw learning method had significant effects on self-efficacy and motivation to learn. The application of jigsaw learning model in a classroom with large number of students was the discussion of this study.

  12. A Swarm-Based Learning Method Inspired by Social Insects

    Science.gov (United States)

    He, Xiaoxian; Zhu, Yunlong; Hu, Kunyuan; Niu, Ben

    Inspired by cooperative transport behaviors of ants, on the basis of Q-learning, a new learning method, Neighbor-Information-Reference (NIR) learning method, is present in the paper. This is a swarm-based learning method, in which principles of swarm intelligence are strictly complied with. In NIR learning, the i-interval neighbor's information, namely its discounted reward, is referenced when an individual selects the next state, so that it can make the best decision in a computable local neighborhood. In application, different policies of NIR learning are recommended by controlling the parameters according to time-relativity of concrete tasks. NIR learning can remarkably improve individual efficiency, and make swarm more "intelligent".

  13. Arts-based Methods and Organizational Learning

    DEFF Research Database (Denmark)

    This thematic volume explores the relationship between the arts and learning in various educational contexts and across cultures, but with a focus on higher education and organizational learning. Arts-based interventions are at the heart of this volume, which addresses how they are conceived, des...

  14. Reasons and Methods to Learn the Management

    Science.gov (United States)

    Li, Hongxin; Ding, Mengchun

    2010-01-01

    Reasons for learning the management include (1) perfecting the knowledge structure, (2) the management is the base of all organizations, (3) one person may be the manager or the managed person, (4) the management is absolutely not simple knowledge, and (5) the learning of the theoretical knowledge of the management can not be replaced by the…

  15. Microgenetic Learning Analytics Methods: Workshop Report

    Science.gov (United States)

    Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin

    2016-01-01

    Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…

  16. Statistical learning modeling method for space debris photometric measurement

    Science.gov (United States)

    Sun, Wenjing; Sun, Jinqiu; Zhang, Yanning; Li, Haisen

    2016-03-01

    Photometric measurement is an important way to identify the space debris, but the present methods of photometric measurement have many constraints on star image and need complex image processing. Aiming at the problems, a statistical learning modeling method for space debris photometric measurement is proposed based on the global consistency of the star image, and the statistical information of star images is used to eliminate the measurement noises. First, the known stars on the star image are divided into training stars and testing stars. Then, the training stars are selected as the least squares fitting parameters to construct the photometric measurement model, and the testing stars are used to calculate the measurement accuracy of the photometric measurement model. Experimental results show that, the accuracy of the proposed photometric measurement model is about 0.1 magnitudes.

  17. Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

    Science.gov (United States)

    Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

    2017-12-04

    Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further

  18. Optimization of instrumental neutron activation analysis method by means of 2k experimental design technique aiming the validation of analytical procedures

    International Nuclear Information System (INIS)

    Petroni, Robson; Moreira, Edson G.

    2013-01-01

    In this study optimization of procedures and standardization of Instrumental Neutron Activation Analysis (INAA) methods were carried out for the determination of the elements arsenic, chromium, cobalt, iron, rubidium, scandium, selenium and zinc in biological materials. The aim is to validate the analytical methods for future accreditation at the National Institute of Metrology, Quality and Technology (INMETRO). The 2 k experimental design was applied for evaluation of the individual contribution of selected variables of the analytical procedure in the final mass fraction result. Samples of Mussel Tissue Certified Reference Material and multi-element standards were analyzed considering the following variables: sample decay time, counting time and sample distance to detector. The standard multi-element concentration (comparator standard), mass of the sample and irradiation time were maintained constant in this procedure. By means of the statistical analysis and theoretical and experimental considerations it was determined the optimized experimental conditions for the analytical methods that will be adopted for the validation procedure of INAA methods in the Neutron Activation Analysis Laboratory (LAN) of the Research Reactor Center (CRPq) at the Nuclear and Energy Research Institute (IPEN - CNEN/SP). Optimized conditions were estimated based on the results of z-score tests, main effect and interaction effects. The results obtained with the different experimental configurations were evaluated for accuracy (precision and trueness) for each measurement. (author)

  19. Optimization of instrumental neutron activation analysis method by means of 2{sup k} experimental design technique aiming the validation of analytical procedures

    Energy Technology Data Exchange (ETDEWEB)

    Petroni, Robson; Moreira, Edson G., E-mail: rpetroni@ipen.br, E-mail: emoreira@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2013-07-01

    In this study optimization of procedures and standardization of Instrumental Neutron Activation Analysis (INAA) methods were carried out for the determination of the elements arsenic, chromium, cobalt, iron, rubidium, scandium, selenium and zinc in biological materials. The aim is to validate the analytical methods for future accreditation at the National Institute of Metrology, Quality and Technology (INMETRO). The 2{sup k} experimental design was applied for evaluation of the individual contribution of selected variables of the analytical procedure in the final mass fraction result. Samples of Mussel Tissue Certified Reference Material and multi-element standards were analyzed considering the following variables: sample decay time, counting time and sample distance to detector. The standard multi-element concentration (comparator standard), mass of the sample and irradiation time were maintained constant in this procedure. By means of the statistical analysis and theoretical and experimental considerations it was determined the optimized experimental conditions for the analytical methods that will be adopted for the validation procedure of INAA methods in the Neutron Activation Analysis Laboratory (LAN) of the Research Reactor Center (CRPq) at the Nuclear and Energy Research Institute (IPEN - CNEN/SP). Optimized conditions were estimated based on the results of z-score tests, main effect and interaction effects. The results obtained with the different experimental configurations were evaluated for accuracy (precision and trueness) for each measurement. (author)

  20. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

    Science.gov (United States)

    Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

  1. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

    Science.gov (United States)

    Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

  2. Question presentation methods for paired-associate learning

    NARCIS (Netherlands)

    Engel, F.L.; Geerings, M.P.W.

    1988-01-01

    Four different methods of question presentation, in interactive computeraided learning of Dutch-English word pairs are evaluated experimentally. These methods are: 1) the 'open-question method', 2) the 'multiple-choice method', 3) the 'sequential method' and 4) the 'true/ false method'. When

  3. Efficient model learning methods for actor-critic control.

    Science.gov (United States)

    Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

    2012-06-01

    We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

  4. Ensemble Machine Learning Methods and Applications

    CERN Document Server

    Ma, Yunqian

    2012-01-01

    It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

  5. Adaptive e-learning methods and IMS Learning Design. An integrated approach

    NARCIS (Netherlands)

    Burgos, Daniel; Specht, Marcus

    2006-01-01

    Please, cite this publication as: Burgos, D., & Specht, M. (2006). Adaptive e-learning methods and IMS Learning Design. In Kinshuk, R. Koper, P. Kommers, P. Kirschner, D. G. Sampson & W. Didderen (Eds.), Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies (pp.

  6. An Innovative Teaching Method To Promote Active Learning: Team-Based Learning

    Science.gov (United States)

    Balasubramanian, R.

    2007-12-01

    Traditional teaching practice based on the textbook-whiteboard- lecture-homework-test paradigm is not very effective in helping students with diverse academic backgrounds achieve higher-order critical thinking skills such as analysis, synthesis, and evaluation. Consequently, there is a critical need for developing a new pedagogical approach to create a collaborative and interactive learning environment in which students with complementary academic backgrounds and learning skills can work together to enhance their learning outcomes. In this presentation, I will discuss an innovative teaching method ('Team-Based Learning (TBL)") which I recently developed at National University of Singapore to promote active learning among students in the environmental engineering program with learning abilities. I implemented this new educational activity in a graduate course. Student feedback indicates that this pedagogical approach is appealing to most students, and promotes active & interactive learning in class. Data will be presented to show that the innovative teaching method has contributed to improved student learning and achievement.

  7. GEP-based method to formulate adhesion strength and hardness of Nb PVD coated on Ti-6Al-7Nb aimed at developing mixed oxide nanotubular arrays.

    Science.gov (United States)

    Rafieerad, A R; Bushroa, A R; Nasiri-Tabrizi, B; Fallahpour, A; Vadivelu, J; Musa, S N; Kaboli, S H A

    2016-08-01

    PVD process as a thin film coating method is highly applicable for both metallic and ceramic materials, which is faced with the necessity of choosing the correct parameters to achieve optimal results. In the present study, a GEP-based model for the first time was proposed as a safe and accurate method to predict the adhesion strength and hardness of the Nb PVD coated aimed at growing the mixed oxide nanotubular arrays on Ti67. Here, the training and testing analysis were executed for both adhesion strength and hardness. The optimum parameter combination for the scratch adhesion strength and micro hardness was determined by the maximum mean S/N ratio, which was 350W, 20 sccm, and a DC bias of 90V. Results showed that the values calculated in the training and testing in GEP model were very close to the actual experiments designed by Taguchi. The as-sputtered Nb coating with highest adhesion strength and microhardness was electrochemically anodized at 20V for 4h. From the FESEM images and EDS results of the annealed sample, a thick layer of bone-like apatite was formed on the sample surface after soaking in SBF for 10 days, which can be connected to the development of a highly ordered nanotube arrays. This novel approach provides an outline for the future design of nanostructured coatings for a wide range of applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Problem-Based Learning Method: Secondary Education 10th Grade Chemistry Course Mixtures Topic

    Science.gov (United States)

    Üce, Musa; Ates, Ismail

    2016-01-01

    In this research; aim was determining student achievement by comparing problem-based learning method with teacher-centered traditional method of teaching 10th grade chemistry lesson mixtures topic. Pretest-posttest control group research design is implemented. Research sample includes; two classes of (total of 48 students) an Anatolian High School…

  9. Unsupervised process monitoring and fault diagnosis with machine learning methods

    CERN Document Server

    Aldrich, Chris

    2013-01-01

    This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data

  10. Methodical approaches to managing risks for endocrine diseases evolvement in children related to impacts of environmental factors occuring on areas aimed for development

    Directory of Open Access Journals (Sweden)

    K.P. Luzhetskiy

    2017-06-01

    Full Text Available It is vital to develop systems of preventing risk-associated pathology due to constantly high levels of endocrine diseases in children exposed to chemicals with trophic effects on endocrine system (lead, cadmium, manganese, chromium, nickel, benzene, phenol, formaldehyde, benzpyrene, chlorine-organic compounds, and nitrates. Applying risk management techniques is one of the most promising trends in prevention of diseases related to environmental impacts. We offer methodical approaches based on system combination of activities at various management levels aimed at improving risk-oriented model of surveillance and control. These approaches enable allowing for detected thropic risk factors in regional social-hygienic monitoring programs, implementing algorithms of case monitoring over exposed children population, and applying contemporary prevention technologies. Social-hygienic monitoring improvement at territorial level implies stricter control and more comprehensive lists of monitored components. This can be achieved by studying compounds which form risks for endocrine system, by working out scientific-methodological grounds for accounting chemical compounds which are trophic for endocrine system, as well as by refining volumes and contents of scheduled inspections performed at high risks objects together with laboratory examination of chemical compounds including those thropic for endocrine system. Local level includes algorithms and schemes of prevention activities aimed at early detection of endocrine disorders related to chemicals impacts. When we give grounds for personified technologies of endocrine diseases prevention (alimentary disorders, physical retardation and obesity related to impacts exerted by chemicals which are trophic for endocrine system we should remember that individual programs choice is based not only on their capacity to eliminate priority compounds determining total chemical load on a person faster but also on

  11. Are students' impressions of improved learning through active learning methods reflected by improved test scores?

    Science.gov (United States)

    Everly, Marcee C

    2013-02-01

    To report the transformation from lecture to more active learning methods in a maternity nursing course and to evaluate whether student perception of improved learning through active-learning methods is supported by improved test scores. The process of transforming a course into an active-learning model of teaching is described. A voluntary mid-semester survey for student acceptance of the new teaching method was conducted. Course examination results, from both a standardized exam and a cumulative final exam, among students who received lecture in the classroom and students who had active learning activities in the classroom were compared. Active learning activities were very acceptable to students. The majority of students reported learning more from having active-learning activities in the classroom rather than lecture-only and this belief was supported by improved test scores. Students who had active learning activities in the classroom scored significantly higher on a standardized assessment test than students who received lecture only. The findings support the use of student reflection to evaluate the effectiveness of active-learning methods and help validate the use of student reflection of improved learning in other research projects. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Exploring an experiential learning project through Kolb's Learning Theory using a qualitative research method

    Science.gov (United States)

    Yuk Chan, Cecilia Ka

    2012-08-01

    Experiential learning pedagogy is taking a lead in the development of graduate attributes and educational aims as these are of prime importance for society. This paper shows a community service experiential project conducted in China. The project enabled students to serve the affected community in a post-earthquake area by applying their knowledge and skills. This paper documented the students' learning process from their project goals, pre-trip preparations, work progress, obstacles encountered to the final results and reflections. Using the data gathered from a focus group interview approach, the four components of Kolb's learning cycle, the concrete experience, reflection observation, abstract conceptualisation and active experimentation, have been shown to transform and internalise student's learning experience, achieving a variety of learning outcomes. The author will also explore how this community service type of experiential learning in the engineering discipline allowed students to experience deep learning and develop their graduate attributes.

  13. A mixed methods process evaluation of the implementation of JUMP-in, a multilevel school-based intervention aimed at physical activity promotion.

    Science.gov (United States)

    de Meij, Judith S B; van der Wal, Marcel F; van Mechelen, Willem; Chinapaw, Mai J M

    2013-09-01

    The aim of the present study was to investigate factors influencing the adoption, implementation, and institutionalization process of JUMP-in-a multilevel school-based physical activity promotion program-to optimize the dissemination of the intervention and improve its effectiveness. The process evaluation concerned the constraints and success and failure factors at sociopolitical, organizational, user, and intervention levels. A mixed methods approach including qualitative and quantitative data was conducted during two school years (2006-2008). JUMP-in was successfully embedded in the Amsterdam municipal policy and in the organizational structure and daily practices of the sectors involved. A general impeding factor was the complexity of the multilevel programme requiring multidisciplinary collaboration between organizations. In addition, there was a discrepancy between the recommendation to standardize and simplify the innovation and the need to tailor the strategies to local environmental, social, and cultural aspects. This process evaluation provides challenges and remedies for managing discrepancies between prerequisites for an effective innovation and demands of daily implementation practice. The main recommendations are (a) standardized, simplified guidelines; (b) stepwise implementation; (c) formalized coalitions, integration of policy, and synchronization of tasks and protocols; and (d) smart planning and control by clear communication and feedback instruments. If these recommendations are incorporated into the JUMP-in intervention and organization, increased effectiveness and long-term effects can be expected.

  14. A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

    OpenAIRE

    Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša

    2014-01-01

    Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...

  15. 331 Asthma Management in Latin America: Learnings from the Latin America Asthma Insight and Management (LA AIM) Survey of Patients

    OpenAIRE

    Maspero, Jorge; Jardim, Jose; González-Díaz, Sandra; Aranda, Alvaro; Tassinari, Paolo

    2012-01-01

    Background In 2003, the Asthma Insights and Reality in Latin America (AIRLA) survey assessed, in part, perception, knowledge, and attitudes related to asthma.1 In 2011 the Latin America Asthma Insight and Management (LA AIM) survey was designed to ascertain the realities of living with asthma, disconnect between expectations in asthma management and patient experience, and unmet needs. Using results from our survey, we investigated the advances made in asthma care and the challenges that rema...

  16. Case-Based Web Learning Versus Face-to-Face Learning: A Mixed-Method Study on University Nursing Students.

    Science.gov (United States)

    Chan, Aileen Wai-Kiu; Chair, Sek-Ying; Sit, Janet Wing-Hung; Wong, Eliza Mi-Ling; Lee, Diana Tze-Fun; Fung, Olivia Wai-Man

    2016-03-01

    Case-based learning (CBL) is an effective educational method for improving the learning and clinical reasoning skills of students. Advances in e-learning technology have supported the development of the Web-based CBL approach to teaching as an alternative or supplement to the traditional classroom approach. This study aims to examine the CBL experience of Hong Kong students using both traditional classroom and Web-based approaches in undergraduate nursing education. This experience is examined in terms of the perceived self-learning ability, clinical reasoning ability, and satisfaction in learning of these students. A mixture of quantitative and qualitative approaches was adopted. All Year-3 undergraduate nursing students were recruited. CBL was conducted using the traditional classroom approach in Semester 1, and the Web-based approach was conducted in Semester 2. Student evaluations were collected at the end of each semester using a self-report questionnaire. In-depth, focus-group interviews were conducted at the end of Semester 2. One hundred twenty-two students returned their questionnaires. No difference between the face-to-face and Web-based approaches was found in terms of self-learning ability (p = .947), clinical reasoning ability (p = .721), and satisfaction (p = .083). Focus group interview findings complemented survey findings and revealed five themes that reflected the CBL learning experience of Hong Kong students. These themes were (a) the structure of CBL, (b) the learning environment of Web-based CBL, (c) critical thinking and problem solving, (d) cultural influence on CBL learning experience, and (e) student-centered and teacher-centered learning. The Web-based CBL approach was comparable but not superior to the traditional classroom CBL approach. The Web-based CBL experience of these students sheds light on the impact of Chinese culture on student learning behavior and preferences.

  17. The Influence of Teaching Methods and Learning Environment to the Student's Learning Achievement of Craft and Entrepreneurship Subjects at Vocational High School

    Science.gov (United States)

    Munawaroh

    2017-01-01

    This research aims to explain the influence of teacher's teaching methods and learning environment to the learning achievement in class XI with the competency of accounting expertise to the subjects of craft and entrepreneurship, according to the students, the subject was very heavy and dull. The population in this research are students in class…

  18. Comparison of the Effects of Cooperative Learning and Traditional Learning Methods on the Improvement of Drug-Dose Calculation Skills of Nursing Students Undergoing Internships

    Science.gov (United States)

    Basak, Tulay; Yildiz, Dilek

    2014-01-01

    Objective: The aim of this study was to compare the effectiveness of cooperative learning and traditional learning methods on the development of drug-calculation skills. Design: Final-year nursing students ("n" = 85) undergoing internships during the 2010-2011 academic year at a nursing school constituted the study group of this…

  19. Using a Mixed Methods Research Design in a Study Investigating the "Heads of e-Learning" Perspective towards Technology Enhanced Learning

    Science.gov (United States)

    Almpanis, Timos

    2016-01-01

    This paper outlines the research design, methodology and methods employed in research conducted in the context of Higher Education Institutions (HEIs) and focuses on the Heads of e-Learning (HeLs) perspective about Technology Enhanced Learning (TEL) by campus-based UK institutions. This paper aims to expand on the research design and the research…

  20. An Analytical framework of social learning facilitated by participatory methods

    NARCIS (Netherlands)

    Scholz, G.; Dewulf, A.; Pahl-Wostl, C.

    2014-01-01

    Social learning among different stakeholders is often a goal in problem solving contexts such as environmental management. Participatory methods (e.g., group model-building and role playing games) are frequently assumed to stimulate social learning. Yet understanding if and why this assumption is

  1. Blended learning – integrating E-learning with traditional learning methods in teaching basic medical science

    OpenAIRE

    J.G. Bagi; N.K. Hashilkar

    2014-01-01

    Background: Blended learning includes an integration of face to face classroom learning with technology enhanced online material. It provides the convenience, speed and cost effectiveness of e-learning with the personal touch of traditional learning. Objective: The objective of the present study was to assess the effectiveness of a combination of e-learning module and traditional teaching (Blended learning) as compared to traditional teaching alone to teach acid base homeostasis to Phase I MB...

  2. Learning Methods for Radial Basis Functions Networks

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman; Kudová, Petra

    2005-01-01

    Roč. 21, - (2005), s. 1131-1142 ISSN 0167-739X R&D Projects: GA ČR GP201/03/P163; GA ČR GA201/02/0428 Institutional research plan: CEZ:AV0Z10300504 Keywords : radial basis function networks * hybrid supervised learning * genetic algorithms * benchmarking Subject RIV: BA - General Mathematics Impact factor: 0.555, year: 2005

  3. Machine Learning Methods to Predict Diabetes Complications.

    Science.gov (United States)

    Dagliati, Arianna; Marini, Simone; Sacchi, Lucia; Cogni, Giulia; Teliti, Marsida; Tibollo, Valentina; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

    2018-03-01

    One of the areas where Artificial Intelligence is having more impact is machine learning, which develops algorithms able to learn patterns and decision rules from data. Machine learning algorithms have been embedded into data mining pipelines, which can combine them with classical statistical strategies, to extract knowledge from data. Within the EU-funded MOSAIC project, a data mining pipeline has been used to derive a set of predictive models of type 2 diabetes mellitus (T2DM) complications based on electronic health record data of nearly one thousand patients. Such pipeline comprises clinical center profiling, predictive model targeting, predictive model construction and model validation. After having dealt with missing data by means of random forest (RF) and having applied suitable strategies to handle class imbalance, we have used Logistic Regression with stepwise feature selection to predict the onset of retinopathy, neuropathy, or nephropathy, at different time scenarios, at 3, 5, and 7 years from the first visit at the Hospital Center for Diabetes (not from the diagnosis). Considered variables are gender, age, time from diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), hypertension, and smoking habit. Final models, tailored in accordance with the complications, provided an accuracy up to 0.838. Different variables were selected for each complication and time scenario, leading to specialized models easy to translate to the clinical practice.

  4. Learning in Non-Stationary Environments Methods and Applications

    CERN Document Server

    Lughofer, Edwin

    2012-01-01

    Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences.   Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...

  5. Comparative Analysis of Kernel Methods for Statistical Shape Learning

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

    2006-01-01

    .... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...

  6. Implementing Adaptive Educational Methods with IMS Learning Design

    NARCIS (Netherlands)

    Specht, Marcus; Burgos, Daniel

    2006-01-01

    Please, cite this publication as: Specht, M. & Burgos, D. (2006). Implementing Adaptive Educational Methods with IMS Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org

  7. Learning Analytics Architecture to Scaffold Learning Experience through Technology-based Methods

    Directory of Open Access Journals (Sweden)

    Jannicke Madeleine Baalsrud Hauge

    2015-02-01

    Full Text Available The challenge of delivering personalized learning experiences is often increased by the size of classrooms and online learning communities. Serious Games (SGs are increasingly recognized for their potential to improve education. However, the issues related to their development and their level of effectiveness can be seriously affected when brought too rapidly into growing online learning communities. Deeper insights into how the students are playing is needed to deliver a comprehensive and intelligent learning framework that facilitates better understanding of learners' knowledge, effective assessment of their progress and continuous evaluation and optimization of the environments in which they learn. This paper discusses current SOTA and aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model (ecosystem and architecture discussed in this paper aims to highlight the key considerations that may advance the current state of learning analytics, adaptive learning and SGs, by leveraging SGs as an suitable medium for gathering data and performing adaptations.

  8. Extremely Randomized Machine Learning Methods for Compound Activity Prediction

    Directory of Open Access Journals (Sweden)

    Wojciech M. Czarnecki

    2015-11-01

    Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  9. AIM Data Services

    Directory of Open Access Journals (Sweden)

    Michael Scholz

    2016-05-01

    Full Text Available AIM Data Services as a virtual facility provides virtual 3D reference tracks for simulation applications in the domain of automotive and railway systems. It offers tools for management and analysis of experiment data and a platform for survey and processing of vehicle data in the public transport domain. Collected spatial data is bundled in a database cluster and published through common web mapping interfaces.

  10. Implementation of Active Learning Method in Unit Operations II Subject

    OpenAIRE

    Ma'mun, Sholeh

    2018-01-01

    ABSTRACT: Active Learning Method which requires students to take an active role in the process of learning in the classroom has been applied in Department of Chemical Engineering, Faculty of Industrial Technology, Islamic University of Indonesia for Unit Operations II subject in the Even Semester of Academic Year 2015/2016. The purpose of implementation of the learning method is to assist students in achieving competencies associated with the Unit Operations II subject and to help in creating...

  11. Studying depression using imaging and machine learning methods

    Directory of Open Access Journals (Sweden)

    Meenal J. Patel

    2016-01-01

    Full Text Available Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1 presents a background on depression, imaging, and machine learning methodologies; (2 reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3 suggests directions for future depression-related studies.

  12. Studying depression using imaging and machine learning methods.

    Science.gov (United States)

    Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J

    2016-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies.

  13. Integration of Traditional and E-Learning Methods to Improve Learning Outcomes for Dental Students in Histopathology.

    Science.gov (United States)

    Ariana, Armin; Amin, Moein; Pakneshan, Sahar; Dolan-Evans, Elliot; Lam, Alfred K

    2016-09-01

    Dental students require a basic ability to explain and apply general principles of pathology to systemic, dental, and oral pathology. Although there have been recent advances in electronic and online resources, the academic effectiveness of using self-directed e-learning tools in pathology courses for dental students is unclear. The aim of this study was to determine if blended learning combining e-learning with traditional learning methods of lectures and tutorials would improve students' scores and satisfaction over those who experienced traditional learning alone. Two consecutive cohorts of Bachelor of Dentistry and Oral Health students taking the general pathology course at Griffith University in Australia were compared. The control cohort experienced traditional methods only, while members of the study cohort were also offered self-directed learning materials including online resources and online microscopy classes. Final assessments for the course were used to compare the differences in effectiveness of the intervention, and students' satisfaction with the teaching format was evaluated using questionnaires. On the final course assessments, students in the study cohort had significantly higher scores than students in the control cohort (plearning tools such as virtual microscopy and interactive online resources for delivering pathology instruction can be an effective supplement for developing dental students' competence, confidence, and satisfaction.

  14. The VicGeneration study - a birth cohort to examine the environmental, behavioural and biological predictors of early childhood caries: background, aims and methods

    Directory of Open Access Journals (Sweden)

    Dashper Stuart

    2010-02-01

    Full Text Available Abstract Background Dental caries (decay during childhood is largely preventable however it remains a significant and costly public health concern, identified as the most prevalent chronic disease of childhood. Caries in children aged less than five years (early childhood caries is a rapid and progressive disease that can be painful and debilitating, and significantly increases the likelihood of poor child growth, development and social outcomes. Early childhood caries may also result in a substantial social burden on families and significant costs to the public health system. A disproportionate burden of disease is also experienced by disadvantaged populations. Methods/Design This study involves the establishment of a birth cohort in disadvantaged communities in Victoria, Australia. Children will be followed for at least 18 months and the data gathered will explore longitudinal relationships and generate new evidence on the natural history of early childhood caries, the prevalence of the disease and relative contributions of risk and protective biological, environmental and behavioural factors. Specifically, the study aims to: 1. Describe the natural history of early childhood caries (at ages 1, 6, 12 and 18 months, tracking pathways from early bacterial colonisation, through non-cavitated enamel white spot lesions to cavitated lesions extending into dentine. 2. Enumerate oral bacterial species in the saliva of infants and their primary care giver. 3. Identify the strength of concurrent associations between early childhood caries and putative risk and protective factors, including biological (eg microbiota, saliva, environmental (fluoride exposure and socio-behavioural factors (proximal factors such as: feeding practices and oral hygiene; and distal factors such as parental health behaviours, physical health, coping and broader socio-economic conditions. 4. Quantify the longitudinal relationships between these factors and the development and

  15. New Learning Methods for Marine Oil Spill Response Training

    Directory of Open Access Journals (Sweden)

    Justiina Halonen

    2017-06-01

    Full Text Available In Finland the Regional Fire and Rescue Services (RFRS are responsible for near shore oil spill response and shoreline cleanup operations. In addition, they assist in other types of maritime incidents, such as search and rescue operations and fire-fighting on board. These statutory assignments require the RFRS to have capability to act both on land and at sea. As maritime incidents occur infrequently, little routine has been established. In order to improve their performance in maritime operations, the RFRS are participating in a new oil spill training programme to be launched by South-Eastern Finland University of Applied Sciences. This training programme aims to utilize new educational methods; e-learning and simulator based training. In addition to fully exploiting the existing navigational bridge simulator, radio communication simulator and crisis management simulator, an entirely new simulator is developed. This simulator is designed to model the oil recovery process; recovery method, rate and volume in various conditions with different oil types. New simulator enables creation of a comprehensive training programme covering training tasks from a distress call to the completion of an oil spill response operation. Structure of the training programme, as well as the training objectives, are based on the findings from competence and education surveys conducted in spring 2016. In these results, a need for vessel maneuvering and navigation exercises together with actual response measures training were emphasized. Also additional training for maritime radio communication, GMDSS-emergency protocols and collaboration with maritime authorities were seemed important. This paper describes new approach to the maritime operations training designed for rescue authorities, a way of learning by doing, without mobilising the vessels at sea.

  16. The concept of training in community network for teaching algebraic structures that are aimed to create a methodical competence of a mathematics teacher

    Directory of Open Access Journals (Sweden)

    Ирина Викторовна Кузнецова

    2012-12-01

    Full Text Available The paper proposes the concept of learning activities in online communities for teaching algebraic structures of the future teachers of mathematics, including a set of theoretical and methodological positions, laws, principles, factors, and pedagogical conditions of its implementation. Work is executed with support of the Russian fund of basic researches under the initiative project № 11-07-00733 «The Hypertext information retrieval thesaurus» a science Meta language» (structure; mathematical, linguistic and program maintenance; sections linguistics, mathematics, economy».

  17. A novel Bayesian learning method for information aggregation in modular neural networks

    DEFF Research Database (Denmark)

    Wang, Pan; Xu, Lida; Zhou, Shang-Ming

    2010-01-01

    Modular neural network is a popular neural network model which has many successful applications. In this paper, a sequential Bayesian learning (SBL) is proposed for modular neural networks aiming at efficiently aggregating the outputs of members of the ensemble. The experimental results on eight...... benchmark problems have demonstrated that the proposed method can perform information aggregation efficiently in data modeling....

  18. The Effect of Virtual Language Learning Method on Writing Ability of Iranian Intermediate EFL Learners

    Science.gov (United States)

    Khoshsima, Hooshang; Sayadi, Fatemeh

    2016-01-01

    This study aimed at investigating the effect of virtual language learning method on Iranian intermediate EFL learners writing ability. The study was conducted with 20 English Translation students at Chabahar Maritime University who were assigned into two groups, control and experimental, after ensuring of their homogeneity by administering a TOEFL…

  19. Blogging as a method to stimulate entrepreneurial reflective practice learning in physiotherapy education

    DEFF Research Database (Denmark)

    Ringby, Betina

    2016-01-01

    The aim was to identify, create and test an easy and low cost method that stimulates physiotherapy students to become reflective practice learners. Thus blogging was selected as a tool for students to use in their learning process. Blogging is considered to be a useful tool to support students...

  20. Improving Junior High School Students' Mathematical Analogical Ability Using Discovery Learning Method

    Science.gov (United States)

    Maarif, Samsul

    2016-01-01

    The aim of this study was to identify the influence of discovery learning method towards the mathematical analogical ability of junior high school's students. This is a research using factorial design 2x2 with ANOVA-Two ways. The population of this research included the entire students of SMPN 13 Jakarta (State Junior High School 13 of Jakarta)…

  1. Critical factors in the empirical performance of temporal difference and evolutionary methods for reinforcement learning

    NARCIS (Netherlands)

    Whiteson, S.; Taylor, M.E.; Stone, P.

    2010-01-01

    Temporal difference and evolutionary methods are two of the most common approaches to solving reinforcement learning problems. However, there is little consensus on their relative merits and there have been few empirical studies that directly compare their performance. This article aims to address

  2. Computerization of Hungarian reforestation manual with machine learning methods

    Science.gov (United States)

    Czimber, Kornél; Gálos, Borbála; Mátyás, Csaba; Bidló, András; Gribovszki, Zoltán

    2017-04-01

    Hungarian forests are highly sensitive to the changing climate, especially to the available precipitation amount. Over the past two decades several drought damages were observed for tree species which are in the lower xeric limit of their distribution. From year to year these affected forest stands become more difficult to reforest with the same native species because these are not able to adapt to the increasing probability of droughts. The climate related parameter set of the Hungarian forest stand database needs updates. Air humidity that was formerly used to define the forest climate zones is not measured anymore and its value based on climate model outputs is highly uncertain. The aim was to develop a novel computerized and objective method to describe the species-specific climate conditions that is essential for survival, growth and optimal production of the forest ecosystems. The method is expected to project the species spatial distribution until 2100 on the basis of regional climate model simulations. Until now, Hungarian forest managers have been using a carefully edited spreadsheet for reforestation purposes. Applying binding regulations this spreadsheet prescribes the stand-forming and admixed tree species and their expected growth rate for each forest site types. We are going to present a new machine learning based method to replace the former spreadsheet. We took into great consideration of various methods, such as maximum likelihood, Bayesian networks, Fuzzy logic. The method calculates distributions, setups classification, which can be validated and modified by experts if necessary. Projected climate change conditions makes necessary to include into this system an additional climate zone that does not exist in our region now, as well as new options for potential tree species. In addition to or instead of the existing ones, the influence of further limiting parameters (climatic extremes, soil water retention) are also investigated. Results will be

  3. Aiming for the ordinary

    DEFF Research Database (Denmark)

    Offersen, Sara Marie Hebsgaard

    that the Danes are encouraged to be alert to still earlier and vaguer bodily signs of potential cancer and seek care ‘in time’. With biomedical constructions such as ‘cancer awareness’ and ‘alarm symptoms of cancer’ and the retrospectively oriented definition of life before symptoms-based healthcare seeking...... and articulation of bodily sensations, and how decisions about healthcare seeking are established in this context. This dissertation aims to explore these matters from the perspective of the Danish middle class, mainly focusing on how sensations are ascribed meaning as symptoms and how they are evoked...... on a continuum between what is locally considered ordinary and extraordinary. Overall, the dissertation argues that inquiries into morality and potentiality provide valuable insights into healthcare seeking practices and the making and management of symptoms in everyday life. The dissertation is based on 18...

  4. A method of teaching critical care skills to undergraduate student midwives using the Maternal-Acute Illness Management (M-AIM) training day.

    Science.gov (United States)

    McCarthy, Rose; Nuttall, Janet; Smith, Joyce; Hollins Martin, Caroline J

    2014-11-01

    The most recent Confidential Enquiry into Maternal Deaths (CMACE, 2011) identified human errors, specifically those of midwives and obstetricians/doctors as a fundamental component in contributing to maternal death in the U.K. This paper discusses these findings and outlines a project to provide training in Maternal-Acute Illness Management (M-AIM) to final year student midwives. Contents of the program are designed to educate and simulate AIM skills and increase confidence and clinical ability in early recognition, management and referral of the acutely ill woman. An outline of the Maternal-AIM program delivered at the University of Salford (Greater Manchester, UK) is presented to illustrate how this particular institution has responded to a perceived need voiced by local midwifery leaders. It is proposed that developing this area of expertise in the education system will better prepare student midwives for contemporary midwifery practice. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  5. Active teaching methods, studying responses and learning

    DEFF Research Database (Denmark)

    Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain

    Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching....

  6. Creative teaching method as a learning strategy for student midwives: A qualitative study.

    Science.gov (United States)

    Rankin, Jean; Brown, Val

    2016-03-01

    Traditional ways of teaching in Higher Education are enhanced with adult-based approaches to learning within the curriculum. Adult-based learning enables students to take ownership of their own learning, working in independence using a holistic approach. Introducing creative activities promotes students to think in alternative ways to the traditional learning models. The study aimed to explore student midwives perceptions of a creative teaching method as a learning strategy. A qualitative design was used adopting a phenomenological approach to gain the lived experience of students within this learning culture. Purposive sampling was used to recruit student midwives (n=30). Individual interviews were conducted using semi-structured interviews with open-ended questions to gain subjective information. Data were transcribed and analyzed into useful and meaningful themes and emerging themes using Colaizzi's framework for analyzing qualitative data in a logical and systematic way. Over 500 meaningful statements were identified from the transcripts. Three key themes strongly emerged from the transcriptions. These included'meaningful learning','inspired to learn and achieve', and 'being connected'. A deep meaningful learning experience was found to be authentic in the context of theory and practice. Students were inspired to learn and achieve and positively highlighted the safe learning environment. The abilities of the facilitators were viewed positively in supporting student learning. This approach strengthened the relationships and social engagement with others in the peer group and the facilitators. On a less positive note, tensions and conflict were noted in group work and indirect negative comments about the approach from the teaching team. Incorporating creative teaching activities is a positive addition to the healthcare curriculum. Creativity is clearly an asset to the range of contemporary learning strategies. In doing so, higher education will continue to keep

  7. Developing a Blended Learning-Based Method for Problem-Solving in Capability Learning

    Science.gov (United States)

    Dwiyogo, Wasis D.

    2018-01-01

    The main objectives of the study were to develop and investigate the implementation of blended learning based method for problem-solving. Three experts were involved in the study and all three had stated that the model was ready to be applied in the classroom. The implementation of the blended learning-based design for problem-solving was…

  8. Motivations, aims and communication around advance directives: a mixed-methods study into the perspective of their owners and the influence of a current illness.

    Science.gov (United States)

    van Wijmen, Matthijs P S; Pasman, H Roeline W; Widdershoven, Guy A M; Onwuteaka-Philipsen, Bregje D

    2014-06-01

    What are motivations of owners of an advance directive (AD) to draft an AD, what do they aim for with their AD and do they communicate about their AD? Written questionnaires were sent to a cohort of people owning different types of ADs (n=5768). A purposive sample of people suffering from an illness was selected from the cohort for an in-depth interview (n=29). About half of our population had no direct motivation to draft their AD. Most mentioned motivation for the other half was an illness of a family member or friend. Many different and specific aims for drafting an AD were mentioned. An often mentioned more general aim in people with different ADs was to prevent unnecessary lengthening of life or treatment (14-16%). Most respondents communicated about having an AD with close-ones (63-88%) and with their GP (65-79%). In the interviews people gave vivid examples of experiences of what they hoped to prevent at the end of life. Some mentioned difficulties foreseeing the future and gave examples of response shift. ADs can give directions to caregivers about what people want at the end of life. ADs have to be discussed in detail by their owners and caregivers, since owners often have specific aims with their AD. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. Deep learning methods for protein torsion angle prediction.

    Science.gov (United States)

    Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

    2017-09-18

    Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

  10. In silico machine learning methods in drug development.

    Science.gov (United States)

    Dobchev, Dimitar A; Pillai, Girinath G; Karelson, Mati

    2014-01-01

    Machine learning (ML) computational methods for predicting compounds with pharmacological activity, specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties are being increasingly applied in drug discovery and evaluation. Recently, machine learning techniques such as artificial neural networks, support vector machines and genetic programming have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic targets. These methods are particularly useful for screening compound libraries of diverse chemical structures, "noisy" and high-dimensional data to complement QSAR methods, and in cases of unavailable receptor 3D structure to complement structure-based methods. A variety of studies have demonstrated the potential of machine-learning methods for predicting compounds as potential drug candidates. The present review is intended to give an overview of the strategies and current progress in using machine learning methods for drug design and the potential of the respective model development tools. We also regard a number of applications of the machine learning algorithms based on common classes of diseases.

  11. TEACHING METHODS IN MBA AND LIFELONG LEARNING PROGRAMMES FOR MANAGERS

    Directory of Open Access Journals (Sweden)

    Jarošová, Eva

    2017-09-01

    Full Text Available Teaching methods in MBA and Lifelong Learning Programmes (LLP for managers should be topically relevant in terms of content as well as the teaching methods used. In terms of the content, the integral part of MBA and Lifelong Learning Programmes for managers should be the development of participants’ leadership competencies and their understanding of current leadership concepts. The teaching methods in educational programmes for managers as adult learners should correspond to the strategy of learner-centred teaching that focuses on the participants’ learning process and their active involvement in class. The focus on the participants’ learning process also raises questions about whether the programme’s participants perceive the teaching methods used as useful and relevant for their development as leaders. The paper presents the results of the analysis of the responses to these questions in a sample of 54 Czech participants in the MBA programme and of lifelong learning programmes at the University of Economics, Prague. The data was acquired based on written or electronically submitted questionnaires. The data was analysed in relation to the usefulness of the teaching methods for understanding the concepts of leadership, leadership skills development as well as respondents’ personal growth. The results show that the respondents most valued the methods that enabled them to get feedback, activated them throughout the programme and got them involved in discussions with others in class. Implications for managerial education practices are discussed.

  12. Finding protein sites using machine learning methods

    Directory of Open Access Journals (Sweden)

    Jaime Leonardo Bobadilla Molina

    2003-07-01

    Full Text Available The increasing amount of protein three-dimensional (3D structures determined by x-ray and NMR technologies as well as structures predicted by computational methods results in the need for automated methods to provide inital annotations. We have developed a new method for recognizing sites in three-dimensional protein structures. Our method is based on a previosly reported algorithm for creating descriptions of protein microenviroments using physical and chemical properties at multiple levels of detail. The recognition method takes three inputs: 1. A set of control nonsites that share some structural or functional role. 2. A set of control nonsites that lack this role. 3. A single query site. A support vector machine classifier is built using feature vectors where each component represents a property in a given volume. Validation against an independent test set shows that this recognition approach has high sensitivity and specificity. We also describe the results of scanning four calcium binding proteins (with the calcium removed using a three dimensional grid of probe points at 1.25 angstrom spacing. The system finds the sites in the proteins giving points at or near the blinding sites. Our results show that property based descriptions along with support vector machines can be used for recognizing protein sites in unannotated structures.

  13. Approximation methods for efficient learning of Bayesian networks

    CERN Document Server

    Riggelsen, C

    2008-01-01

    This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order to provide a coherent treatment of matters, thereby helping the reader to gain a thorough understanding of the whole concept of learning Bayesian networks from (in)complete data, this publication combines in a clarifying way all the issues presented in the papers with previously unpublished work.

  14. Experts in Teams – An experiential learning method

    DEFF Research Database (Denmark)

    Johansen, Steffen Kjær

    2017-01-01

    T becomes a learning method rather than a teaching method. Besides discussing the pedagogical characteristics of EiT, the study also gives a general introduction to EiT as it was taught at SDU fall 2016 as well as a brief review of the basic theory behind experiential learning. As such this study serves...... courses. Most of the practical courses are group work along the lines of project based learning. EiT is in a way both. It is a practical course in as much as our students get hands-on experience with interdisciplinary team work and innovation processes. EiT is a theoretical course in as much as our...... both as an introduction to e.g. new teachers of EiT but also as a starting point for a clarification of the features that makes EiT an experiential learning endeavor....

  15. Reform-Based-Instructional Method and Learning Styles on Students' Achievement and Retention in Mathematics: Administrative Implications

    Science.gov (United States)

    Modebelu, M. N.; Ogbonna, C. C.

    2014-01-01

    This study aimed at determining the effect of reform-based-instructional method learning styles on students' achievement and retention in mathematics. A sample size of 119 students was randomly selected. The quasiexperimental design comprising pre-test, post-test, and randomized control group were employed. The Collin Rose learning styles…

  16. The Effectiveness of Neurological Impress Method on Reading Fluency of Students with Learning Disabilities in Amman, Jordan

    Science.gov (United States)

    Ziadat, Ayed H.; AL-Awan, Mohammad Soud A.

    2018-01-01

    The aim of this study was to evaluate the effectiveness of Neurological Impress Method (NIM) on reading fluency of students with learning disabilities in Amman, Jordan. A sample of forty students (boys and girls) between the ages 10-12 years old with learning disabilities were selected from the Fourth Amman Educational Directorate in the Hashemite…

  17. Research on demand-oriented Business English learning method

    Directory of Open Access Journals (Sweden)

    Zhou Yuan

    2016-01-01

    Full Text Available Business English is integrated with visual-audio-oral English, which focuses on the application for English listening and speaking skills in common business occasions, and acquire business knowledge and improve skills through English. This paper analyzes the Business English Visual-audio-oral Course, and learning situation of higher vocational students’ learning objectives, interests, vocabulary, listening and speaking, and focuses on the research of effective methods to guide the higher vocational students to learn Business English Visual-audio-oral Course, master Business English knowledge, and improve communicative competence of Business English.

  18. The Efficacy of Three Learning Methods Collaborative, Context-Based Learning and Traditional, on Learning, Attitude and Behaviour of Undergraduate Nursing Students: Integrating Theory and Practice.

    Science.gov (United States)

    Hasanpour-Dehkordi, Ali; Solati, Kamal

    2016-04-01

    Communication skills training, responsibility, respect, and self-awareness are important indexes of changing learning behaviours in modern approaches. The aim of this study was to investigate the efficacy of three learning approaches, collaborative, context-based learning (CBL), and traditional, on learning, attitude, and behaviour of undergraduate nursing students. This study was a clinical trial with pretest and post-test of control group. The participants were senior nursing students. The samples were randomly assigned to three groups; CBL, collaborative, and traditional. To gather data a standard questionnaire of students' behaviour and attitude was administered prior to and after the intervention. Also, the rate of learning was investigated by a researcher-developed questionnaire prior to and after the intervention in the three groups. In CBL and collaborative training groups, the mean score of behaviour and attitude increased after the intervention. But no significant association was obtained between the mean scores of behaviour and attitude prior to and after the intervention in the traditional group. However, the mean learning score increased significantly in the CBL, collaborative, and traditional groups after the study in comparison to before the study. Both CBL and collaborative approaches were useful in terms of increased respect, self-awareness, self-evaluation, communication skills and responsibility as well as increased motivation and learning score in comparison to traditional method.

  19. [Which learning methods are expected for ultrasound training? Blended learning on trial].

    Science.gov (United States)

    Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R

    2014-10-01

    Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.

  20. Research on demand-oriented Business English learning method

    OpenAIRE

    Zhou Yuan

    2016-01-01

    Business English is integrated with visual-audio-oral English, which focuses on the application for English listening and speaking skills in common business occasions, and acquire business knowledge and improve skills through English. This paper analyzes the Business English Visual-audio-oral Course, and learning situation of higher vocational students’ learning objectives, interests, vocabulary, listening and speaking, and focuses on the research of effective methods to guide the higher voca...

  1. Future Competencies and Learning Methods in Engineering Education

    DEFF Research Database (Denmark)

    Kolmos, Anette

    2002-01-01

    What are the competencies for tommorow´s enginnering education and the implications of these regarding the choice of teaching content and learning methods? The paper analyses two trends: the traditional and the techo-science approach. These two trends are based on technological innovation...... and change processes and impact on educational content and methods....

  2. Empowering and Engaging Students in Learning Research Methods

    Science.gov (United States)

    Liu, Shuang; Breit, Rhonda

    2013-01-01

    The capacity to conduct research is essential for university graduates to survive and thrive in their future career. However, research methods courses have often been considered by students as "abstract", "uninteresting", and "hard". Thus, motivating students to engage in the process of learning research methods has become a crucial challenge for…

  3. Radiochemical methods. Analytical chemistry by open learning

    Energy Technology Data Exchange (ETDEWEB)

    Geary, W.J.; James, A.M. (ed.)

    1986-01-01

    This book presents the analytical uses of radioactive isotopes within the context of radiochemistry as a whole. It is designed for scientists with relatively little background knowledge of the subject. Thus the initial emphasis is on developing the basic concepts of radioactive decay, particularly as they affect the potential usage of radioisotopes. Discussion of the properties of various types of radiation, and of factors such as half-life, is related to practical considerations such as counting and preparation methods, and handling/disposal problems. Practical aspects are then considered in more detail, and the various radioanalytical methods are outlined with particular reference to their applicability. The approach is 'user friendly' and the use of self assessment questions allows the reader to test his/her understanding of individual sections easily. For those who wish to develop their knowledge further, a reading list is provided.

  4. Uncertain Photometric Redshifts with Deep Learning Methods

    Science.gov (United States)

    D'Isanto, A.

    2017-06-01

    The need for accurate photometric redshifts estimation is a topic that has fundamental importance in Astronomy, due to the necessity of efficiently obtaining redshift information without the need of spectroscopic analysis. We propose a method for determining accurate multi-modal photo-z probability density functions (PDFs) using Mixture Density Networks (MDN) and Deep Convolutional Networks (DCN). A comparison with a Random Forest (RF) is performed.

  5. Monte Carlo methods for preference learning

    DEFF Research Database (Denmark)

    Viappiani, P.

    2012-01-01

    Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....

  6. A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

    Directory of Open Access Journals (Sweden)

    Zekić-Sušac Marijana

    2014-09-01

    Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.

  7. Machine Learning Methods for Attack Detection in the Smart Grid.

    Science.gov (United States)

    Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent

    2016-08-01

    Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

  8. Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method

    Directory of Open Access Journals (Sweden)

    Wei Xue

    2016-08-01

    Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.

  9. Métodos de extração de sementes de mangaba visando à qualidade fisiológica Different extraction methods aiming mangaba seeds quality

    Directory of Open Access Journals (Sweden)

    Daniella Inácio Barros

    2006-04-01

    Full Text Available A mangaba (Hancornia speciosa Gomes tem a via sexuada como principal forma de propagação. São escassas as pesquisas referentes à extração de suas sementes; entretanto, a viabilidade e o vigor dependem diretamente do método empregado. O presente trabalho teve como objetivo avaliar a qualidade fisiológica de sementes de mangaba extraídas sobre três métodos, sendo um manual (peneira e outros dois mecânicos (despolpadeira e batedeira. Em seguida, as sementes foram submetidas aos testes de umidade, germinação, condutividade elétrica, primeira contagem, emergência de plântulas em areia e massa seca de plântulas. A extração manual proporcionou sementes com maior qualidade fisiológica, e entre os métodos mecânicos, a batedeira resultou em sementes mais viáveis e vigorosas, enquanto a despolpadeira provocou danos agudos.Mangaba (Hancornia speciosa Gomes has the sexual way as the main propagation form. Researches regarding the extraction of its seeds are scarce; however, viability and vigor depend directly on the applied method. The present work had as objective to evaluate physiologic quality of extracted mangaba seeds on three methods, in which one is manual (drizzles and the other two are mechanical (content removing device and mixer, further the mentioned seeds were submitted to humidity, germination, electric conductivity, first count, seedling emergence and seedlings dry mass tests. Manual extraction provided seeds with a larger physiologic quality and, among mechanical methods; the mixer resulted in viable and vigorous seeds, while the content removing device caused sharp damages.

  10. A study of active learning methods for named entity recognition in clinical text.

    Science.gov (United States)

    Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

    2015-12-01

    Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random

  11. Comparison of the effect of lecture and blended teaching methods on students’ learning and satisfaction

    Science.gov (United States)

    SADEGHI, ROYA; SEDAGHAT, MOHAMMAD MEHDI; SHA AHMADI, FARAMARZ

    2014-01-01

    Introduction: Blended learning, a new approach in educational planning, is defined as an applying more than one method, strategy, technique or media in education. Todays, due to the development of infrastructure of Internet networks and the access of most of the students, the Internet can be utilized along with traditional and conventional methods of training. The aim of this study was to compare the students’ learning and satisfaction in combination of lecture and e-learning with conventional lecture methods. Methods: This quasi-experimental study is conducted among the sophomore students of Public Health School, Tehran University of Medical Science in 2012-2013. Four classes of the school are randomly selected and are divided into two groups. Education in two classes (45 students) was in the form of lecture method and in the other two classes (48 students) was blended method with e-Learning and lecture methods. The students’ knowledge about tuberculosis in two groups was collected and measured by using pre and post-test. This step has been done by sending self-reported electronic questionnaires to the students' email addresses through Google Document software. At the end of educational programs, students' satisfaction and comments about two methods were also collected by questionnaires. Statistical tests such as descriptive methods, paired t-test, independent t-test and ANOVA were done through the SPSS 14 software, and p≤0.05 was considered as significant difference. Results: The mean scores of the lecture and blended groups were 13.18±1.37 and 13.35±1.36, respectively; the difference between the pre-test scores of the two groups was not statistically significant (p=0.535). Knowledge scores increased in both groups after training, and the mean and standard deviation of knowledge scores of the lectures and combined groups were 16.51±0.69 and 16.18±1.06, respectively. The difference between the post-test scores of the two groups was not statistically

  12. Comparison of teaching about breast cancer via mobile or traditional learning methods in gynecology residents.

    Science.gov (United States)

    Alipour, Sadaf; Moini, Ashraf; Jafari-Adli, Shahrzad; Gharaie, Nooshin; Mansouri, Khorshid

    2012-01-01

    Mobile learning enables users to interact with educational resources while in variable locations. Medical students in residency positions need to assimilate considerable knowledge besides their practical training and we therefore aimed to evaluate the impact of using short message service via cell phone as a learning tool in residents of Obstetrics and Gynecology in our hospital. We sent short messages including data about breast cancer to the cell phones of 25 residents of gynecology and obstetrics and asked them to study a well-designed booklet containing another set of information about the disease in the same period. The rate of learning derived from the two methods was compared by pre- and post-tests and self-satisfaction assessed by a relevant questionnaire at the end of the program. The mobile learning method had a significantly better effect on learning and created more interest in the subject. Learning via receiving SMS can be an effective and appealing method of knowledge acquisition in higher levels of education.

  13. On Combining Elements of Different Ways of Learning, Methods and Knowledge

    Directory of Open Access Journals (Sweden)

    Dušana Findeisen

    2013-12-01

    Full Text Available The paper deals with different thinkers' attitude towards methods in adult education. It examines the value of some elements of »trial and error learning« and »non-directive learning«. Like a multifaceted approach based on elements drawn from different methods, the way we learn can also be eclectic.  To illustrate this assertion, the author analyses the »anti method« used by Maurice Pialat, a French film director, contrasting it with methods in which the aim is set in advance and the process leading towards it is organised in sequences. This is most often the case in script-based shooting of films, directing a theatre performance or running adult education. Moreover, the author argues that learning about how to do something is combined with learning about how to be. She further emphasises that methods should not be used to impose one’s knowledge and one’s reality on the learner, thus destroying circumstances necessary for gaining or creating knowledge.

  14. Chiang Mai University Health Worker Study aiming toward a better understanding of noncommunicable disease development in Thailand: methods and description of study population.

    Science.gov (United States)

    Angkurawaranon, Chaisiri; Wisetborisut, Anawat; Jiraporncharoen, Wichuda; Likhitsathian, Surinporn; Uaphanthasath, Ronnaphob; Gomutbutra, Patama; Jiraniramai, Surin; Lerssrimonkol, Chawin; Aramrattanna, Apinun; Doyle, Pat; Nitsch, Dorothea

    2014-01-01

    Urbanization is considered to be one of the key drivers of noncommunicable diseases (NCDs) in Thailand and other developing countries. These influences, in turn, may affect an individual's behavior and risk of developing NCDs. The Chiang Mai University (CMU) Health Worker Study aims to provide evidence for a better understanding of the development of NCDs and ultimately to apply the evidence toward better prevention, risk modification, and improvement of clinical care for patients with NCDs and NCD-related conditions. A cross-sectional survey of health care workers from CMU Hospital was conducted between January 2013 and June 2013. Questionnaires, interviews, and physical and laboratory examinations were used to assess urban exposure, occupational shift work, risk factors for NCDs, self-reported NCDs, and other NCD-related health conditions. From 5,364 eligible workers, 3,204 participated (59.7%). About 11.1% of the participants had high blood pressure (systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) and almost 30% were considered to be obese (body mass index ≥25 kg/m(2)). A total of 2.3% had a high fasting blood glucose level (≥126 mg/dL), and the most common abnormal lipid profile was high low-density lipoprotein (≥160 mg/dL), which was found in 19.2% of participants. The study of health workers offers three potential advantages. The first is that the study of migrants was possible. Socioenvironmental influence on NCD risk factors can be explored, as changes in environmental exposures can be documented. Second, it allows the investigators to control for access to care. Access to care is potentially a key confounder toward understanding the development of NCDs. Lastly, a study of health personnel allows easy access to laboratory investigations and potential for long-term follow-up. This enables ascertainment of a number of clinical outcomes and provides potential for future studies focusing on therapeutic and prognostic issues

  15. Exploring an Experiential Learning Project through Kolb's Learning Theory Using a Qualitative Research Method

    Science.gov (United States)

    Chan, Cecilia Ka Yuk

    2012-01-01

    Experiential learning pedagogy is taking a lead in the development of graduate attributes and educational aims as these are of prime importance for society. This paper shows a community service experiential project conducted in China. The project enabled students to serve the affected community in a post-earthquake area by applying their knowledge…

  16. Comparison of the effect of lecture and blended teaching methods on students' learning and satisfaction.

    Science.gov (United States)

    Sadeghi, Roya; Sedaghat, Mohammad Mehdi; Sha Ahmadi, Faramarz

    2014-10-01

    Blended learning, a new approach in educational planning, is defined as an applying more than one method, strategy, technique or media in education. Todays, due to the development of infrastructure of Internet networks and the access of most of the students, the Internet can be utilized along with traditional and conventional methods of training. The aim of this study was to compare the students' learning and satisfaction in combination of lecture and e-learning with conventional lecture methods. This quasi-experimental study is conducted among the sophomore students of Public Health School, Tehran University of Medical Science in 2012-2013. Four classes of the school are randomly selected and are divided into two groups. Education in two classes (45 students) was in the form of lecture method and in the other two classes (48 students) was blended method with e-Learning and lecture methods. The students' knowledge about tuberculosis in two groups was collected and measured by using pre and post-test. This step has been done by sending self-reported electronic questionnaires to the students' email addresses through Google Document software. At the end of educational programs, students' satisfaction and comments about two methods were also collected by questionnaires. Statistical tests such as descriptive methods, paired t-test, independent t-test and ANOVA were done through the SPSS 14 software, and p≤0.05 was considered as significant difference. The mean scores of the lecture and blended groups were 13.18±1.37 and 13.35±1.36, respectively; the difference between the pre-test scores of the two groups was not statistically significant (p=0.535). Knowledge scores increased in both groups after training, and the mean and standard deviation of knowledge scores of the lectures and combined groups were 16.51±0.69 and 16.18±1.06, respectively. The difference between the post-test scores of the two groups was not statistically significant (p=0.112). Students

  17. Investigation on the effectiveness of various methods of information dissemination aiming at a change of occupant behaviour related to thermal comfort and exergy consumption

    International Nuclear Information System (INIS)

    Schweiker, Marcel; Shukuya, Masanori

    2011-01-01

    These days the number of projects trying to urge a change in the occupant's behaviour towards a sustainable one is increasing. However, still less is known about the effect of such measures. This paper describes the findings of two investigations, a field measurement and an Internet-based survey, both including the dissemination of information about strategies for a high level of comfort without much energy usage. The focus was on the ability to quantify the effect of such measures on the heating and cooling behaviour. As a result, those who participated in a workshop were more likely to change their behaviour than those who received an information brochure only; whether this was due to the method employed or the type of participants could not be ascertained. However, the workshop participants reduced their cooling device usage by up to 16%. The concept of exergy was used to show how this reduction affects the exergy consumption of the cooling device, because it enables us to consider the qualitative aspect of energy as a quantity to be calculated. This showed that the exergy consumed by the workshop group was reduced by up to 20% comparing their behaviour before and after the information dissemination. - Research Highlights: → Data collection through field measurement and an Internet-based survey. → Both surveys included the distribution of information about strategies for a high level of comfort without much energy usage. → Logistic regression analysis in order to quantify the effect of such knowledge transfer measures on the heating and cooling behaviour. → Those participating in the workshop reduced their cooling device usage by up to 20% compared to a control group. → As constraints, time limitations and tediousness are identified.

  18. "Mastery Learning" Como Metodo Psicoeducativo para Ninos con Problemas Especificos de Aprendizaje. ("Mastery Learning" as a Psychoeducational Method for Children with Specific Learning Problems.)

    Science.gov (United States)

    Coya, Liliam de Barbosa; Perez-Coffie, Jorge

    1982-01-01

    "Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching…

  19. Comparisons and Analyses of Gifted Students' Characteristics and Learning Methods

    Science.gov (United States)

    Lu, Jiamei; Li, Daqi; Stevens, Carla; Ye, Renmin

    2017-01-01

    Using PISA 2009, an international education database, this study compares gifted and talented (GT) students in three groups with normal (non-GT) students by examining student characteristics, reading, schooling, learning methods, and use of strategies for understanding and memorizing. Results indicate that the GT and non-GT gender distributions…

  20. Identification of alternative method of teaching and learning the ...

    African Journals Online (AJOL)

    This study examines alternative method of teaching and learning of the concept of diffusion. An improvised U-shape glass tube called ionic mobility tube was used to observed and measure the rate of movement of divalent metal ions in an aqueous medium in the absence of an electric current. The study revealed that the ...

  1. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

  2. Research on Language Learning Strategies: Methods, Findings, and Instructional Issues.

    Science.gov (United States)

    Oxford, Rebecca; Crookall, David

    1989-01-01

    Surveys research on formal and informal second-language learning strategies, covering the effectiveness of research methods involving making lists, interviews and thinking aloud, note-taking, diaries, surveys, and training. Suggestions for future and improved research are presented. (131 references) (CB)

  3. Second-Order Learning Methods for a Multilayer Perceptron

    International Nuclear Information System (INIS)

    Ivanov, V.V.; Purehvdorzh, B.; Puzynin, I.V.

    1994-01-01

    First- and second-order learning methods for feed-forward multilayer neural networks are studied. Newton-type and quasi-Newton algorithms are considered and compared with commonly used back-propagation algorithm. It is shown that, although second-order algorithms require enhanced computer facilities, they provide better convergence and simplicity in usage. 13 refs., 2 figs., 2 tabs

  4. Educational integrating projects as a method of interactive learning

    Directory of Open Access Journals (Sweden)

    Иван Николаевич Куринин

    2013-12-01

    Full Text Available The article describes a method of interactive learning based on educational integrating projects. Some examples of content of such projects for the disciplines related to the study of information and Internet technologies and their application in management are presented.

  5. Learning by Designing Interview Methods in Special Education

    DEFF Research Database (Denmark)

    Jönsson, Lise Høgh

    2017-01-01

    , and people with learning disabilities worked together to develop five new visual and digital methods for interviewing in special education. Thereby not only enhancing the students’ competences, knowledge and proficiency in innovation and research, but also proposing a new teaching paradigm for university...

  6. A Simulator to Enhance Teaching and Learning of Mining Methods ...

    African Journals Online (AJOL)

    Audio visual education that incorporates devices and materials which involve sight, sound, or both has become a sine qua non in recent times in the teaching and learning process. An automated physical model of mining methods aided with video instructions was designed and constructed by harnessing locally available ...

  7. The Keyimage Method of Learning Sound-Symbol Correspondences: A Case Study of Learning Written Khmer

    Directory of Open Access Journals (Sweden)

    Elizabeth Lavolette

    2009-01-01

    Full Text Available I documented my strategies for learning sound-symbol correspondences during a Khmer course. I used a mnemonic strategy that I call the keyimage method. In this method, a character evokes an image (the keyimage, which evokes the corresponding sound. For example, the keyimage for the character 2 could be a swan with its head tucked in. This evokes the sound "kaw" that a swan makes, which sounds similar to the Khmer sound corresponding to 2. The method has some similarities to the keyword method. Considering the results of keyword studies, I hypothesize that the keyimage method is more effective than rote learning and that peer-generated keyimages are more effective than researcher- or teacher-generated keyimages, which are more effective than learner-generated ones. In Dr. Andrew Cohen's plenary presentation at the Hawaii TESOL 2007 conference, he mentioned that more case studies are needed on learning strategies (LSs. One reason to study LSs is that what learners do with input to produce output is unclear, and knowing what strategies learners use may help us understand that process (Dornyei, 2005, p. 170. Hopefully, we can use that knowledge to improve language learning, perhaps by teaching learners to use the strategies that we find. With that in mind, I have examined the LSs that I used in studying Khmer as a foreign language, focusing on learning the syllabic alphabet.

  8. A Fast Optimization Method for General Binary Code Learning.

    Science.gov (United States)

    Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng

    2016-09-22

    Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.

  9. Method to predict process signals to learn for SVM

    International Nuclear Information System (INIS)

    Minowa, Hirotsugu; Gofuku, Akio

    2013-01-01

    Study of diagnostic system using machine learning to reduce the incidents of the plant is in advance because an accident causes large damage about human, economic and social loss. There is a problem that 2 performances between a classification performance and generalization performance on the machine diagnostic machine is exclusive. However, multi agent diagnostic system makes it possible to use a diagnostic machine specialized either performance by multi diagnostic machines can be used. We propose method to select optimized variables to improve classification performance. The method can also be used for other supervised learning machine but Support Vector Machine. This paper reports that our method and result of evaluation experiment applied our method to output 40% of Monju. (author)

  10. Studying depression using imaging and machine learning methods

    OpenAIRE

    Patel, Meenal J.; Khalaf, Alexander; Aizenstein, Howard J.

    2015-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presen...

  11. Student's Perceptions of Quality Learning in a Malaysian University--A Mixed Method Approach

    Science.gov (United States)

    Choy, S. Chee; Yim, Joanne Sau-Ching; Tan, Poh Leong

    2017-01-01

    Purpose: This paper aims to examine students' perceptions of quality learning using a mixed-methods approach in a Malaysian university, with an aim to fill existing knowledge gaps in the literature on relationships among relevant quality variables. The study also assesses the extent to which detailed results from a few participants can be…

  12. Frank Gilbreth and health care delivery method study driven learning.

    Science.gov (United States)

    Towill, Denis R

    2009-01-01

    The purpose of this article is to look at method study, as devised by the Gilbreths at the beginning of the twentieth century, which found early application in hospital quality assurance and surgical "best practice". It has since become a core activity in all modern methods, as applied to healthcare delivery improvement programmes. The article traces the origin of what is now currently and variously called "business process re-engineering", "business process improvement" and "lean healthcare" etc., by different management gurus back to the century-old pioneering work of Frank Gilbreth. The outcome is a consistent framework involving "width", "length" and "depth" dimensions within which healthcare delivery systems can be analysed, designed and successfully implemented to achieve better and more consistent performance. Healthcare method (saving time plus saving motion) study is best practised as co-joint action learning activity "owned" by all "players" involved in the re-engineering process. However, although process mapping is a key step forward, in itself it is no guarantee of effective re-engineering. It is not even the beginning of the end of the change challenge, although it should be the end of the beginning. What is needed is innovative exploitation of method study within a healthcare organisational learning culture accelerated via the Gilbreth Knowledge Flywheel. It is shown that effective healthcare delivery pipeline improvement is anchored into a team approach involving all "players" in the system especially physicians. A comprehensive process study, constructive dialogue, proper and highly professional re-engineering plus managed implementation are essential components. Experience suggests "learning" is thereby achieved via "natural groups" actively involved in healthcare processes. The article provides a proven method for exploiting Gilbreths' outputs and their many successors in enabling more productive evidence-based healthcare delivery as summarised

  13. The Graduating European Dentist: Contemporaneous Methods of Teaching, Learning and Assessment in Dental Undergraduate Education.

    Science.gov (United States)

    Field, J C; Walmsley, A D; Paganelli, C; McLoughlin, J; Szep, S; Kavadella, A; Manzanares Cespedes, M C; Davies, J R; DeLap, E; Levy, G; Gallagher, J; Roger-Leroi, V; Cowpe, J G

    2017-12-01

    It is often the case that good teachers just "intuitively" know how to teach. Whilst that may be true, there is now a greater need to understand the various processes that underpin both the ways in which a curriculum is delivered, and the way in which the students engage with learning; curricula need to be designed to meet the changing needs of our new graduates, providing new, and robust learning opportunities, and be communicated effectively to both staff and students. The aim of this document is to draw together robust and contemporaneous methods of teaching, learning and assessment that help to overcome some of the more traditional barriers within dental undergraduate programmes. The methods have been chosen to map specifically to The Graduating European Dentist, and should be considered in parallel with the benchmarking process that educators and institutions employ locally. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. Non-Gaussian Methods for Causal Structure Learning.

    Science.gov (United States)

    Shimizu, Shohei

    2018-05-22

    Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.

  15. Teaching Research Methods and Statistics in eLearning Environments:Pedagogy, Practical Examples and Possible Futures

    Directory of Open Access Journals (Sweden)

    Adam John Rock

    2016-03-01

    Full Text Available Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal, Ginsburg, & Schau, 1997. Given the ubiquitous and distributed nature of eLearning systems (Nof, Ceroni, Jeong, & Moghaddam, 2015, teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

  16. Mobile Learning as a Method of Ubiquitous Learning: Students' Attitudes, Readiness, and Possible Barriers to Implementation in Higher Education

    Science.gov (United States)

    Alhassan, Riyadh

    2016-01-01

    The purpose of this study was to explore the attitudes and level of readiness, and possible barriers to implementing Mobile Learning as a part of ubiquitous learning. In addition, the study attempted to find out to what extent students are interested in mobile learning. It also aimed to answer the question regarding the readiness of college…

  17. Aggregative Learning Method and Its Application for Communication Quality Evaluation

    Science.gov (United States)

    Akhmetov, Dauren F.; Kotaki, Minoru

    2007-12-01

    In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

  18. Learning and retention of quantum concepts with different teaching methods

    Science.gov (United States)

    Deslauriers, Louis; Wieman, Carl

    2011-06-01

    We measured mastery and retention of conceptual understanding of quantum mechanics in a modern physics course. This was studied for two equivalent cohorts of students taught with different pedagogical approaches using the Quantum Mechanics Conceptual Survey. We measured the impact of pedagogical approach both on the original conceptual learning and on long-term retention. The cohort of students who had a very highly rated traditional lecturer scored 19% lower than the equivalent cohort that was taught using interactive engagement methods. However, the amount of retention was very high for both cohorts, showing only a few percent decrease in scores when retested 6 and 18 months after completion of the course and with no exposure to the material in the interim period. This high level of retention is in striking contrast to the retention measured for more factual learning from university courses and argues for the value of emphasizing conceptual learning.

  19. Sunspot drawings handwritten character recognition method based on deep learning

    Science.gov (United States)

    Zheng, Sheng; Zeng, Xiangyun; Lin, Ganghua; Zhao, Cui; Feng, Yongli; Tao, Jinping; Zhu, Daoyuan; Xiong, Li

    2016-05-01

    High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.

  20. A diagram retrieval method with multi-label learning

    Science.gov (United States)

    Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

    2015-01-01

    In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

  1. Advanced Steel Microstructural Classification by Deep Learning Methods.

    Science.gov (United States)

    Azimi, Seyed Majid; Britz, Dominik; Engstler, Michael; Fritz, Mario; Mücklich, Frank

    2018-02-01

    The inner structure of a material is called microstructure. It stores the genesis of a material and determines all its physical and chemical properties. While microstructural characterization is widely spread and well known, the microstructural classification is mostly done manually by human experts, which gives rise to uncertainties due to subjectivity. Since the microstructure could be a combination of different phases or constituents with complex substructures its automatic classification is very challenging and only a few prior studies exist. Prior works focused on designed and engineered features by experts and classified microstructures separately from the feature extraction step. Recently, Deep Learning methods have shown strong performance in vision applications by learning the features from data together with the classification step. In this work, we propose a Deep Learning method for microstructural classification in the examples of certain microstructural constituents of low carbon steel. This novel method employs pixel-wise segmentation via Fully Convolutional Neural Network (FCNN) accompanied by a max-voting scheme. Our system achieves 93.94% classification accuracy, drastically outperforming the state-of-the-art method of 48.89% accuracy. Beyond the strong performance of our method, this line of research offers a more robust and first of all objective way for the difficult task of steel quality appreciation.

  2. Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

    Science.gov (United States)

    da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

    2018-02-01

    In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

  3. Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

    Directory of Open Access Journals (Sweden)

    da Costa Tavares Ofelia Cizela

    2018-01-01

    Full Text Available In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process and SAW (simple additive Weighting method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

  4. Machine learning methods without tears: a primer for ecologists.

    Science.gov (United States)

    Olden, Julian D; Lawler, Joshua J; Poff, N LeRoy

    2008-06-01

    Machine learning methods, a family of statistical techniques with origins in the field of artificial intelligence, are recognized as holding great promise for the advancement of understanding and prediction about ecological phenomena. These modeling techniques are flexible enough to handle complex problems with multiple interacting elements and typically outcompete traditional approaches (e.g., generalized linear models), making them ideal for modeling ecological systems. Despite their inherent advantages, a review of the literature reveals only a modest use of these approaches in ecology as compared to other disciplines. One potential explanation for this lack of interest is that machine learning techniques do not fall neatly into the class of statistical modeling approaches with which most ecologists are familiar. In this paper, we provide an introduction to three machine learning approaches that can be broadly used by ecologists: classification and regression trees, artificial neural networks, and evolutionary computation. For each approach, we provide a brief background to the methodology, give examples of its application in ecology, describe model development and implementation, discuss strengths and weaknesses, explore the availability of statistical software, and provide an illustrative example. Although the ecological application of machine learning approaches has increased, there remains considerable skepticism with respect to the role of these techniques in ecology. Our review encourages a greater understanding of machin learning approaches and promotes their future application and utilization, while also providing a basis from which ecologists can make informed decisions about whether to select or avoid these approaches in their future modeling endeavors.

  5. The Effect of Using Cooperative Learning Method on Tenth Grade Students' Learning Achievement and Attitude towards Biology

    Science.gov (United States)

    Rabgay, Tshewang

    2018-01-01

    The study investigated the effect of using cooperative learning method on tenth grade students' learning achievement in biology and their attitude towards the subject in a Higher Secondary School in Bhutan. The study used a mixed method approach. The quantitative component included an experimental design where cooperative learning was the…

  6. Introduction of active learning method in learning physiology by MBBS students.

    Science.gov (United States)

    Gilkar, Suhail Ahmad; Lone, Shabiruddin; Lone, Riyaz Ahmad

    2016-01-01

    Active learning has received considerable attention over the past several years, often presented or perceived as a radical change from traditional instruction methods. Current research on learning indicates that using a variety of teaching strategies in the classroom increases student participation and learning. To introduce active learning methodology, i.e., "jigsaw technique" in undergraduate medical education and assess the student and faculty response to it. This study was carried out in the Department of Physiology in a Medical College of North India. A topic was chosen and taught using one of the active learning methods (ALMs), i.e., jigsaw technique. An instrument (questionnaire) was developed in English through an extensive review of literature and was properly validated. The students were asked to give their response on a five-point Likert scale. The feedback was kept anonymous. Faculty also provided their feedback in a separately provided feedback proforma. The data were collected, compiled, and analyzed. Of 150 students of MBBS-first year batch 2014, 142 participated in this study along with 14 faculty members of the Physiology Department. The majority of the students (>90%) did welcome the introduction of ALM and strongly recommended the use of such methods in teaching many more topics in future. 100% faculty members were of the opinion that many more topics shall be taken up using ALMs. This study establishes the fact that both the medical students and faculty want a change from the traditional way of passive, teacher-centric learning, to the more active teaching-learning techniques.

  7. Data Mining and Machine Learning Methods for Dementia Research.

    Science.gov (United States)

    Li, Rui

    2018-01-01

    Patient data in clinical research often includes large amounts of structured information, such as neuroimaging data, neuropsychological test results, and demographic variables. Given the various sources of information, we can develop computerized methods that can be a great help to clinicians to discover hidden patterns in the data. The computerized methods often employ data mining and machine learning algorithms, lending themselves as the computer-aided diagnosis (CAD) tool that assists clinicians in making diagnostic decisions. In this chapter, we review state-of-the-art methods used in dementia research, and briefly introduce some recently proposed algorithms subsequently.

  8. A Pharmacy Preregistration Course Using Online Teaching and Learning Methods

    Science.gov (United States)

    McDowell, Jenny; Marriott, Jennifer L.; Calandra, Angela; Duncan, Gregory

    2009-01-01

    Objective To design and evaluate a preregistration course utilizing asynchronous online learning as the primary distance education delivery method. Design Online course components including tutorials, quizzes, and moderated small-group asynchronous case-based discussions were implemented. Online delivery was supplemented with self-directed and face-to-face learning. Assessment Pharmacy graduates who had completed the course in 2004 and 2005 were surveyed. The majority felt they had benefited from all components of the course, and that online delivery provided benefits including increased peer support, shared learning, and immediate feedback on performance. A majority of the first cohort reported that the workload associated with asynchronous online discussions was too great. The course was altered in 2005 to reduce the online component. Participant satisfaction improved, and most felt that the balance of online to face-to-face delivery was appropriate. Conclusion A new pharmacy preregistration course was successfully implemented. Online teaching and learning was well accepted and appeared to deliver benefits over traditional distance education methods once workload issues were addressed. PMID:19777092

  9. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models

    NARCIS (Netherlands)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A.; van t Veld, Aart A.

    2012-01-01

    PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator

  10. Take AIM and Keep Your Students Engaged

    Science.gov (United States)

    Nash, Catherine

    2014-01-01

    This paper outlines the benefits to distance education teachers of formatting a weekly online newsletter in accordance with motivational learning theory. It reflects on the delivery of weekly AIM newsletters to undergraduate economics students at the Open Polytechnic of New Zealand via Moodle. The acronym, AIM, stands for Academic content,…

  11. Comparison effectiveness of cooperative learning type STAD with cooperative learning type TPS in terms of mathematical method of Junior High School students

    Science.gov (United States)

    Wahyuni, A.

    2018-05-01

    This research is aimed to find out whether the model of cooperative learning type Student Team Achievement Division (STAD) is more effective than cooperative learning type Think-Pair-Share in SMP Negeri 7 Yogyakarta. This research was a quasi-experimental research, using two experimental groups. The population of research was all students of 7thclass in SMP Negeri 7 Yogyakarta that consists of 5 Classes. From the population were taken 2 classes randomly which used as sample. The instrument to collect data was a description test. Measurement of instrument validity use content validity and construct validity, while measuring instrument reliability use Cronbach Alpha formula. To investigate the effectiveness of cooperative learning type STAD and cooperative learning type TPS on the aspect of student’s mathematical method, the datas were analyzed by one sample test. Comparing the effectiveness of cooperative learning type STAD and TPS in terms of mathematical communication skills by using t-test. Normality test was not conducted because the sample of research more than 30 students, while homogeneity tested by using Kolmogorov Smirnov test. The analysis was performed at 5% confidence level.The results show as follows : 1) The model of cooperative learning type STAD and TPS are effective in terms of mathematical method of junior high school students. 2). STAD type cooperative learning model is more effective than TPS type cooperative learning model in terms of mathematical methods of junior high school students.

  12. The Effects of Using Jigsaw Method Based on Cooperative Learning Model in the Undergraduate Science Laboratory Practices

    Science.gov (United States)

    Karacop, Ataman

    2017-01-01

    The main aim of the present study is to determine the influence of a Jigsaw method based on cooperative learning and a confirmatory laboratory method on prospective science teachers' achievements of physics in science teaching laboratory practice courses. The sample of this study consisted of 33 female and 15 male third-grade prospective science…

  13. The Learners’ Attitudes towards Using Different Learning Methods in E-Learning Portal Environment

    Directory of Open Access Journals (Sweden)

    Issham Ismail

    2011-09-01

    Full Text Available This study investigates the learners’ preference of academic, collaborative and social interaction towards interaction methods in e-learning portal. Academic interaction consists of interaction between learners and online learning resources such as online reading, online explanation, online examination and also online question answering. Collaborative interaction occurs when learners interact among themselves using online group discussion. Social interaction happens when learners and instructors participate in the session either via online text chatting or voice chatting. The study employed qualitative methodology where data were collected through questionnaire that was administered to 933 distance education students from Bachelor of Management, Bachelor of Science, Bachelor of Social Science and Bachelor of Art. The survey responses were tabulated in a 5-point Likert scale and analyzed using the Statistical Package for Social Science (SPSS Version 12.0 based on frequency and percentage distribution. The result of the study suggest that among three types of interaction, most of the student prefer academic interaction for their learning supports in e-learning portal compared to collaborative and social interaction. They wish to interact with learning content rather than interact with people. They prefer to read and learn from the resources rather than sharing knowledge among themselves and instructors via collaborative and social interaction.

  14. Realization of Chinese word segmentation based on deep learning method

    Science.gov (United States)

    Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

    2017-08-01

    In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

  15. A Photometric Machine-Learning Method to Infer Stellar Metallicity

    Science.gov (United States)

    Miller, Adam A.

    2015-01-01

    Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

  16. A Photometric Machine-Learning Method to Infer Stellar Metallicity

    Science.gov (United States)

    Miller, Adam A.

    2015-01-01

    Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

  17. Perceptions about traditional and novel methods to learn about postoperative pain management: a qualitative study.

    Science.gov (United States)

    Ingadottir, Brynja; Blondal, Katrin; Jaarsma, Tiny; Thylen, Ingela

    2016-11-01

    The aim of this study was to explore the perceptions of surgical patients about traditional and novel methods to learn about postoperative pain management. Patient education is an important part of postoperative care. Contemporary technology offers new ways for patients to learn about self-care, although face-to-face discussions and brochures are the most common methods of delivering education in nursing practice. A qualitative design with a vignette and semi-structured interviews used for data collection. A purposeful sample of 13 postsurgical patients, who had been discharged from hospital, was recruited during 2013-2014. The patients were given a vignette about anticipated hospital discharge after surgery with four different options for communication (face-to-face, brochure, website, serious game) to learn about postoperative pain management. They were asked to rank their preferred method of learning and thereafter to reflect on their choices. Data were analysed using an inductive content analysis approach. Patients preferred face-to-face education with a nurse, followed by brochures and websites, while games were least preferred. Two categories, each with two sub-categories, emerged from the data. These conceptualized the factors affecting patients' perceptions: (1) 'Trusting the source', sub-categorized into 'Being familiar with the method' and 'Having own prejudgments'; and (2) 'Being motivated to learn' sub-categorized into 'Managing an impaired cognition' and 'Aspiring for increased knowledge'. To implement successfully novel educational methods into postoperative care, healthcare professionals need to be aware of the factors influencing patients' perceptions about how to learn, such as trust and motivation. © 2016 John Wiley & Sons Ltd.

  18. Comparing three experiential learning methods and their effect on medical students' attitudes to learning communication skills.

    Science.gov (United States)

    Koponen, Jonna; Pyörälä, Eeva; Isotalus, Pekka

    2012-01-01

    Despite numerous studies exploring medical students' attitudes to communication skills learning (CSL), there are apparently no studies comparing different experiential learning methods and their influence on students' attitudes. We compared medical students' attitudes to learning communication skills before and after a communication course in the data as a whole, by gender and when divided into three groups using different methods. Second-year medical students (n = 129) were randomly assigned to three groups. In group A (n = 42) the theatre in education method, in group B (n = 44) simulated patients and in group C (n = 43) role-play were used. The data were gathered before and after the course using Communication Skills Attitude Scale. Students' positive attitudes to learning communication skills (PAS; positive attitude scale) increased significantly and their negative attitudes (NAS; negative attitude scale) decreased significantly between the beginning and end of the course. Female students had more positive attitudes than the male students. There were no significant differences in the three groups in the mean scores for PAS or NAS measured before or after the course. The use of experiential methods and integrating communication skills training with visits to health centres may help medical students to appreciate the importance of CSL.

  19. Housing Value Forecasting Based on Machine Learning Methods

    OpenAIRE

    Mu, Jingyi; Wu, Fang; Zhang, Aihua

    2014-01-01

    In the era of big data, many urgent issues to tackle in all walks of life all can be solved via big data technique. Compared with the Internet, economy, industry, and aerospace fields, the application of big data in the area of architecture is relatively few. In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing...

  20. Learning with Generalization Capability by Kernel Methods of Bounded Complexity

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2005-01-01

    Roč. 21, č. 3 (2005), s. 350-367 ISSN 0885-064X R&D Projects: GA AV ČR 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : supervised learning * generalization * model complexity * kernel methods * minimization of regularized empirical errors * upper bounds on rates of approximate optimization Subject RIV: BA - General Mathematics Impact factor: 1.186, year: 2005

  1. Critical thinking instruction and technology enhanced learning from the student perspective: A mixed methods research study.

    Science.gov (United States)

    Swart, Ruth

    2017-03-01

    Critical thinking is acclaimed as a valuable asset for graduates from higher education programs. Technology has advanced in quantity and quality; recognized as a requirement of 21st century learners. A mixed methods research study was undertaken, examining undergraduate nursing student engagement with critical thinking instruction, platformed on two technology-enhanced learning environments: a classroom response system face-to-face in-class and an online discussion forum out-of-class. The Community of Inquiry framed the study capturing constructivist collaborative inquiry to support learning, and facilitate critical thinking capability. Inclusion of quantitative and qualitative data sources aimed to gather a comprehensive understanding of students' development of critical thinking and engagement with technology-enhanced learning. The findings from the students' perspectives were positive toward the inclusion of technology-enhanced learning, and use in supporting their development of critical thinking. Students considered the use of two forms of technology beneficial in meeting different needs and preferences, offering varied means to actively participate in learning. They valued critical thinking instruction being intentionally aligned with subject-specific content facilitating understanding, application, and relevance of course material. While the findings are limited to student participants, the instructional strategies and technology-enhanced learning identified as beneficial can inform course design for the development of critical thinking. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Strategy to Promote Active Learning of an Advanced Research Method

    Science.gov (United States)

    McDermott, Hilary J.; Dovey, Terence M.

    2013-01-01

    Research methods courses aim to equip students with the knowledge and skills required for research yet seldom include practical aspects of assessment. This reflective practitioner report describes and evaluates an innovative approach to teaching and assessing advanced qualitative research methods to final-year psychology undergraduate students. An…

  3. A Doctoral Seminar in Qualitative Research Methods: Lessons Learned

    Directory of Open Access Journals (Sweden)

    Suzanne Franco

    2016-09-01

    Full Text Available New qualitative research methods continue to emerge in response to factors such as renewed interest in mixed methods, better understanding of the importance of a researcher’s philosophical stance, as well as the increased use of technology in data collection and analysis, to name a few. As a result, those facilitating research methods courses must revisit content and instructional strategies in order to prepare well-informed researchers. Approaches range from paradigm to pragmatic emphasis. This descriptive case study of a doctoral seminar for novice qualitative researchers describes the intricacies of the syllabus of a pragmatic approach in a constructivist/social constructionist learning environment. The purpose was to document the delivery and faculty/student interactions and reactions. Noteworthy were the contradictions and frustrations in the delivery as well as in student experiences. In the end, student input led to seminal learning experiences. The confirmation of the effectiveness of a constructivist/social constructivist learning environment is applicable to higher education pedagogy in general.

  4. Deep Learning Methods for Underwater Target Feature Extraction and Recognition

    Directory of Open Access Journals (Sweden)

    Gang Hu

    2018-01-01

    Full Text Available The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved.

  5. The evaluation of student-centredness of teaching and learning: a new mixed-methods approach.

    Science.gov (United States)

    Lemos, Ana R; Sandars, John E; Alves, Palmira; Costa, Manuel J

    2014-08-14

    The aim of the study was to develop and consider the usefulness of a new mixed-methods approach to evaluate the student-centredness of teaching and learning on undergraduate medical courses. An essential paradigm for the evaluation was the coherence between how teachers conceptualise their practice (espoused theories) and their actual practice (theories-in-use). The context was a module within an integrated basic sciences course in an undergraduate medical degree programme. The programme had an explicit intention of providing a student-centred curriculum. A content analysis framework based on Weimer's dimensions of student-centred teaching was used to analyze data collected from individual interviews with seven teachers to identify espoused theories and 34h of classroom observations and one student focus group to identify theories-in-use. The interviewees were identified by purposeful sampling. The findings from the three methods were triangulated to evaluate the student-centredness of teaching and learning on the course. Different, but complementary, perspectives of the student-centredness of teaching and learning were identified by each method. The triangulation of the findings revealed coherence between the teachers' espoused theories and theories-in-use. A mixed-methods approach that combined classroom observations with interviews from a purposeful sample of teachers and students offered a useful evaluation of the extent of student-centredness of teaching and learning of this basic science course. Our case study suggests that this new approach is applicable to other courses in medical education.

  6. Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method.

    Science.gov (United States)

    Yamaguchi, Tomohiro; Kinugasa, Yusuke; Shiomi, Akio; Sato, Sumito; Yamakawa, Yushi; Kagawa, Hiroyasu; Tomioka, Hiroyuki; Mori, Keita

    2015-07-01

    Few data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single institute. From December 2011 to August 2013, a total of 80 consecutive patients who underwent robotic-assisted surgery for rectal cancer performed by the same surgeon were included in this study. The learning curve was analyzed using the cumulative sum method. This method was used for all 80 cases, taking into account operative time. Operative procedures included anterior resections in 6 patients, low anterior resections in 46 patients, intersphincteric resections in 22 patients, and abdominoperineal resections in 6 patients. Lateral lymph node dissection was performed in 28 patients. Median operative time was 280 min (range 135-683 min), and median blood loss was 17 mL (range 0-690 mL). No postoperative complications of Clavien-Dindo classification Grade III or IV were encountered. We arranged operative times and calculated cumulative sum values, allowing differentiation of three phases: phase I, Cases 1-25; phase II, Cases 26-50; and phase III, Cases 51-80. Our data suggested three phases of the learning curve in robotic-assisted surgery for rectal cancer. The first 25 cases formed the learning phase.

  7. Application of machine learning methods for traffic signs recognition

    Science.gov (United States)

    Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.

    2018-02-01

    This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.

  8. Kernel methods for interpretable machine learning of order parameters

    Science.gov (United States)

    Ponte, Pedro; Melko, Roger G.

    2017-11-01

    Machine learning is capable of discriminating phases of matter, and finding associated phase transitions, directly from large data sets of raw state configurations. In the context of condensed matter physics, most progress in the field of supervised learning has come from employing neural networks as classifiers. Although very powerful, such algorithms suffer from a lack of interpretability, which is usually desired in scientific applications in order to associate learned features with physical phenomena. In this paper, we explore support vector machines (SVMs), which are a class of supervised kernel methods that provide interpretable decision functions. We find that SVMs can learn the mathematical form of physical discriminators, such as order parameters and Hamiltonian constraints, for a set of two-dimensional spin models: the ferromagnetic Ising model, a conserved-order-parameter Ising model, and the Ising gauge theory. The ability of SVMs to provide interpretable classification highlights their potential for automating feature detection in both synthetic and experimental data sets for condensed matter and other many-body systems.

  9. A cross-benchmark comparison of 87 learning to rank methods

    NARCIS (Netherlands)

    Tax, N.; Bockting, S.; Hiemstra, D.

    2015-01-01

    Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. New learning to rank methods are generally evaluated on benchmark test collections. However, comparison of learning to rank methods based on evaluation results is hindered

  10. Characteristics and Consequences of Adult Learning Methods and Strategies. Practical Evaluation Reports, Volume 2, Number 1

    Science.gov (United States)

    Trivette, Carol M.; Dunst, Carl J.; Hamby, Deborah W.; O'Herin, Chainey E.

    2009-01-01

    The effectiveness of four adult learning methods (accelerated learning, coaching, guided design, and just-in-time training) constituted the focus of this research synthesis. Findings reported in "How People Learn" (Bransford et al., 2000) were used to operationally define six adult learning method characteristics, and to code and analyze…

  11. Introducing the Collaborative E-Learning Design Method (CoED)

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Buus, Lillian; Nyvang, Tom

    2015-01-01

    In this chapter, a specific learning design method is introduced and explained, namely the Collaborative E-learning Design method (CoED), which has been developed through various projects in “e-Learning Lab – Centre for User Driven Innovation, Learning and Design” (Nyvang & Georgsen, 2007). We br...

  12. Actively Teaching Research Methods with a Process Oriented Guided Inquiry Learning Approach

    Science.gov (United States)

    Mullins, Mary H.

    2017-01-01

    Active learning approaches have shown to improve student learning outcomes and improve the experience of students in the classroom. This article compares a Process Oriented Guided Inquiry Learning style approach to a more traditional teaching method in an undergraduate research methods course. Moving from a more traditional learning environment to…

  13. Effect of Chemistry Triangle Oriented Learning Media on Cooperative, Individual and Conventional Method on Chemistry Learning Result

    Science.gov (United States)

    Latisma D, L.; Kurniawan, W.; Seprima, S.; Nirbayani, E. S.; Ellizar, E.; Hardeli, H.

    2018-04-01

    The purpose of this study was to see which method are well used with the Chemistry Triangle-oriented learning media. This quasi experimental research involves first grade of senior high school students in six schools namely each two SMA N in Solok city, in Pasaman and two SMKN in Pariaman. The sampling technique was done by Cluster Random Sampling. Data were collected by test and analyzed by one-way anova and Kruskall Wallish test. The results showed that the high school students in Solok learning taught by cooperative method is better than the results of student learning taught by conventional and Individual methods, both for students who have high initial ability and low-ability. Research in SMK showed that the overall student learning outcomes taught by conventional method is better than the student learning outcomes taught by cooperative and individual methods. Student learning outcomes that have high initial ability taught by individual method is better than student learning outcomes that are taught by cooperative method and for students who have low initial ability, there is no difference in student learning outcomes taught by cooperative, individual and conventional methods. Learning in high school in Pasaman showed no significant difference in learning outcomes of the three methods undertaken.

  14. Measuring the surgical 'learning curve': methods, variables and competency.

    Science.gov (United States)

    Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

    2014-03-01

    To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.

  15. When practice precedes theory - A mixed methods evaluation of students' learning experiences in an undergraduate study program in nursing.

    Science.gov (United States)

    Falk, Kristin; Falk, Hanna; Jakobsson Ung, Eva

    2016-01-01

    A key area for consideration is determining how optimal conditions for learning can be created. Higher education in nursing aims to prepare students to develop their capabilities to become independent professionals. The aim of this study was to evaluate the effects of sequencing clinical practice prior to theoretical studies on student's experiences of self-directed learning readiness and students' approach to learning in the second year of a three-year undergraduate study program in nursing. 123 nursing students was included in the study and divided in two groups. In group A (n = 60) clinical practice preceded theoretical studies. In group (n = 63) theoretical studies preceded clinical practice. Learning readiness was measured using the Directed Learning Readiness Scale for Nursing Education (SDLRSNE), and learning process was measured using the revised two-factor version of the Study Process Questionnaire (R-SPQ-2F). Students were also asked to write down their personal reflections throughout the course. By using a mixed method design, the qualitative component focused on the students' personal experiences in relation to the sequencing of theoretical studies and clinical practice. The quantitative component provided information about learning readiness before and after the intervention. Our findings confirm that students are sensitive and adaptable to their learning contexts, and that the sequencing of courses is subordinate to a pedagogical style enhancing students' deep learning approaches, which needs to be incorporated in the development of undergraduate nursing programs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Application of unsupervised learning methods in high energy physics

    Energy Technology Data Exchange (ETDEWEB)

    Koevesarki, Peter; Nuncio Quiroz, Adriana Elizabeth; Brock, Ian C. [Physikalisches Institut, Universitaet Bonn, Bonn (Germany)

    2011-07-01

    High energy physics is a home for a variety of multivariate techniques, mainly due to the fundamentally probabilistic behaviour of nature. These methods generally require training based on some theory, in order to discriminate a known signal from a background. Nevertheless, new physics can show itself in ways that previously no one thought about, and in these cases conventional methods give little or no help. A possible way to discriminate between known processes (like vector bosons or top-quark production) or look for new physics is using unsupervised machine learning to extract the features of the data. A technique was developed, based on the combination of neural networks and the method of principal curves, to find a parametrisation of the non-linear correlations of the data. The feasibility of the method is shown on ATLAS data.

  17. Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

    Directory of Open Access Journals (Sweden)

    Vladimir S. Kublanov

    2017-01-01

    Full Text Available The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suffering from the arterial hypertension of II-III degree. The following machine learning approaches were studied: linear and quadratic discriminant analysis, k-nearest neighbors, support vector machine with radial basis, decision trees, and naive Bayes classifier. Moreover, in the study, different methods of feature extraction are analyzed: statistical, spectral, wavelet, and multifractal. All in all, 53 features were investigated. Investigation results show that discriminant analysis achieves the highest classification accuracy. The suggested approach of noncorrelated feature set search achieved higher results than data set based on the principal components.

  18. Digital game based learning: A new method in teaching and learning mathematics

    Science.gov (United States)

    Hussain, Sayed Yusoff bin Syed; Hoe, Tan Wee; Idris, Muhammad Zaffwan bin

    2017-05-01

    Digital game-based learning (DGBL) had been regarded as a sound learning strategy in raising pupils' willingness and interest in many disciplines. Normally, video and digital games are used in the teaching and learning mathematics. based on literature, digital games have proven its capability in making pupils motivated and are more likely to contribute to effective learning mathematics. Hence this research aims to construct a DGBL in the teaching of Mathematics for Year 1 pupils. Then, a quasi-experimental study was carried out in a school located in Gua Musang, Kelantan, involving 39 pupils. Specifically, this article tests the effectiveness of the use of DGBL in the teaching of the topic Addition of Less than 100 on pupil's achievement. This research employed a quasi-experiment, Pre and Post Test of Non-equivalent Control Group design. The data were analysed using the Nonparametric test namely the Mann-Whitney U. The research finding shows the use of the DGBL could increase the pupils' achievement in the topic of Addition of Less than 100. In practice, this research indicates that the DBGL can utilized as an alternative reference strategy for Mathematics teacher.

  19. Implementation of a virtual learning from discrepancy meeting: a method to improve attendance and facilitate shared learning from radiological error

    International Nuclear Information System (INIS)

    Carlton Jones, A.L.; Roddie, M.E.

    2016-01-01

    Aim: To assess the effect on radiologist participation in learning from discrepancy meetings (LDMs) in a multisite radiology department by establishing virtual LDMs using OsiriX (Pixmeo). Materials and methods: Sets of anonymised discrepancy cases were added to an OsiriX database available for viewing on iMacs in all radiology reporting rooms. Radiologists were given a 3-week period to review the cases and send their feedback to the LDM convenor. Group learning points and consensus feedback were added to each case before it was moved to a permanent digital LDM library. Participation was recorded and compared with that from the previous 4 years of conventional LDMs. Radiologist feedback comparing the two types of LDM was collected using an anonymous online questionnaire. Results: Numbers of radiologists attending increased significantly from a mean of 12±2.9 for the conventional LDM to 32.7±7 for the virtual LDM (p<0.0001) and the percentage of radiologists achieving the UK standard of participation in at least 50% of LDMs annually rose from an average of 18% to 68%. The number of cases submitted per meeting rose significantly from an average of 11.1±3 for conventional LDMs to 15.9±5.9 for virtual LDMs (p<0.0097). Analysis of 35 returned questionnaires showed that radiologists welcomed being able to review cases at a time and place of their choosing and at their own pace. Conclusion: Introduction of virtual LDMs in a multisite radiology department improved radiologist participation in shared learning from radiological discrepancy and increased the number of submitted cases. - Highlights: • Learning from error is an important way to improve patient safety. • Consultant attendance at learning from discrepancy meetings (LDMs) was persistently poor in a large, multisite Trust. • Introduction of a ‘virtual’ LDM improved consultant participation and increased the number of cases submitted.

  20. Bedside Teaching: Is it Effective Methods in Clinical Nursing Students Learning?

    Directory of Open Access Journals (Sweden)

    Fatikhu Yatuni Asmara

    2017-01-01

    Full Text Available Introduction: Clinical learning is the centre of medical students education. Students not only learn about practical skills but also communication with patient and other health care givers which both competencies are useful for students when they come into working world (Spencer, 2003. There are variations of methods applied in clinical learning process; one of them is bedside teaching. The aim of this study was to observe the bedside teaching process which is held in group of students, teacher, and patient. Another aim was to know responses of students, teacher, and patients to the bedside teaching process. Method: The method which was applied in this study is observation in which bedside teaching process was observed related to the roles and function of each component of bedside teaching: students, teacher, and patient in each phase: preparation, process, and evaluation. Then it was continued by interview to know the responses of students, teacher, and patient related to bedside teaching process. Result: The result showed that both students and teacher felt that bedside teaching is an effective method since it helped students to achieve their competences in clinical setting and develop their communication skill. Furthermore teacher stated that bedside teaching facilitated her to be a good role model for students. As well as students and teacher, patient got advantage from the bedside teaching process that she got information related to her case; however the time to discuss was limited. During the observation, each component of bedside teaching did their roles and function, such as: during the preparation teacher asked inform consent from patient, and patient gave inform consent as well while students prepared the material. Discussions: Suggestion for next research is conducting a deeper study about perception of students, teacher, and patient about bedside teaching process and the strategies to develop it to be better method. Keywords: bedside

  1. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  2. A comparative study on effect of e-learning and instructor-led methods on nurses' documentation competency.

    Science.gov (United States)

    Abbaszadeh, Abbas; Sabeghi, Hakimeh; Borhani, Fariba; Heydari, Abbas

    2011-01-01

    Accurate recording of the nursing care indicates the care performance and its quality, so that, any failure in documentation can be a reason for inadequate patient care. Therefore, improving nurses' skills in this field using effective educational methods is of high importance. Since traditional teaching methods are not suitable for communities with rapid knowledge expansion and constant changes, e-learning methods can be a viable alternative. To show the importance of e-learning methods on nurses' care reporting skills, this study was performed to compare the e-learning methods with the traditional instructor-led methods. This was a quasi-experimental study aimed to compare the effect of two teaching methods (e-learning and lecture) on nursing documentation and examine the differences in acquiring competency on documentation between nurses who participated in the e-learning (n = 30) and nurses in a lecture group (n = 31). The results of the present study indicated that statistically there was no significant difference between the two groups. The findings also revealed that statistically there was no significant correlation between the two groups toward demographic variables. However, we believe that due to benefits of e-learning against traditional instructor-led method, and according to their equal effect on nurses' documentation competency, it can be a qualified substitute for traditional instructor-led method. E-learning as a student-centered method as well as lecture method equally promote competency of the nurses on documentation. Therefore, e-learning can be used to facilitate the implementation of nursing educational programs.

  3. MATLAB-aided teaching and learning in optics and photonics using the methods of computational photonics

    Science.gov (United States)

    Lin, Zhili; Li, Xiaoyan; Zhu, Daqing; Pu, Jixiong

    2017-08-01

    Due to the nature of light fields of laser waves and pulses as vector quantities with complex spatial distribution and temporal dependence, the optics and photonics courses have always been difficult to teach and learn without the support of graphical visualization, numerical simulations and hands-on experiments. One of the state-of-the-art method of computational photonics, the finite-difference time-domain(FDTD) method, is applied with MATLAB simulations to model typical teaching cases in optics and photonics courses. The obtained results with graphical visualization in the form of animated pictures allow students to more deeply understand the dynamic process of light interaction with classical optical structures. The discussed teaching methodology is aimed to enhance the teaching effectiveness of optics and photonics courses and arousing the students' learning interest.

  4. IP-MLI: An Independency of Learning Materials from Platforms in a Mobile Learning using Intelligent Method

    Directory of Open Access Journals (Sweden)

    Mohammed Abdallh Otair

    2006-06-01

    Full Text Available Attempting to deliver a monolithic mobile learning system is too inflexible in view of the heterogeneous mixture of hardware and services available and the desirability of facility blended approaches to learning delivery, and how to build learning materials to run on all platforms[1]. This paper proposes a framework of mobile learning system using an intelligent method (IP-MLI . A fuzzy matching method is used to find suitable learning material design. It will provide a best matching for each specific platform type for each learner. The main contribution of the proposed method is to use software layer to insulate learning materials from device-specific features. Consequently, many versions of learning materials can be designed to work on many platform types.

  5. Learning methods and strategies of anatomy among medical students in two different Institutions in Riyadh, Saudi Arabia.

    Science.gov (United States)

    Al-Mohrej, Omar A; Al-Ayedh, Noura K; Masuadi, Emad M; Al-Kenani, Nader S

    2017-04-01

    Anatomy instructors adopt individual teaching methods and strategies to convey anatomical information to medical students for learning. Students also exhibit their own individual learning preferences. Instructional methods preferences vary between both instructors and students across different institutions. In attempt to bridge the gap between teaching methods and the students' learning preferences, this study aimed to identify students' learning methods and different strategies of studying anatomy in two different Saudi medical schools in Riyadh. A cross-sectional study, conducted in Saudi Arabia in April 2015, utilized a three-section questionnaire, which was distributed to a consecutive sample of 883 medical students to explore their methods and strategies in learning and teaching anatomy in two separate institutions in Riyadh, Saudi Arabia. Medical students' learning styles and preferences were found to be predominantly affected by different cultural backgrounds, gender, and level of study. Many students found it easier to understand and remember anatomy components using study aids. In addition, almost half of the students felt confident to ask their teachers questions after class. The study also showed that more than half of the students found it easier to study by concentrating on a particular part of the body rather than systems. Students' methods of learning were distributed equally between memorizing facts and learning by hands-on dissection. In addition, the study showed that two thirds of the students felt satisfied with their learning method and believed it was well suited for anatomy. There is no single teaching method which proves beneficial; instructors should be flexible in their teaching in order to optimize students' academic achievements.

  6. Lessons learned: advantages and disadvantages of mixed method research

    DEFF Research Database (Denmark)

    Malina, Mary A.; Nørreklit, Hanne; Selto, Frank H.

    2011-01-01

    on the use and usefulness of a specialized balanced scorecard; and third, to encourage researchers to actually use multiple methods and sources of data to address the very many accounting phenomena that are not fully understood. Design/methodology/approach – This paper is an opinion piece based...... on the authors' experience conducting a series of longitudinal mixed method studies. Findings – The authors suggest that in many studies, using a mixed method approach provides the best opportunity for addressing research questions. Originality/value – This paper provides encouragement to those who may wish......Purpose – The purpose of this paper is first, to discuss the theoretical assumptions, qualities, problems and myopia of the dominating quantitative and qualitative approaches; second, to describe the methodological lessons that the authors learned while conducting a series of longitudinal studies...

  7. Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides

    Directory of Open Access Journals (Sweden)

    Stanislawski Jerzy

    2013-01-01

    Full Text Available Abstract Background Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. Results We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%. The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile to 0.5 CPU-hours (simplified 3D profile to seconds (machine learning. Conclusions We showed that the simplified profile generation method does not introduce an error with regard to the original method, while

  8. Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides.

    Science.gov (United States)

    Stanislawski, Jerzy; Kotulska, Malgorzata; Unold, Olgierd

    2013-01-17

    Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning). We showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset

  9. Bayesian methods for addressing long-standing problems in associative learning: The case of PREE.

    Science.gov (United States)

    Blanco, Fernando; Moris, Joaquín

    2017-07-20

    Most associative models typically assume that learning can be understood as a gradual change in associative strength that captures the situation into one single parameter, or representational state. We will call this view single-state learning. However, there is ample evidence showing that under many circumstances different relationships that share features can be learned independently, and animals can quickly switch between expressing one or another. We will call this multiple-state learning. Theoretically, it is understudied because it needs a different data analysis approach from those usually employed. In this paper, we present a Bayesian model of the Partial Reinforcement Extinction Effect (PREE) that can test the predictions of the multiple-state view. This implies estimating the moment of change in the responses (from the acquisition to the extinction performance), both at the individual and at the group levels. We used this model to analyze data from a PREE experiment with three levels of reinforcement during acquisition (100%, 75% and 50%). We found differences in the estimated moment of switch between states during extinction, so that it was delayed after leaner partial reinforcement schedules. The finding is compatible with the multiple-state view. It is the first time, to our knowledge, that the predictions from the multiple-state view are tested directly. The paper also aims to show the benefits that Bayesian methods can bring to the associative learning field.

  10. Best practices for learning physiology: combining classroom and online methods.

    Science.gov (United States)

    Anderson, Lisa C; Krichbaum, Kathleen E

    2017-09-01

    Physiology is a requisite course for many professional allied health programs and is a foundational science for learning pathophysiology, health assessment, and pharmacology. Given the demand for online learning in the health sciences, it is important to evaluate the efficacy of online and in-class teaching methods, especially as they are combined to form hybrid courses. The purpose of this study was to compare two hybrid physiology sections in which one section was offered mostly in-class (85% in-class), and the other section was offered mostly online (85% online). The two sections in 2 yr ( year 1 and year 2 ) were compared in terms of knowledge of physiology measured in exam scores and pretest-posttest improvement, and in measures of student satisfaction with teaching. In year 1 , there were some differences on individual exam scores between the two sections, but no significant differences in mean exam scores or in pretest-posttest improvements. However, in terms of student satisfaction, the mostly in-class students in year 1 rated the instructor significantly higher than did the mostly online students. Comparisons between in-class and online students in the year 2 cohort yielded data that showed that mean exam scores were not statistically different, but pre-post changes were significantly greater in the mostly online section; student satisfaction among mostly online students also improved significantly. Education researchers must investigate effective combinations of in-class and online methods for student learning outcomes, while maintaining the flexibility and convenience that online methods provide. Copyright © 2017 the American Physiological Society.

  11. MACHINE LEARNING METHODS IN DIGITAL AGRICULTURE: ALGORITHMS AND CASES

    Directory of Open Access Journals (Sweden)

    Aleksandr Vasilyevich Koshkarov

    2018-05-01

    Full Text Available Ensuring food security is a major challenge in many countries. With a growing global population, the issues of improving the efficiency of agriculture have become most relevant. Farmers are looking for new ways to increase yields, and governments of different countries are developing new programs to support agriculture. This contributes to a more active implementation of digital technologies in agriculture, helping farmers to make better decisions, increase yields and take care of the environment. The central point is the collection and analysis of data. In the industry of agriculture, data can be collected from different sources and may contain useful patterns that identify potential problems or opportunities. Data should be analyzed using machine learning algorithms to extract useful insights. Such methods of precision farming allow the farmer to monitor individual parts of the field, optimize the consumption of water and chemicals, and identify problems quickly. Purpose: to make an overview of the machine learning algorithms used for data analysis in agriculture. Methodology: an overview of the relevant literature; a survey of farmers. Results: relevant algorithms of machine learning for the analysis of data in agriculture at various levels were identified: soil analysis (soil assessment, soil classification, soil fertility predictions, weather forecast (simulation of climate change, temperature and precipitation prediction, and analysis of vegetation (weed identification, vegetation classification, plant disease identification, crop forecasting. Practical implications: agriculture, crop production.

  12. Estimating building energy consumption using extreme learning machine method

    International Nuclear Information System (INIS)

    Naji, Sareh; Keivani, Afram; Shamshirband, Shahaboddin; Alengaram, U. Johnson; Jumaat, Mohd Zamin; Mansor, Zulkefli; Lee, Malrey

    2016-01-01

    The current energy requirements of buildings comprise a large percentage of the total energy consumed around the world. The demand of energy, as well as the construction materials used in buildings, are becoming increasingly problematic for the earth's sustainable future, and thus have led to alarming concern. The energy efficiency of buildings can be improved, and in order to do so, their operational energy usage should be estimated early in the design phase, so that buildings are as sustainable as possible. An early energy estimate can greatly help architects and engineers create sustainable structures. This study proposes a novel method to estimate building energy consumption based on the ELM (Extreme Learning Machine) method. This method is applied to building material thicknesses and their thermal insulation capability (K-value). For this purpose up to 180 simulations are carried out for different material thicknesses and insulation properties, using the EnergyPlus software application. The estimation and prediction obtained by the ELM model are compared with GP (genetic programming) and ANNs (artificial neural network) models for accuracy. The simulation results indicate that an improvement in predictive accuracy is achievable with the ELM approach in comparison with GP and ANN. - Highlights: • Buildings consume huge amounts of energy for operation. • Envelope materials and insulation influence building energy consumption. • Extreme learning machine is used to estimate energy usage of a sample building. • The key effective factors in this study are insulation thickness and K-value.

  13. Evaluation Methods on Usability of M-Learning Environments

    Directory of Open Access Journals (Sweden)

    Teresa Magal-Royo

    2007-10-01

    Full Text Available Nowadays there are different evaluation methods focused in the assessment of the usability of telematic methods. The assessment of 3rd generation web environments evaluates the effectiveness and usability of application with regard to the user needs. Wireless usability and, specifically in mobile phones, is concentrated in the validation of the features and tools management using conventional interactive environments. There is not a specific and suitable criterion to evaluate created environments and m-learning platforms, where the restricted and sequential representation is a fundamental aspect to be considered.The present paper exposes the importance of the conventional usability methods to verify both: the employed contents in wireless formats, and the possible interfaces from the conception phases, to the validations of the platform with such characteristics.The development of usability adapted inspection could be complemented with the Remote’s techniques of usability testing, which are being carried out these days in the mobile devices field and which pointed out the need to apply common criteria in the validation of non-located learning scenarios.

  14. A Preliminary Survey of the Preferred Learning Methods for Interpretation Students

    Science.gov (United States)

    Heinz, Michael

    2013-01-01

    There are many different methods that individuals use to learn languages like reading books or writing essays. Not all methods are equally successful for second language learners but nor do all successful learners of a second language show identical preferences for learning methods. Additionally, at the highest level of language learning various…

  15. Characterizing Engineering Learners' Preferences for Active and Passive Learning Methods

    Science.gov (United States)

    Magana, Alejandra J.; Vieira, Camilo; Boutin, Mireille

    2018-01-01

    This paper studies electrical engineering learners' preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called "slectures," and some others. The results suggest that…

  16. Comparisons of likelihood and machine learning methods of individual classification

    Science.gov (United States)

    Guinand, B.; Topchy, A.; Page, K.S.; Burnham-Curtis, M. K.; Punch, W.F.; Scribner, K.T.

    2002-01-01

    Classification methods used in machine learning (e.g., artificial neural networks, decision trees, and k-nearest neighbor clustering) are rarely used with population genetic data. We compare different nonparametric machine learning techniques with parametric likelihood estimations commonly employed in population genetics for purposes of assigning individuals to their population of origin (“assignment tests”). Classifier accuracy was compared across simulated data sets representing different levels of population differentiation (low and high FST), number of loci surveyed (5 and 10), and allelic diversity (average of three or eight alleles per locus). Empirical data for the lake trout (Salvelinus namaycush) exhibiting levels of population differentiation comparable to those used in simulations were examined to further evaluate and compare classification methods. Classification error rates associated with artificial neural networks and likelihood estimators were lower for simulated data sets compared to k-nearest neighbor and decision tree classifiers over the entire range of parameters considered. Artificial neural networks only marginally outperformed the likelihood method for simulated data (0–2.8% lower error rates). The relative performance of each machine learning classifier improved relative likelihood estimators for empirical data sets, suggesting an ability to “learn” and utilize properties of empirical genotypic arrays intrinsic to each population. Likelihood-based estimation methods provide a more accessible option for reliable assignment of individuals to the population of origin due to the intricacies in development and evaluation of artificial neural networks. In recent years, characterization of highly polymorphic molecular markers such as mini- and microsatellites and development of novel methods of analysis have enabled researchers to extend investigations of ecological and evolutionary processes below the population level to the level of

  17. Advanced methods in NDE using machine learning approaches

    Science.gov (United States)

    Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank

    2018-04-01

    Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability

  18. Instructional methods and cognitive and learning styles in web-based learning: report of two randomised trials.

    Science.gov (United States)

    Cook, David A; Gelula, Mark H; Dupras, Denise M; Schwartz, Alan

    2007-09-01

    Adapting web-based (WB) instruction to learners' individual differences may enhance learning. Objectives This study aimed to investigate aptitude-treatment interactions between learning and cognitive styles and WB instructional methods. We carried out a factorial, randomised, controlled, crossover, post-test-only trial involving 89 internal medicine residents, family practice residents and medical students at 2 US medical schools. Parallel versions of a WB course in complementary medicine used either active or reflective questions and different end-of-module review activities ('create and study a summary table' or 'study an instructor-created table'). Participants were matched or mismatched to question type based on active or reflective learning style. Participants used each review activity for 1 course module (crossover design). Outcome measurements included the Index of Learning Styles, the Cognitive Styles Analysis test, knowledge post-test, course rating and preference. Post-test scores were similar for matched (mean +/- standard error of the mean 77.4 +/- 1.7) and mismatched (76.9 +/- 1.7) learners (95% confidence interval [CI] for difference - 4.3 to 5.2l, P = 0.84), as were course ratings (P = 0.16). Post-test scores did not differ between active-type questions (77.1 +/- 2.1) and reflective-type questions (77.2 +/- 1.4; P = 0.97). Post-test scores correlated with course ratings (r = 0.45). There was no difference in post-test subscores for modules completed using the 'construct table' format (78.1 +/- 1.4) or the 'table provided' format (76.1 +/- 1.4; CI - 1.1 to 5.0, P = 0.21), and wholist and analytic styles had no interaction (P = 0.75) or main effect (P = 0.18). There was no association between activity preference and wholist or analytic scores (P = 0.37). Cognitive and learning styles had no apparent influence on learning outcomes. There were no differences in outcome between these instructional methods.

  19. Identification of the Learning Styles and "On-the-Job" Learning Methods Implemented by Nurses for Promoting Their Professional Knowledge and Skills.

    Science.gov (United States)

    Rassin, Michal; Kurzweil, Yaffa; Maoz, Yael

    2015-05-09

    The aim of this study was to identify the learning styles and methods used by nurses to promote their professional knowledge and skills. 928 nurses from 11 hospitals across Israel completed 2 questionnaires, (1) Kolb's Learning Style Inventory, Version 3.1. and (2) the On-The-Job Learning Styles Questionnaire for the Nursing Profession. The most common learning style was the convergent style. The other learning styles were rated in the following descending order: accommodation, assimilation, and divergence. The on-the-job learning style consistently ranked highest was experience of relevant situations. On the other hand, seeking knowledge from books, journals, television, or the Internet was ranked lowest on all the indicators examined. With respect to general and on-the-job learning styles, statistically significant differences were found between groups of nurses by: country of birth, gender, department, age, education, and role. Nurses required to take more personal responsibility for their own professional development by deepening their self-learning skills.

  20. Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.

    Science.gov (United States)

    Ranjith, G; Parvathy, R; Vikas, V; Chandrasekharan, Kesavadas; Nair, Suresh

    2015-04-01

    With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine learning, a branch of artificial intelligence, is increasingly being used in medical image analysis applications such as image segmentation, registration and computer-aided diagnosis and detection. Histopathological analysis is currently the gold standard for classification of brain tumors. The use of machine learning algorithms along with extraction of relevant features from magnetic resonance imaging (MRI) holds promise of replacing conventional invasive methods of tumor classification. The aim of the study is to classify gliomas into benign and malignant types using MRI data. Retrospective data from 28 patients who were diagnosed with glioma were used for the analysis. WHO Grade II (low-grade astrocytoma) was classified as benign while Grade III (anaplastic astrocytoma) and Grade IV (glioblastoma multiforme) were classified as malignant. Features were extracted from MR spectroscopy. The classification was done using four machine learning algorithms: multilayer perceptrons, support vector machine, random forest and locally weighted learning. Three of the four machine learning algorithms gave an area under ROC curve in excess of 0.80. Random forest gave the best performance in terms of AUC (0.911) while sensitivity was best for locally weighted learning (86.1%). The performance of different machine learning algorithms in the classification of gliomas is promising. An even better performance may be expected by integrating features extracted from other MR sequences. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  1. A Dynamic Hidden Forwarding Path Planning Method Based on Improved Q-Learning in SDN Environments

    Directory of Open Access Journals (Sweden)

    Yun Chen

    2018-01-01

    Full Text Available Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3 to O(N2. In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately.

  2. A literature review about usability evaluation methods for e-learning platforms.

    Science.gov (United States)

    Freire, Luciana Lopes; Arezes, Pedro Miguel; Campos, José Creissac

    2012-01-01

    The usability analysis of information systems has been the target of several research studies over the past thirty years. These studies have highlighted a great diversity of points of view, including researchers from different scientific areas such as Ergonomics, Computer Science, Design and Education. Within the domain of information ergonomics, the study of tools and methods used for usability evaluation dedicated to E-learning presents evidence that there is a continuous and dynamic evolution of E-learning systems, in many different contexts -academics and corporative. These systems, also known as LMS (Learning Management Systems), can be classified according to their educational goals and their technological features. However, in these systems the usability issues are related with the relationship/interactions between user and system in the user's context. This review is a synthesis of research project about Information Ergonomics and embraces three dimensions, namely the methods, models and frameworks that have been applied to evaluate LMS. The study also includes the main usability criteria and heuristics used. The obtained results show a notorious change in the paradigms of usability, with which it will be possible to discuss about the studies carried out by different researchers that were focused on usability ergonomic principles aimed at E-learning.

  3. The experimental field work as practical learning method

    Directory of Open Access Journals (Sweden)

    Nicolás Fernández Losa

    2014-11-01

    Full Text Available This paper describes a teaching experience about experimental field work as practical learning method implemented in the subject of Organizational Behaviour. With this teaching experience we pretend to change the practical training, as well as in its evaluation process, in order to favour the development of transversal skills of students. For this purpose, the use of a practice plan, tackled through an experimental field work and carried out with the collaboration of a business organization within a work team (as organic unity of learning, arises as an alternative to the traditional method of practical teachings and allows the approach of business reality into the classroom, as well as actively promote the use of transversal skills. In particular, we develop the experience in three phases. Initially, the students, after forming a working group and define a field work project, should get the collaboration of a nearby business organization in which to obtain data on one or more functional areas of organizational behaviour. Subsequently, students carry out the field work with the realization of the scheduled visits and elaboration of a memory to establish a diagnosis of the strategy followed by the company in these functional areas in order to propose and justify alternative actions that improve existing ones. Finally, teachers assess the different field work memories and their public presentations according to evaluation rubrics, which try to objectify and unify to the maximum the evaluation criteria and serve to guide the learning process of students. The results of implementation of this teaching experience, measured through a Likert questionnaire, are very satisfactory for students.

  4. Application of blended learning in teaching statistical methods

    Directory of Open Access Journals (Sweden)

    Barbara Dębska

    2012-12-01

    Full Text Available The paper presents the application of a hybrid method (blended learning - linking traditional education with on-line education to teach selected problems of mathematical statistics. This includes the teaching of the application of mathematical statistics to evaluate laboratory experimental results. An on-line statistics course was developed to form an integral part of the module ‘methods of statistical evaluation of experimental results’. The course complies with the principles outlined in the Polish National Framework of Qualifications with respect to the scope of knowledge, skills and competencies that students should have acquired at course completion. The paper presents the structure of the course and the educational content provided through multimedia lessons made accessible on the Moodle platform. Following courses which used the traditional method of teaching and courses which used the hybrid method of teaching, students test results were compared and discussed to evaluate the effectiveness of the hybrid method of teaching when compared to the effectiveness of the traditional method of teaching.

  5. Methods of Efficient Study Habits and Physics Learning

    Science.gov (United States)

    Zettili, Nouredine

    2010-02-01

    We want to discuss the methods of efficient study habits and how they can be used by students to help them improve learning physics. In particular, we deal with the most efficient techniques needed to help students improve their study skills. We focus on topics such as the skills of how to develop long term memory, how to improve concentration power, how to take class notes, how to prepare for and take exams, how to study scientific subjects such as physics. We argue that the students who conscientiously use the methods of efficient study habits achieve higher results than those students who do not; moreover, a student equipped with the proper study skills will spend much less time to learn a subject than a student who has no good study habits. The underlying issue here is not the quantity of time allocated to the study efforts by the students, but the efficiency and quality of actions so that the student can function at peak efficiency. These ideas were developed as part of Project IMPACTSEED (IMproving Physics And Chemistry Teaching in SEcondary Education), an outreach grant funded by the Alabama Commission on Higher Education. This project is motivated by a major pressing local need: A large number of high school physics teachers teach out of field. )

  6. A Photometric Machine-Learning Method to Infer Stellar Metallicity

    Science.gov (United States)

    Miller, Adam A.

    2015-01-01

    Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' < or = 18 mag), with 4500 K < or = Teff < or = 7000 K, corresponding to those with the most reliable SSPP estimates, I find that the model predicts [Fe/H] values with a root-mean-squared-error (RMSE) of approx.0.27 dex. The RMSE from this machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

  7. Multiple instance learning tracking method with local sparse representation

    KAUST Repository

    Xie, Chengjun

    2013-10-01

    When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.

  8. The Effect of Instructional Methods (Lecture-Discussion versus Group Discussion) and Teaching Talent on Teacher Trainees Student Learning Outcomes

    Science.gov (United States)

    Mutrofin; Degeng, Nyoman Sudana; Ardhana, Wayan; Setyosari, Punaji

    2017-01-01

    The aim of this study is to examine difference in the effect of instructional methods (lecture-discussion versus group discussion) and teaching talent on teacher trainees student learning outcomes. It was conducted by a quasi-experimental design using the factorialized (2 x 2) version of the nonequivalent control group design. The subjects were…

  9. Enhancing Learning Outcomes through New E-Textbooks: A Desirable Combination of Presentation Methods and Concept Maps

    Science.gov (United States)

    Huang, Kuo-Liang; Chen, Kuo-Hsiang; Ho, Chun-Heng

    2014-01-01

    It is possible that e-textbook readers and tablet PC's will become mainstream reading devices in the future. However, knowledge about instructional design in this field of learning sciences is inadequate. This study aimed to analyse how two factors, that is, presentation methods and concept maps, interact with cognitive load and learning…

  10. Deep Learning Methods for Improved Decoding of Linear Codes

    Science.gov (United States)

    Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

    2018-02-01

    The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

  11. Machine learning methods for clinical forms analysis in mental health.

    Science.gov (United States)

    Strauss, John; Peguero, Arturo Martinez; Hirst, Graeme

    2013-01-01

    In preparation for a clinical information system implementation, the Centre for Addiction and Mental Health (CAMH) Clinical Information Transformation project completed multiple preparation steps. An automated process was desired to supplement the onerous task of manual analysis of clinical forms. We used natural language processing (NLP) and machine learning (ML) methods for a series of 266 separate clinical forms. For the investigation, documents were represented by feature vectors. We used four ML algorithms for our examination of the forms: cluster analysis, k-nearest neigh-bours (kNN), decision trees and support vector machines (SVM). Parameters for each algorithm were optimized. SVM had the best performance with a precision of 64.6%. Though we did not find any method sufficiently accurate for practical use, to our knowledge this approach to forms has not been used previously in mental health.

  12. A Learning-Based Steganalytic Method against LSB Matching Steganography

    Directory of Open Access Journals (Sweden)

    Z. Xia

    2011-04-01

    Full Text Available This paper considers the detection of spatial domain least significant bit (LSB matching steganography in gray images. Natural images hold some inherent properties, such as histogram, dependence between neighboring pixels, and dependence among pixels that are not adjacent to each other. These properties are likely to be disturbed by LSB matching. Firstly, histogram will become smoother after LSB matching. Secondly, the two kinds of dependence will be weakened by the message embedding. Accordingly, three features, which are respectively based on image histogram, neighborhood degree histogram and run-length histogram, are extracted at first. Then, support vector machine is utilized to learn and discriminate the difference of features between cover and stego images. Experimental results prove that the proposed method possesses reliable detection ability and outperforms the two previous state-of-the-art methods. Further more, the conclusions are drawn by analyzing the individual performance of three features and their fused feature.

  13. Relabeling exchange method (REM) for learning in neural networks

    Science.gov (United States)

    Wu, Wen; Mammone, Richard J.

    1994-02-01

    The supervised training of neural networks require the use of output labels which are usually arbitrarily assigned. In this paper it is shown that there is a significant difference in the rms error of learning when `optimal' label assignment schemes are used. We have investigated two efficient random search algorithms to solve the relabeling problem: the simulated annealing and the genetic algorithm. However, we found them to be computationally expensive. Therefore we shall introduce a new heuristic algorithm called the Relabeling Exchange Method (REM) which is computationally more attractive and produces optimal performance. REM has been used to organize the optimal structure for multi-layered perceptrons and neural tree networks. The method is a general one and can be implemented as a modification to standard training algorithms. The motivation of the new relabeling strategy is based on the present interpretation of dyslexia as an encoding problem.

  14. Incorporating Meaningful Gamification in a Blended Learning Research Methods Class: Examining Student Learning, Engagement, and Affective Outcomes

    Science.gov (United States)

    Tan, Meng; Hew, Khe Foon

    2016-01-01

    In this study, we investigated how the use of meaningful gamification affects student learning, engagement, and affective outcomes in a short, 3-day blended learning research methods class using a combination of experimental and qualitative research methods. Twenty-two postgraduates were randomly split into two groups taught by the same…

  15. The Effect of Learning Method and Confidence Level on the Ability of Interpreting Religious Poem

    Directory of Open Access Journals (Sweden)

    Kinayati Djojosuroto

    2017-11-01

    Full Text Available This research aims to determine the effect of the learning method (expository and authentic and the level of confidence in the ability of religious poetry interpretation of the students of the third semester, majoring in the Indonesian Language and Literature Education of Universitas Negeri Manado. The method used is the quasi-experimental method with 2 x 2 factorial designs. The measurement of Y variable (ability to interpret the religious poetry uses the writing test and the level of confidence uses a questionnaire. Data analysis technique in this study is analysis of variance (ANOVA followed by two lanes and Tuckey test to look at the interaction of the group. Before the test, the hypothesis is that analysis requirements normality data test using Liliefors test and homogeneity test data using Bartlett test. The results show differences in the ability to explain the religious poetry among students who study with the expository method and the students who study with the authentic method. That is, overall, the expository method is better than the authentic method to improve the ability of the students. To improve the ability of the students to interpret the religious poetry, it is better to use the authentic method for the group that has a lower level of confidence. There is the influence of the interaction between learning method (expository and authentic and the level of confidence in the ability of religious poetry interpretation. Based on these results, it can be concluded that: First, lecturers can determine what materials and method that can be used to enhance the ability to interpret religious poetry when the level of confidence of the students has been known. Second, expository teaching methods and authentic teaching method for group of students with different level of confidence will give you different result on the ability of that group of students to interpret religious poetry as well. Third, the increase of the ability to interpret

  16. Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

    Directory of Open Access Journals (Sweden)

    Mingjie Tan

    2015-02-01

    Full Text Available The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN, Decision Tree (DT and Bayesian Networks (BNs. A large sample of 62375 students was utilized in the procedures of model training and testing. The results of each model were presented in confusion matrix, and analyzed by calculating the rates of accuracy, precision, recall, and F-measure. The results suggested all of the three machine learning methods were effective in student dropout prediction, and DT presented a better performance. Finally, some suggestions were made for considerable future research.

  17. A Simple Deep Learning Method for Neuronal Spike Sorting

    Science.gov (United States)

    Yang, Kai; Wu, Haifeng; Zeng, Yu

    2017-10-01

    Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

  18. PYRAMID METHOD OF DISTANCE LEARNING IN HIGER EDUCATION

    Directory of Open Access Journals (Sweden)

    Дмитрий Васильевич Сенашенко

    2017-12-01

    Full Text Available The article deals with modern methods of distance learning in the corporate sector. On the specifics of the application of the described methods is their classification and be subject to review their specific differences based on the features and applications of these techniques given the characteristics of the organization of teaching in higher education, a conclusion about their preferred sides, which can be used in distance education. Later in the article, taking into account the above factors, it is proposed an innovative method of formation of educational programs. In view of the similarity of the rendered appearance of the pyramids, this technique proposed name “pyramid”. Offered by the authors, this technique is best synthesis of the best features of the previously described in the article for the online teaching methods. In the future, we are given a detailed description and conducted a preliminary analysis of the applicability of this technique to the training process in the Russian Federation. The analysis describes the eight alleged authors of distance education problems of high school that this method can help to solve.

  19. Learning Specific Content in Technology Education: Learning Study as a Collaborative Method in Swedish Preschool Class Using Hands-On Material

    Science.gov (United States)

    Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin

    2014-01-01

    This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study…

  20. A Learning Method for Neural Networks Based on a Pseudoinverse Technique

    Directory of Open Access Journals (Sweden)

    Chinmoy Pal

    1996-01-01

    Full Text Available A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented. The efficiency and robustness of the method are verified with the help of an Exclusive OR problem and a dynamic system identification of a linear single degree of freedom mass–spring problem. It is observed that, compared with the conventional backpropagation method, the proposed method has a better convergence rate and a higher degree of learning accuracy with a lower equivalent learning coefficient. It is also found that unlike the steepest descent method, the learning capability of which is dependent on the value of the learning coefficient ν, the proposed pseudoinverse based backpropagation algorithm is comparatively robust with respect to its equivalent variable learning coefficient. A combination of the pseudoinverse method and the steepest descent method is proposed for a faster, more accurate learning capability.

  1. Internet-based versus traditional teaching and learning methods.

    Science.gov (United States)

    Guarino, Salvatore; Leopardi, Eleonora; Sorrenti, Salvatore; De Antoni, Enrico; Catania, Antonio; Alagaratnam, Swethan

    2014-10-01

    The rapid and dramatic incursion of the Internet and social networks in everyday life has revolutionised the methods of exchanging data. Web 2.0 represents the evolution of the Internet as we know it. Internet users are no longer passive receivers, and actively participate in the delivery of information. Medical education cannot evade this process. Increasingly, students are using tablets and smartphones to instantly retrieve medical information on the web or are exchanging materials on their Facebook pages. Medical educators cannot ignore this continuing revolution, and therefore the traditional academic schedules and didactic schemes should be questioned. Analysing opinions collected from medical students regarding old and new teaching methods and tools has become mandatory, with a view towards renovating the process of medical education. A cross-sectional online survey was created with Google® docs and administrated to all students of our medical school. Students were asked to express their opinion on their favourite teaching methods, learning tools, Internet websites and Internet delivery devices. Data analysis was performed using spss. The online survey was completed by 368 students. Although textbooks remain a cornerstone for training, students also identified Internet websites, multimedia non-online material, such as the Encyclopaedia on CD-ROM, and other non-online computer resources as being useful. The Internet represented an important aid to support students' learning needs, but textbooks are still their resource of choice. Among the websites noted, Google and Wikipedia significantly surpassed the peer-reviewed medical databases, and access to the Internet was primarily through personal computers in preference to other Internet access devices, such as mobile phones and tablet computers. Increasingly, students are using tablets and smartphones to instantly retrieve medical information. © 2014 John Wiley & Sons Ltd.

  2. The Keyword Method of Foreign Vocabulary Learning: An Investigation of Its Generalizability. Working Paper No. 270.

    Science.gov (United States)

    Pressley, Michael; And Others

    In five experiments, college-age students of differing foreign language-learning abilities were asked to learn Latin word translations to determine the effectiveness of the keyword method of foreign language vocabulary learning. The Latin words were the types for which it has been argued that the keyword method effects would be maximized (the…

  3. Ethics teaching in a medical education environment: preferences for diversity of learning and assessment methods.

    Science.gov (United States)

    AlMahmoud, Tahra; Hashim, M Jawad; Elzubeir, Margaret Ann; Branicki, Frank

    2017-01-01

    Ethics and professionalism are an integral part of medical school curricula; however, medical students' views on these topics have not been assessed in many countries.  The study aimed to examine medical students' perceptions toward ethics and professionalism teaching, and its learning and assessment methods. A self-administered questionnaire eliciting views on professionalism and ethics education was distributed to a total of 128 final-year medical students. A total of 108 students completed the survey, with an 84% response rate. Medical students reported frequently encountering ethical conflicts during training but stated only a moderate level of ethics training at medical school (mean = 5.14 ± 1.8). They noted that their education had helped somewhat to deal with ethical conflicts (mean = 5.39 ± 2.0). Students strongly affirmed the importance of ethics education (mean = 7.63 ± 1.03) and endorsed the value of positive role models (mean = 7.45 ± 1.5) as the preferred learning method. The cohort voiced interest in direct faculty supervision as an approach to assessment of knowledge and skills (mean = 7.62 ± 1.26). Female students perceived greater need for more ethics education compared to males (p = methods for learning.

  4. Learning outcomes associated with patient simulation method in pharmacotherapy education: an integrative review.

    Science.gov (United States)

    Aura, Suvi M; Sormunen, Marjorita S T; Jordan, Sue E; Tossavainen, Kerttu A; Turunen, Hannele E

    2015-06-01

    The aims of this systematic integrative review were to identify evidence for the use of patient simulation teaching methods in pharmacotherapy education and to explore related learning outcomes. A systematic literature search was conducted using 6 databases as follows: CINAHL, PubMed, SCOPUS, ERIC, MEDIC, and the Cochrane Library, using the key words relating to patient simulation and pharmacotherapy. The methodological quality of each study was evaluated. Eighteen articles met the inclusion criteria. The earliest article was published in 2005. The selected research articles were subjected to qualitative content analysis. Patient simulation has been used in pharmacotherapy education for preregistration nursing, dental, medical, and pharmacy students and for the continuing education of nurses. Learning outcomes reported were summarized as follows: (1) commitment to pharmacotherapy learning, (2) development of pharmacotherapy evaluation skills, (3) improvement in pharmacotherapy application skills, and (4) knowledge and understanding of pharmacotherapy. To develop effective teaching methods and ensure health care professionals' competence in medication management, further research is needed to determine the educational and clinical effectiveness of simulation teaching methods.

  5. Are Prospective Elementary School Teachers' Social Studies Teaching Efficacy Beliefs Related to Their Learning Approaches in a Social Studies Teaching Methods Course?

    Science.gov (United States)

    Dündar, Sahin

    2015-01-01

    This study aimed to contribute to the growing literature on learning approaches and teacher self-efficacy beliefs by examining associations between prospective elementary school teachers' learning approaches in a social studies teaching methods course and their social studies teaching efficacy beliefs. One hundred ninety-two prospective elementary…

  6. Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods.

    Science.gov (United States)

    Gonzalez-Navarro, Felix F; Stilianova-Stoytcheva, Margarita; Renteria-Gutierrez, Livier; Belanche-Muñoz, Lluís A; Flores-Rios, Brenda L; Ibarra-Esquer, Jorge E

    2016-10-26

    Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB) modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization.

  7. Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Felix F. Gonzalez-Navarro

    2016-10-01

    Full Text Available Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization.

  8. Statistical and Machine Learning forecasting methods: Concerns and ways forward.

    Science.gov (United States)

    Makridakis, Spyros; Spiliotis, Evangelos; Assimakopoulos, Vassilios

    2018-01-01

    Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions.

  9. Statistical and Machine Learning forecasting methods: Concerns and ways forward

    Science.gov (United States)

    Makridakis, Spyros; Assimakopoulos, Vassilios

    2018-01-01

    Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784

  10. Learning the scientific method using GloFish.

    Science.gov (United States)

    Vick, Brianna M; Pollak, Adrianna; Welsh, Cynthia; Liang, Jennifer O

    2012-12-01

    Here we describe projects that used GloFish, brightly colored, fluorescent, transgenic zebrafish, in experiments that enabled students to carry out all steps in the scientific method. In the first project, students in an undergraduate genetics laboratory course successfully tested hypotheses about the relationships between GloFish phenotypes and genotypes using PCR, fluorescence microscopy, and test crosses. In the second and third projects, students doing independent research carried out hypothesis-driven experiments that also developed new GloFish projects for future genetics laboratory students. Brianna Vick, an undergraduate student, identified causes of the different shades of color found in orange GloFish. Adrianna Pollak, as part of a high school science fair project, characterized the fluorescence emission patterns of all of the commercially available colors of GloFish (red, orange, yellow, green, blue, and purple). The genetics laboratory students carrying out the first project found that learning new techniques and applying their knowledge of genetics were valuable. However, assessments of their learning suggest that this project was not challenging to many of the students. Thus, the independent projects will be valuable as bases to widen the scope and range of difficulty of experiments available to future genetics laboratory students.

  11. Machine Learning-Empowered Biometric Methods for Biomedicine Applications

    Directory of Open Access Journals (Sweden)

    Qingxue Zhang

    2017-07-01

    Full Text Available Nowadays, pervasive computing technologies are paving a promising way for advanced smart health applications. However, a key impediment faced by wide deployment of these assistive smart devices, is the increasing privacy and security issue, such as how to protect access to sensitive patient data in the health record. Focusing on this challenge, biometrics are attracting intense attention in terms of effective user identification to enable confidential health applications. In this paper, we take special interest in two bio-potential-based biometric modalities, electrocardiogram (ECG and electroencephalogram (EEG, considering that they are both unique to individuals, and more reliable than token (identity card and knowledge-based (username/password methods. After extracting effective features in multiple domains from ECG/EEG signals, several advanced machine learning algorithms are introduced to perform the user identification task, including Neural Network, K-nearest Neighbor, Bagging, Random Forest and AdaBoost. Experimental results on two public ECG and EEG datasets show that ECG is a more robust biometric modality compared to EEG, leveraging a higher signal to noise ratio and also more distinguishable morphological patterns. Among different machine learning classifiers, the random forest greatly outperforms the others and owns an identification rate as high as 98%. This study is expected to demonstrate that properly selected biometric empowered by an effective machine learner owns a great potential, to enable confidential biomedicine applications in the era of smart digital health.

  12. E-learning support for Economic-mathematical methods

    Directory of Open Access Journals (Sweden)

    Pavel Kolman

    2009-01-01

    Full Text Available Article is describing process of creating and using of e-learning program for graphical solution of li­near programming problems that is used in the Economic mathematical methods course on Faculty of Business and Economics, MZLU. The program was created within FRVŠ 788/2008 grant and is intended for practicing of graphical solution of LP problems and allows better understanding of the li­near programming problems. In the article is on one hand described the way, how does the program work, it means how were the algorithms implemented, and on the other hand there is described way of use of that program. The program is constructed for working with integer and rational numbers. At the end of the article are shown basic statistics of programs use of students in the present form and the part-time form of study. It is mainly the number of programs downloads and comparison to another programs and students opinion on the e-learning support.

  13. Geocoding location expressions in Twitter messages: A preference learning method

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2014-12-01

    Full Text Available Resolving location expressions in text to the correct physical location, also known as geocoding or grounding, is complicated by the fact that so many places around the world share the same name. Correct resolution is made even more difficult when there is little context to determine which place is intended, as in a 140-character Twitter message, or when location cues from different sources conflict, as may be the case among different metadata fields of a Twitter message. We used supervised machine learning to weigh the different fields of the Twitter message and the features of a world gazetteer to create a model that will prefer the correct gazetteer candidate to resolve the extracted expression. We evaluated our model using the F1 measure and compared it to similar algorithms. Our method achieved results higher than state-of-the-art competitors.

  14. Employing Machine-Learning Methods to Study Young Stellar Objects

    Science.gov (United States)

    Moore, Nicholas

    2018-01-01

    Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.

  15. Inter-laboratory exercise with an aim to compare methods for "9"0Sr and "2"3"9","2"4"0Pu determination in environmental soil samples

    International Nuclear Information System (INIS)

    Jixin Qiao; Per Roos; Salminen-Paatero, Susanna; Stina Holmgren Rondahl; Lagerkvist, Petra; Bourgeaux-Goget, Marie; Stralberg, Elisabeth; Rameback, Henrik; Chalmers University of Technology, Gothenburg

    2017-01-01

    In order to deliver reliable results for a multitude of different scenarios, e.g. emergency preparedness, environmental monitoring, nuclear decommissioning and waste management, there is a constant process of method development in the field of radioanalytical chemistry. This work presents the results of a method comparison exercise aimed at quantifying "9"0Sr and "2"3"9","2"4"0Pu in environmental soil samples, with the intention of evaluating the performance and applicability of different methods. From the methods examined in this work, recommendations are given in order to find a radioanalytical measurement procedure, for "9"0Sr and "2"3"9","2"4"0Pu analysis, which is fit-for-purpose for a particular scenario. (author)

  16. ENTERPRISE RESTRUCTURING AIM AND TYPES

    Directory of Open Access Journals (Sweden)

    S. P. Baranenko

    2011-01-01

    Full Text Available Enterprise restructuring is aimed at adapting it to market conditions and improving its competitiveness through selection of most effective model of using material, technical, technological, organizational, commercial, economical, financial, tax-related and other resources with due account of the demand. Restructuring classification signs and types as well as restructuring aims specific for industrial enterprises are provided for.

  17. BEBP: An Poisoning Method Against Machine Learning Based IDSs

    OpenAIRE

    Li, Pan; Liu, Qiang; Zhao, Wentao; Wang, Dongxu; Wang, Siqi

    2018-01-01

    In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). However, practical IDSs generally update their decision module by feeding new data then retraining learning models in a periodical way. Hence, some attacks that comprise the data for training or testing classifiers significantly challenge the detecting capability of machine learning-based IDSs. Poisoning attack, which is one of the most recognized security threats towards machine learning...

  18. Learning Opportunities for Group Learning

    Science.gov (United States)

    Gil, Alfonso J.; Mataveli, Mara

    2017-01-01

    Purpose: This paper aims to analyse the impact of organizational learning culture and learning facilitators in group learning. Design/methodology/approach: This study was conducted using a survey method applied to a statistically representative sample of employees from Rioja wine companies in Spain. A model was tested using a structural equation…

  19. Survey compare team based learning and lecture teaching method, on learning-teaching process nursing student\\'s, in Surgical and Internal Diseases course

    Directory of Open Access Journals (Sweden)

    AA Vaezi

    2015-12-01

    Full Text Available Introduction: The effect of teaching methods on learning process of students will help teachers to improve the quality of teaching by selecting an appropriate method. This study aimed to compare the team- based learning and lecture teaching method on learning-teaching process of nursing students in surgical and internal diseases courses. Method: This quasi-experimental study was carried on the nursing students in the School of Nursing and Midwifery in Yazd and Meybod cities. Studied sample was all of the students in the sixth term in the Faculty of Nursing in Yazd (48 persons and the Faculty of Nursing in Meybod (28 persons. The rate of students' learning through lecture was measured using MCQ tests and teaching based on team-based learning (TBL method was run using MCQ tests (IRAT, GRAT, Appeals and Task group. Therefore, in order to examine the students' satisfaction about the TBL method, a 5-point Likert scale (translated questionnaire (1=completely disagree, 2= disagree, 3=not effective, 4=agree, and 5=completely agree consisted of 22 items was utilized. The reliability and validity of this translated questionnaire was measured. The collected data were analyzed through SPSS 17.0 using descriptive and analytical statistic. Result: The results showed that the mean scores in team-based learning were meaningful in individual assessment (17±84 and assessment group (17.2±1.17. The mean of overall scores in TBL method (17.84±0.98% was higher compared with the lecture teaching method (16±2.31. Most of the students believed that TBL method has improved their interpersonal and group interaction skills (100%. Among them, 97.7% of students mentioned that this method (TBL helped them to understand the course content better. The lowest levels of the satisfaction have related to the continuous learning during lifelong (51.2%. Conclusion: The results of the present study showed that the TBL method led to improving the communication skills, understanding

  20. A deep learning method for classifying mammographic breast density categories.

    Science.gov (United States)

    Mohamed, Aly A; Berg, Wendie A; Peng, Hong; Luo, Yahong; Jankowitz, Rachel C; Wu, Shandong

    2018-01-01

    Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density categories. It is particularly difficult for radiologists to consistently distinguish the two most common and most variably assigned BI-RADS categories, i.e., "scattered density" and "heterogeneously dense". The aim of this work was to investigate a deep learning-based breast density classifier to consistently distinguish these two categories, aiming at providing a potential computerized tool to assist radiologists in assigning a BI-RADS category in current clinical workflow. In this study, we constructed a convolutional neural network (CNN)-based model coupled with a large (i.e., 22,000 images) digital mammogram imaging dataset to evaluate the classification performance between the two aforementioned breast density categories. All images were collected from a cohort of 1,427 women who underwent standard digital mammography screening from 2005 to 2016 at our institution. The truths of the density categories were based on standard clinical assessment made by board-certified breast imaging radiologists. Effects of direct training from scratch solely using digital mammogram images and transfer learning of a pretrained model on a large nonmedical imaging dataset were evaluated for the specific task of breast density classification. In order to measure the classification performance, the CNN classifier was also tested on a refined version of the mammogram image dataset by removing some potentially inaccurately labeled images. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to measure the accuracy of the classifier. The AUC was 0.9421 when the CNN-model was trained from scratch on our own mammogram images, and the accuracy increased gradually along with an increased size of training samples

  1. Housing Value Forecasting Based on Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Jingyi Mu

    2014-01-01

    Full Text Available In the era of big data, many urgent issues to tackle in all walks of life all can be solved via big data technique. Compared with the Internet, economy, industry, and aerospace fields, the application of big data in the area of architecture is relatively few. In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing the real estate on corresponding regions or not. In this paper, support vector machine (SVM, least squares support vector machine (LSSVM, and partial least squares (PLS methods are used to forecast the home values. And these algorithms are compared according to the predicted results. Experiment shows that although the data set exists serious nonlinearity, the experiment result also show SVM and LSSVM methods are superior to PLS on dealing with the problem of nonlinearity. The global optimal solution can be found and best forecasting effect can be achieved by SVM because of solving a quadratic programming problem. In this paper, the different computation efficiencies of the algorithms are compared according to the computing times of relevant algorithms.

  2. Nurse practitioner preferences for distance education methods related to learning style, course content, and achievement.

    Science.gov (United States)

    Andrusyszyn, M A; Cragg, C E; Humbert, J

    2001-04-01

    The relationships among multiple distance delivery methods, preferred learning style, content, and achievement was sought for primary care nurse practitioner students. A researcher-designed questionnaire was completed by 86 (71%) participants, while 6 engaged in follow-up interviews. The results of the study included: participants preferred learning by "considering the big picture"; "setting own learning plans"; and "focusing on concrete examples." Several positive associations were found: learning on own with learning by reading, and setting own learning plans; small group with learning through discussion; large group with learning new things through hearing and with having learning plans set by others. The most preferred method was print-based material and the least preferred method was audio tape. The most suited method for content included video teleconferencing for counseling, political action, and transcultural issues; and video tape for physical assessment. Convenience, self-direction, and timing of learning were more important than delivery method or learning style. Preferred order of learning was reading, discussing, observing, doing, and reflecting. Recommended considerations when designing distance courses include a mix of delivery methods, specific content, outcomes, learner characteristics, and state of technology.

  3. Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

    Science.gov (United States)

    Niegowski, Maciej; Zivanovic, Miroslav

    2016-03-01

    We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the suitability of certain wavelet decomposition bases which provide sparse electrocardiogram time-frequency representations, with the capacity of non-negative matrix factorization (NMF) for extracting patterns from images. In order to overcome convergence problems which often arise in NMF-related applications, we design a novel robust initialization strategy which ensures proper signal decomposition in a wide range of ECG contamination levels. Moreover, the method can be readily used because no a priori knowledge or parameter adjustment is needed. The proposed method was evaluated on real surface EMG signals against two state-of-the-art unsupervised learning algorithms and a singular spectrum analysis based method. The results, expressed in terms of high-to-low energy ratio, normalized median frequency, spectral power difference and normalized average rectified value, suggest that the proposed method enables better ECG-EMG separation quality than the reference methods. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

  4. Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

    Science.gov (United States)

    Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

    2017-03-01

    Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Lexical and semantic representations of L2 cognate and noncognate words acquisition in children : evidence from two learning methods

    OpenAIRE

    Comesaña, Montserrat; Soares, Ana Paula; Sánchez-Casas, Rosa; Lima, Cátia

    2012-01-01

    How bilinguals represent words in two languages and which mechanisms are responsible for second language acquisition are important questions in the bilingual and vocabulary acquisition literature. This study aims to analyze the effect of two learning methods (picture-based vs. word-based method) and two types of words (cognates and noncognates) in early stages of children’s L2 acquisition. Forty-eight native speakers of European Portuguese, all sixth graders (mean age= 10.87 years; SD= 0....

  6. Understanding the Effects of Time on Collaborative Learning Processes in Problem Based Learning: A Mixed Methods Study

    Science.gov (United States)

    Hommes, J.; Van den Bossche, P.; de Grave, W.; Bos, G.; Schuwirth, L.; Scherpbier, A.

    2014-01-01

    Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning…

  7. Cross-organism learning method to discover new gene functionalities.

    Science.gov (United States)

    Domeniconi, Giacomo; Masseroli, Marco; Moro, Gianluca; Pinoli, Pietro

    2016-04-01

    Knowledge of gene and protein functions is paramount for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. Analyses for biomedical knowledge discovery greatly benefit from the availability of gene and protein functional feature descriptions expressed through controlled terminologies and ontologies, i.e., of gene and protein biomedical controlled annotations. In the last years, several databases of such annotations have become available; yet, these valuable annotations are incomplete, include errors and only some of them represent highly reliable human curated information. Computational techniques able to reliably predict new gene or protein annotations with an associated likelihood value are thus paramount. Here, we propose a novel cross-organisms learning approach to reliably predict new functionalities for the genes of an organism based on the known controlled annotations of the genes of another, evolutionarily related and better studied, organism. We leverage a new representation of the annotation discovery problem and a random perturbation of the available controlled annotations to allow the application of supervised algorithms to predict with good accuracy unknown gene annotations. Taking advantage of the numerous gene annotations available for a well-studied organism, our cross-organisms learning method creates and trains better prediction models, which can then be applied to predict new gene annotations of a target organism. We tested and compared our method with the equivalent single organism approach on different gene annotation datasets of five evolutionarily related organisms (Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum). Results show both the usefulness of the perturbation method of available annotations for better prediction model training and a great improvement of the cross-organism models with respect to the single-organism ones

  8. Machine Learning Methods for Prediction of CDK-Inhibitors

    Science.gov (United States)

    Ramana, Jayashree; Gupta, Dinesh

    2010-01-01

    Progression through the cell cycle involves the coordinated activities of a suite of cyclin/cyclin-dependent kinase (CDK) complexes. The activities of the complexes are regulated by CDK inhibitors (CDKIs). Apart from its role as cell cycle regulators, CDKIs are involved in apoptosis, transcriptional regulation, cell fate determination, cell migration and cytoskeletal dynamics. As the complexes perform crucial and diverse functions, these are important drug targets for tumour and stem cell therapeutic interventions. However, CDKIs are represented by proteins with considerable sequence heterogeneity and may fail to be identified by simple similarity search methods. In this work we have evaluated and developed machine learning methods for identification of CDKIs. We used different compositional features and evolutionary information in the form of PSSMs, from CDKIs and non-CDKIs for generating SVM and ANN classifiers. In the first stage, both the ANN and SVM models were evaluated using Leave-One-Out Cross-Validation and in the second stage these were tested on independent data sets. The PSSM-based SVM model emerged as the best classifier in both the stages and is publicly available through a user-friendly web interface at http://bioinfo.icgeb.res.in/cdkipred. PMID:20967128

  9. Machine-learning methods in the classification of water bodies

    Directory of Open Access Journals (Sweden)

    Sołtysiak Marek

    2016-06-01

    Full Text Available Amphibian species have been considered as useful ecological indicators. They are used as indicators of environmental contamination, ecosystem health and habitat quality., Amphibian species are sensitive to changes in the aquatic environment and therefore, may form the basis for the classification of water bodies. Water bodies in which there are a large number of amphibian species are especially valuable even if they are located in urban areas. The automation of the classification process allows for a faster evaluation of the presence of amphibian species in the water bodies. Three machine-learning methods (artificial neural networks, decision trees and the k-nearest neighbours algorithm have been used to classify water bodies in Chorzów – one of 19 cities in the Upper Silesia Agglomeration. In this case, classification is a supervised data mining method consisting of several stages such as building the model, the testing phase and the prediction. Seven natural and anthropogenic features of water bodies (e.g. the type of water body, aquatic plants, the purpose of the water body (destination, position of the water body in relation to any possible buildings, condition of the water body, the degree of littering, the shore type and fishing activities have been taken into account in the classification. The data set used in this study involved information about 71 different water bodies and 9 amphibian species living in them. The results showed that the best average classification accuracy was obtained with the multilayer perceptron neural network.

  10. Recent Advances in Conotoxin Classification by Using Machine Learning Methods.

    Science.gov (United States)

    Dao, Fu-Ying; Yang, Hui; Su, Zhen-Dong; Yang, Wuritu; Wu, Yun; Hui, Ding; Chen, Wei; Tang, Hua; Lin, Hao

    2017-06-25

    Conotoxins are disulfide-rich small peptides, which are invaluable peptides that target ion channel and neuronal receptors. Conotoxins have been demonstrated as potent pharmaceuticals in the treatment of a series of diseases, such as Alzheimer's disease, Parkinson's disease, and epilepsy. In addition, conotoxins are also ideal molecular templates for the development of new drug lead compounds and play important roles in neurobiological research as well. Thus, the accurate identification of conotoxin types will provide key clues for the biological research and clinical medicine. Generally, conotoxin types are confirmed when their sequence, structure, and function are experimentally validated. However, it is time-consuming and costly to acquire the structure and function information by using biochemical experiments. Therefore, it is important to develop computational tools for efficiently and effectively recognizing conotoxin types based on sequence information. In this work, we reviewed the current progress in computational identification of conotoxins in the following aspects: (i) construction of benchmark dataset; (ii) strategies for extracting sequence features; (iii) feature selection techniques; (iv) machine learning methods for classifying conotoxins; (v) the results obtained by these methods and the published tools; and (vi) future perspectives on conotoxin classification. The paper provides the basis for in-depth study of conotoxins and drug therapy research.

  11. Learning a specific content in technology education : Learning Study as collaborative method in Swedish preschool class using hands-on material 

    OpenAIRE

    Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin

    2014-01-01

    This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study concerns strong constructions and framed structures. This article describes how this learning study was conducted and discusses reflections made du...

  12. The diverse aims of science.

    Science.gov (United States)

    Potochnik, Angela

    2015-10-01

    There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. I suggest that continuing, widespread idealization calls into question the idea that science aims for truth. If instead science aims to produce understanding, this would enable idealizations to directly contribute to science's epistemic success. I also use the fact of widespread idealization to motivate the idea that science's wide variety aims, epistemic and non-epistemic, are best served by different kinds of scientific products. Finally, I show how these diverse aims—most rather distant from truth—result in the expanded influence of social values on science. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Effect of Software Designed by Computer Conceptual Map Method in Mobile Environment on Learning Level of Nursing Students

    Directory of Open Access Journals (Sweden)

    Salmani N

    2015-12-01

    Full Text Available Aims: In order to preserve its own progress, nursing training has to be utilized new training methods, in such a case that the teaching methods used by the nursing instructors enhance significant learning via preventing superficial learning in the students. Conceptual Map Method is one of the new training strategies playing important roles in the field. The aim of this study was to investigate the effectiveness of the designed software based on the mobile phone computer conceptual map on the learning level of the nursing students. Materials & Methods: In the semi-experimental study with pretest-posttest plan, 60 students, who were studying at the 5th semester, were studied at the 1st semester of 2015-16. Experimental group (n=30 from Meibod Nursing Faculty and control group (n=30 from Yazd Shahid Sadoughi Nursing Faculty were trained during the first 4 weeks of the semester, using computer conceptual map method and computer conceptual map method in mobile phone environment. Data was collected, using a researcher-made academic progress test including “knowledge” and “significant learning”. Data was analyzed in SPSS 21 software using Independent T, Paired T, and Fisher tests. Findings: There were significant increases in the mean scores of knowledge and significant learning in both groups before and after the intervention (p0.05. Nevertheless, the process of change of the scores of significant learning level between the groups was statistically significant (p<0.05.   Conclusion: Presenting the course content as conceptual map in mobile phone environment positively affects the significant learning of the nursing students.

  14. Women with learning disabilities and access to cervical screening: retrospective cohort study using case control methods

    Science.gov (United States)

    Reynolds, Fiona; Stanistreet, Debbi; Elton, Peter

    2008-01-01

    Background Several studies in the UK have suggested that women with learning disabilities may be less likely to receive cervical screening tests and a previous local study in had found that GPs considered screening unnecessary for women with learning disabilities. This study set out to ascertain whether women with learning disabilities are more likely to be ceased from a cervical screening programme than women without; and to examine the reasons given for ceasing women with learning disabilities. It was carried out in Bury, Heywood-and-Middleton and Rochdale. Methods Carried out using retrospective cohort study methods, women with learning disabilities were identified by Read code; and their cervical screening records were compared with the Call-and-Recall records of women without learning disabilities in order to examine their screening histories. Analysis was carried out using case-control methods – 1:2 (women with learning disabilities: women without learning disabilities), calculating odds ratios. Results 267 women's records were compared with the records of 534 women without learning disabilities. Women with learning disabilities had an odds ratio (OR) of 0.48 (Confidence Interval (CI) 0.38 – 0.58; X2: 72.227; p.value learning disabilities. Conclusion The reasons given for ceasing and/or not screening suggest that merely being coded as having a learning disability is not the sole reason for these actions. There are training needs among smear takers regarding appropriate reasons not to screen and providing screening for women with learning disabilities. PMID:18218106

  15. Assessment of two e-learning methods teaching undergraduate students cephalometry in orthodontics.

    Science.gov (United States)

    Ludwig, B; Bister, D; Schott, T C; Lisson, J A; Hourfar, J

    2016-02-01

    Cephalometry is important for orthodontic diagnosis and treatment planning and is part of the core curriculum for training dentists. Training involves identifying anatomical landmarks. The aim of this investigation was to assess whether e-learning improves learning efficiency; a programme specifically designed for this purpose was compared to commercially available software. Thirty undergraduate students underwent traditional training of cephalometry consisting of lectures and tutorials. Tracing skills were tested immediately afterwards (T0). The students were then randomly allocated to three groups: 10 students served as control (CF); they were asked to improve their skills using the material provided so far. Ten students were given a program specifically designed for this study that was based on a power point presentation (PPT). The last group was given a commercially available program that included teaching elements (SW). The groups were tested at the end the six week training (T1). The test consisted of tracing 30 points on two radiographs and a point score improvement was calculated. The students were interviewed after the second test. Both e-learning groups improved more than the traditional group. Improvement scores were four for CF; 8.6 for PPT and 2.8 for SW. For PPT all participants improved and the student feedback was the best compared to the other groups. For the other groups some candidates worsened. Blended learning produced better learning outcomes compared to using a traditional teaching method alone. The easy to use Power Point based custom software produced better results than the commercially available software. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  16. Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

    Directory of Open Access Journals (Sweden)

    Rondon Silmara

    2013-02-01

    Full Text Available Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method, short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.

  17. L2 Vocabulary Acquisition in Children: Effects of Learning Method and Cognate Status

    Science.gov (United States)

    Tonzar, Claudio; Lotto, Lorella; Job, Remo

    2009-01-01

    In this study we investigated the effects of two learning methods (picture- or word-mediated learning) and of word status (cognates vs. noncognates) on the vocabulary acquisition of two foreign languages: English and German. We examined children from fourth and eighth grades in a school setting. After a learning phase during which L2 words were…

  18. Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

    Science.gov (United States)

    Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

    2014-01-01

    This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

  19. Application of a Novel Collaboration Engineering Method for Learning Design: A Case Study

    Science.gov (United States)

    Cheng, Xusen; Li, Yuanyuan; Sun, Jianshan; Huang, Jianqing

    2016-01-01

    Collaborative case studies and computer-supported collaborative learning (CSCL) play an important role in the modern education environment. A number of researchers have given significant attention to learning design in order to improve the satisfaction of collaborative learning. Although collaboration engineering (CE) is a mature method widely…

  20. Strategic Management: An Evaluation of the Use of Three Learning Methods.

    Science.gov (United States)

    Jennings, David

    2002-01-01

    A study of 46 management students compared three methods for learning strategic management: cases, simulation, and action learning through consulting projects. Simulation was superior to action learning on all outcomes and equal or superior to cases on two. Simulation gave students a central role in management and greater control of the learning…

  1. Using Problem Based Learning Methods from Engineering Education in Company Based Development

    DEFF Research Database (Denmark)

    Kofoed, Lise B.; Jørgensen, Frances

    2007-01-01

    This paper discusses how Problem-Based Learning (PBL) methods were used to support a Danish company in its efforts to become more of a 'learning organisation', characterized by sharing of knowledge and experiences. One of the central barriers to organisational learning in this company involved...

  2. Investigating Learning with an Interactive Tutorial: A Mixed-Methods Strategy

    Science.gov (United States)

    de Villiers, M. R.; Becker, Daphne

    2017-01-01

    From the perspective of parallel mixed-methods research, this paper describes interactivity research that employed usability-testing technology to analyse cognitive learning processes; personal learning styles and times; and errors-and-recovery of learners using an interactive e-learning tutorial called "Relations." "Relations"…

  3. Multi-Role Project (MRP): A New Project-Based Learning Method for STEM

    Science.gov (United States)

    Warin, Bruno; Talbi, Omar; Kolski, Christophe; Hoogstoel, Frédéric

    2016-01-01

    This paper presents the "Multi-Role Project" method (MRP), a broadly applicable project-based learning method, and describes its implementation and evaluation in the context of a Science, Technology, Engineering, and Mathematics (STEM) course. The MRP method is designed around a meta-principle that considers the project learning activity…

  4. Aim For a Healthy Weight

    Science.gov (United States)

    ... out of your control, you can make positive lifestyle changes to lose weight and to maintain a healthy weight. These include a healthy eating plan and being more physically active. Take the Challenge When it comes to aiming for a healthy ...

  5. An online supervised learning method based on gradient descent for spiking neurons.

    Science.gov (United States)

    Xu, Yan; Yang, Jing; Zhong, Shuiming

    2017-09-01

    The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. RULE-BASE METHOD FOR ANALYSIS OF QUALITY E-LEARNING IN HIGHER EDUCATION

    Directory of Open Access Journals (Sweden)

    darsih darsih darsih

    2016-04-01

    Full Text Available ABSTRACT Assessing the quality of e-learning courses to measure the success of e-learning systems in online learning is essential. The system can be used to improve education. The study analyzes the quality of e-learning course on the web site www.kulon.undip.ac.id used a questionnaire with questions based on the variables of ISO 9126. Penilaiann Likert scale was used with a web app. Rule-base reasoning method is used to subject the quality of e-learningyang assessed. A case study conducted in four e-learning courses with 133 sample / respondents as users of the e-learning course. From the obtained results of research conducted both for the value of e-learning from each subject tested. In addition, each e-learning courses have different advantages depending on certain variables. Keywords : E-Learning, Rule-Base, Questionnaire, Likert, Measuring.

  7. Approximation Methods for Inference and Learning in Belief Networks: Progress and Future Directions

    National Research Council Canada - National Science Library

    Pazzan, Michael

    1997-01-01

    .... In this research project, we have investigated methods and implemented algorithms for efficiently making certain classes of inference in belief networks, and for automatically learning certain...

  8. Multiresolution, Geometric, and Learning Methods in Statistical Image Processing, Object Recognition, and Sensor Fusion

    National Research Council Canada - National Science Library

    Willsky, Alan

    2004-01-01

    .... Our research blends methods from several fields-statistics and probability, signal and image processing, mathematical physics, scientific computing, statistical learning theory, and differential...

  9. Computer game-based and traditional learning method: a comparison regarding students' knowledge retention.

    Science.gov (United States)

    Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina

    2013-02-25

    Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students' prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students' performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students' short and long-term knowledge retention.

  10. Aims, assessments and workplace needs

    Science.gov (United States)

    Black, Paul

    1997-03-01

    This paper attempts to consider the aims that undergraduate physics degree courses actually reflect and serve in the light of the employment patterns of graduates and of the expressed needs of employers. Calling on evidence mainly from the UK, it reviews analyses of what degree examinations actually test, and goes on to quote criticisms of their courses and radical proposals to change them adopted by the senior physics professors in the UK. The discussion is then broadened by discussion of evidence, about the employment of graduates and about the priorities that some industrialists now give in the qualities that they look for when recruiting new graduates. The evidence leads to a view that radical changes are needed, both in courses and examinations, and that there is a need for university departments to work more closely with employers in re-formulating the aims and priorities in their teaching.

  11. A lifelong learning hyper-heuristic method for bin packing.

    Science.gov (United States)

    Sim, Kevin; Hart, Emma; Paechter, Ben

    2015-01-01

    We describe a novel hyper-heuristic system that continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; and representative problems and heuristics are incorporated into a self-sustaining network of interacting entities inspired by methods in artificial immune systems. The network is plastic in both its structure and content, leading to the following properties: it exploits existing knowledge captured in the network to rapidly produce solutions; it can adapt to new problems with widely differing characteristics; and it is capable of generalising over the problem space. The system is tested on a large corpus of 3,968 new instances of 1D bin-packing problems as well as on 1,370 existing problems from the literature; it shows excellent performance in terms of the quality of solutions obtained across the datasets and in adapting to dynamically changing sets of problem instances compared to previous approaches. As the network self-adapts to sustain a minimal repertoire of both problems and heuristics that form a representative map of the problem space, the system is further shown to be computationally efficient and therefore scalable.

  12. Teaching organization theory for healthcare management: three applied learning methods.

    Science.gov (United States)

    Olden, Peter C

    2006-01-01

    Organization theory (OT) provides a way of seeing, describing, analyzing, understanding, and improving organizations based on patterns of organizational design and behavior (Daft 2004). It gives managers models, principles, and methods with which to diagnose and fix organization structure, design, and process problems. Health care organizations (HCOs) face serious problems such as fatal medical errors, harmful treatment delays, misuse of scarce nurses, costly inefficiency, and service failures. Some of health care managers' most critical work involves designing and structuring their organizations so their missions, visions, and goals can be achieved-and in some cases so their organizations can survive. Thus, it is imperative that graduate healthcare management programs develop effective approaches for teaching OT to students who will manage HCOs. Guided by principles of education, three applied teaching/learning activities/assignments were created to teach OT in a graduate healthcare management program. These educationalmethods develop students' competency with OT applied to HCOs. The teaching techniques in this article may be useful to faculty teaching graduate courses in organization theory and related subjects such as leadership, quality, and operation management.

  13. Modeling Music Emotion Judgments Using Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Naresh N. Vempala

    2018-01-01

    Full Text Available Emotion judgments and five channels of physiological data were obtained from 60 participants listening to 60 music excerpts. Various machine learning (ML methods were used to model the emotion judgments inclusive of neural networks, linear regression, and random forests. Input for models of perceived emotion consisted of audio features extracted from the music recordings. Input for models of felt emotion consisted of physiological features extracted from the physiological recordings. Models were trained and interpreted with consideration of the classic debate in music emotion between cognitivists and emotivists. Our models supported a hybrid position wherein emotion judgments were influenced by a combination of perceived and felt emotions. In comparing the different ML approaches that were used for modeling, we conclude that neural networks were optimal, yielding models that were flexible as well as interpretable. Inspection of a committee machine, encompassing an ensemble of networks, revealed that arousal judgments were predominantly influenced by felt emotion, whereas valence judgments were predominantly influenced by perceived emotion.

  14. Matching Learning Style to Instructional Method: Effects on Comprehension

    Science.gov (United States)

    Rogowsky, Beth A.; Calhoun, Barbara M.; Tallal, Paula

    2015-01-01

    While it is hypothesized that providing instruction based on individuals' preferred learning styles improves learning (i.e., reading for visual learners and listening for auditory learners, also referred to as the "meshing hypothesis"), after a critical review of the literature Pashler, McDaniel, Rohrer, and Bjork (2008) concluded that…

  15. Newton Methods for Large Scale Problems in Machine Learning

    Science.gov (United States)

    Hansen, Samantha Leigh

    2014-01-01

    The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…

  16. Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method

    Directory of Open Access Journals (Sweden)

    Muneki Yasuda

    2018-04-01

    Full Text Available The machine learning techniques for Markov random fields are fundamental in various fields involving pattern recognition, image processing, sparse modeling, and earth science, and a Boltzmann machine is one of the most important models in Markov random fields. However, the inference and learning problems in the Boltzmann machine are NP-hard. The investigation of an effective learning algorithm for the Boltzmann machine is one of the most important challenges in the field of statistical machine learning. In this paper, we study Boltzmann machine learning based on the (first-order spatial Monte Carlo integration method, referred to as the 1-SMCI learning method, which was proposed in the author’s previous paper. In the first part of this paper, we compare the method with the maximum pseudo-likelihood estimation (MPLE method using a theoretical and a numerical approaches, and show the 1-SMCI learning method is more effective than the MPLE. In the latter part, we compare the 1-SMCI learning method with other effective methods, ratio matching and minimum probability flow, using a numerical experiment, and show the 1-SMCI learning method outperforms them.

  17. WebMail versus WebApp: Comparing Problem-Based Learning Methods in a Business Research Methods Course

    Science.gov (United States)

    Williams van Rooij, Shahron

    2007-01-01

    This study examined the impact of two Problem-Based Learning (PBL) approaches on knowledge transfer, problem-solving self-efficacy, and perceived learning gains among four intact classes of adult learners engaged in a group project in an online undergraduate business research methods course. With two of the classes using a text-only PBL workbook…

  18. Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis.

    Science.gov (United States)

    Isupova, Olga; Kuzin, Danil; Mihaylova, Lyudmila

    2017-09-27

    Semisupervised and unsupervised systems provide operators with invaluable support and can tremendously reduce the operators' load. In the light of the necessity to process large volumes of video data and provide autonomous decisions, this paper proposes new learning algorithms for activity analysis in video. The activities and behaviors are described by a dynamic topic model. Two novel learning algorithms based on the expectation maximization approach and variational Bayes inference are proposed. Theoretical derivations of the posterior estimates of model parameters are given. The designed learning algorithms are compared with the Gibbs sampling inference scheme introduced earlier in the literature. A detailed comparison of the learning algorithms is presented on real video data. We also propose an anomaly localization procedure, elegantly embedded in the topic modeling framework. It is shown that the developed learning algorithms can achieve 95% success rate. The proposed framework can be applied to a number of areas, including transportation systems, security, and surveillance.

  19. THE INFLUENCE OF THE ASSESSMENT MODEL AND METHOD TOWARD THE SCIENCE LEARNING ACHIEVEMENT BY CONTROLLING THE STUDENTS? PREVIOUS KNOWLEDGE OF MATHEMATICS.

    OpenAIRE

    Adam rumbalifar; I. g. n. Agung; Burhanuddin tola.

    2018-01-01

    This research aims to study the influence of the assessment model and method toward the science learning achievement by controlling the students? previous knowledge of mathematics. This study was conducted at SMP East Seram district with the population of 295 students. This study applied a quasi-experimental method with 2 X 2 factorial design using the ANCOVA model. The findings after controlling the students\\' previous knowledge of mathematics show that the science learning achievement of th...

  20. Towards a Quality Assessment Method for Learning Preference Profiles in Negotiation

    Science.gov (United States)

    Hindriks, Koen V.; Tykhonov, Dmytro

    In automated negotiation, information gained about an opponent's preference profile by means of learning techniques may significantly improve an agent's negotiation performance. It therefore is useful to gain a better understanding of how various negotiation factors influence the quality of learning. The quality of learning techniques in negotiation are typically assessed indirectly by means of comparing the utility levels of agreed outcomes and other more global negotiation parameters. An evaluation of learning based on such general criteria, however, does not provide any insight into the influence of various aspects of negotiation on the quality of the learned model itself. The quality may depend on such aspects as the domain of negotiation, the structure of the preference profiles, the negotiation strategies used by the parties, and others. To gain a better understanding of the performance of proposed learning techniques in the context of negotiation and to be able to assess the potential to improve the performance of such techniques a more systematic assessment method is needed. In this paper we propose such a systematic method to analyse the quality of the information gained about opponent preferences by learning in single-instance negotiations. The method includes measures to assess the quality of a learned preference profile and proposes an experimental setup to analyse the influence of various negotiation aspects on the quality of learning. We apply the method to a Bayesian learning approach for learning an opponent's preference profile and discuss our findings.

  1. Lesson learned - CGID based on the Method 1 and Method 2 for digital equipment

    International Nuclear Information System (INIS)

    Hwang, Wonil; Sohn, Kwang Young; Cho, Chang Hwan; Kim, Sung Jong

    2015-01-01

    The acceptance methods associated with commercial-grade dedication are the following: 1) Special tests and inspection (Method 1) 2) Commercial-grade surveys (Method 2) 3) Source verification (Method 3) 4) An acceptable item and supplier performance record (Method 4) Special tests and inspections, often referred to as Method 1, are performed by the dedicating entity after the item is received to verify selected critical characteristics. Conducting a commercial-grade survey of a supplier is often referred to as Method 2. Supplier audits to verify compliance with a nuclear QA program do not meet the intent of a commercial-grade survey. Source verification, often referred to as Method 3, entails verification of critical characteristics during manufacture and testing of the item being procured. The performance history (good or bad) of the item and supplier is a consideration when determining the use of the other acceptance methods and the rigor with which they are used on a case-by-case basis. Some digital equipment system has the delivery reference and its operating history for Nuclear Power Plant as far as surveyed. However it was found that there is difficulty in collecting this of supporting data sheet, so that supplier usually decide to conduct the CGID based on the Method-1 and Method-2 based on the initial qualification likely. It is conceived that the Method-4 might be a better approach for CGID(Commercial Grade Item Dedication) even if there are some difficulties in data package for justifying CGID from the vendor and operating organization. This paper present the lesson learned from the consulting for Method-1 and 2 for digital equipment dedication. Considering all the information above, there are a couple of issues to remind in order to perform the CGID for Method-2. In doing commercial grade survey based on Method 2, quality personnel as well as technical engineer shall be involved for integral dedication. Other than this, the review of critical

  2. Student’s Perceptions on Simulation as Part of Experiential Learning in Approaches, Methods, and Techniques (AMT Course

    Directory of Open Access Journals (Sweden)

    Marselina Karina Purnomo

    2017-03-01

    Full Text Available Simulation is a part of Experiential Learning which represents certain real-life events. In this study, simulation is used as a learning activity in Approaches, Methods, and Techniques (AMT course which is one of the courses in English Language Education Study Program (ELESP of Sanata Dharma University. Since simulation represents the real-life events, it encourages students to apply the approaches, methods, and techniques being studied based on the real-life classroom. Several experts state that students are able to involve their personal experiences through simulation which additionally is believed to create a meaningful learning in the class. This study aimed to discover ELESP students’ perceptions toward simulation as a part of Experiential Learning in AMT course. From the findings, it could be inferred that students agreed that simulation in class was important for students’ learning for it formed a meaningful learning in class.  DOI: https://doi.org/10.24071/llt.2017.200104

  3. Teaching Dental Students to Understand the Temporomandibular Joint Using MRI: Comparison of Conventional and Digital Learning Methods.

    Science.gov (United States)

    Arús, Nádia A; da Silva, Átila M; Duarte, Rogério; da Silveira, Priscila F; Vizzotto, Mariana B; da Silveira, Heraldo L D; da Silveira, Heloisa E D

    2017-06-01

    The aims of this study were to evaluate and compare the performance of dental students in interpreting the temporomandibular joint (TMJ) with magnetic resonance imaging (MRI) scans using two learning methods (conventional and digital interactive learning) and to examine the usability of the digital learning object (DLO). The DLO consisted of tutorials about MRI and anatomic and functional aspects of the TMJ. In 2014, dental students in their final year of study who were enrolled in the elective "MRI Interpretation of the TMJ" course comprised the study sample. After exclusions for nonattendance and other reasons, 29 of the initial 37 students participated in the study, for a participation rate of 78%. The participants were divided into two groups: a digital interactive learning group (n=14) and a conventional learning group (n=15). Both methods were assessed by an objective test applied before and after training and classes. Aspects such as support and training requirements, complexity, and consistency of the DLO were also evaluated using the System Usability Scale (SUS). A significant between-group difference in the posttest results was found, with the conventional learning group scoring better than the DLO group, indicated by mean scores of 9.20 and 8.11, respectively, out of 10. However, when the pretest and posttest results were compared, both groups showed significantly improved performance. The SUS score was 89, which represented a high acceptance of the DLO by the users. The students who used the conventional method of learning showed superior performance in interpreting the TMJ using MRI compared to the group that used digital interactive learning.

  4. The simulation method in learning interpersonal communication competence--experiences of masters' degree students of health sciences.

    Science.gov (United States)

    Saaranen, Terhi; Vaajoki, Anne; Kellomäki, Marjaana; Hyvärinen, Marja-Leena

    2015-02-01

    This article describes the experiences of master students of nursing science in learning interpersonal communication competence through the simulation method. The exercises reflected challenging interactive situations in the field of health care. Few studies have been published on using the simulation method in the communication education of teachers, managers, and experts in this field. The aim of this study is to produce information which can be utilised in developing the simulation method to promote the interpersonal communication competence of master-level students of health sciences. This study used the qualitative, descriptive research method. At the Department of Nursing Science, the University of Eastern Finland, students major in nursing science specialise in nursing leadership and management, preventive nursing science, or nurse teacher education. Students from all three specialties taking the Challenging Situations in Speech Communication course participated (n=47). Essays on meaningful learning experiences collected using the critical incident technique, underwent content analysis. Planning of teaching, carrying out different stages of the simulation exercise, participant roles, and students' personal factors were central to learning interpersonal communication competence. Simulation is a valuable method in developing the interpersonal communication competence of students of health sciences at the masters' level. The methods used in the simulation teaching of emergency care are not necessarily applicable as such to communication education. The role of teacher is essential to supervising students' learning in simulation exercises. In the future, it is important to construct questions that help students to reflect specifically on communication. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Working on educational research methods with masters students in an international online learning community

    NARCIS (Netherlands)

    Hudson, B; Owen, D; van Veen, K

    In this paper we discuss the background to this study in the development of the international MSc e-Learning Multimedia and Consultancy. The aims of the study focus on the conditions for achieving communication, interaction and collaboration in open and flexible e-learning environments. We present

  6. A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

    Science.gov (United States)

    Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

    2013-01-01

    Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  7. Utility of learning plans in general practice vocational training: a mixed-methods national study of registrar, supervisor, and educator perspectives.

    Science.gov (United States)

    Garth, Belinda; Kirby, Catherine; Silberberg, Peter; Brown, James

    2016-08-19

    Learning plans are a compulsory component of the training and assessment requirements of general practice (GP) registrars in Australia. There is a small but growing number of studies reporting that learning plans are not well accepted or utilised in general practice training. There is a lack of research examining this apparent contradiction. The aim of this study was to examine use and perceived utility of formal learning plans in GP vocational training. This mixed-method Australian national research project utilised online learning plan usage data from 208 GP registrars and semi-structured focus groups and telephone interviews with 35 GP registrars, 12 recently fellowed GPs, 16 supervisors and 17 medical educators across three Regional Training Providers (RTPs). Qualitative data were analysed thematically using template analysis. Learning plans were used mostly as a log of activities rather than as a planning tool. Most learning needs were entered and ticked off as complete on the same day. Learning plans were perceived as having little value for registrars in their journey to becoming a competent GP, and as a bureaucratic hurdle serving as a distraction rather than an aid to learning. The process of learning planning was valued more so than the documentation of learning planning. This study provides creditable evidence that mandated learning plans are broadly considered by users to be a bureaucratic impediment with little value as a learning tool. It is more important to support registrars in planning their learning than to enforce documentation of this process in a learning plan. If learning planning is to be an assessed competence, methods of assessment other than the submission of a formal learning plan should be explored.

  8. Robust Control Methods for On-Line Statistical Learning

    Directory of Open Access Journals (Sweden)

    Capobianco Enrico

    2001-01-01

    Full Text Available The issue of controlling that data processing in an experiment results not affected by the presence of outliers is relevant for statistical control and learning studies. Learning schemes should thus be tested for their capacity of handling outliers in the observed training set so to achieve reliable estimates with respect to the crucial bias and variance aspects. We describe possible ways of endowing neural networks with statistically robust properties by defining feasible error criteria. It is convenient to cast neural nets in state space representations and apply both Kalman filter and stochastic approximation procedures in order to suggest statistically robustified solutions for on-line learning.

  9. Comparison of two different synthesis methods of perovskites, SrCo0.5FeO3 type, aiming at evaluating their use as membranes for partial oxidation of methane

    Directory of Open Access Journals (Sweden)

    Noronha F.B.

    2004-01-01

    Full Text Available In this work two different synthesis methods of perovskites, SrCo0.5FeO3, were compared: combustion synthesis and oxides mixture aiming at evaluating their use as membranes for partial oxidation of methane. The combustion synthesis method explores an exothermic, generally very fast and self-sustaining chemical reaction between the desired metal salts and a suitable organic fuel, which is ignited at a temperature much lower than the actual phase formation temperature. The oxides mixture are based on a physical mixture of the powder oxides followed by calcination to obtain the desired phase. In order to obtain the membranes, we studied the conformation of bodies and the temperatures of sintering in the two powders synthesized. The powders were analyzed by density and grain size distribution and characterized by X-ray diffraction (XRD and scanning electron microscopy (SEM. After conformation, in cylindrical form, the green bodies were analyzed by density. After sintering at 1150 °C, the membranes were analyzed by density and they were characterized by XRD and SEM. The powder obtained by combustion synthesis shows lower density and fine grains than the other obtained by oxides mixture. The membranes obtained present very different morphology depending on the precursor powder synthesis. The sintered membranes obtained by combustion method also present a very uniform morphology without segregation.

  10. Comparison the Effect of Teaching by Group Guided Discovery Learning, Questions & Answers and Lecturing Methods on the Level of Learning and Information Durability of Students

    Directory of Open Access Journals (Sweden)

    Mardanparvar H.

    2016-02-01

    Full Text Available Aims: The requirements for revising the traditional education methods and utilization of new and active student-oriented learning methods have come into the scope of the educational systems long ago. Therefore, the new methods are being popular in different sciences including medical sciences. The aim of this study was to compare the effectiveness of teaching through three methods (group guided discovery, questions and answers, and lecture methods on the learning level and information durability in the nursing students. Instrument & Methods: In the semi-experimental study, 62 forth-semester nursing students of Nursing and Midwifery Faculty of Isfahan University of Medical Sciences, who were passing the infectious course for the first time at the first semester of the academic year 2015-16, were studied. The subjects were selected via census method and randomly divided into three groups including group guided discovery, questions and answers, and lecture groups. The test was conducted before, immediately after, and one month after the conduction of the training program using a researcher-made questionnaire. Data was analyzed by SPSS 19 software using Chi-square test, one-way ANOVA, ANOVA with repeated observations, and LSD post-hoc test. Findings: The mean score of the test conducted immediately after the training program in the lecture group was significantly lesser than guided discovery and question and answer groups (p<0.001. In addition, the mean score of the test conducted one month after the training program in guided discovery group was significantly higher than both question and answer (p=0.004 and lecture (p=0.001 groups. Conclusion: Active educational methods lead to a higher level of the students’ participation in the educational issues and provided a background to enhance learning and for better information durability. 

  11. Change Of Learning Environment Using Game Production ­Theory, Methods And Practice

    DEFF Research Database (Denmark)

    Reng, Lars; Kofoed, Lise; Schoenau-Fog, Henrik

    2018-01-01

    will focus on cases in which development of games did change the learning environments into production units where students or employees were producing games as part of the learning process. The cases indicate that the motivation as well as the learning curve became very high. The pedagogical theories......Game Based Learning has proven to have many possibilities for supporting better learning outcomes, when using educational or commercial games in the classroom. However, there is also a great potential in using game development as a motivator in other kinds of learning scenarios. This study...... and methods are based on Problem Based Learning (PBL), but are developed further by combining PBL with a production-oriented/design based approach. We illustrate the potential of using game production as a learning environment with investigation of three game productions. We can conclude that using game...

  12. Sparse Machine Learning Methods for Understanding Large Text Corpora

    Data.gov (United States)

    National Aeronautics and Space Administration — Sparse machine learning has recently emerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational...

  13. A blended learning approach to teaching sociolinguistic research methods

    Directory of Open Access Journals (Sweden)

    Olivier, Jako

    2014-12-01

    Full Text Available This article reports on the use of Wiktionary, an open source online dictionary, as well as generic wiki pages within a university’s e-learning environment as teaching and learning resources in an Afrikaans sociolinguistics module. In a communal constructivist manner students learnt, but also constructed learning content. From the qualitative research conducted with students it is clear that wikis provide for effective facilitation of a blended learning approach to sociolinguistic research. The use of this medium was positively received, however, some students did prefer handing in assignments in hard copy. The issues of computer literacy and access to the internet were also raised by the respondents. The use of wikis and Wiktionary prompted useful unplanned discussions around reliability and quality of public wikis. The use of a public wiki such as Wiktionary served as encouragement for students as they were able to contribute to the promotion of Afrikaans in this way.

  14. How Learning Designs, Teaching Methods and Activities Differ by Discipline in Australian Universities

    Science.gov (United States)

    Cameron, Leanne

    2017-01-01

    This paper reports on the learning designs, teaching methods and activities most commonly employed within the disciplines in six universities in Australia. The study sought to establish if there were significant differences between the disciplines in learning designs, teaching methods and teaching activities in the current Australian context, as…

  15. "Debate" Learning Method and Its Implications for the Formal Education System

    Science.gov (United States)

    Najafi, Mohammad; Motaghi, Zohre; Nasrabadi, Hassanali Bakhtiyar; Heshi, Kamal Nosrati

    2016-01-01

    Regarding the importance of enhancement in learner's social skills, especially in learning process, this study tries to introduce one of the group learning programs entitled "debate" as a teaching method in Iran religious universities. It also considers the concept and the history of this method by qualitative and descriptive-analytical…

  16. An exploration of learning to link with Wikipedia: features, methods and training collection

    NARCIS (Netherlands)

    He, J.; de Rijke, M.

    2010-01-01

    We describe our participation in the Link-the-Wiki track at INEX 2009. We apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of our approaches: features, learning methods as well as the collection used for training the models. We

  17. APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis

    Science.gov (United States)

    Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara

    2009-01-01

    Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…

  18. Listening to Our Students: Understanding How They Learn Research Methods in Geography

    Science.gov (United States)

    Keenan, Kevin; Fontaine, Danielle

    2012-01-01

    How undergraduate students learn research methods in geography has been understudied. Existing work has focused on course description from the instructor's perspective. This study, however, uses a grounded theory approach to allow students' voices to shape a new theory of how they themselves say that they learn research methods. Data from two…

  19. Learning Practice-Based Research Methods: Capturing the Experiences of MSW Students

    Science.gov (United States)

    Natland, Sidsel; Weissinger, Erika; Graaf, Genevieve; Carnochan, Sarah

    2016-01-01

    The literature on teaching research methods to social work students identifies many challenges, such as dealing with the tensions related to producing research relevant to practice, access to data to teach practice-based research, and limited student interest in learning research methods. This is an exploratory study of the learning experiences of…

  20. Square Pegs, Round Holes: An Exploration of Teaching Methods and Learning Styles of Millennial College Students

    Science.gov (United States)

    Bailey, Regina M.

    2012-01-01

    In an information-saturated world, today's college students desire to be engaged both in and out of their college classrooms. This mixed-methods study sought to explore how replacing traditional teaching methods with engaged learning activities affects millennial college student attitudes and perceptions about learning. The sub-questions…

  1. Exploring Non-Traditional Learning Methods in Virtual and Real-World Environments

    Science.gov (United States)

    Lukman, Rebeka; Krajnc, Majda

    2012-01-01

    This paper identifies the commonalities and differences within non-traditional learning methods regarding virtual and real-world environments. The non-traditional learning methods in real-world have been introduced within the following courses: Process Balances, Process Calculation, and Process Synthesis, and within the virtual environment through…

  2. Adult Learners' Preferred Methods of Learning Preventative Heart Disease Care

    Science.gov (United States)

    Alavi, Nasim

    2016-01-01

    The purpose of this study was to investigate the preferred method of learning about heart disease by adult learners. This research study also investigated if there was a statistically significant difference between race/ethnicity, age, and gender of adult learners and their preferred method of learning preventative heart disease care. This…

  3. Studying learning in the healthcare setting: the potential of quantitative diary methods.

    Science.gov (United States)

    Ciere, Yvette; Jaarsma, Debbie; Visser, Annemieke; Sanderman, Robbert; Snippe, Evelien; Fleer, Joke

    2015-08-01

    Quantitative diary methods are longitudinal approaches that involve the repeated measurement of aspects of peoples' experience of daily life. In this article, we outline the main characteristics and applications of quantitative diary methods and discuss how their use may further research in the field of medical education. Quantitative diary methods offer several methodological advantages, such as measuring aspects of learning with great detail, accuracy and authenticity. Moreover, they enable researchers to study how and under which conditions learning in the health care setting occurs and in which way learning can be promoted. Hence, quantitative diary methods may contribute to theory development and the optimization of teaching methods in medical education.

  4. Simultaneous anatomical sketching as learning by doing method of teaching human anatomy.

    Science.gov (United States)

    Noorafshan, Ali; Hoseini, Leila; Amini, Mitra; Dehghani, Mohammad-Reza; Kojuri, Javad; Bazrafkan, Leila

    2014-01-01

    Learning by lecture is a passive experience. Many innovative techniques have been presented to stimulate students to assume a more active attitude toward learning. In this study, simultaneous sketch drawing, as an interactive learning technique was applied to teach anatomy to the medical students. We reconstructed a fun interactive model of teaching anatomy as simultaneous anatomic sketching. To test the model's instruction effectiveness, we conducted a quasi- experimental study and then the students were asked to write their learning experiences in their portfolio, also their view was evaluated by a questionnaire. The results of portfolio evaluation revealed that students believed that this method leads to deep learning and understanding anatomical subjects better. Evaluation of the students' views on this teaching approach was showed that, more than 80% of the students were agreed or completely agreed with this statement that leaning anatomy concepts are easier and the class is less boring with this method. More than 60% of the students were agreed or completely agreed to sketch anatomical figures with professor simultaneously. They also found the sketching make anatomy more attractive and it reduced the time for learning anatomy. These number of students were agree or completely agree that the method help them learning anatomical concept in anatomy laboratory. More than 80% of the students found the simultaneous sketching is a good method for learning anatomy overall. Sketch drawing, as an interactive learning technique, is an attractive for students to learn anatomy.

  5. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  6. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    International Nuclear Information System (INIS)

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t

    2012-01-01

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  7. Different protein-protein interface patterns predicted by different machine learning methods.

    Science.gov (United States)

    Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi

    2017-11-22

    Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

  8. Evaluation of Students' Perceptions Towards An Innovative Teaching-Learning Method During Pharmacology Revision Classes: Autobiography of Drugs.

    Science.gov (United States)

    Joshi, Anuradha; Ganjiwale, Jaishree

    2015-07-01

    Various studies in medical education have shown that active learning strategies should be incorporated into the teaching-learning process to make learning more effective, efficient and meaningful. The aim of this study was to evaluate student's perceptions on an innovative revision method conducted in Pharmacology i.e. in form of Autobiography of Drugs. The main objective of study was to help students revise the core topics in Pharmacology in an interesting way. Questionnaire based survey on a newer method of pharmacology revision in two batches of second year MBBS students of a tertiary care teaching medical college. Various sessions on Autobiography of Drugs were conducted amongst two batches of second year MBBS students, during their Pharmacology revision classes. Student's perceptions were documented with the help of a five point likert scale through a questionnaire regarding quality, content and usefulness of this method. Descriptive analysis. Students of both the batches appreciated the innovative method taken up for revision. The median scores in most of the domains in both batches were four out of five, indicative of good response. Feedback from open-ended questions also revealed that the innovative module on "Autobiography of Drugs" was taken as a positive learning experience by students. Autobiography of drugs has been used to help students recall topics that they have learnt through other teachings methods. Autobiography sessions in Pharmacology during revision slots, can be one of the interesting ways in helping students revise and recall topics which have already been taught in theory classes.

  9. Learning physics: A comparative analysis between instructional design methods

    Science.gov (United States)

    Mathew, Easow

    The purpose of this research was to determine if there were differences in academic performance between students who participated in traditional versus collaborative problem-based learning (PBL) instructional design approaches to physics curricula. This study utilized a quantitative quasi-experimental design methodology to determine the significance of differences in pre- and posttest introductory physics exam performance between students who participated in traditional (i.e., control group) versus collaborative problem solving (PBL) instructional design (i.e., experimental group) approaches to physics curricula over a college semester in 2008. There were 42 student participants (N = 42) enrolled in an introductory physics course at the research site in the Spring 2008 semester who agreed to participate in this study after reading and signing informed consent documents. A total of 22 participants were assigned to the experimental group (n = 22) who participated in a PBL based teaching methodology along with traditional lecture methods. The other 20 students were assigned to the control group (n = 20) who participated in the traditional lecture teaching methodology. Both the courses were taught by experienced professors who have qualifications at the doctoral level. The results indicated statistically significant differences (p traditional (i.e., lower physics posttest scores and lower differences between pre- and posttest scores) versus collaborative (i.e., higher physics posttest scores, and higher differences between pre- and posttest scores) instructional design approaches to physics curricula. Despite some slight differences in control group and experimental group demographic characteristics (gender, ethnicity, and age) there were statistically significant (p = .04) differences between female average academic improvement which was much higher than male average academic improvement (˜63%) in the control group which may indicate that traditional teaching methods

  10. A reward optimization method based on action subrewards in hierarchical reinforcement learning.

    Science.gov (United States)

    Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

    2014-01-01

    Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.

  11. Game-Based Methods to Encourage EFL Learners to Transition to Autonomous Learning

    Directory of Open Access Journals (Sweden)

    Janine Berger

    2014-09-01

    Full Text Available This paper describes a work in progress in which we aim to encourage EFL students to take their learning beyond the classroom in order to experience English in different ways. Inspired by what is being done at the Quest to Learn middle and high school in New York City and ChicagoQuest (Institute of Play, 2014b our idea involves conducting an action research project in order to find out if game-like learning techniques, modified and adapted to the needs of university-aged EFL learners in Ecuador will help to increase motivation and independent learning for our students.

  12. Blockchain learning: can crypto-currency methods be appropriated to enhance online learning?

    OpenAIRE

    Devine, Peter

    2015-01-01

    Blockchain is a distributed database that maintains a dynamic list of data records, hardened to prevent tampering and revision. It is the framework for cryptocurrencies like Bitcoin.\\ud \\ud A Blockchain learning tool would provide a secure and verifiable learning transaction ledger. Its decentralised nature would ensure a learner, rather than institution-centred record of achievements that would be difficult to tamper with, enabling parties, such as employers or learning institutions, to revi...

  13. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

    2012-03-15

    To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

  14. Non-linguistic learning in aphasia: Effects of training method and stimulus characteristics

    Science.gov (United States)

    Vallila-Rohter, Sofia; Kiran, Swathi

    2013-01-01

    Purpose The purpose of the current study was to explore non-linguistic learning ability in patients with aphasia, examining the impact of stimulus typicality and feedback on success with learning. Method Eighteen patients with aphasia and eight healthy controls participated in this study. All participants completed four computerized, non-linguistic category-learning tasks. We probed learning ability under two methods of instruction: feedback-based (FB) and paired-associate (PA). We also examined the impact of task complexity on learning ability, comparing two stimulus conditions: typical (Typ) and atypical (Atyp). Performance was compared between groups and across conditions. Results Results demonstrated that healthy controls were able to successfully learn categories under all conditions. For our patients with aphasia, two patterns of performance arose. One subgroup of patients was able to maintain learning across task manipulations and conditions. The other subgroup of patients demonstrated a sensitivity to task complexity, learning successfully only in the typical training conditions. Conclusions Results support the hypothesis that impairments of general learning are present in aphasia. Some patients demonstrated the ability to extract category information under complex training conditions, while others learned only under conditions that were simplified and emphasized salient category features. Overall, the typical training condition facilitated learning for all participants. Findings have implications for therapy, which are discussed. PMID:23695914

  15. A novel time series link prediction method: Learning automata approach

    Science.gov (United States)

    Moradabadi, Behnaz; Meybodi, Mohammad Reza

    2017-09-01

    Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

  16. Comparison of two methods: TBL-based and lecture-based learning in nursing care of patients with diabetes in nursing students

    Directory of Open Access Journals (Sweden)

    Masoud Khodaveisi

    2016-08-01

    Full Text Available Learning plays an important role in developing nursing skills and right care-taking. The Present study aims to evaluate two learning methods based on team –based learning and lecture-based learning in learning care-taking of patients with diabetes in nursing students. In this quasi-experimental study, 64 students in term 4 in nursing college of Bukan and Miandoab were included in the study based on knowledge and performance questionnaire including 15 questions based on knowledge and 5 questions based on performance on care-taking in patients with diabetes were used as data collection tool whose reliability was confirmed by cronbach alpha (r=0.83 by the researcher. To compare the mean score of knowledge and performance in each group in pre-test step and post-test step, pair –t test and to compare mean of scores in two groups of control and intervention, the independent t- test was used. There was not significant statistical difference between two groups in pre terms of knowledge and performance score (p=0.784. There was significant difference between the mean of knowledge scores and diabetes performance in the post-test in the team-based learning group and lecture-based learning group (p=0.001. There was significant difference between the mean score of knowledge of diabetes care in pre-test and post-test in base learning groups (p=0.001. In both methods team-based and lecture-based learning approaches resulted in improvement in learning in students, but the rate of learning in the team-based learning approach is greater compared to that of lecturebased learning and it is recommended that this method be used as a higher education method in the education of students.

  17. Measuring the learning effectiveness of Web-based teacher professional development in the hypothesis based learning method of teaching science

    Science.gov (United States)

    Wilson, Penne L.

    2007-12-01

    This study was conducted as part of the five year evaluation of the Star Schools grant awarded to Oklahoma State University for the development on online teacher professional development in the Hypothesis Based Learning (HbL) method of science instruction. Participants in this research were five teachers who had completed the online workshop, submitted a lesson plan, and who allowed this researcher and other members of the University of New Mexico Evaluation Team into their classrooms to observe and to determine if the learning of the method from the online HbL workshop had translated into practice. These teachers worked in inner city, suburban, metropolitan, and rural communities in the U.S. Southwest. This study was conducted to determine if teachers learned the HbL method from the online HbL workshop, to examine the relationship of satisfaction to learning, and to determine the elements of the online workshop that led to teacher learning. To measure learning of HbL, three different assessment instruments were used: embedded assessments within the online HbL workshop that gave teachers a scenario and asked them to generate questions to facilitate the HbL process; the analysis of a lesson plan provided by teachers using a science concept that they wished to incorporate in their curriculum using an HbL lesson template provided at the HbL website; and, observations of teachers facilitating the HbL process conducted at three different times during the year that they began the HbL online workshop. To determine if teachers were satisfied with the learning environment, the online HbL workshop, and the product, HbL Method for Teaching Science, and to determine if teachers could identify the elements of the online workshop that led to learning, interviews with the participants were conducted. The research findings were presented in two parts: Part I is an analysis of data provided by the assessment instruments and a content analysis of the transcripts of the teacher

  18. Review of Statistical Learning Methods in Integrated Omics Studies (An Integrated Information Science).

    Science.gov (United States)

    Zeng, Irene Sui Lan; Lumley, Thomas

    2018-01-01

    Integrated omics is becoming a new channel for investigating the complex molecular system in modern biological science and sets a foundation for systematic learning for precision medicine. The statistical/machine learning methods that have emerged in the past decade for integrated omics are not only innovative but also multidisciplinary with integrated knowledge in biology, medicine, statistics, machine learning, and artificial intelligence. Here, we review the nontrivial classes of learning methods from the statistical aspects and streamline these learning methods within the statistical learning framework. The intriguing findings from the review are that the methods used are generalizable to other disciplines with complex systematic structure, and the integrated omics is part of an integrated information science which has collated and integrated different types of information for inferences and decision making. We review the statistical learning methods of exploratory and supervised learning from 42 publications. We also discuss the strengths and limitations of the extended principal component analysis, cluster analysis, network analysis, and regression methods. Statistical techniques such as penalization for sparsity induction when there are fewer observations than the number of features and using Bayesian approach when there are prior knowledge to be integrated are also included in the commentary. For the completeness of the review, a table of currently available software and packages from 23 publications for omics are summarized in the appendix.

  19. Aligning professional skills and active learning methods: an application for information and communications technology engineering

    Science.gov (United States)

    Llorens, Ariadna; Berbegal-Mirabent, Jasmina; Llinàs-Audet, Xavier

    2017-07-01

    Engineering education is facing new challenges to effectively provide the appropriate skills to future engineering professionals according to market demands. This study proposes a model based on active learning methods, which is expected to facilitate the acquisition of the professional skills most highly valued in the information and communications technology (ICT) market. The theoretical foundations of the study are based on the specific literature on active learning methodologies. The Delphi method is used to establish the fit between learning methods and generic skills required by the ICT sector. An innovative proposition is therefore presented that groups the required skills in relation to the teaching method that best develops them. The qualitative research suggests that a combination of project-based learning and the learning contract is sufficient to ensure a satisfactory skills level for this profile of engineers.

  20. Millennial Students' Preferred Methods for Learning Concepts in Psychiatric Nursing.

    Science.gov (United States)

    Garwood, Janet K

    2015-09-01

    The current longitudinal, descriptive, and correlational study explored which traditional teaching strategies can engage Millennial students and adequately prepare them for the ultimate test of nursing competence: the National Council Licensure Examination. The study comprised a convenience sample of 40 baccalaureate nursing students enrolled in a psychiatric nursing course. The students were exposed to a variety of traditional (e.g., PowerPoint(®)-guided lectures) and nontraditional (e.g., concept maps, group activities) teaching and learning strategies, and rated their effectiveness. The students' scores on the final examination demonstrated that student learning outcomes met or exceeded national benchmarks. Copyright 2015, SLACK Incorporated.

  1. Aims and harvest of moral case deliberation.

    Science.gov (United States)

    Weidema, Froukje C; Molewijk, Bert A C; Kamsteeg, Frans; Widdershoven, Guy A M

    2013-09-01

    Deliberative ways of dealing with ethical issues in health care are expanding. Moral case deliberation is an example, providing group-wise, structured reflection on dilemmas from practice. Although moral case deliberation is well described in literature, aims and results of moral case deliberation sessions are unknown. This research shows (a) why managers introduce moral case deliberation and (b) what moral case deliberation participants experience as moral case deliberation results. A responsive evaluation was conducted, explicating moral case deliberation experiences by analysing aims (N = 78) and harvest (N = 255). A naturalistic data collection included interviews with managers and evaluation questionnaires of moral case deliberation participants (nurses). From the analysis, moral case deliberation appeals for cooperation, team bonding, critical attitude towards routines and nurses' empowerment. Differences are that managers aim to foster identity of the nursing profession, whereas nurses emphasize learning processes and understanding perspectives. We conclude that moral case deliberation influences team cooperation that cannot be controlled with traditional management tools, but requires time and dialogue. Exchanging aims and harvest between manager and team could result in co-creating (moral) practice in which improvements for daily cooperation result from bringing together perspectives of managers and team members.

  2. Impact of a Modified Jigsaw Method for Learning an Unfamiliar, Complex Topic

    Directory of Open Access Journals (Sweden)

    Denise Kolanczyk

    2017-09-01

    Full Text Available Objective: The aim of this study was to use the jigsaw method with an unfamiliar, complex topic and to evaluate the effectiveness of the jigsaw teaching method on student learning of assigned material (“jigsaw expert” versus non-assigned material (“jigsaw learner”. Innovation: The innovation was implemented in an advanced cardiology elective. Forty students were assigned a pre-reading and one of four valvular heart disorders, a topic not previously taught in the curriculum. A pre-test and post-test evaluated overall student learning. Student performance on pre/post tests as the “jigsaw expert” and “jigsaw learner” was also compared. Critical Analysis: Overall, the post-test mean score of 85.75% was significantly higher than that of the pre-test score of 56.75% (p<0.05. There was significant improvement in scores regardless of whether the material was assigned (“jigsaw experts” pre=58.8% and post=82.5%; p<0.05 or not assigned (“jigsaw learners” pre= 56.25% and post= 86.56%, p<0.05 for pre-study. Next Steps: The use of the jigsaw method to teach unfamiliar, complex content helps students to become both teachers and active listeners, which are essential to the skills and professionalism of a health care provider. Further studies are needed to evaluate use of the jigsaw method to teach unfamiliar, complex content on long-term retention and to further examine the effects of expert vs. non-expert roles. Conflict of Interest We declare no conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received, employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties.   Type: Note

  3. An Activity-based Approach to the Learning and Teaching of Research Methods: Measuring Student Engagement and Learning

    Directory of Open Access Journals (Sweden)

    Eimear Fallon

    2013-05-01

    Full Text Available This paper discusses a research project carried out with 82 final and third year undergraduate students, learning Research Methods prior to undertaking an undergraduate thesis during the academic years 2010 and 2011. The research had two separate, linked objectives, (a to develop a Research Methods module that embraces an activity-based approach to learning in a group environment, (b to improve engagement by all students. The Research Methods module was previously taught through a traditional lecture-based format. Anecdotally, it was felt that student engagement was poor and learning was limited. It was believed that successful completion of the development of this Module would equip students with a deeply-learned battery of research skills to take into their further academic and professional careers. Student learning was achieved through completion of a series of activities based on different research methods. In order to encourage student engagement, a wide variety of activities were used. These activities included workshops, brainstorming, mind-mapping, presentations, written submissions, peer critiquing, lecture/seminar, and ‘speed dating’ with more senior students and self reflection. Student engagement was measured through a survey based on a U.S. National Survey of Student Engagement (2000. A questionnaire was devised to establish whether, and to what degree, students were engaged in the material that they were learning, while they were learning it. The results of the questionnaire were very encouraging with between 63% and 96% of students answering positively to a range of questions concerning engagement. In terms of the two objectives set, these were satisfactorily met. The module was successfully developed and continues to be delivered, based upon this new and significant level of student engagement.

  4. Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

    Science.gov (United States)

    Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

    2009-05-01

    Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

  5. Constructivist Teaching/Learning Theory and Participatory Teaching Methods

    Science.gov (United States)

    Fernando, Sithara Y. J. N.; Marikar, Faiz M. M. T.

    2017-01-01

    Evidence for the teaching involves transmission of knowledge, superiority of guided transmission is explained in the context of our knowledge, but it is also much more that. In this study we have examined General Sir John Kotelawala Defence University's cadet and civilian students' response to constructivist learning theory and participatory…

  6. Active Learning Methods and Technology: Strategies for Design Education

    Science.gov (United States)

    Coorey, Jillian

    2016-01-01

    The demands in higher education are on the rise. Charged with teaching more content, increased class sizes and engaging students, educators face numerous challenges. In design education, educators are often torn between the teaching of technology and the teaching of theory. Learning the formal concepts of hierarchy, contrast and space provide the…

  7. Sensor Data Air Pollution Prediction by Machine Learning Methods

    Czech Academy of Sciences Publication Activity Database

    Vidnerová, Petra; Neruda, Roman

    submitted 25. 1. (2018) ISSN 1530-437X R&D Projects: GA ČR GA15-18108S Grant - others:GA MŠk(CZ) LM2015042 Institutional support: RVO:67985807 Keywords : machine learning * sensors * air pollution * deep neural networks * regularization networks Subject RIV: IN - Informatics, Computer Science Impact factor: 2.512, year: 2016

  8. Classification of carcinogenic and mutagenic properties using machine learning method

    DEFF Research Database (Denmark)

    Moorthy, N. S.Hari Narayana; Kumar, Surendra; Poongavanam, Vasanthanathan

    2017-01-01

    An accurate calculation of carcinogenicity of chemicals became a serious challenge for the health assessment authority around the globe because of not only increased cost for experiments but also various ethical issues exist using animal models. In this study, we provide machine learning...

  9. Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

    Science.gov (United States)

    Xu, Bo; Lin, Hongfei; Lin, Yuan; Ma, Yunlong; Yang, Liang; Wang, Jian; Yang, Zhihao

    2016-06-14

    In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the problem automatically, providing users with the needed information. However, it is a great challenge to apply these technologies directly for biomedical retrieval, because of the abundance of domain specific terminologies. To enhance biomedical retrieval, we propose a novel framework based on learning to rank. Learning to rank is a series of state-of-the-art information retrieval techniques, and has been proved effective in many information retrieval tasks. In the proposed framework, we attempt to tackle the problem of the abundance of terminologies by constructing ranking models, which focus on not only retrieving the most relevant documents, but also diversifying the searching results to increase the completeness of the resulting list for a given query. In the model training, we propose two novel document labeling strategies, and combine several traditional retrieval models as learning features. Besides, we also investigate the usefulness of different learning to rank approaches in our framework. Experimental results on TREC Genomics datasets demonstrate the effectiveness of our framework for biomedical information retrieval.

  10. Vygotskian methods of teaching and learning in the English ...

    African Journals Online (AJOL)

    This paper describes an alternative approachto the teaching of concepts related to theEnglish curriculum, namely literature, writing summaries and grammar. It combines ashift in the theory of school learning development by a combination with a psychologicaltheory of development. The research was conducted over the ...

  11. Understanding Sample Surveys: Selective Learning about Social Science Research Methods

    Science.gov (United States)

    Currin-Percival, Mary; Johnson, Martin

    2010-01-01

    We investigate differences in what students learn about survey methodology in a class on public opinion presented in two critically different ways: with the inclusion or exclusion of an original research project using a random-digit-dial telephone survey. Using a quasi-experimental design and data obtained from pretests and posttests in two public…

  12. Predicting Solar Activity Using Machine-Learning Methods

    Science.gov (United States)

    Bobra, M.

    2017-12-01

    Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

  13. A study on the engineering education methods with a learning management system

    OpenAIRE

    海老澤, 賢史; Ebisawa, Satoshi

    2017-01-01

    The educational methods with Learning Management System (LMS) are described, which are applied to two specialized courses for engineering education and a research guidance for graduation work at Niigata Institute of Technology.According to the analysis of LMS usage situation for graduation work, the LMS has provided an effect that learning time outside class hour is held and the convenience of students in learning is enhanced.In the specializedcourses, the rate of utilization of LMS has depen...

  14. Interest in Currency Trading Learning – Preferred Methods and Motivational Factors

    Directory of Open Access Journals (Sweden)

    Pintar Rok

    2016-02-01

    Full Text Available Background and purpose: This paper analyzes the interest of potential users for learning in the field of currency trading or foreign exchange (forex, FX. The purpose of our article is a to present currency trading, b to present different options, methods and learning approaches to educating in forex, c to present the research results discovering the interest of potential users for learning in the field of currency trading.

  15. A deep learning-based multi-model ensemble method for cancer prediction.

    Science.gov (United States)

    Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

    2018-01-01

    Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

    Directory of Open Access Journals (Sweden)

    Kuchin Yan

    2017-12-01

    Full Text Available The paper explores geophysical methods of wells survey, as well as their role in the development of Kazakhstan’s uranium deposit mining efforts. An analysis of the existing methods for solving the problem of interpreting geophysical data using machine learning in petroleum geophysics is made. The requirements and possible applications of machine learning methods in regard to uranium deposits of Kazakhstan are formulated in the paper.

  17. Perspective for applying traditional and inovative teaching and learning methods to nurses continuing education

    OpenAIRE

    Bendinskaitė, Irmina

    2015-01-01

    Bendinskaitė I. Perspective for applying traditional and innovative teaching and learning methods to nurse’s continuing education, magister thesis / supervisor Assoc. Prof. O. Riklikienė; Departament of Nursing and Care, Faculty of Nursing, Lithuanian University of Health Sciences. – Kaunas, 2015, – p. 92 The purpose of this study was to investigate traditional and innovative teaching and learning methods perspective to nurse’s continuing education. Material and methods. In a period fro...

  18. Comparing two methods of education (virtual versus traditional) on learning of Iranian dental students: a post-test only design study.

    Science.gov (United States)

    Moazami, Fariborz; Bahrampour, Ehsan; Azar, Mohammad Reza; Jahedi, Farzad; Moattari, Marzieh

    2014-03-05

    The importance of using technologies such as e-learning in different disciplines is discussed in the literature. Researchers have measured the effectiveness of e-learning in a number of fields.Considering the lack of research on the effectiveness of online learning in dental education particularly in Iran, the advantages of these learning methods and the positive university atmosphere regarding the use of online learning. This study, therefore, aims to compare the effects of two methods of teaching (virtual versus traditional) on student learning. This post-test only design study approached 40, fifth year dental students of Shiraz University of Medical Sciences. From this group, 35 students agreed to participate. These students were randomly allocated into two groups, experimental (virtual learning) and comparison (traditional learning). To ensure similarity between groups, we compared GPAs of all participants by the Mann-Whitney U test (P > 0.05). The experimental group received a virtual learning environment courseware package specifically designed for this study, whereas the control group received the same module structured in a traditional lecture form. The virtual learning environment consisted of online and offline materials. Two identical valid, reliable post-tests that consisted of 40 multiple choice questions (MCQs) and 4 essay questions were administered immediately (15 min) after the last session and two months later to assess for knowledge retention. Data were analyzed by SPSS version 20. A comparison of the mean knowledge score of both groups showed that virtual learning was more effective than traditional learning (effect size = 0.69). The newly designed virtual learning package is feasible and will result in more effective learning in comparison with lecture-based training. However further studies are needed to generalize the findings of this study.

  19. Effectiveness of flipped classroom with Poll Everywhere as a teaching-learning method for pharmacy students.

    Science.gov (United States)

    Gubbiyappa, Kumar Shiva; Barua, Ankur; Das, Biswadeep; Vasudeva Murthy, C R; Baloch, Hasnain Zafar

    2016-10-01

    Flipped classroom (FC) is a pedagogical model to engage students in learning process by replacing the didactic lectures. Using technology, lectures are moved out of the classroom and delivered online as means to provide interaction and collaboration. Poll Everywhere is an audience response system (ARS) which can be used in an FC to make the activities more interesting, engaging, and interactive. This study aims to study the perception of undergraduate pharmacy students on FC activity using Poll Everywhere ARS and to study the effectiveness of FC activity as a teaching-learning tool for delivering complementary medicine module in the undergraduate pharmacy program. In this nonrandomized trial on interrupted time series study, flipped class was conducted on group of 112 students of bachelor of pharmacy semester V. The topic selected was popular herbal remedies of the complementary medicine module. Flipped class was conducted with audio and video presentation in the form of a quiz using ten one-best-answer type of multiple-choice questions covering the learning objectives. Audience response was captured using web-based interaction with Poll Everywhere. Feedback was obtained from participants at the end of FC activity and debriefing was done. Randomly selected 112 complete responses were included in the final analysis. There were 47 (42%) male and 65 (58%) female respondents. The overall Cronbach's alpha of feedback questionnaire was 0.912. The central tendencies and dispersions of items in the questionnaire indicated the effectiveness of FC. The low or middle achievers of quiz session (pretest) during the FC activity were three times (95% confidence interval [CI] = 1.1-8.9) at the risk of providing neutral or negative feedback than high achievers ( P = 0.040). Those who gave neutral or negative feedback on FC activity were 3.9 times (95% CI = 1.3-11.8) at the risk of becoming low or middle achievers during the end of semester examination ( P = 0.013). The multivariate

  20. Project-Based Learning in Undergraduate Environmental Chemistry Laboratory: Using EPA Methods to Guide Student Method Development for Pesticide Quantitation

    Science.gov (United States)

    Davis, Eric J.; Pauls, Steve; Dick, Jonathan

    2017-01-01

    Presented is a project-based learning (PBL) laboratory approach for an upper-division environmental chemistry or quantitative analysis course. In this work, a combined laboratory class of 11 environmental chemistry students developed a method based on published EPA methods for the extraction of dichlorodiphenyltrichloroethane (DDT) and its…

  1. Evaluation of a Didactic Method for the Active Learning of Greedy Algorithms

    Science.gov (United States)

    Esteban-Sánchez, Natalia; Pizarro, Celeste; Velázquez-Iturbide, J. Ángel

    2014-01-01

    An evaluation of the educational effectiveness of a didactic method for the active learning of greedy algorithms is presented. The didactic method sets students structured-inquiry challenges to be addressed with a specific experimental method, supported by the interactive system GreedEx. This didactic method has been refined over several years of…

  2. Pioneering a Nursing Home Quality Improvement Learning Collaborative: A Case Study of Method and Lessons Learned.

    Science.gov (United States)

    Gillespie, Suzanne M; Olsan, Tobie; Liebel, Dianne; Cai, Xueya; Stewart, Reginald; Katz, Paul R; Karuza, Jurgis

    2016-02-01

    To describe the development of a nursing home (NH) quality improvement learning collaborative (QILC) that provides Lean Six Sigma (LSS) training and infrastructure support for quality assurance performance improvement change efforts. Case report. Twenty-seven NHs located in the Greater Rochester, NY area. The learning collaborative approach in which interprofessional teams from different NHs work together to improve common clinical and organizational processes by sharing experiences and evidence-based practices to achieve measurable changes in resident outcomes and system efficiencies. NH participation, curriculum design, LSS projects. Over 6 years, 27 NHs from urban and rural settings joined the QILC as organizational members and sponsored 47 interprofessional teams to learn LSS techniques and tools, and to implement quality improvement projects. NHs, in both urban and rural settings, can benefit from participation in QILCs and are able to learn and apply LSS tools in their team-based quality improvement efforts. Published by Elsevier Inc.

  3. The Effect of WhatsApp Messenger As Mobile Learning Integrated with Group Investigation Method of Learning Achievement

    Directory of Open Access Journals (Sweden)

    Hendrik Pratama

    2017-12-01

    Full Text Available The purpose of this research was determined the effect of application WhatsApp Messenger in the Group Investigation (GI method on learning achievement. The methods used experimental research with control group pretest-postest design. The sampling procedure used the purposive sampling technique that consists of 17 students as a control group and 17 students as an experimental group. The sample in this research is students in Electrical Engineering Education Study Program. The experimental group used the GI method that integrated with WhatsApp Messenger. The control group used lecture method without social media integration. The collecting data used observation, documentation, interview, questionnaire, and test. The researcher used a t-test for compared the control group and the experimental group’s learning outcomes at an alpha level of 0,05. The results showed differences between the experiment group and the control group. The study result of the experimental higher than the control groups. This learning was designed with start, grouping, planning, presenting, organizing, investigating, evaluating, ending’s stage. Integration of WhatsApp with group investigation method could cause the positive communication between student and lecturer. Discussion in this learning was well done, the student’s knowledge could appear in a group and the information could spread evenly and quickly.

  4. Perception of mathematics teachers on cooperative learning method in the 21st century

    Science.gov (United States)

    Taufik, Nurshahira Alwani Mohd; Maat, Siti Mistima

    2017-05-01

    Mathematics education is one of the branches to be mastered by students to help them compete with the upcoming challenges that are very challenging. As such, all parties should work together to help increase student achievement in Mathematics education in line with the Malaysian Education Blueprint (MEB) 2010-2025. Teaching methods play a very important role in attracting and fostering student understanding and interested in learning Mathematics. Therefore, this study was conducted to identify the perceptions of teachers in carrying out cooperative methods in the teaching and learning of mathematics. Participants of this study involving 4 teachers who teach Mathematics in primary schools around the state of Negeri Sembilan. Interviews are used as a method for gathering data. The findings indicate that cooperative methods help increasing interest and understanding in the teaching and learning of mathematics. In conclusion, the teaching methods affect the interest and understanding of students in the learning of Mathematics in the classroom.

  5. Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments

    OpenAIRE

    Kidziński, Łukasz; Mohanty, Sharada Prasanna; Ong, Carmichael; Huang, Zhewei; Zhou, Shuchang; Pechenko, Anton; Stelmaszczyk, Adam; Jarosik, Piotr; Pavlov, Mikhail; Kolesnikov, Sergey; Plis, Sergey; Chen, Zhibo; Zhang, Zhizheng; Chen, Jiale; Shi, Jun

    2018-01-01

    In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle course. Top participants were invited to describe their algorithms. In this work, we present eight solutions that used deep reinforcement learning approaches, based on algorithms such as Deep Deterministic Policy Gradient, Proximal Policy Optimization, and Trust Region Policy Optimization. Many solutions use similar ...

  6. Blended Learning: A Mixed-Methods Study on Successful Schools and Effective Practices

    Science.gov (United States)

    Mathews, Anne

    2017-01-01

    Blended learning is a teaching technique that utilizes face-to-face teaching and online or technology-based practice in which the learner has the ability to exert some level of control over the pace, place, path, or time of learning. Schools that employ this method of teaching often demonstrate larger gains than traditional face-to-face programs…

  7. Effects of Cooperative Learning Method on the Development of Listening Comprehension and Listening Skills

    Science.gov (United States)

    Kirbas, Abdulkadir

    2017-01-01

    In this study, the effect of the learning together technique, which is one of the cooperative learning methods, on the development of the listening comprehension and listening skills of the secondary school eighth grade students was investigated. Regarding the purpose of the research, experimental and control groups consisting of 75 students from,…

  8. Methods and Case Studies for Teaching and Learning about Failure and Safety.

    Science.gov (United States)

    Bignell, Victor

    1999-01-01

    Discusses methods for analyzing case studies of failures of technological systems. Describes two distance learning courses that compare standard models of failure and success with the actuality of given scenarios. Provides teaching and learning materials and information sources for application to aspects of design, manufacture, inspection, use,…

  9. An Approachment to Cooperative Learning in Higher Education: Comparative Study of Teaching Methods in Engineering

    Science.gov (United States)

    Estébanez, Raquel Pérez

    2017-01-01

    In the way of continuous improvement in teaching methods this paper explores the effects of Cooperative Learning (CL) against Traditional Learning (TL) in academic performance of students in higher education in two groups of the first course of Computer Science Degree at the university. The empirical study was conducted through an analysis of…

  10. e-Research and Learning Theory: What Do Sequence and Process Mining Methods Contribute?

    Science.gov (United States)

    Reimann, Peter; Markauskaite, Lina; Bannert, Maria

    2014-01-01

    This paper discusses the fundamental question of how data-intensive e-research methods could contribute to the development of learning theories. Using methodological developments in research on self-regulated learning as an example, it argues that current applications of data-driven analytical techniques, such as educational data mining and its…

  11. Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses

    Science.gov (United States)

    Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema

    2011-01-01

    This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…

  12. Exploring Service Learning Outcomes in Students: A Mixed Methods Study for Nursing

    Science.gov (United States)

    Martin, John F.

    2017-01-01

    This mixed methods study exploring student outcomes of service learning experiences is inter-disciplinary, near the intersection of higher education research, moral development, and nursing. The specific problem examined in this study is that service learning among university students is utilized by educators, but largely without a full…

  13. Applying Cognitive Behavioural Methods to Retrain Children's Attributions for Success and Failure in Learning

    Science.gov (United States)

    Toland, John; Boyle, Christopher

    2008-01-01

    This study involves the use of methods derived from cognitive behavioral therapy (CBT) to change the attributions for success and failure of school children with regard to learning. Children with learning difficulties and/or motivational and self-esteem difficulties (n = 29) were identified by their schools. The children then took part in twelve…

  14. Linked-Class Problem-Based Learning in Engineering: Method and Evaluation

    Science.gov (United States)

    Hunt, Emily M.; Lockwood-Cooke, Pamela; Kelley, Judy

    2010-01-01

    Problem-Based Learning (PBL) is a problem-centered teaching method with exciting potential in engineering education for motivating and enhancing student learning. Implementation of PBL in engineering education has the potential to bridge the gap between theory and practice. Two common problems are encountered when attempting to integrate PBL into…

  15. Women with learning disabilities and access to cervical screening: retrospective cohort study using case control methods

    Directory of Open Access Journals (Sweden)

    Stanistreet Debbi

    2008-01-01

    Full Text Available Abstract Background Several studies in the UK have suggested that women with learning disabilities may be less likely to receive cervical screening tests and a previous local study in had found that GPs considered screening unnecessary for women with learning disabilities. This study set out to ascertain whether women with learning disabilities are more likely to be ceased from a cervical screening programme than women without; and to examine the reasons given for ceasing women with learning disabilities. It was carried out in Bury, Heywood-and-Middleton and Rochdale. Methods Carried out using retrospective cohort study methods, women with learning disabilities were identified by Read code; and their cervical screening records were compared with the Call-and-Recall records of women without learning disabilities in order to examine their screening histories. Analysis was carried out using case-control methods – 1:2 (women with learning disabilities: women without learning disabilities, calculating odds ratios. Results 267 women's records were compared with the records of 534 women without learning disabilities. Women with learning disabilities had an odds ratio (OR of 0.48 (Confidence Interval (CI 0.38 – 0.58; X2: 72.227; p.value X2: 24.236; p.value X2: 286.341; p.value Conclusion The reasons given for ceasing and/or not screening suggest that merely being coded as having a learning disability is not the sole reason for these actions. There are training needs among smear takers regarding appropriate reasons not to screen and providing screening for women with learning disabilities.

  16. A mixed methods evaluation of team-based learning for applied pathophysiology in undergraduate nursing education.

    Science.gov (United States)

    Branney, Jonathan; Priego-Hernández, Jacqueline

    2018-02-01

    It is important for nurses to have a thorough understanding of the biosciences such as pathophysiology that underpin nursing care. These courses include content that can be difficult to learn. Team-based learning is emerging as a strategy for enhancing learning in nurse education due to the promotion of individual learning as well as learning in teams. In this study we sought to evaluate the use of team-based learning in the teaching of applied pathophysiology to undergraduate student nurses. A mixed methods observational study. In a year two, undergraduate nursing applied pathophysiology module circulatory shock was taught using Team-based Learning while all remaining topics were taught using traditional lectures. After the Team-based Learning intervention the students were invited to complete the Team-based Learning Student Assessment Instrument, which measures accountability, preference and satisfaction with Team-based Learning. Students were also invited to focus group discussions to gain a more thorough understanding of their experience with Team-based Learning. Exam scores for answers to questions based on Team-based Learning-taught material were compared with those from lecture-taught material. Of the 197 students enrolled on the module, 167 (85% response rate) returned the instrument, the results from which indicated a favourable experience with Team-based Learning. Most students reported higher accountability (93%) and satisfaction (92%) with Team-based Learning. Lectures that promoted active learning were viewed as an important feature of the university experience which may explain the 76% exhibiting a preference for Team-based Learning. Most students wanted to make a meaningful contribution so as not to let down their team and they saw a clear relevance between the Team-based Learning activities and their own experiences of teamwork in clinical practice. Exam scores on the question related to Team-based Learning-taught material were comparable to those

  17. Machine learning methods in predicting the student academic motivation

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    Ivana Đurđević Babić

    2017-01-01

    Full Text Available Academic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting student academic motivation based on their behaviour in learning management system (LMS courses, this paper intends to establish links between the predicted student academic motivation and their behaviour in the LMS course. Students from all years at the Faculty of Education in Osijek participated in this research. Three machine learning classifiers (neural networks, decision trees, and support vector machines were used. To establish whether a significant difference in the performance of models exists, a t-test of the difference in proportions was used. Although, all classifiers were successful, the neural network model was shown to be the most successful in detecting the student academic motivation based on their behaviour in LMS course.

  18. Survey of Machine Learning Methods for Database Security

    Science.gov (United States)

    Kamra, Ashish; Ber, Elisa

    Application of machine learning techniques to database security is an emerging area of research. In this chapter, we present a survey of various approaches that use machine learning/data mining techniques to enhance the traditional security mechanisms of databases. There are two key database security areas in which these techniques have found applications, namely, detection of SQL Injection attacks and anomaly detection for defending against insider threats. Apart from the research prototypes and tools, various third-party commercial products are also available that provide database activity monitoring solutions by profiling database users and applications. We present a survey of such products. We end the chapter with a primer on mechanisms for responding to database anomalies.

  19. NetiNeti: discovery of scientific names from text using machine learning methods

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    Akella Lakshmi

    2012-08-01

    Full Text Available Abstract Background A scientific name for an organism can be associated with almost all biological data. Name identification is an important step in many text mining tasks aiming to extract useful information from biological, biomedical and biodiversity text sources. A scientific name acts as an important metadata element to link biological information. Results We present NetiNeti (Name Extraction from Textual Information-Name Extraction for Taxonomic Indexing, a machine learning based approach for recognition of scientific names including the discovery of new species names from text that will also handle misspellings, OCR errors and other variations in names. The system generates candidate names using rules for scientific names and applies probabilistic machine learning methods to classify names based on structural features of candidate names and features derived from their contexts. NetiNeti can also disambiguate scientific names from other names using the contextual information. We evaluated NetiNeti on legacy biodiversity texts and biomedical literature (MEDLINE. NetiNeti performs better (precision = 98.9% and recall = 70.5% compared to a popular dictionary based approach (precision = 97.5% and recall = 54.3% on a 600-page biodiversity book that was manually marked by an annotator. On a small set of PubMed Central’s full text articles annotated with scientific names, the precision and recall values are 98.5% and 96.2% respectively. NetiNeti found more than 190,000 unique binomial and trinomial names in more than 1,880,000 PubMed records when used on the full MEDLINE database. NetiNeti also successfully identifies almost all of the new species names mentioned within web pages. Conclusions We present NetiNeti, a machine learning based approach for identification and discovery of scientific names. The system implementing the approach can be accessed at http://namefinding.ubio.org.

  20. Musical Chairs: An Innovative Teaching and Learning Method

    Science.gov (United States)

    Kuo, Ya-Hui

    2010-01-01

    How teaching and learning takes place in classrooms can be easily seen by the way classrooms are set up: Students' desks and chairs are arranged in rolls while teachers' desks are up front. Yet, why must teachers be the ones who lecture, why can't it be students? Would it be better or worse when teachers are the receivers and the students are the…

  1. Tracing policy movements: methods for studying learning and policy circulation

    OpenAIRE

    Wood, Astrid

    2016-01-01

    Policy flows are not quantifiable and calculating processes but part of the uneven movement of ideas and experiences that involves power and personalities. Processes of learning and policy circulation have thus proven difficult to study especially as the exchanges taking place between actors and localities rarely lead directly to uptake. This paper outlines a conceptual and methodological framework for conducting policy mobilities research by attending to the plethora of ordinary practices – ...

  2. Study of Meta-Cognitive Beliefs and Learning Methods and Their Relationship with Exam Anxiety in High School Students Bandar Abbas City, 2014

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    Ghazal Motazed Keyvani

    2016-08-01

    Full Text Available Background Nowadays, one of the principal difficulties faced by educational systems worldwide is anxiety, a mental problem, which is evidently difficult to be endured by many students and leads to various types of mental and physical disorders or reduction of educational efficiency, and has gained attention of sociologists for its consequent psychological, social, and economical impacts. Objectives The current study aimed at predicting exam anxiety based on meta-cognitive beliefs and learning methods among high school students of Bandar Abbas. Methods The study population included 351 students (197 males and 154 females, who were selected randomly by the cluster approach and answered the research tools including Meta-Cognitive Beliefs Questionnaires (MCQ-30, Learning methods questionnaires of Marton and Saljoo (1996 and also test anxiety questionnaire of Alpert and Haber (1960. The study plan was correlative-descriptive. Pearson simple correlation coefficient, multi variable regression, and multi variable variance analysis were used to analyze the obtained data. Results The study results indicated that there was a positive significant relationship between meta-cognitive beliefs and exam anxiety, a negative significant relationship between profound learning and learning methods and exam anxiety, and a positive significant relationship between smattering learning method and exam anxiety. The regression exam results also revealed that meta-cognitive beliefs and smattering learning methods could positively predict and determine exam anxiety in students. A significant relationship was observed between meta-cognitive beliefs in females and males, and female students showed greater intention and interest toward meta-cognitive beliefs than males, however, no significant difference was observed between learning methods and exam anxiety in females and males. Conclusions It was concluded from the study results that profound learning methods lead to the

  3. Implementation of Simulation Based-Concept Attainment Method to Increase Interest Learning of Engineering Mechanics Topic

    Science.gov (United States)

    Sultan, A. Z.; Hamzah, N.; Rusdi, M.

    2018-01-01

    The implementation of concept attainment method based on simulation was used to increase student’s interest in the subjects Engineering of Mechanics in second semester of academic year 2016/2017 in Manufacturing Engineering Program, Department of Mechanical PNUP. The result of the implementation of this learning method shows that there is an increase in the students’ learning interest towards the lecture material which is summarized in the form of interactive simulation CDs and teaching materials in the form of printed books and electronic books. From the implementation of achievement method of this simulation based concept, it is noted that the increase of student participation in the presentation and discussion as well as the deposit of individual assignment of significant student. With the implementation of this method of learning the average student participation reached 89%, which before the application of this learning method only reaches an average of 76%. And also with previous learning method, for exam achievement of A-grade under 5% and D-grade above 8%. After the implementation of the new learning method (simulation based-concept attainment method) the achievement of Agrade has reached more than 30% and D-grade below 1%.

  4. Childhood fever management program for Korean pediatric nurses: A comparison between blended and face-to-face learning method.

    Science.gov (United States)

    Jeong, Yong Sun; Kim, Jin Sun

    2014-01-01

    A blended learning can be a useful learning strategy to improve the quality of fever and fever management education for pediatric nurses. This study compared the effects of a blended and face-to-face learning program on pediatric nurses' childhood fever management, using theory of planned behavior. A nonequivalent control group pretest-posttest design was used. A fever management education program using blended learning (combining face-to-face and online learning components) was offered to 30 pediatric nurses, and 29 pediatric nurses received face-to-face education. Learning outcomes did not significantly differ between the two groups. However, learners' satisfaction was higher for the blended learning program than the face-to-face learning program. A blended learning pediatric fever management program was as effective as a traditional face-to-face learning program. Therefore, a blended learning pediatric fever management-learning program could be a useful and flexible learning method for pediatric nurses.

  5. The effect of high fidelity simulated learning methods on physiotherapy pre-registration education: a systematic review protocol.

    Science.gov (United States)

    Roberts, Fiona; Cooper, Kay

    2017-11-01

    The objective of this review is to identify if high fidelity simulated learning methods are effective in enhancing clinical/practical skills compared to usual, low fidelity simulated learning methods in pre-registration physiotherapy education.

  6. Impact and appreciation of two methods aiming at reducing hazardous drug environmental contamination: The centralization of the priming of IV tubing in the pharmacy and use of a closed-system transfer device.

    Science.gov (United States)

    Guillemette, Annie; Langlois, Hélène; Voisine, Maxime; Merger, Delphine; Therrien, Roxane; Mercier, Genevieve; Lebel, Denis; Bussières, Jean-François

    2014-12-01

    The main objective was to evaluate the impact of two methods aiming at reducing hazardous drug environmental contamination: the centralization of the priming of IV tubing in the pharmacy and the use of a closed-system transfer device. The secondary objective was to evaluate the satisfaction of pharmacy technicians using a survey. Sites in the hematology-oncology satellite pharmacy and care unit were analyzed for the presence of cyclophosphamide, ifosfamide and methotrexate before and after the centralization of the priming of IV tubing in the pharmacy and before and after using a closed-system transfer device. The limits of detection for cyclophosphamide, ifosfamide and methotrexate were, respectively, of 0.0015 ng/cm(2), 0.0012 ng/cm(2) and 0.0060 ng/cm(2). The pharmacy technician satisfaction was evaluated using a questionnaire. A total of 225 samples was quantified. After the centralization of priming in the pharmacy, no significant difference was found in the proportion of positive samples for cyclophosphamide, ifosfamide and methotrexate. Traces of cyclophosphamide found on the floor in patient care areas was significantly reduced (median[min-max] 0.08[0.06-0.09]ng/cm(2) vs. 0.03[0.02-0.05], p tubing in the pharmacy reduced floor contamination in patient care areas without increasing surface contamination in the pharmacy. Closed-system transfer devices reduced contamination in pharmacy, but handling issues were raised by pharmacy technicians. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  7. Understanding the effects of time on collaborative learning processes in problem based learning: a mixed methods study.

    Science.gov (United States)

    Hommes, J; Van den Bossche, P; de Grave, W; Bos, G; Schuwirth, L; Scherpbier, A

    2014-10-01

    Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning processes developed within and over three periods in the first 1,5 study years of an undergraduate curriculum. Next, a qualitative study using semi-structured individual interviews focused on detailed development of group processes driving collaborative learning during one period in seven tutorial groups. The hierarchic multilevel analyses of the quantitative data showed that a varying combination of group processes developed within and over the three observed periods. The qualitative study illustrated development in psychological safety, interdependence, potency, group learning behaviour, social and task cohesion. Two new processes emerged: 'transactive memory' and 'convergence in mental models'. The results indicate that groups are dynamic social systems with numerous contextual influences. Future research should thus include time as an important influence on collaborative learning. Practical implications are discussed.

  8. Considerations for Task Analysis Methods and Rapid E-Learning Development Techniques

    Directory of Open Access Journals (Sweden)

    Dr. Ismail Ipek

    2014-02-01

    Full Text Available The purpose of this paper is to provide basic dimensions for rapid training development in e-learning courses in education and business. Principally, it starts with defining task analysis and how to select tasks for analysis and task analysis methods for instructional design. To do this, first, learning and instructional technologies as visions of the future were discussed. Second, the importance of task analysis methods in rapid e-learning was considered, with learning technologies as asynchronous and synchronous e-learning development. Finally, rapid instructional design concepts and e-learning design strategies were defined and clarified with examples, that is, all steps for effective task analysis and rapid training development techniques based on learning and instructional design approaches were discussed, such as m-learning and other delivery systems. As a result, the concept of task analysis, rapid e-learning development strategies and the essentials of online course design were discussed, alongside learner interface design features for learners and designers.

  9. Teaching Theory in Occupational Therapy Using a Cooperative Learning: A Mixed-Methods Study.

    Science.gov (United States)

    Howe, Tsu-Hsin; Sheu, Ching-Fan; Hinojosa, Jim

    2018-01-01

    Cooperative learning provides an important vehicle for active learning, as knowledge is socially constructed through interaction with others. This study investigated the effect of cooperative learning on occupational therapy (OT) theory knowledge attainment in professional-level OT students in a classroom environment. Using a pre- and post-test group design, 24 first-year, entry-level OT students participated while taking a theory course in their second semester of the program. Cooperative learning methods were implemented via in-class group assignments. The students were asked to complete two questionnaires regarding their attitudes toward group environments and their perception toward group learning before and after the semester. MANCOVA was used to examine changes in attitudes and perceived learning among groups. Students' summary sheets for each in-class assignment and course evaluations were collected for content analysis. Results indicated significant changes in students' attitude toward working in small groups regardless of their prior group experience.

  10. The «PBL WORKING ENVIRONMENT» as interactive and expert system to learn the problem-based learning method

    Directory of Open Access Journals (Sweden)

    Susana Correnti

    2016-01-01

    Full Text Available The «PBL working environment» is a virtual environment developed in the framework of SCENE project (profeSsional development for an effeCtive PBL approach: a practical experiENce through ICT-enabled lEarning solution, co-funded by the European Lifelong Learning Program. The «PBL working environment» is devoted to prepare headmasters and teachers of secondary and vocational schools to use Problem-Based Learning (PBL pedagogy effectively. It is a student-centered pedagogy where learners are «actively» engaged in real world problems to solve or challenges to meet. Students develop problem-solving, self-directed learning and team skills. The «PBL working environment» is an virtual tool including three main elements: e-learning platform, virtual facilitator and PBL repository. Teachers, trainers and headmasters/school managers learn the PBL pedagogy by attending an on-line course (e-learning platform delivered through the «inductive method». It allows learners to experience PBL approach, by practicing it stage by stage, and then learn to turn practice into theory by abstracting their experience to build a theoretical understanding. Since generating the proper scenario is the most critical aspect of PBL, after benefiting from the on-line course, users can benefit from a further support: the Virtual Facilitator. It provides tips and hints on how correctly design a problem scenario and by asking questions to collect data on user's specific needs. The Virtual Facilitator is able to provide a/or more suitable example(s which match as closest as possible the teacher/trainer need. Finally, users can share problem scenarios and projects of different subjects of studies and with different characteristics uploaded and downloaded in the PBL repository.

  11. Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

    Science.gov (United States)

    Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

    2016-06-21

    Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Results of a study assessing teaching methods of faculty after measuring student learning style preference.

    Science.gov (United States)

    Stirling, Bridget V

    2017-08-01

    Learning style preference impacts how well groups of students respond to their curricula. Faculty have many choices in the methods for delivering nursing content, as well as assessing students. The purpose was to develop knowledge around how faculty delivered curricula content, and then considering these findings in the context of the students learning style preference. Following an in-service on teaching and learning styles, faculty completed surveys on their methods of teaching and the proportion of time teaching, using each learning style (visual, aural, read/write and kinesthetic). This study took place at the College of Nursing a large all-female university in Saudi Arabia. 24 female nursing faculty volunteered to participate in the project. A cross-sectional design was used. Faculty reported teaching using mostly methods that were kinesthetic and visual, although lecture was also popular (aural). Students preferred kinesthetic and aural learning methods. Read/write was the least preferred by students and the least used method of teaching by faculty. Faculty used visual methods about one third of the time, although they were not preferred by the students. Students' preferred learning style (kinesthetic) was the method most used by faculty. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

    Science.gov (United States)

    Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

    2015-12-01

    Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

  14. Comparing the Effects of Objective Structured Assessment of Technical Skills (OSATS) and Traditional Method on Learning of Students.

    Science.gov (United States)

    Mansoorian, Mohammad Reza; Hosseiny, Marzeih Sadat; Khosravan, Shahla; Alami, Ali; Alaviani, Mehri

    2015-06-01

    Despite the benefits of the objective structured assessment of technical skills (OSATS) and it appropriateness for evaluating clinical abilities of nursing students , few studies are available on the application of this method in nursing education. The purpose of this study was to compare the effect of using OSATS and traditional methods on the students' learning. We also aimed to signify students' views about these two methods and their views about the scores they received in these methods in a medical emergency course. A quasi-experimental study was performed on 45 first semester students in nursing and medical emergencies passing a course on fundamentals of practice. The students were selected by a census method and evaluated by both the OSATS and traditional methods. Data collection was performed using checklists prepared based on the 'text book of nursing procedures checklists' published by Iranian nursing organization and a questionnaire containing learning rate and students' estimation of their received scores. Descriptive statistics as well as paired t-test and independent samples t-test were used in data analysis. The mean of students' score in OSATS was significantly higher than their mean score in traditional method (P = 0.01). Moreover, the mean of self-evaluation score after the traditional method was relatively the same as the score the students received in the exam. However, the mean of self-evaluation score after the OSATS was relatively lower than the scores the students received in the OSATS exam. Most students believed that OSATS can evaluate a wide range of students' knowledge and skills compared to traditional method. Results of this study indicated the better effect of OSATS on learning and its relative superiority in precise assessment of clinical skills compared with the traditional evaluation method. Therefore, we recommend using this method in evaluation of students in practical courses.

  15. WHAT ARE AGRICULTURAL ECONOMICS PH.D. STUDENTS LEARNING ABOUT AGRIBUSINESS RESEARCH METHODS AND SUBJECT AREAS?

    OpenAIRE

    House, Lisa; Sterns, James A.

    2002-01-01

    This document contains the PowerPoint presentation given by the authors at the 2002 WCC-72 meetings, regarding what agricultural economics Ph.D students are learning about agribusiness research methods and subject areas.

  16. Application of Computer-Assisted Learning Methods in the Teaching of Chemical Spectroscopy.

    Science.gov (United States)

    Ayscough, P. B.; And Others

    1979-01-01

    Discusses the application of computer-assisted learning methods to the interpretation of infrared, nuclear magnetic resonance, and mass spectra; and outlines extensions into the area of integrated spectroscopy. (Author/CMV)

  17. On Plant Detection of Intact Tomato Fruits Using Image Analysis and Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Kyosuke Yamamoto

    2014-07-01

    Full Text Available Fully automated yield estimation of intact fruits prior to harvesting provides various benefits to farmers. Until now, several studies have been conducted to estimate fruit yield using image-processing technologies. However, most of these techniques require thresholds for features such as color, shape and size. In addition, their performance strongly depends on the thresholds used, although optimal thresholds tend to vary with images. Furthermore, most of these techniques have attempted to detect only mature and immature fruits, although the number of young fruits is more important for the prediction of long-term fluctuations in yield. In this study, we aimed to develop a method to accurately detect individual intact tomato fruits including mature, immature and young fruits on a plant using a conventional RGB digital camera in conjunction with machine learning approaches. The developed method did not require an adjustment of threshold values for fruit detection from each image because image segmentation was conducted based on classification models generated in accordance with the color, shape, texture and size of the images. The results of fruit detection in the test images showed that the developed method achieved a recall of 0.80, while the precision was 0.88. The recall values of mature, immature and young fruits were 1.00, 0.80 and 0.78, respectively.

  18. Active semi-supervised learning method with hybrid deep belief networks.

    Science.gov (United States)

    Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

    2014-01-01

    In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

  19. Improved Saturated Hydraulic Conductivity Pedotransfer Functions Using Machine Learning Methods

    Science.gov (United States)

    Araya, S. N.; Ghezzehei, T. A.

    2017-12-01

    Saturated hydraulic conductivity (Ks) is one of the fundamental hydraulic properties of soils. Its measurement, however, is cumbersome and instead pedotransfer functions (PTFs) are often used to estimate it. Despite a lot of progress over the years, generic PTFs that estimate hydraulic conductivity generally don't have a good performance. We develop significantly improved PTFs by applying state of the art machine learning techniques coupled with high-performance computing on a large database of over 20,000 soils—USKSAT and the Florida Soil Characterization databases. We compared the performance of four machine learning algorithms (k-nearest neighbors, gradient boosted model, support vector machine, and relevance vector machine) and evaluated the relative importance of several soil properties in explaining Ks. An attempt is also made to better account for soil structural properties; we evaluated the importance of variables derived from transformations of soil water retention characteristics and other soil properties. The gradient boosted models gave the best performance with root mean square errors less than 0.7 and mean errors in the order of 0.01 on a log scale of Ks [cm/h]. The effective particle size, D10, was found to be the single most important predictor. Other important predictors included percent clay, bulk density, organic carbon percent, coefficient of uniformity and values derived from water retention characteristics. Model performances were consistently better for Ks values greater than 10 cm/h. This study maximizes the extraction of information from a large database to develop generic machine learning based PTFs to estimate Ks. The study also evaluates the importance of various soil properties and their transformations in explaining Ks.

  20. News Conference: Serbia hosts teachers' seminar Resources: Teachers TV website closes for business Festival: Science takes to the stage in Denmark Research: How noise affects learning in secondary schools CERN: CERN visit inspires new teaching ideas Education: PLS aims to improve perception of science for school students Conference: Scientix conference discusses challenges in science education

    Science.gov (United States)

    2011-07-01

    Conference: Serbia hosts teachers' seminar Resources: Teachers TV website closes for business Festival: Science takes to the stage in Denmark Research: How noise affects learning in secondary schools CERN: CERN visit inspires new teaching ideas Education: PLS aims to improve perception of science for school students Conference: Scientix conference discusses challenges in science education