Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

Science.gov (United States)

Lochner, Lukas; Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

2016-02-21

The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome. Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize 'student passivity' as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes.

Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

Science.gov (United States)

Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

2016-01-01

Objectives The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. Methods A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Results Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome.  Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. Conclusions By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize ‘student passivity’ as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes. PMID:26897012

Modafinil combined with cognitive training is associated with improved learning in healthy volunteers--a randomised controlled trial.

Science.gov (United States)

Gilleen, J; Michalopoulou, P G; Reichenberg, A; Drake, R; Wykes, T; Lewis, S W; Kapur, S

2014-04-01

Improving cognition in people with neuropsychiatric disorders remains a major clinical target. By themselves pharmacological and non-pharmacological approaches have shown only modest effects in improving cognition. In the present study we tested a recently-proposed methodology to combine CT with a 'cognitive-enhancing' drug to improve cognitive test scores and expanded on previous approaches by delivering combination drug and CT, over a long intervention of repeated sessions, and used multiple tasks to reveal the cognitive processes being enhanced. We also aimed to determine whether gains from this combination approach generalised to untrained tests. In this proof of principle randomised-controlled trial thirty-three healthy volunteers were randomised to receive either modafinil or placebo combined with daily cognitive training over two weeks. Volunteers were trained on tasks of new-language learning, working memory and verbal learning following 200 mg modafinil or placebo for ten days. Improvements in trained and untrained tasks were measured. Rate of new-language learning was significantly enhanced with modafinil, and effects were greatest over the first five sessions. Modafinil improved within-day learning rather than between-day retention. No enhancement of gains with modafinil was observed in working memory nor rate of verbal learning. Gains in all tasks were retained post drug-administration, but transfer effects to broad cognitive abilities were not seen. This study shows that combining CT with modafinil specifically elevates learning over early training sessions compared to CT with placebo and provides a proof of principle experimental paradigm for pharmacological enhancement of cognitive remediation. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

An ensemble machine learning approach to predict survival in breast cancer.

Science.gov (United States)

Djebbari, Amira; Liu, Ziying; Phan, Sieu; Famili, Fazel

2008-01-01

Current breast cancer predictive signatures are not unique. Can we use this fact to our advantage to improve prediction? From the machine learning perspective, it is well known that combining multiple classifiers can improve classification performance. We propose an ensemble machine learning approach which consists of choosing feature subsets and learning predictive models from them. We then combine models based on certain model fusion criteria and we also introduce a tuning parameter to control sensitivity. Our method significantly improves classification performance with a particular emphasis on sensitivity which is critical to avoid misclassifying poor prognosis patients as good prognosis.

Supporting teachers integrating web 2.0 in a Problem Based Learning approach

DEFF Research Database (Denmark)

Buus, Lillian

2010-01-01

Based on theoretical and methodological considerations within problem-based learning (PBL), web 2.0 technologies and learning designs, the article try to illustrate a design model for supporting teachers in their learning design trying to integrate web 2.0 technologies into their PBL approach...... that a transition from curriculum-based teaching to PBL entails a movement from a teacher-centered approach to a learner-centered approach [4],[5]. This move can in many ways be compared to the conceptual move from web 1.0 to web 2.0 that by some is seen as a transition from ‘users/learners as consumers’ towards...... ‘users/learners as producers’ [6]. Consequently, it makes good sense to connect Web 2.0 with a problem-based approach to learning. Therefore it’s interesting to look upon a learning design model supporting teachers at AAU in their pedagogical design combining these two. The Collaborative E...

An Investigation on Individual Students' Perceptions of Interest Utilizing a Blended Learning Approach

Science.gov (United States)

Shroff, Ronnie H.; Vogel, Douglas R.

2010-01-01

Research has established that individual student interest has a positive effect on learning and academic achievement. However, little is known about the impact of a blended learning approach on individual student interest and whether combinations of online and face-to-face learning activities significantly enhance student interest. This paper…

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning.

Science.gov (United States)

Zechendorf, Elisabeth; Vaßen, Phillip; Zhang, Jieyi; Hallawa, Ahmed; Martincuks, Antons; Krenkel, Oliver; Müller-Newen, Gerhard; Schuerholz, Tobias; Simon, Tim-Philipp; Marx, Gernot; Ascheid, Gerd; Schmeink, Anke; Dartmann, Guido; Thiemermann, Christoph; Martin, Lukas

2018-01-01

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical- In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p  machine learning algorithms.

Effects of a blended learning approach on student outcomes in a graduate-level public health course.

Science.gov (United States)

Kiviniemi, Marc T

2014-03-11

Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, "traditional" approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses.

E-learning on the job : training taking a more virtual approach

Energy Technology Data Exchange (ETDEWEB)

Macedo, R.

2008-07-15

A growing number of companies are using web-based e-learning systems to train employees. The activities of 3 E-learning companies were described in this article, notably dominKnow Learning Systems, NGRAIN Corporation and Blatant Media. One of the greatest challenges facing the oilsands industry is to build a skilled labour force to operate massive upgraders. The benefit of the e-learning approach is that consistent information can be delivered to learners, with no variation in information. The training takes on many forms, either through online simulations or simply placing a manual online. In addition to saving time, e-learning familiarizes workers with specific pieces of equipment that would be much too expensive to purchase. Three-dimensional equipment simulations are also made available for training purposes. This article presented an online e-learning approach that has been used effectively for safety training and corporate governance. E-learning simplified the process compared to actual classroom training. It allowed staff to combine training time with regular work schedules. The online e-learning approach was shown to save companies many of hours in training time. 2 figs.

Use of the 5E learning cycle model combined with problem-based learning for a fundamentals of nursing course.

Science.gov (United States)

Jun, Won Hee; Lee, Eun Ju; Park, Han Jong; Chang, Ae Kyung; Kim, Mi Ja

2013-12-01

The 5E learning cycle model has shown a positive effect on student learning in science education, particularly in courses with theory and practice components. Combining problem-based learning (PBL) with the 5E learning cycle was suggested as a better option for students' learning of theory and practice. The purpose of this study was to compare the effects of the traditional learning method with the 5E learning cycle model with PBL. The control group (n = 78) was subjected to a learning method that consisted of lecture and practice. The experimental group (n = 83) learned by using the 5E learning cycle model with PBL. The results showed that the experimental group had significantly improved self-efficacy, critical thinking, learning attitude, and learning satisfaction. Such an approach could be used in other countries to enhance students' learning of fundamental nursing. Copyright 2013, SLACK Incorporated.

Combining lived experience with the facilitation of enquiry-based learning: a 'trigger' for transformative learning.

Science.gov (United States)

Stacey, G; Oxley, R; Aubeeluck, A

2015-09-01

What is known on the subject The values underpinning recovery-orientated practice are recited in the literature and influential in the content of mental health nurse education internationally. However, scepticism exists regarding the degree to which students' assimilate the principles of recovery into their practice due to the troublesome and challenging nature of learning at a transformational level, also known as threshold concept learning. Evaluation suggests that this combination of educational approaches positively influences students' prior understandings, beliefs and values in relation to the prospect for people with significant mental health problems to recover. The components of threshold concepts are useful as a deductive framework for the evaluation of educational initiatives which attempt to initiate transformative learning. While this forum clearly holds significant potential for student development, support and preparation is needed for both the student and the facilitator in order to enable the possibility of learning which influences attitudes, beliefs and practice. The aim of this paper is to discuss the potential for combining lived experience of mental distress with the facilitation of enquiry-based learning (EBL) to act as a trigger for transformative learning in the context of promoting the understanding of mental health 'recovery' in nurse education.The values underpinning recovery-orientated practice are recited in the literature and influential in mental health nurse education internationally. However, scepticism exists regarding the degree to which students assimilate into their practice. An open-ended was distributed to a cohort of pre-registration nursing students receiving the co-facilitated EBL (n = 112). Data demonstrated how the specific attributes of this educational approach were identified by students as impacting positively on ill-informed preconceptions, understanding of complex theory and their future practice. Results were

Effects of a blended learning approach on student outcomes in a graduate-level public health course

Science.gov (United States)

2014-01-01

Background Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. Method The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, “traditional” approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. Results There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Conclusions Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses. PMID:24612923

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

Science.gov (United States)

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

Directory of Open Access Journals (Sweden)

Yi Zhang

2015-01-01

Full Text Available Maximum likelihood classifier (MLC and support vector machines (SVM are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

A novel deep learning approach for classification of EEG motor imagery signals.

Science.gov (United States)

Tabar, Yousef Rezaei; Halici, Ugur

2017-02-01

Signal classification is an important issue in brain computer interface (BCI) systems. Deep learning approaches have been used successfully in many recent studies to learn features and classify different types of data. However, the number of studies that employ these approaches on BCI applications is very limited. In this study we aim to use deep learning methods to improve classification performance of EEG motor imagery signals. In this study we investigate convolutional neural networks (CNN) and stacked autoencoders (SAE) to classify EEG Motor Imagery signals. A new form of input is introduced to combine time, frequency and location information extracted from EEG signal and it is used in CNN having one 1D convolutional and one max-pooling layers. We also proposed a new deep network by combining CNN and SAE. In this network, the features that are extracted in CNN are classified through the deep network SAE. The classification performance obtained by the proposed method on BCI competition IV dataset 2b in terms of kappa value is 0.547. Our approach yields 9% improvement over the winner algorithm of the competition. Our results show that deep learning methods provide better classification performance compared to other state of art approaches. These methods can be applied successfully to BCI systems where the amount of data is large due to daily recording.

In the business of learning : approaches to learning of undergraduate students in business

NARCIS (Netherlands)

Hooijer, J.G.

2010-01-01

Three approaches to learning are distinguished in the learning literature: a surface, deep and strategic approach to learning. The surface approach to learning is characterized as undirected rote learning, motivated by a fear of failure. The deep approach to learning is characterized as interested

Motivations, Learning, Approaches, and Strategies in Biochemistry Students at a Public University in Argentina

Directory of Open Access Journals (Sweden)

Silvia Raquel Salim

2006-05-01

Full Text Available The aim of the present paper is to understand how university students learn, and to comprehend the motivations and learning strategies they use when deciding in what field to major. We chose a combined research design: qualitative and quantitative. We applied the Questionnaire for the Evaluation of Learning and Studying Processes (CEPEA to Biochemistry students attending the National University of Tucumán (Argentina, and performed individual semi-structured interviews. Cluster analysis allowed us to identify three groups of students having who use different learning approaches: deep, superficial and ambivalent. We found that learning approaches are closely related with some teaching practices that encourage or inhibit them; among these are the types of learning evaluation.

Teaching European Studies: A Blended Learning Approach

Directory of Open Access Journals (Sweden)

Alina Christova

2011-12-01

Full Text Available This paper will be looking into the teaching method developed by the Institute for European Studies in Brussels, combining an e-learning tool- the E-modules- with face-to-face training sessions and webinars. The main aim is to analyse the three different components of this “blended learning” pedagogical approach, as well as the way they complement each other and to address a few of the challenges that have emerged from the experience of working with them so far. The E-modules are an e-learning platform that has been designed with the purpose of offering a structured and interactive way of learning how the European Union functions. The face-to-face training component currently takes the form of three days in-house seminars, covering in an intensive manner the most important areas of the curriculum. The lectures are held by a mix of academics and practitioners, hereby ensuring a balanced approach, in which theory and practice come together to facilitate the learning experience. The third element of the “blended learning” method is placed in-between online and face-to-face learning: interactive seminars and debates are held online, giving the participants the chance to deepen their knowledge in certain fields of interest and to discuss the content of the course with specialists and among themselves. The mixture of delivery and interaction methods was chosen in order to accommodate a large variety of target groups, ranging from students to professionals working with EU-related issues, with different backgrounds and geographical origins. One of the main challenges is to use each medium for the functionalities it is best designed for and to ensure that the various pieces of the pedagogical puzzle fit together perfectly, while allowing the learners the flexibility that had initially directed them towards “blended learning” instead of a classical classroom approach.

Addressing Indigenous (ICT) Approaches in South-East Asian Learning Systems

Science.gov (United States)

Amato, Silvia

2013-01-01

Purpose: The purpose of this paper is to provide a structural overview about indigenous approaches to learning in South East Asian countries, with a particular reference to education initiatives that have been operating in this region; and especially to investigate information and communication technologies (ICT) systems, in combination with…

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

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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.

Blended Learning Model on Hands-On Approach for In-Service Secondary School Teachers: Combination of E-Learning and Face-to-Face Discussion

Science.gov (United States)

Ho, Vinh-Thang; Nakamori, Yoshiteru; Ho, Tu-Bao; Lim, Cher Ping

2016-01-01

The purpose of this study was to examine the effectiveness of a blended learning model on hands-on approach for in-service secondary school teachers using a quasi-experimental design. A 24-h teacher-training course using the blended learning model was administered to 117 teachers, while face-to-face instruction was given to 60 teachers. The…

A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

Science.gov (United States)

Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

2017-11-01

Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

Effectiveness of teaching and learning mathematics for Thai university engineering students through a combination of activity and lecture based classroom

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Parinya S. Ngiamsunthorn

2014-04-01

Full Text Available There are concerns of developing effective pedagogical practices for teaching mathematics for engineering students as many engineering students experience difficulties in learning compulsory mathematics subjects in their first and second years of the degree. This paper aims to investigate the effectiveness of using a variety of teaching and learning approaches including lecture based learning, activity based learning, e-learning via learning management system (LMS and practice or tutorial session in mathematics subjects for engineering students. This study was carried out on 160 students who need to enroll three basic mathematics subjects (MTH101, MTH102 and MTH201 for an engineering degree during academic year 2011 – 2012. The students were divided into three groups according to their majors of study. The first two groups of students were given a combination of various teaching approaches for only one semester (either MTH102 or MTH201, while the last group was given a combination of various teaching approaches for two semesters (both MTH102 and MTH201. To evaluate the effectiveness of teaching and learning, examination results, questionnaires on attitude towards teaching and learning, and a formal university teaching evaluation by students were collected and analyzed. It is found that different students perceive mathematics contents from different teaching methods according to their preferred learning styles. Moreover, most students in all groups performed at least the same or better in their final subject (MTH201. However, there is an interesting finding that low proficiency students in earlier mathematics subjects who received a combination of various teaching approaches for two semesters can improve their examination results better than other groups, on average. This is also reflected from an increasing average score on teaching evaluation from this group of students about teaching techniques.

Ensemble approach combining multiple methods improves human transcription start site prediction

LENUS (Irish Health Repository)

Dineen, David G

2010-11-30

Abstract Background The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets. Results We demonstrate the heterogeneity of current prediction sets, and take advantage of this heterogeneity to construct a two-level classifier (\\'Profisi Ensemble\\') using predictions from 7 programs, along with 2 other data sources. Support vector machines using \\'full\\' and \\'reduced\\' data sets are combined in an either\\/or approach. We achieve a 14% increase in performance over the current state-of-the-art, as benchmarked by a third-party tool. Conclusions Supervised learning methods are a useful way to combine predictions from diverse sources.

Problem-Based Learning and Creative Instructional Approaches for Laboratory Exercises in Introductory Crop Science

Science.gov (United States)

Teplitski, Max; McMahon, Margaret J.

2006-01-01

The implementation of problem-based learning (PBL) and other inquiry-driven educational techniques is often resisted by both faculty and students, who may not be comfortable with this learning/instructional style. We present here a hybrid approach, which combines elements of expository education with inquiry-driven laboratory exercises and…

Examining Change in Metacognitive Knowledge and Metacognitive Control During Motor Learning: What Can be Learned by Combining Methodological Approaches?

Directory of Open Access Journals (Sweden)

Claire Sangster Jokić

2014-04-01

Full Text Available Growing recognition of the importance of understanding metacognitive behaviour as it occurs in everyday learning situations has prompted an expansion of the methodological approaches used to examine metacognition. This becomes especially pertinent when examining the process of metacognitive change, where 'on-line' observational approaches able to capture metacognitive performance as it occurs during socially-mediated learning are being increasingly applied. This study applied a mixed methods approach to examine children's metacognitive performance as it was exhibited during participation in an intervention program aimed at addressing motor performance difficulties. Participants in the study were ten 7-9 year old children with developmental coordination disorder (DCD, a condition characterized by poor motor coordination and difficulty acquiring motor-based tasks. All participants engaged in a 10-session program in which children were taught to use a problem-solving strategy for addressing motor performance difficulties. To examine children's metacognitive performance, sessions were video-taped and subsequently analysed using a quantitative observational coding method and an in-depth qualitative review of therapist-child interactions. This allowed for a fine-grained analysis of children's demonstration of metacognitive knowledge and control and how such performance evolved over the course of the program. Of particular interest was the finding that while children were often able to express task-specific knowledge, they failed to apply this knowledge during practice. Conversely, children were often able to demonstrate performance-based evidence for metacognitive control but were not able to make conscious reports of such skill following practice. This finding is consistent with models of metacognitive development which suggest that the emergence of performance-based metacognitive skills precede the ability for the conscious expression of

Study strategies and approaches to learning

DEFF Research Database (Denmark)

Christensen, Hans Peter

Process Questionnaire to identify their approach to learning. It was hypothesised that the students’ learning approach would depend more on the quality of the study work than on the quantity; that an active and reflective study strategy was required to obtain deep conceptual understanding. The result...... showed a weak correlation between the student’s main learning approach as defined by the ratio of the deep approach score to the surface approach score and the student’s study intensity as identified by the ratio of non-scheduled independent activities to scheduled teacher-controlled activities....... There was however a much stronger linear correlation (significant at the 0.01 level) between the deep-surface ratio and the total study load. The same result was observed when measuring other students’ study strategy and learning approach for a single course. The empirical basis is still too limited to draw...

Does the acceptance of hybrid learning affect learning approaches in France?

Science.gov (United States)

Marco, Lionel Di; Venot, Alain; Gillois, Pierre

2017-01-01

Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

Achieving effective learning effects in the blended course: a combined approach of online self-regulated learning and collaborative learning with initiation.

Science.gov (United States)

Tsai, Chia-Wen

2011-09-01

In many countries, undergraduates are required to take at least one introductory computer course to enhance their computer literacy and computing skills. However, the application software education in Taiwan can hardly be deemed as effective in developing students' practical computing skills. The author applied online self-regulated learning (SRL) and collaborative learning (CL) with initiation in a blended computing course and examined the effects of different combinations on enhancing students' computing skills. Four classes, comprising 221 students, participated in this study. The online SRL and CL with initiation (G1, n = 53), online CL with initiation (G2, n = 68), and online CL without initiation (G3, n = 68) were experimental groups, and the last class, receiving traditional lecture (G4, n = 32), was the control group. The results of this study show that students who received the intervention of online SRL and CL with initiation attained significantly best grades for practical computing skills, whereas those that received the traditional lectures had statistically poorest grades among the four classes. The implications for schools and educators who plan to provide online or blended learning for their students, particularly in computing courses, are also provided in this study.

SYSTEM APPROACH TO THE BLENDED LEARNING

Directory of Open Access Journals (Sweden)

Vladimir Kukharenko

2015-10-01

Full Text Available Currently, much attention is paid to the development of learning sour cream – a combination of traditional and distance (30-70% of training. Such training is sometimes called hybrid and referred to disruptive technologies. Purpose – to show that the use of systemic campaign in blended learning provides a high quality of education, and the technology can be devastating. The subject of the study – blended learning, object of study – Mixed learning process. The analysis results show that the combined training increases the motivation of students, qualification of teachers, personalized learning process. At the same time there are no reliable methods of assessing the quality of education and training standards. It is important that blended learning strategy to support the institutional goals and had an effective organizational model for support.

Detection of eardrum abnormalities using ensemble deep learning approaches

Science.gov (United States)

Senaras, Caglar; Moberly, Aaron C.; Teknos, Theodoros; Essig, Garth; Elmaraghy, Charles; Taj-Schaal, Nazhat; Yua, Lianbo; Gurcan, Metin N.

2018-02-01

In this study, we proposed an approach to report the condition of the eardrum as "normal" or "abnormal" by ensembling two different deep learning architectures. In the first network (Network 1), we applied transfer learning to the Inception V3 network by using 409 labeled samples. As a second network (Network 2), we designed a convolutional neural network to take advantage of auto-encoders by using additional 673 unlabeled eardrum samples. The individual classification accuracies of the Network 1 and Network 2 were calculated as 84.4%(+/- 12.1%) and 82.6% (+/- 11.3%), respectively. Only 32% of the errors of the two networks were the same, making it possible to combine two approaches to achieve better classification accuracy. The proposed ensemble method allows us to achieve robust classification because it has high accuracy (84.4%) with the lowest standard deviation (+/- 10.3%).

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Science.gov (United States)

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Linking Action Learning and Inter-Organisational Learning: The Learning Journey Approach

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Schumacher, Thomas

2015-01-01

The article presents and illustrates the learning journey (LJ)--a new management development approach to inter-organisational learning based on observation, reflection and problem-solving. The LJ involves managers from different organisations and applies key concepts of action learning and systemic organisational development. Made up of…

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

Science.gov (United States)

Ravi, Daniele; Wong, Charence; Lo, Benny; Yang, Guang-Zhong

2017-01-01

The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires efficient methods of classification and analysis where deep learning is a promising technique for large-scale data analytics. While deep learning has been successful in implementations that utilize high-performance computing platforms, its use on low-power wearable devices is limited by resource constraints. In this paper, we propose a deep learning methodology, which combines features learned from inertial sensor data together with complementary information from a set of shallow features to enable accurate and real-time activity classification. The design of this combined method aims to overcome some of the limitations present in a typical deep learning framework where on-node computation is required. To optimize the proposed method for real-time on-node computation, spectral domain preprocessing is used before the data are passed onto the deep learning framework. The classification accuracy of our proposed deep learning approach is evaluated against state-of-the-art methods using both laboratory and real world activity datasets. Our results show the validity of the approach on different human activity datasets, outperforming other methods, including the two methods used within our combined pipeline. We also demonstrate that the computation times for the proposed method are consistent with the constraints of real-time on-node processing on smartphones and a wearable sensor platform.

Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

Science.gov (United States)

Shamir, Reuben R; Dolber, Trygve; Noecker, Angela M; Walter, Benjamin L; McIntyre, Cameron C

2015-01-01

Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery. Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Learning styles and approaches to learning among medical undergraduates and postgraduates.

Science.gov (United States)

Samarakoon, Lasitha; Fernando, Tharanga; Rodrigo, Chaturaka

2013-03-25

The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners.Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period.

Toward a Social Approach to Learning in Community Service Learning

Science.gov (United States)

Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda

2004-01-01

The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…

The combination of appetitive and aversive reinforcers and the nature of their interaction during auditory learning.

Science.gov (United States)

Ilango, A; Wetzel, W; Scheich, H; Ohl, F W

2010-03-31

Learned changes in behavior can be elicited by either appetitive or aversive reinforcers. It is, however, not clear whether the two types of motivation, (approaching appetitive stimuli and avoiding aversive stimuli) drive learning in the same or different ways, nor is their interaction understood in situations where the two types are combined in a single experiment. To investigate this question we have developed a novel learning paradigm for Mongolian gerbils, which not only allows rewards and punishments to be presented in isolation or in combination with each other, but also can use these opposite reinforcers to drive the same learned behavior. Specifically, we studied learning of tone-conditioned hurdle crossing in a shuttle box driven by either an appetitive reinforcer (brain stimulation reward) or an aversive reinforcer (electrical footshock), or by a combination of both. Combination of the two reinforcers potentiated speed of acquisition, led to maximum possible performance, and delayed extinction as compared to either reinforcer alone. Additional experiments, using partial reinforcement protocols and experiments in which one of the reinforcers was omitted after the animals had been previously trained with the combination of both reinforcers, indicated that appetitive and aversive reinforcers operated together but acted in different ways: in this particular experimental context, punishment appeared to be more effective for initial acquisition and reward more effective to maintain a high level of conditioned responses (CRs). The results imply that learning mechanisms in problem solving were maximally effective when the initial punishment of mistakes was combined with the subsequent rewarding of correct performance. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.

QSAR modelling using combined simple competitive learning networks and RBF neural networks.

Science.gov (United States)

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

A hybrid ensemble learning approach to star-galaxy classification

Science.gov (United States)

Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias

2015-10-01

There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

Assessing Approaches to Learning in School Readiness

Directory of Open Access Journals (Sweden)

Otilia C. Barbu

2015-07-01

Full Text Available This study examines the psychometric properties of two assessments of children’s approaches to learning: the Devereux Early Childhood Assessment (DECA and a 13-item approaches to learning rating scale (AtL derived from the Arizona Early Learning Standards (AELS. First, we administered questionnaires to 1,145 randomly selected parents/guardians of first-time kindergarteners. Second, we employed confirmatory factor analysis (CFA with parceling for DECA to reduce errors due to item specificity and prevent convergence difficulties when simultaneously estimating DECA and AtL models. Results indicated an overlap of 55% to 72% variance between the domains of the two instruments and suggested that the new AtL instrument is an easily administered alternative to the DECA for measuring children’s approaches to learning. This is one of the first studies that investigated DECA’s approaches to learning dimension and explored the measurement properties of an instrument purposely derived from a state’s early learning guidelines.

Learning about Severe Combined Immunodeficiency (SCID)

Science.gov (United States)

... immunodeficiency From The Journal of Allergy and Clinical Immunology Learning About Severe Combined Immunodeficiency (SCID) What is ... immunodeficiency From The Journal of Allergy and Clinical Immunology Get Email Updates Privacy Copyright Contact Accessibility Plug- ...

An Interactive Approach to Learning and Teaching in Visual Arts Education

Directory of Open Access Journals (Sweden)

Zlata Tomljenović

2015-09-01

Full Text Available The present research focuses on modernising the approach to learning and teaching the visual arts in teaching practice, as well as examining the performance of an interactive approach to learning and teaching in visual arts classes with the use of a combination of general and specific (visual arts teaching methods. The study uses quantitative analysis of data on the basis of results obtained from a pedagogical experiment. The subjects of the research were 285 second- and fourth-grade students from four primary schools in the city of Rijeka, Croatia. Paintings made by the students in the initial and final stage of the pedagogical experiment were evaluated. The research results confirmed the hypotheses about the positive effect of interactive approaches to learning and teaching on the following variables: (1 knowledge and understanding of visual arts terms, (2 abilities and skills in the use of art materials and techniques within the framework of planned painting tasks, and (3 creativity in solving visual arts problems. The research results can help shape an optimised model for the planning and performance of visual arts education, and provide guidelines for planning professional development and the further professional education of teachers, with the aim of establishing more efficient learning and teaching of the visual arts in primary school.

Learners for life : student approaches to learning

NARCIS (Netherlands)

Artelt, Cordula; Baumert, Jürgen; Julius-McElvany, Nele; Peschar, Jules

2003-01-01

What are students like as learners as they approach the end of compulsory education? The answer matters greatly, not only because those with stronger approaches to learning get better results at school but also because young adults able to set learning goals and manage their own learning are much

Cooperative learning as an approach to pedagogy.

Science.gov (United States)

Nolinske, T; Millis, B

1999-01-01

Lecture-based pedagogical approaches cannot adequately prepare students in professional and technical occupational therapy programs. Faculty members in other disciplines are turning to a well-known and well-researched teaching approach called cooperative learning, which is more carefully structured and defined than most other forms of small group learning. Cooperative learning includes several key principles: positive interdependence, individual responsibility, appropriate grouping, group maintenance, cooperative skills, and promotive (interaction) time. This article provides ideas for managing the classroom with cooperative learning activities and describes eight of them: Three-Step Interview, Roundtable, Think-Pair-Share, Structured Problem Solving, Send/Pass-a-Problem, Generic Question Stems, Double Entry Journal, and Dyadic Essay Confrontation. Each activity is applied to content embedded in professional and technical occupational therapy curricula. A cooperative learning approach to evaluating learning is also presented.

The High Scope Approach To Early Learning

OpenAIRE

French, Geraldine

2012-01-01

Learning Objectives: After studying this chapter the reader should be able to: • Describe the historical origins, the longitudinal research, and the theoretical underpinnings of the HighScope approach. • Identify the teaching strategies adopted by HighScope educators. • Appreciate the curriculum content. • Understand the HighScope approach to the assessment of children’s learning. • Consider some criticisms of the HighScope research and approach to early learning. This ...

Accounting Student's Learning Approaches And Impact On Academic Performance

OpenAIRE

Ismail, Suhaiza

2009-01-01

The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student's academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST) was used...

Machine learning approaches for the prediction of signal peptides and otherprotein sorting signals

DEFF Research Database (Denmark)

Nielsen, Henrik; Brunak, Søren; von Heijne, Gunnar

1999-01-01

Prediction of protein sorting signals from the sequence of amino acids has great importance in the field of proteomics today. Recently,the growth of protein databases, combined with machine learning approaches, such as neural networks and hidden Markov models, havemade it possible to achieve...

Relations between blended learning possibilities and teachers' approaches to blended learning

DEFF Research Database (Denmark)

Stenalt, Maria Hvid; Nielsen, Tobias Alsted; Bager-Elsborg, Anna

Higher Education has embraced blended learning as a way of enhancing quality in teaching and helping students to learn. This presentation addresses relations between blended learning possiblities presented to teachers in a teacher training project and teachers’ approaches to blended learning. We...... suggest that in order to identify the level of impact of integrating technologies in teaching and learning, we need to understand the factors influencing approaches to design of courses for blended contexts. Participants in the teacher training project come from the Department of Law at Aarhus University......: • Optain locally-embedded knowledge about blended learning • Develop opportunities for law students to receive (more) feedback • Comply with strategic aims The results so far suggest that teachers provide a disciplinary perspective on the key dimensions of blended learning, which influences...

Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.

Science.gov (United States)

Biggs, John B.

This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…

A program wide framework for evaluating data driven teaching and learning - earth analytics approaches, results and lessons learned

Science.gov (United States)

Wasser, L. A.; Gold, A. U.

2017-12-01

There is a deluge of earth systems data available to address cutting edge science problems yet specific skills are required to work with these data. The Earth analytics education program, a core component of Earth Lab at the University of Colorado - Boulder - is building a data intensive program that provides training in realms including 1) interdisciplinary communication and collaboration 2) earth science domain knowledge including geospatial science and remote sensing and 3) reproducible, open science workflows ("earth analytics"). The earth analytics program includes an undergraduate internship, undergraduate and graduate level courses and a professional certificate / degree program. All programs share the goals of preparing a STEM workforce for successful earth analytics driven careers. We are developing an program-wide evaluation framework that assesses the effectiveness of data intensive instruction combined with domain science learning to better understand and improve data-intensive teaching approaches using blends of online, in situ, asynchronous and synchronous learning. We are using targeted online search engine optimization (SEO) to increase visibility and in turn program reach. Finally our design targets longitudinal program impacts on participant career tracts over time.. Here we present results from evaluation of both an interdisciplinary undergrad / graduate level earth analytics course and and undergraduate internship. Early results suggest that a blended approach to learning and teaching that includes both synchronous in-person teaching and active classroom hands-on learning combined with asynchronous learning in the form of online materials lead to student success. Further we will present our model for longitudinal tracking of participant's career focus overtime to better understand long-term program impacts. We also demonstrate the impact of SEO optimization on online content reach and program visibility.

ENVIRONMENTAL LEARNING APPROACHES IN IMPROVING LEARNING OUTCOMES IN ACID-BASE SUBJECT

Directory of Open Access Journals (Sweden)

Rachmat Sahputra

2016-03-01

Full Text Available Learning in the understanding of acid-base chemistry in schools needs to be improved so research to determine differences in learning outcomes between students taught using environmental approaches and methods lectures in class XI SMA on acid-base subject needs to be done. In this study, using a quasi-experimental method using a data collection tool achievement test essay form. The test statistic results of the post-test learning has been obtained Asymp value. Sig (2-tailed 0,026 that showed the differences between students' learning outcomes with a control experimental class with effect size of 0.63 or much influence difference with the percentage 23.57% which indicated that the learning environment approach can improve learning outcomes of high school students.

Combining Unsupervised and Supervised Statistical Learning Methods for Currency Exchange Rate Forecasting

OpenAIRE

Vasiljeva, Polina

2016-01-01

In this thesis we revisit the challenging problem of forecasting currency exchange rate. We combine machine learning methods such as agglomerative hierarchical clustering and random forest to construct a two-step approach for predicting movements in currency exchange prices of the Swedish krona and the US dollar. We use a data set with over 200 predictors comprised of different financial and macro-economic time series and their transformations. We perform forecasting for one week ahead with d...

Evoked prior learning experience and approach to learning as predictors of academic achievement.

Science.gov (United States)

Trigwell, Keith; Ashwin, Paul; Millan, Elena S

2013-09-01

In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. To investigate how students' evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. A 77-item questionnaire was used to gather students' self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was

Machine learning an artificial intelligence approach

CERN Document Server

Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

1983-01-01

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

A Janus-Faced Approach to Learning. A Critical Discussion of Habermas' Pragmatic Approach

Science.gov (United States)

Italia, Salvatore

2017-01-01

A realist approach to learning is what I propose here. This is based on a non-epistemic dimension whose presence is a necessary assumption for a concept of learning of a life-world as complementary to learning within a life-world. I develop my approach in opposition to Jürgen Habermas' pragmatic approach, which seems to lack of something from a…

How are learning strategies reflected in the eyes? Combining results from self-reports and eye-tracking.

Science.gov (United States)

Catrysse, Leen; Gijbels, David; Donche, Vincent; De Maeyer, Sven; Lesterhuis, Marije; Van den Bossche, Piet

2018-03-01

Up until now, empirical studies in the Student Approaches to Learning field have mainly been focused on the use of self-report instruments, such as interviews and questionnaires, to uncover differences in students' general preferences towards learning strategies, but have focused less on the use of task-specific and online measures. This study aimed at extending current research on students' learning strategies by combining general and task-specific measurements of students' learning strategies using both offline and online measures. We want to clarify how students process learning contents and to what extent this is related to their self-report of learning strategies. Twenty students with different generic learning profiles (according to self-report questionnaires) read an expository text, while their eye movements were registered to answer questions on the content afterwards. Eye-tracking data were analysed with generalized linear mixed-effects models. The results indicate that students with an all-high profile, combining both deep and surface learning strategies, spend more time on rereading the text than students with an all-low profile, scoring low on both learning strategies. This study showed that we can use eye-tracking to distinguish very strategic students, characterized using cognitive processing and regulation strategies, from low strategic students, characterized by a lack of cognitive and regulation strategies. These students processed the expository text according to how they self-reported. © 2017 The British Psychological Society.

Dialogical, Enquiry and Participatory Approaches to Learning

DEFF Research Database (Denmark)

Hurford, Donna; Rowley, Chris

2018-01-01

Dialogical enquiry and participatory approaches This chapter is concerned with approaches to leading children into active participation and enquiry, through involvement in their own learning, both at Key Stages 1 and 2. The terms ‘enquiry’, ‘learning’ and ‘active participation’ are closely related....... We link these approaches to dialogue and discussion because these aspects of learning are often dealt with separately in the literature and yet clearly they are a form of enquiry and participatory learning. We draw upon a range of literature and research in order to justify these approaches and we...... Years (REPEY) Project (Siraj-Blatchford et al. 2002). This project found that the most effective strategies and techniques for promoting learning in the early years involved adult–child interactions in which the adult responds to the child’s understanding of a subject or activity, the child responds...

Heutagogy: An alternative practice based learning approach.

Science.gov (United States)

Bhoyrub, John; Hurley, John; Neilson, Gavin R; Ramsay, Mike; Smith, Margaret

2010-11-01

Education has explored and utilised multiple approaches in attempts to enhance the learning and teaching opportunities available to adult learners. Traditional pedagogy has been both directly and indirectly affected by andragogy and transformational learning, consequently widening our understandings and approaches toward view teaching and learning. Within the context of nurse education, a major challenge has been to effectively apply these educational approaches to the complex, unpredictable and challenging environment of practice based learning. While not offered as a panacea to such challenges, heutagogy is offered in this discussion paper as an emerging and potentially highly congruent educational framework to place around practice based learning. Being an emergent theory its known conceptual underpinnings and possible applications to nurse education need to be explored and theoretically applied. Through placing the adult learner at the foreground of grasping learning opportunities as they unpredictability emerge from a sometimes chaotic environment, heutagogy can be argued as offering the potential to minimise many of the well published difficulties of coordinating practice with faculty teaching and learning. Copyright © 2010 Elsevier Ltd. All rights reserved.

Supporting teachers integrating web 2.0 in a Problem Based Learning approach

DEFF Research Database (Denmark)

Buus, Lillian

2010-01-01

‘users/learners as producers’ [6]. Consequently, it makes good sense to connect Web 2.0 with a problem-based approach to learning. Therefore it’s interesting to look upon a learning design model supporting teachers at AAU in their pedagogical design combining these two. The Collaborative E-learning...... at Aalborg University (AAU). Problem-Based Learning (PBL) has gained a lot of interest since it was launched in established educational settings over 30 years ago in the medical programmes at McMaster University, Canada. Essentially it is a leaning methods based on the principle of using problems......, in particular, in the work of the German philosopher and sociologist Oskar Negt. Negt’s work gained a lot of interest in Denmark and the Problem oriented project based learning (POPBL) was developed under this inspiration. It was implemented as a framework for learning when Aalborg University was established...

E-Learning Systems, Environments and Approaches

OpenAIRE

Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.

2015-01-01

The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...

Investigative Primary Science: A Problem-Based Learning Approach

Science.gov (United States)

Etherington, Matthew B.

2011-01-01

This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…

ACCOUNTING STUDENT’S LEARNING APPROACHES AND IMPACT ON ACADEMIC PERFORMANCE

Directory of Open Access Journals (Sweden)

Suhaiza Ismail

2009-12-01

Full Text Available The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student’s academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST was used to assess the approaches to learning adopted by students whilst the students final examination result was considered in examining the performance of the students. The results indicate that majority of the accounting students, both male andfemale groups prefer to use the deep approach in studying Business Finance. The findings also reveal that there were significant relationships between learning approaches and academic performance with positive direction appears for deep and strategic approaches whilst negative relationship reveals for surface approach.

ACCOUNTING STUDENT’S LEARNING APPROACHES AND IMPACT ON ACADEMIC PERFORMANCE

OpenAIRE

Suhaiza Ismail

2009-01-01

The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student’s academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST) was used...

Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

Directory of Open Access Journals (Sweden)

Gatis Špats

2016-07-01

Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

Meta-Learning Approach for Automatic Parameter Tuning: A Case Study with Educational Datasets

Science.gov (United States)

Molina, M. M.; Luna, J. M.; Romero, C.; Ventura, S.

2012-01-01

This paper proposes to the use of a meta-learning approach for automatic parameter tuning of a well-known decision tree algorithm by using past information about algorithm executions. Fourteen educational datasets were analysed using various combinations of parameter values to examine the effects of the parameter values on accuracy classification.…

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.

A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

Science.gov (United States)

Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

2018-01-01

This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

Economic Gardening through Entrepreneurship Education: A Service-Learning Approach

Science.gov (United States)

Desplaces, David E.; Wergeles, Fred; McGuigan, Patrick

2009-01-01

This article outlines the implementation of a service-learning approach in an entrepreneurship programme using an "economic gardening" strategy. Economic Gardening through Service-Learning (EGS-L) is an approach to economic development that helps local businesses and students grow through a facilitated learning process. Learning is made possible…

Students' Perception of a Flipped Classroom Approach to Facilitating Online Project-Based Learning in Marketing Research Courses

Science.gov (United States)

Shih, Wen-Ling; Tsai, Chun-Yen

2017-01-01

This study investigated students' perception of a flipped classroom approach to facilitating online project-based learning (FC-OPBL) in a marketing research course at a technical university. This combined strategy was aimed at improving teaching quality and learning efficiency. Sixty-seven students taking a marketing research course were surveyed.…

Learning Approaches - Final Report Sub-Project 4

DEFF Research Database (Denmark)

Dirckinck-Holmfeld, Lone; Rodríguez Illera, José Luis; Escofet, Anna

2007-01-01

The overall aim of Subproject 4 is to apply learning approaches that are appropriate and applicable using ICT. The task is made up of two components 4.1 dealing with learning approaches (see deliverable 4.1), and component 4.2 application of ICT (see deliverable 4.2, deliverable 4.3 & deliverable...

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

Science.gov (United States)

Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I

2016-01-01

Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.

E-Learning Approach in Teacher Training

Science.gov (United States)

Yucel, Seda A.

2006-01-01

There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational…

Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment.

Science.gov (United States)

Cheung, Y M; Leung, W M; Xu, L

1997-01-01

We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.

Designing Science Learning with Game-Based Approaches

Science.gov (United States)

Liu, Min; Rosenblum, Jason A.; Horton, Lucas; Kang, Jina

2014-01-01

Given the growing popularity of digital games as a form of entertainment, educators are interested in exploring using digital games as a tool to facilitate learning. In this study, we examine game-based learning by describing a learning environment that combines game elements, play, and authenticity in the real world for the purpose of engaging…

Statistical and machine learning approaches for network analysis

CERN Document Server

Dehmer, Matthias

2012-01-01

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

Understanding Fatty Acid Metabolism through an Active Learning Approach

Science.gov (United States)

Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.

2010-01-01

A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less…

Development of Scientific Approach Based on Discovery Learning Module

Science.gov (United States)

Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

2018-04-01

Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on

Action-Emotion Style, Learning Approach and Coping Strategies, in Undergraduate University Students

Directory of Open Access Journals (Sweden)

Jesús de la Fuente

Full Text Available Action-Emotion Style (AES is an affective-motivational construct that describes the achievement motivation that is characteristic of students in their interaction with stressful situations. Using elements from the Type-A Behavior Pattern (TABP, characteristics of competitiveness and overwork occur in different combinations with emotions of impatience and hostility, leading to a classification containing five categories of action-emotion style (Type B, Impatient-hostile type, Medium type, Competitive-Overworking type and Type A. The objective of the present research is to establish how characteristics of action-emotion style relate to learning approach (deep and surface approaches and to coping strategies (emotion-focused and problem-focused. The sample was composed of 225 students from the Psychology degree program. Pearson correlation analyses, ANOVAs and MANOVAs were used. Results showed that competitiveness-overwork characteristics have a significant positive association with the deep approach and with problem-focused strategies, while impatience-hostility is thus related to surface approach and emotion-focused strategies. The level of action-emotion style had a significant main effect. The results verified our hypotheses with reference to the relationships between action-emotion style, learning approaches and coping strategies.

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

Science.gov (United States)

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

E-Learning Approach in Teacher Training

OpenAIRE

YUCEL, A. Seda

2015-01-01

There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational system on platform with Internet, Intranet or computer access. The concept of e-learning has two main subtitles as synchronized (where a group of stu...

Machine Learning Approaches for Clinical Psychology and Psychiatry.

Science.gov (United States)

Dwyer, Dominic B; Falkai, Peter; Koutsouleris, Nikolaos

2018-05-07

Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.

Effects of Elicited Reflections combined with Tutor or Peer Feedback on Self-Regulated Learning and Learning Outcomes

NARCIS (Netherlands)

Van den Boom, Gerard; Paas, Fred; Van Merriënboer, Jeroen

2009-01-01

Van den Boom, G., Paas, F., & Van Merriënboer, J. J. G. (2007). Effects of elicited reflections combined with tutor or peer feedback on self-regulated learning and learning outcomes. Learning and Instruction, 17, 532-548.

A Learning Object Approach To Evidence based learning

OpenAIRE

Zabin Visram; Bruce Elson; Patricia Reynolds

2005-01-01

This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

Science.gov (United States)

Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

2016-02-01

This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.

Project Management Approaches for Online Learning Design

Science.gov (United States)

Eby, Gulsun; Yuzer, T. Volkan

2013-01-01

Developments in online learning and its design are areas that continue to grow in order to enhance students' learning environments and experiences. However, in the implementation of new technologies, the importance of properly and fairly overseeing these courses is often undervalued. "Project Management Approaches for Online Learning Design"…

Machine learning approaches in medical image analysis

DEFF Research Database (Denmark)

de Bruijne, Marleen

2016-01-01

Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

International Nuclear Information System (INIS)

Wang, Jianzhou; Hu, Jianming

2015-01-01

With the increasing importance of wind power as a component of power systems, the problems induced by the stochastic and intermittent nature of wind speed have compelled system operators and researchers to search for more reliable techniques to forecast wind speed. This paper proposes a combination model for probabilistic short-term wind speed forecasting. In this proposed hybrid approach, EWT (Empirical Wavelet Transform) is employed to extract meaningful information from a wind speed series by designing an appropriate wavelet filter bank. The GPR (Gaussian Process Regression) model is utilized to combine independent forecasts generated by various forecasting engines (ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM)) in a nonlinear way rather than the commonly used linear way. The proposed approach provides more probabilistic information for wind speed predictions besides improving the forecasting accuracy for single-value predictions. The effectiveness of the proposed approach is demonstrated with wind speed data from two wind farms in China. The results indicate that the individual forecasting engines do not consistently forecast short-term wind speed for the two sites, and the proposed combination method can generate a more reliable and accurate forecast. - Highlights: • The proposed approach can make probabilistic modeling for wind speed series. • The proposed approach adapts to the time-varying characteristic of the wind speed. • The hybrid approach can extract the meaningful components from the wind speed series. • The proposed method can generate adaptive, reliable and more accurate forecasting results. • The proposed model combines four independent forecasting engines in a nonlinear way.

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

Science.gov (United States)

Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna

2015-01-27

To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

Scaffolding Teachers Integrate Social Media Into a Problem‑Based Learning Approach?

DEFF Research Database (Denmark)

Buus, Lillian

2012-01-01

to develop design specifications and/or early prototypes within a few hours of starting work. In order to achieve one of the objectives of my PhD, I aim to further developing and elaborate on this method, which hopefully will lead to a pedagogical design method scaffolding teachers in their learning designs......At Aalborg University (AAU) we are known to work with problem‑based learning (PBL) in a particular way designated “The Aalborg PBL model”. In PBL the focus is on participant control, knowledge sharing, collaboration among participants, which makes it interesting to consider the integration...... to learning design when combining the PBL approach with social media or web 2.0 activities or/and technologies. With regard to the discussions about PBL, three important characteristics of PBL can be extracted; the problem, the work process, and the solution, which can be used to distinguish between various...

Machine Learning Approaches in Cardiovascular Imaging.

Science.gov (United States)

Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

2017-10-01

Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

Teaching Professionals Environmental Management: Combining Educational Learning and Practice Learning

DEFF Research Database (Denmark)

Jørgensen, Michael Søgaard; Jørgensen, Ulrik

2003-01-01

semesters. The target groups are professional environmental managers working in businesses including consultants, governmental institutions and organizations. To get access to the education the students must have a technical/nature science competence at master level or bachelor level combined with relevant...... job experience. Generally the participants have had 5-15 years of practical experience and many have been or are in the position of an internal or external job change towards new tasks that require new knowledge, methodologies or management skills. The education of "Masters of Environmental Management...... they can use in complex situations on the job is not simply a question of combining different university disciplines in the right blend and topping it with some experience. It involves combining science-based knowledge into thematic structures in carefully organized learning processes. The education...

Biosafety capacity building: experiences and challenges from a distance learning approach.

Science.gov (United States)

Pertry, Ine; Sabbadini, Silvia; Goormachtig, Sofie; Lokko, Yvonne; Gheysen, Godelieve; Burssens, Sylvia; Mezzetti, Bruno

2014-01-25

Biotechnology is revolutionizing industrial and agricultural practice as the number of commercial biotechnology products is increasing each year. Simultaneously, several regulatory approaches are put into place to allow technological advancement while preserving public health and the environment. Developing and/or emerging countries often face major barriers to access biotechnologies and biotechnology derived products as they frequently lack the institutional capacities and professional competence in exercising regulatory oversight. To address this need, intensive biosafety capacity building is required. Different training approaches can be used to train individuals in biosafety ranging from long-term leading to a postgraduate certificate or a Masters degree, to short term courses. In this paper, we discuss the applicability of a different approach to biosafety capacity building based on a distance e-learning system, the UNIDO e-Biosafety program that has been annually organized at the Marche Polytechnic University (MPU) in Italy and Ghent University (UGent) in Belgium since 2006. Even though there are some challenges, we can conclude based on our experience that distance learning in combination with on-campus tuition is amendable for biosafety capacity building. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Learning approaches of Indonesian EFL Gen Z students in a Flipped Learning context

Directory of Open Access Journals (Sweden)

Made Hery Santosa

2017-09-01

Full Text Available The 21st-century learning has eventually transformed today’s classroom. With more digital natives in the class, both educators and students face a changing classroom that should accommodate different learning paces, styles and needs. This study aimed at helping students in becoming English as Foreign Language (EFL competent in-service teachers. Using Flipped Learning, the study utilizes four FLIP pillars into EFL learning, namely Flexible environment, Learning culture, Intentional content, Professional educators. The study employed three instruments, namely survey, tests, and interview. The result of tests showed a promising students’ progress from low to high achievement. The survey showed that students tended to perform deep approaches to learning while findings from the interview provided more interesting phenomena underlying students’ motives in their learning approaches, involving dynamic power distance relationship between lecturer and students. Heavier task loads and learning model familiarity have been highlighted. Effective socialization of the model using technology and sustainability of use of the model are suggested.

Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

Science.gov (United States)

Tseng, Min-Chen; Chen, Chia-Cheng

2017-06-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.

E-Learning 2.0: Learning Redefined

OpenAIRE

Kumar, Rupesh

2009-01-01

The conventional e-learning approach emphasizes a learning system more than a learning environment. While traditional e-learning systems continue to be significant, there is a new set of services emerging, embracing the philosophy of Web 2.0. Known as e-learning 2.0, it aims to create a personalized learning environment. E-learning 2.0 combines the use of discrete but complementary tools and web services to support the creation of ad-hoc learning communities. This paper discusses the influenc...

Component-Based Approach in Learning Management System Development

Science.gov (United States)

Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

2013-01-01

The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

(CBTP) on knowledge, problem-solving and learning approach

African Journals Online (AJOL)

In the first instance attention is paid to the effect of a computer-based teaching programme (CBTP) on the knowledge, problem-solving skills and learning approach of student ... In the practice group (oncology wards) no statistically significant change in the learning approach of respondents was found after using the CBTP.

Integrated approaches to perceptual learning.

Science.gov (United States)

Jacobs, Robert A

2010-04-01

New technologies and new ways of thinking have recently led to rapid expansions in the study of perceptual learning. We describe three themes shared by many of the nine articles included in this topic on Integrated Approaches to Perceptual Learning. First, perceptual learning cannot be studied on its own because it is closely linked to other aspects of cognition, such as attention, working memory, decision making, and conceptual knowledge. Second, perceptual learning is sensitive to both the stimulus properties of the environment in which an observer exists and to the properties of the tasks that the observer needs to perform. Moreover, the environmental and task properties can be characterized through their statistical regularities. Finally, the study of perceptual learning has important implications for society, including implications for science education and medical rehabilitation. Contributed articles relevant to each theme are summarized. Copyright © 2010 Cognitive Science Society, Inc.

Group investigation with scientific approach in mathematics learning

Science.gov (United States)

Indarti, D.; Mardiyana; Pramudya, I.

2018-03-01

The aim of this research is to find out the effect of learning model toward mathematics achievement. This research is quasi-experimental research. The population of research is all VII grade students of Karanganyar regency in the academic year of 2016/2017. The sample of this research was taken using stratified cluster random sampling technique. Data collection was done based on mathematics achievement test. The data analysis technique used one-way ANOVA following the normality test with liliefors method and homogeneity test with Bartlett method. The results of this research is the mathematics learning using Group Investigation learning model with scientific approach produces the better mathematics learning achievement than learning with conventional model on material of quadrilateral. Group Investigation learning model with scientific approach can be used by the teachers in mathematics learning, especially in the material of quadrilateral, which is can improve the mathematics achievement.

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

Science.gov (United States)

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

Numbered head together with scientific approach in geometry learning

Science.gov (United States)

Indarti, Dwi; Mardiyana; Pramudya, Ikrar

2017-12-01

The aim of this research was to find out the influence of learning model implementation toward student’s achievement in mathematics. This research was using quasi-experimental research. The population of the research was all of 7th grade students in Karanganyar. Sample was taken using stratified cluster random sampling technique. The data collection has been conducted based on students’ mathematics achievement test. The results from the data analysis showed that the learning mathematics by using Numbered Head Together (NHT) learning model with scientific approach improved student’s achievement in mathematics rather than direct learning model particularly in learning object of quadrilateral. Implementation of NHT learning model with scientific approach could be used by the teachers in teaching and learning, particularly in learning object of quadrilateral.

Learning from tutorials: a qualitative study of approaches to learning and perceptions of tutorial interaction

DEFF Research Database (Denmark)

Herrmann, Kim Jesper

2014-01-01

This study examines differences in university students’ approaches to learning when attending tutorials as well as variation in students’ perceptions of tutorials as an educational arena. In-depth qualitative analysis of semi-structured interviews with undergraduates showed how surface and deep...... approaches to learning were revealed in the students’ note-taking, listening, and engaging in dialogue. It was also shown how variation in the students’ approaches to learning were coherent with variation in the students’ perceptions of the tutors’ pedagogical role, the value of peer interaction......, and the overall purpose of tutorials. The results are discussed regarding the paradox that students relying on surface approaches to learning seemingly are the ones least likely to respond to tutorials in the way they were intended....

The relationship between learning preferences (styles and approaches) and learning outcomes among pre-clinical undergraduate medical students.

Science.gov (United States)

Liew, Siaw-Cheok; Sidhu, Jagmohni; Barua, Ankur

2015-03-11

Learning styles and approaches of individual undergraduate medical students vary considerably and as a consequence, their learning needs also differ from one student to another. This study was conducted to identify different learning styles and approaches of pre-clinical, undergraduate medical students and also to determine the relationships of learning preferences with performances in the summative examinations. A cross-sectional study was conducted among randomly selected 419 pre-clinical, undergraduate medical students of the International Medical University (IMU) in Kuala Lumpur. The number of students from Year 2 was 217 while that from Year 3 was 202. The Visual, Auditory, Read/Write, Kinesthetic (VARK) and the Approaches and Study Skills Inventory for Students (ASSIST) questionnaires were used for data collection. This study revealed that 343 students (81.9%) had unimodal learning style, while the remaining 76 (18.1%) used a multimodal learning style. Among the unimodal learners, a majority (30.1%) were of Kinesthetic (K) type. Among the middle and high achievers in summative examinations, a majority had unimodal (Kinaesthetic) learning style (30.5%) and were also strategic/deep learners (79.4%). However, the learning styles and approaches did not contribute significantly towards the learning outcomes in summative examinations. A majority of the students in this study had Unimodal (Kinesthetic) learning style. The learning preferences (styles and approaches) did not contribute significantly to the learning outcomes. Future work to re-assess the viability of these learning preferences (styles and approaches) after the incorporation of teaching-learning instructions tailored specifically to the students will be beneficial to help medical teachers in facilitating students to become more capable learners.

The Implementation of Discovery Learning Model with Scientific Learning Approach to Improve Students’ Critical Thinking in Learning History

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Edi Nurcahyo

2018-03-01

Full Text Available Historical learning has not reached optimal in the learning process. It is caused by the history teachers’ learning model has not used the innovative learning models. Furthermore, it supported by the perception of students to the history subject because it does not become final exam (UN subject so it makes less improvement and builds less critical thinking in students’ daily learning. This is due to the lack of awareness of historical events and the availability of history books for students and teachers in the library are still lacking. Discovery learning with scientific approach encourages students to solve problems actively and able to improve students' critical thinking skills with scientific approach so student can build scientific thinking include observing, asking, reasoning, trying, and networking   Keywords: discovery learning, scientific, critical thinking

Design of Learning Objects for Concept Learning: Effects of Multimedia Learning Principles and an Instructional Approach

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Chiu, Thomas K. F.; Churchill, Daniel

2016-01-01

Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…

Exam Success at Undergraduate and Graduate-Entry Medical Schools: Is Learning Style or Learning Approach More Important? A Critical Review Exploring Links Between Academic Success, Learning Styles, and Learning Approaches Among School-Leaver Entry ("Traditional") and Graduate-Entry ("Nontraditional") Medical Students.

Science.gov (United States)

Feeley, Anne-Marie; Biggerstaff, Deborah L

2015-01-01

PHENOMENON: The literature on learning styles over many years has been replete with debate and disagreement. Researchers have yet to elucidate exactly which underlying constructs are measured by the many learning styles questionnaires available. Some academics question whether learning styles exist at all. When it comes to establishing the value of learning styles for medical students, a further issue emerges. The demographics of medical students in the United Kingdom have changed in recent years, so past studies may not be applicable to students today. We wanted to answer a very simple, practical question: what can the literature on learning styles tell us that we can use to help today's medical students succeed academically at medical school? We conducted a literature review to synthesise the available evidence on how two different aspects of learning-the way in which students like to receive information in a learning environment (termed learning "styles") and the motivations that drive their learning (termed learning "approaches")-can impact on medical students' academic achievement. Our review confirms that although learning "styles" do not correlate with exam performance, learning "approaches" do: those with "strategic" and "deep" approaches to learning (i.e., motivated to do well and motivated to learn deeply respectively) perform consistently better in medical school examinations. Changes in medical school entrant demographics in the past decade have not altered these correlations. Optimistically, our review reveals that students' learning approaches can change and more adaptive approaches may be learned. Insights: For educators wishing to help medical students succeed academically, current evidence demonstrates that helping students develop their own positive learning approach using "growth mind-set" is a more effective (and more feasible) than attempting to alter students' learning styles. This conclusion holds true for both "traditional" and graduate

Multi-dimensional technology-enabled social learning approach

DEFF Research Database (Denmark)

Petreski, Hristijan; Tsekeridou, Sofia; Prasad, Neeli R.

2013-01-01

’t respond to this systemic and structural changes and/or challenges and retains its status quo than it is jeopardizing its own existence or the existence of the education, as we know it. This paper aims to precede one step further by proposing a multi-dimensional approach for technology-enabled social...... in learning while socializing within their learning communities. However, their “educational” usage is still limited to facilitation of online learning communities and to collaborative authoring of learning material complementary to existing formal (e-) learning services. If the educational system doesn...

Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches

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Wang, Victor C. X.

2010-01-01

As adult learners and educators pioneer the use of technology in the new century, attention has been focused on developing strategic approaches to effectively integrate adult learning and technology in different learning environments. "Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches" provides innovative…

An ensemble deep learning based approach for red lesion detection in fundus images.

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Orlando, José Ignacio; Prokofyeva, Elena; Del Fresno, Mariana; Blaschko, Matthew B

2018-01-01

Diabetic retinopathy (DR) is one of the leading causes of preventable blindness in the world. Its earliest sign are red lesions, a general term that groups both microaneurysms (MAs) and hemorrhages (HEs). In daily clinical practice, these lesions are manually detected by physicians using fundus photographs. However, this task is tedious and time consuming, and requires an intensive effort due to the small size of the lesions and their lack of contrast. Computer-assisted diagnosis of DR based on red lesion detection is being actively explored due to its improvement effects both in clinicians consistency and accuracy. Moreover, it provides comprehensive feedback that is easy to assess by the physicians. Several methods for detecting red lesions have been proposed in the literature, most of them based on characterizing lesion candidates using hand crafted features, and classifying them into true or false positive detections. Deep learning based approaches, by contrast, are scarce in this domain due to the high expense of annotating the lesions manually. In this paper we propose a novel method for red lesion detection based on combining both deep learned and domain knowledge. Features learned by a convolutional neural network (CNN) are augmented by incorporating hand crafted features. Such ensemble vector of descriptors is used afterwards to identify true lesion candidates using a Random Forest classifier. We empirically observed that combining both sources of information significantly improve results with respect to using each approach separately. Furthermore, our method reported the highest performance on a per-lesion basis on DIARETDB1 and e-ophtha, and for screening and need for referral on MESSIDOR compared to a second human expert. Results highlight the fact that integrating manually engineered approaches with deep learned features is relevant to improve results when the networks are trained from lesion-level annotated data. An open source implementation of our

Implementation of Reseptive Esteemy Approach Model in Learning Reading Literature

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Titin Nurhayatin

2017-03-01

Full Text Available Research on the implementation of aesthetic model of receptive aesthetic approach in learning to read the literature on the background of the low quality of results and learning process of Indonesian language, especially the study of literature. Students as prospective teachers of Indonesian language are expected to have the ability to speak, have literature, and their learning in a balanced manner in accordance with the curriculum demands. This study examines the effectiveness, quality, acceptability, and sustainability of the aesthetic approach of receptions in improving students' literary skills. Based on these problems, this study is expected to produce a learning model that contributes high in improving the quality of results and the process of learning literature. This research was conducted on the students of Language Education Program, Indonesian Literature and Regional FKIP Pasundan University. The research method used is experiment with randomized type pretest-posttest control group design. Based on preliminary and final test data obtained in the experimental class the average preliminary test was 55.86 and the average final test was 76.75. From the preliminary test data in the control class the average score was 55.07 and the average final test was 68.76. These data suggest that there is a greater increase in grades in the experimental class using the aesthetic approach of the reception compared with the increase in values in the control class using a conventional approach. The results show that the aesthetic approach of receptions is more effective than the conventional approach in literary reading. Based on observations, acceptance, and views of sustainability, the aesthetic approach of receptions in literary learning is expected to be an alternative and solution in overcoming the problems of literary learning and improving the quality of Indonesian learning outcomes and learning process.

Problem Posing with Realistic Mathematics Education Approach in Geometry Learning

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Mahendra, R.; Slamet, I.; Budiyono

2017-09-01

One of the difficulties of students in the learning of geometry is on the subject of plane that requires students to understand the abstract matter. The aim of this research is to determine the effect of Problem Posing learning model with Realistic Mathematics Education Approach in geometry learning. This quasi experimental research was conducted in one of the junior high schools in Karanganyar, Indonesia. The sample was taken using stratified cluster random sampling technique. The results of this research indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students’ conceptual understanding significantly in geometry learning especially on plane topics. It is because students on the application of Problem Posing with Realistic Mathematics Education Approach are become to be active in constructing their knowledge, proposing, and problem solving in realistic, so it easier for students to understand concepts and solve the problems. Therefore, the model of Problem Posing learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on geometry material. Furthermore, the impact can improve student achievement.

Looking at Learning Approaches from the Angle of Student Profiles

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Kyndt, Eva; Dochy, Filip; Struyven, Katrien; Cascallar, Eduardo

2012-01-01

This study starts with investigating the relation of perceived workload, motivation for learning and working memory capacity (WMC) with students' approaches to learning. Secondly, this study investigates if differences exist between different student profiles concerning their approach to the learning and the influence of workloads thereon. Results…

The Flipped MOOC: Using Gamification and Learning Analytics in MOOC Design—A Conceptual Approach

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Roland Klemke

2018-02-01

Full Text Available Recently, research has highlighted the potential of Massive Open Online Courses (MOOCs for education, as well as their drawbacks, which are well known. Several studies state that the main limitations of the MOOCs are low completion and high dropout rates of participants. However, MOOCs suffer also from the lack of participant engagement, personalization, and despite the fact that several formats and types of MOOCs are reported in the literature, the majority of them contain a considerable amount of content that is mainly presented in a video format. This is in contrast to the results reported in other educational settings, where engagement and active participation are identified as success factors. We present the results of a study that involved educational experts and learning scientists giving new and interesting insights towards the conceptualization of a new design approach, the flipped MOOC, applying the flipped classroom approach to the MOOCs’ design and making use of gamification and learning analytics. We found important indications, applicable to the concept of a flipped MOOC, which entails turning MOOCs from mainly content-oriented delivery machines into personalized, interactive, and engaging learning environments. Our findings support the idea that MOOCs can be enriched by the orchestration of a flipped classroom approach in combination with the support of gamification and learning analytics.

Investigating the Efficiency of Scenario Based Learning and Reflective Learning Approaches in Teacher Education

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Hursen, Cigdem; Fasli, Funda Gezer

2017-01-01

The main purpose of this research is to investigate the efficiency of scenario based learning and reflective learning approaches in teacher education. The impact of applications of scenario based learning and reflective learning on prospective teachers' academic achievement and views regarding application and professional self-competence…

The Effect of Known-and-Unknown Word Combinations on Intentional Vocabulary Learning

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Kasahara, Kiwamu

2011-01-01

The purpose of this study is to examine whether learning a known-and-unknown word combination is superior in terms of retention and retrieval of meaning to learning a single unknown word. The term "combination" in this study means a two-word collocation of a familiar word and a word that is new to the participants. Following the results of…

E-learning and blended learning in textile engineering education: a closed feedback loop approach

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Charitopoulos, A.; Vassiliadis, S.; Rangoussi, M.; Koulouriotis, D.

2017-10-01

E-learning has gained a significant role in typical education and in professional training, thanks to the flexibility it offers to the time and location parameters of the education event framework. Purely e-learning scenarios are mostly limited either to Open University-type higher education institutions or to graduate level or professional degrees; blended learning scenarios are progressively becoming popular thanks to their balanced approach. The aim of the present work is to propose approaches that exploit the e-learning and the blended-learning scenarios for Textile Engineering education programmes, especially for multi-institutional ones. The “E-Team” European MSc degree programme organized by AUTEX is used as a case study. The proposed solution is based on (i) a free and open-source e-learning platform (moodle) and (ii) blended learning educational scenarios. Educational challenges addressed include student engagement, student error / failure handling, as well as collaborative learning promotion and support.

Science of learning is learning of science: why we need a dialectical approach to science education research

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Roth, Wolff-Michael

2012-06-01

Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.

Learning environment, approaches to learning and learning preferences: medical students versus general education students.

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Ullah, Raza

2016-05-01

The main objective of the study was to see whether medical students use more desirable approaches to studying than general education students. Survey method was used to collect data from both the medical students and the general education students. The survey of the medical students was carried out between January and March, 2012. The survey was administered to all the medical students present in lecture halls on day of data collection, while general education students were randomly selected from four subject areas at two universities. In total, 976 medical students and 912 general students participated in the study. Of the general students, 494(54%) were boys and 418(46%)were girls with an overall mean age of 20.53±1.77 years (range: 17-27 years). The medical students' perceptions of their learning environment and their learning preferences were broadly similar to that of general education students with the exception of workload. The medical students perceived the workload to be less appropriate (Mean = 2.06±0.72) than the students in general education (Mean = 2.84±0.90). The medical students were more likely to use the deep approach to studying (Mean = 3.66±0.59) than the students in general education (Mean = 3.16±0.91). The students in general education were slightly more likely to use the organized studying (Mean = 3.44±0.90) than the medical students (Mean =3.23±0.90). Both medical students and the students in general education tended to use the surface approaches along with other approaches to studying. There was not a great difference between the medical students and the students pursuing general education with regard to perceptions of the learning environment and approaches to learning.

Towards a Standards-Based Approach to E-Learning Personalization Using Reusable Learning Objects.

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Conlan, Owen; Dagger, Declan; Wade, Vincent

E-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners' cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of…

Content-Based Instruction Approach In Instructional Multimedia For English Learning

OpenAIRE

Farani, Rizki

2016-01-01

Content-based Instruction (CBI) is an approach in English learning that integrates certain topic and English learning objectives. This approach focuses on using English competencies as a “bridge” to comprehend certain topic or theme in English. Nowadays, this approach can be used in instructional multimedia to support English learning by using computer. Instructional multimedia with computer system refers to the sequential or simultaneous use of variety of media formats in a given presentatio...

Predicting DPP-IV inhibitors with machine learning approaches

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Cai, Jie; Li, Chanjuan; Liu, Zhihong; Du, Jiewen; Ye, Jiming; Gu, Qiong; Xu, Jun

2017-04-01

Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema, and hypoglycemia. However, the marketed DPP-IV inhibitors have adverse effects such as nasopharyngitis, headache, nausea, hypersensitivity, skin reactions and pancreatitis. Therefore, it is still expected for novel DPP-IV inhibitors with minimal adverse effects. The scaffolds of existing DPP-IV inhibitors are structurally diversified. This makes it difficult to build virtual screening models based upon the known DPP-IV inhibitor libraries using conventional QSAR approaches. In this paper, we report a new strategy to predict DPP-IV inhibitors with machine learning approaches involving naïve Bayesian (NB) and recursive partitioning (RP) methods. We built 247 machine learning models based on 1307 known DPP-IV inhibitors with optimized molecular properties and topological fingerprints as descriptors. The overall predictive accuracies of the optimized models were greater than 80%. An external test set, composed of 65 recently reported compounds, was employed to validate the optimized models. The results demonstrated that both NB and RP models have a good predictive ability based on different combinations of descriptors. Twenty "good" and twenty "bad" structural fragments for DPP-IV inhibitors can also be derived from these models for inspiring the new DPP-IV inhibitor scaffold design.

Hong Kong Students' Approaches to Learning: Cross-Cultural Comparisons

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Dasari, Bhoomiah

2009-01-01

Anecdotal evidence abounds in Hong Kong to the effect that students entering tertiary education are predisposed to a "rote" learning approach. With the internalisation of higher education in many countries, there is still insufficient understanding of how Chinese students approach their learning. Except few studies were conducted…

Comparison of student's learning achievement through realistic mathematics education (RME) approach and problem solving approach on grade VII

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Ilyas, Muhammad; Salwah

2017-02-01

The type of this research was experiment. The purpose of this study was to determine the difference and the quality of student's learning achievement between students who obtained learning through Realistic Mathematics Education (RME) approach and students who obtained learning through problem solving approach. This study was a quasi-experimental research with non-equivalent experiment group design. The population of this study was all students of grade VII in one of junior high school in Palopo, in the second semester of academic year 2015/2016. Two classes were selected purposively as sample of research that was: year VII-5 as many as 28 students were selected as experiment group I and VII-6 as many as 23 students were selected as experiment group II. Treatment that used in the experiment group I was learning by RME Approach, whereas in the experiment group II by problem solving approach. Technique of data collection in this study gave pretest and posttest to students. The analysis used in this research was an analysis of descriptive statistics and analysis of inferential statistics using t-test. Based on the analysis of descriptive statistics, it can be concluded that the average score of students' mathematics learning after taught using problem solving approach was similar to the average results of students' mathematics learning after taught using realistic mathematics education (RME) approach, which are both at the high category. In addition, It can also be concluded that; (1) there was no difference in the results of students' mathematics learning taught using realistic mathematics education (RME) approach and students who taught using problem solving approach, (2) quality of learning achievement of students who received RME approach and problem solving approach learning was same, which was at the high category.

Combining Formal, Non-Formal and Informal Learning for Workforce Skill Development

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Misko, Josie

2008-01-01

This literature review, undertaken for Australian Industry Group, shows how multiple variations and combinations of formal, informal and non-formal learning, accompanied by various government incentives and organisational initiatives (including job redesign, cross-skilling, multi-skilling, diversified career pathways, action learning projects,…

Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

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Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

2017-01-01

This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…

Use of machine learning approaches for novel drug discovery.

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Lima, Angélica Nakagawa; Philot, Eric Allison; Trossini, Gustavo Henrique Goulart; Scott, Luis Paulo Barbour; Maltarollo, Vinícius Gonçalves; Honorio, Kathia Maria

2016-01-01

The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds. This article presents an overview on some applications of ML techniques in drug design. These techniques can be employed in ligand-based drug design (LBDD) and structure-based drug design (SBDD) studies, such as similarity searches, construction of classification and/or prediction models of biological activity, prediction of secondary structures and binding sites docking and virtual screening. Successful cases have been reported in the literature, demonstrating the efficiency of ML techniques combined with traditional approaches to study medicinal chemistry problems. Some ML techniques used in drug design are: support vector machine, random forest, decision trees and artificial neural networks. Currently, an important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.

The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

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Mekarina, M.; Ningsih, Y. P.

2017-09-01

This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.

Learning from doing: the case for combining normalisation process theory and participatory learning and action research methodology for primary healthcare implementation research.

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de Brún, Tomas; O'Reilly-de Brún, Mary; O'Donnell, Catherine A; MacFarlane, Anne

2016-08-03

The implementation of research findings is not a straightforward matter. There are substantive and recognised gaps in the process of translating research findings into practice and policy. In order to overcome some of these translational difficulties, a number of strategies have been proposed for researchers. These include greater use of theoretical approaches in research focused on implementation, and use of a wider range of research methods appropriate to policy questions and the wider social context in which they are placed. However, questions remain about how to combine theory and method in implementation research. In this paper, we respond to these proposals. Focussing on a contemporary social theory, Normalisation Process Theory, and a participatory research methodology, Participatory Learning and Action, we discuss the potential of their combined use for implementation research. We note ways in which Normalisation Process Theory and Participatory Learning and Action are congruent and may therefore be used as heuristic devices to explore, better understand and support implementation. We also provide examples of their use in our own research programme about community involvement in primary healthcare. Normalisation Process Theory alone has, to date, offered useful explanations for the success or otherwise of implementation projects post-implementation. We argue that Normalisation Process Theory can also be used to prospectively support implementation journeys. Furthermore, Normalisation Process Theory and Participatory Learning and Action can be used together so that interventions to support implementation work are devised and enacted with the expertise of key stakeholders. We propose that the specific combination of this theory and methodology possesses the potential, because of their combined heuristic force, to offer a more effective means of supporting implementation projects than either one might do on its own, and of providing deeper understandings of

Automated Extraction of Cranial Landmarks from Computed Tomography Data using a Combined Method of Knowledge and Pattern Based Approaches

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Roshan N. RAJAPAKSE

2016-03-01

Full Text Available Accurate identification of anatomical structures from medical imaging data is a significant and critical function in the medical domain. Past studies in this context have mainly utilized two main approaches, the knowledge and learning methodologies based methods. Further, most of previous reported studies have focused on identification of landmarks from lateral X-ray Computed Tomography (CT data, particularly in the field of orthodontics. However, this study focused on extracting cranial landmarks from large sets of cross sectional CT slices using a combined method of the two aforementioned approaches. The proposed method of this study is centered mainly on template data sets, which were created using the actual contour patterns extracted from CT cases for each of the landmarks in consideration. Firstly, these templates were used to devise rules which are a characteristic of the knowledge based method. Secondly, the same template sets were employed to perform template matching related to the learning methodologies approach. The proposed method was tested on two landmarks, the Dorsum sellae and the Pterygoid plate, using CT cases of 5 subjects. The results indicate that, out of the 10 tests, the output images were within the expected range (desired accuracy in 7 instances and acceptable range (near accuracy for 2 instances, thus verifying the effectiveness of the combined template sets centric approach proposed in this study.

Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening

OpenAIRE

He, Frank S.; Liu, Yang; Schwing, Alexander G.; Peng, Jian

2016-01-01

We propose a novel training algorithm for reinforcement learning which combines the strength of deep Q-learning with a constrained optimization approach to tighten optimality and encourage faster reward propagation. Our novel technique makes deep reinforcement learning more practical by drastically reducing the training time. We evaluate the performance of our approach on the 49 games of the challenging Arcade Learning Environment, and report significant improvements in both training time and...

E-Learning Approach in Teacher Training

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A. Seda YUCEL

2006-10-01

Full Text Available There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational system on platform with Internet, Intranet or computer access. The concept of e-learning has two main subtitles as synchronized (where a group of students and an instructor actualize an online conference meeting in a computer environment an asynchronized (where individuals actualize self-training in computer environments. Students have access to the course contents whenever they want and communicate with their peers or teachers via communication tools such as e-mail and forums. In order the distance learning system to succeed in e-learning, the program should be planned as both synchronized and asynchronized.

Examining the benefits of combining two learning strategies on recall of functional information in persons with multiple sclerosis.

Science.gov (United States)

Goverover, Yael; Basso, Michael; Wood, Hali; Chiaravalloti, Nancy; DeLuca, John

2011-12-01

Forgetfulness occurs commonly in people with multiple sclerosis (MS), but few treatments alleviate this problem. This study examined the combined effect of two cognitive rehabilitation strategies to improve learning and memory in MS: self-generation and spaced learning. The hypothesis was that the combination of spaced learning and self-generation would yield better learning and memory recall performance than spaced learning alone. Using a within groups design, 20 participants with MS and 18 healthy controls (HC) were presented with three tasks (learning names, appointment, and object location), each in three learning conditions (Massed, Spaced Learning, and combination of spaced and generated information). Participants were required to recall the information they learned in each of these conditions immediately and 30 min following the initial presentation. The combination of spaced learning and self-generation yielded better recall than did spaced learning alone. In turn, spaced learning resulted in better recall than the massed rehearsal condition. These findings reveal that the combination of these two learning strategies may possess utility as a cognitive rehabilitation strategy.

Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

Science.gov (United States)

Le, Laetitia Minh Maï; Kégl, Balázs; Gramfort, Alexandre; Marini, Camille; Nguyen, David; Cherti, Mehdi; Tfaili, Sana; Tfayli, Ali; Baillet-Guffroy, Arlette; Prognon, Patrice; Chaminade, Pierre; Caudron, Eric

2018-07-01

The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%). Copyright © 2018 Elsevier B.V. All rights reserved.

Enhancing the Teaching-Learning Process: A Knowledge Management Approach

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Bhusry, Mamta; Ranjan, Jayanthi

2012-01-01

Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…

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

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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.

Developing Learning Scenarios for Educational Web Radio: a Learning Design Approach

DEFF Research Database (Denmark)

Triantafyllou, Evangelia; Liokou, Effrosyni; Economou, Anastasia

2018-01-01

schools. In this paper, we present a survey study that aimed to evaluate a Visual Learning Design (VLD) approach for developing educational scenari-os in web radio. The study results indicated that the VLD approach helped teachers to think about the educational aspects of the web radio production...

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

Directory of Open Access Journals (Sweden)

Michael Jae-Yoon Chung

Full Text Available A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i learn probabilistic models of actions through self-discovery and experience, (ii utilize these learned models for inferring the goals of human actions, and (iii perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i a simulated robot that learns human-like gaze following behavior, and (ii a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

Predicting protein complexes using a supervised learning method combined with local structural information.

Science.gov (United States)

Dong, Yadong; Sun, Yongqi; Qin, Chao

2018-01-01

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

A machine learning approach for the classification of metallic glasses

Science.gov (United States)

Gossett, Eric; Perim, Eric; Toher, Cormac; Lee, Dongwoo; Zhang, Haitao; Liu, Jingbei; Zhao, Shaofan; Schroers, Jan; Vlassak, Joost; Curtarolo, Stefano

Metallic glasses possess an extensive set of mechanical properties along with plastic-like processability. As a result, they are a promising material in many industrial applications. However, the successful synthesis of novel metallic glasses requires trial and error, costing both time and resources. Therefore, we propose a high-throughput approach that combines an extensive set of experimental measurements with advanced machine learning techniques. This allows us to classify metallic glasses and predict the full phase diagrams for a given alloy system. Thus this method provides a means to identify potential glass-formers and opens up the possibility for accelerating and reducing the cost of the design of new metallic glasses.

Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance

Science.gov (United States)

Pardo, Abelardo; Han, Feifei; Ellis, Robert A.

2017-01-01

Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…

Artificial neuron-glia networks learning approach based on cooperative coevolution.

Science.gov (United States)

Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

2015-06-01

Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

A Professional Learning Community Approach

African Journals Online (AJOL)

This paper provides insights into how Life Sciences teachers in the Eastern Cape can be supported through professional learning communities (PLCs) as a potential approach to enhancing their biodiversity knowledge. PLCs are communities that provide the setting and necessary support for groups of classroom teachers to ...

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

Science.gov (United States)

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

Influence of open- and closed-book tests on medical students' learning approaches

NARCIS (Netherlands)

Heijne-Penninga, Marjolein; Kuks, Jan B. M.; Hofman, W. H. Adriaan; Cohen-Schotanus, Janke

2008-01-01

CONTEXT Two learning approaches are consistently distinguished in the literature: deep and surface learning. The deep learning approach is considered preferable. Open-book tests are expected to stimulate deep learning and to offer a possible way of handling the substantial growth in medical

The relationship between learning preferences (styles and approaches) and learning outcomes among pre-clinical undergraduate medical students

OpenAIRE

Liew, Siaw-Cheok; Sidhu, Jagmohni; Barua, Ankur

2015-01-01

Background Learning styles and approaches of individual undergraduate medical students vary considerably and as a consequence, their learning needs also differ from one student to another. This study was conducted to identify different learning styles and approaches of pre-clinical, undergraduate medical students and also to determine the relationships of learning preferences with performances in the summative examinations. Methods A cross-sectional study was conducted among randomly selected...

Relationship between motivational goal orientations, perceptions of general education classroom learning environment, and deep approaches to learning

OpenAIRE

Chanut Poondej; Thanita Lerdpornkulrat

2016-01-01

Researchers have reported empirical evidence that the deep approaches to learning account for significant successful learning. The present study aimed to investigate the relationship between students' motivational goal orientation, their perceptions of the general education classroom learning environment, and deep approaches to learning strategies. Participants (N = 494) were first- and second-year college students enrolled in any of the general education courses in higher education in Thaila...

Combining brain stimulation and video game to promote long-term transfer of learning and cognitive enhancement.

Science.gov (United States)

Looi, Chung Yen; Duta, Mihaela; Brem, Anna-Katharine; Huber, Stefan; Nuerk, Hans-Christoph; Cohen Kadosh, Roi

2016-02-23

Cognitive training offers the potential for individualised learning, prevention of cognitive decline, and rehabilitation. However, key research challenges include ecological validity (training design), transfer of learning and long-term effects. Given that cognitive training and neuromodulation affect neuroplasticity, their combination could promote greater, synergistic effects. We investigated whether combining transcranial direct current stimulation (tDCS) with cognitive training could further enhance cognitive performance compared to training alone, and promote transfer within a short period of time. Healthy adults received real or sham tDCS over their dorsolateral prefrontal cortices during two 30-minute mathematics training sessions involving body movements. To examine the role of training, an active control group received tDCS during a non-mathematical task. Those who received real tDCS performed significantly better in the game than the sham group, and showed transfer effects to working memory, a related but non-numerical cognitive domain. This transfer effect was absent in active and sham control groups. Furthermore, training gains were more pronounced amongst those with lower baseline cognitive abilities, suggesting the potential for reducing cognitive inequalities. All effects associated with real tDCS remained 2 months post-training. Our study demonstrates the potential benefit of this approach for long-term enhancement of human learning and cognition.

An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

Science.gov (United States)

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

2013-01-01

Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…

Combining Education and Practice Learning in Environmental Management and Cleaner Technology

DEFF Research Database (Denmark)

Jørgensen, Ulrik; Jørgensen, Michael Søgaard

2004-01-01

to overcome these problems are discussed. The educational principles are presented as a combination of educational learning and practice learning named as reflexive learning. The experience from working with reflexive learning is discussed and relation to the role it can play in creating profes......This chapter argues for a new role for universities in adding the training of (existing) professionals to the core agenda in parallel to academic education and scientific research. Based on experiences from Denmark new challenges both to academic knowledge and training are presented and way...

The Activity Theory Approach to Learning

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Ritva Engeström

2014-12-01

Full Text Available In this paper the author offers a practical view of the theory-grounded research on education action. She draws on studies carried out at the Center for Research on Activity, Development and Learning (CRADLE at the University of Helsinki in Finland. In its work, the Center draws on cultural-historical activity theory (CHAT and is well-known for the theory of Expansive Learning and its more practical application called Developmental Work Research (DWR. These approaches are widely used to understand professional learning and have served as a theoreticaland methodological foundation for studies examining change and professional development in various human activities.

Combining theories to reach multi-faceted insights into learning opportunities in doctoral supervision

DEFF Research Database (Denmark)

Kobayashi, Sofie; Rump, Camilla Østerberg

The aim of this paper is to illustrate how theories can be combined to explore opportunities for learning in doctoral supervision. While our earlier research into learning dynamics in doctoral supervision in life science research (Kobayashi, 2014) has focused on illustrating learning opportunitie...

The FITS model: an improved Learning by Design approach

NARCIS (Netherlands)

Drs. Ing. Koen Michels; Prof. Dr. Marc de Vries; MEd Dave van Breukelen; MEd Frank Schure

2016-01-01

Learning by Design (LBD) is a project-based inquiry approach for interdisciplinary teaching that uses design contexts to learn skills and conceptual knowledge. Research around the year 2000 showed that LBD students achieved high skill performances but disappointing conceptual learning gains. A

A Multi-Faceted Approach to Inquiry-Based Learning

Science.gov (United States)

Brudzinski, M. R.; Sikorski, J.

2009-12-01

In order to fully attain the benefits of inquiry-based learning, instructors who typically employ the traditional lecture format need to make several adjustments to their approach. This change in styles can be intimidating and logistically difficult to overcome. A stepwise approach to this transformation is likely to be more manageable for individual faculty or departments. In this session, we will describe several features that we are implementing in our introductory geology course with the ultimate goal of converting to an entirely inquiry-based approach. Our project is part of the Miami University initiative in the top 25 enrolled courses to move towards the “student as scholar” model for engaged learning. Some of the features we developed for our course include: student learning outcomes, student development outcomes, out-of-class content quizzes, in-class conceptests, pre-/post-course assessment, reflective knowledge surveys, and daily group activities.

A global learning-centered approach to higher education: workplace development in the 21st century

Directory of Open Access Journals (Sweden)

Carlos Tasso Eira de Aquino

2017-01-01

Full Text Available Competition in the 21st century economy requires corporations, organizations, and professionals to face a common challenge: diverse individuals need consistent motivation towards building competences that increase personal marketability using a combination of higher education and professional development. This article represents an evolving report summary and non-traditional learning-centered approach focusing on adult competences necessary for succeeding in the competitive global marketplace of the 21st century. The purpose of this article is to understand the needs of constantly changing employer demands in the work environment. Exploring contemporary approaches related to skill development, adult education, and learning processes, will be the path towards higher levels of professional success. This article will provide readers with an enlightening discussion focusing on the necessary adult skills and competencies professionals need to succeed in the global marketplace.

Synthesizing Technology Adoption and Learners' Approaches towards Active Learning in Higher Education

Science.gov (United States)

Chan, Kevin; Cheung, George; Wan, Kelvin; Brown, Ian; Luk, Green

2015-01-01

In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners' variations, particularly regarding their styles and approaches to learning, on intention and use of learning technologies. This study contributes to further…

Approaches to learning, need for cognition, and strategic flexibility among university students.

Science.gov (United States)

Evans, Christina J; Kirby, John R; Fabrigar, Leandre R

2003-12-01

Considerable research has described students' deep and surface approaches to learning. Other research has described individuals' self-regulated learning and need for cognition. There is a need for research examining the relationships among these constructs. This study explored relationships among approaches to learning (deep, surface), need for cognition, and three types of control of learning (adaptive, inflexible, irresolute). Theory suggested similarities among the deep approach, need for cognition, and adaptive control (aspects of self-regulated learning); and among surface, inflexible, and irresolute control (aspects of an ineffective approach to learning). One-factor and two-factor models were proposed. Participants were 226 Canadian military college students. Participants completed the following questionnaires: the Study Process Questionnaire (Biggs, 1978), the Need for Cognition Scale (Cacioppo & Petty, 1982), and the Strategic Flexibility Questionnaire (Cantwell & Moore, 1996). Confirmatory factor analysis supported the identification of the six scale factors. Second order confirmatory factor analysis indicated three factors representing constructs underlying these factors. Neither the one- nor two-factor models accounted adequately for the data. Self-regulated learning was defined by measures of the deep approach to learning, need for cognition, and adaptive control of learning. The second factor divided into one factor consisting of irresolute control, the surface approach, and negative need for cognition; and another consisting of inflexible and negative adaptive control. Substantial relationships among scales support the need for further theory development.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

Science.gov (United States)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

An Investigative, Cooperative Learning Approach to the General Microbiology Laboratory

Science.gov (United States)

Seifert, Kyle; Fenster, Amy; Dilts, Judith A.; Temple, Louise

2009-01-01

Investigative- and cooperative-based learning strategies have been used effectively in a variety of classrooms to enhance student learning and engagement. In the General Microbiology laboratory for juniors and seniors at James Madison University, these strategies were combined to make a semester-long, investigative, cooperative learning experience…

The wonder approach to learning

Directory of Open Access Journals (Sweden)

Catherine eL'Ecuyer

2014-10-01

Full Text Available Wonder, innate in the child, is an inner desire to learn that awaits reality in order to be awakened. Wonder is at the origin of reality-based consciousness, thus of learning. The scope of wonder, which occurs at a metaphysical level, is greater than that of curiosity. Unfortunate misinterpretations of neuroscience have led to false brain-based ideas in the field of education, all of these based on the scientifically wrong assumption that children’s learning depends on an enriched environment. These beliefs have re-enforced the Behaviorist Approach to education and to parenting and have contributed to deadening our children’s sense of wonder. We suggest wonder as the center of all motivation and action in the child. Wonder is what makes life genuinely personal. Beauty is what triggers wonder. Wonder attunes to beauty through sensitivity and is unfolded by attachment. When wonder, beauty, sensitivity and secure attachment are present, learning is meaningful.On the contrary, when there is no volitional dimension involved (no wonder, no end or meaning (no beauty and no trusting predisposition (secure attachment, the rigid and limiting mechanical process of so-called learning through mere repetition become a deadening and alienating routine. This could be described as training, not as learning, because it does not contemplate the human being as a whole.

E-learning project assessment: A new approach through the analysis of learners’ posts on social media

Directory of Open Access Journals (Sweden)

A. Caione

2016-04-01

Full Text Available E-learning assessment is a key aspect in the overall e-learning process. There are several parameters to consider during the assessment. In recent years, several sets of factors, called Critical Success Factors, have been defined to provide a structural approach to assessment. They focus on many aspects but, in our view, they do not properly consider student satisfaction with courses. In e-learning applications, student opinion must be examined where it is expressed: on e-learning course social pages and/or social pages outside the platform but specific to the e-learning course. The problem is that these resources are unstructured and thus it is important to structure these resources before using them for assessment. In this paper, we discuss a proposal that can capture student opinion from social pages, combining several techniques, such as Natural Language Processing, Information Extraction; ontologies that help us to understand what and how students discuss about e-learning courses.

Meaningful Learning in the Teaching of Culture: The Project Based Learning Approach

Science.gov (United States)

Kean, Ang Chooi; Kwe, Ngu Moi

2014-01-01

This paper reports on a collaborative effort taken by a team of three teacher educators in using the Project Based Learning (PBL) approach in the teaching of Japanese culture with the aim to investigate the presence of actual "meaningful learning" among 15 students of a 12-Week Preparatory Japanese Language course under a teacher…

Advancing the skill set of SCM graduates – An active learning approach

NARCIS (Netherlands)

Scholten, Kirstin; Dubois, Anna

2017-01-01

Purpose Drawing on a novel approach to active learning in supply chain management, the purpose of this paper is to describe and analyze how the students’ learning process as well as their learning outcomes are influenced by the learning and teaching contexts. Design/methodology/approach A case study

Advancing the skill set of SCM graduates – An active learning approach

NARCIS (Netherlands)

Scholten, Kirstin; Dubois, Anna

Purpose Drawing on a novel approach to active learning in supply chain management, the purpose of this paper is to describe and analyze how the students’ learning process as well as their learning outcomes are influenced by the learning and teaching contexts. Design/methodology/approach A case study

The study of effectiveness of blended learning approach for medical training courses.

Science.gov (United States)

Karamizadeh, Z; Zarifsanayei, N; Faghihi, A A; Mohammadi, H; Habibi, M

2012-01-01

Blended learning as a method of learning that includes face to face learning, pure E-learning and didactic learning. This study aims to investigate the efficacy of medical education by this approach. This interventional study was performed in 130 students at different clinical levels participating in class sessions on "congenital adrenal hyperplasia and ambiguous genitalia". Sampling was done gradually during 6 months and all of them filled a pretest questionnaire and received an educational compact disk. One week later, a presence class session was held in a question and answer and problem solving method. Two to four weeks later, they filled a posttest questionnaire. There was a significant correlation between pretest and posttest scores and the posttest scores were significantly more than the pretest ones. Sub-specialized residents had the most and the students had the least attitude towards blended learning approach. There was a significant correlation between the research samples' accessibility to computer and their attitude and satisfaction to blended learning approach. Findings generally showed that the blended learning was an effective approach in making a profound learning of academic subjects.

Tensor Voting A Perceptual Organization Approach to Computer Vision and Machine Learning

CERN Document Server

Mordohai, Philippos

2006-01-01

This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California. It is not written as a historical recount of the work, since the sequence of the presentation is not in chronological order. It aims at presenting an approach to a wide range of problems in computer vision and machine learning that is data-driven, local and requires a minimal number of assumptions. The tensor voting framework combines these properties and provides a unified perceptual organiza

Dental students' perception of their approaches to learning in a PBL programme.

Science.gov (United States)

Haghparast, H; Ghorbani, A; Rohlin, M

2017-08-01

To compare dental students' perceptions of their learning approaches between different years of a problem-based learning (PBL) programme. The hypothesis was that in a comparison between senior and junior students, the senior students would perceive themselves as having a higher level of deep learning approach and a lower level of surface learning approach than junior students would. This hypothesis was based on the fact that senior students have longer experience of a student-centred educational context, which is supposed to underpin student learning. Students of three cohorts (first year, third year and fifth year) of a PBL-based dental programme were asked to respond to a questionnaire (R-SPQ-2F) developed to analyse students' learning approaches, that is deep approach and surface approach, using four subscales including deep strategy, surface strategy, deep motive and surface motive. The results of the three cohorts were compared using a one-way analysis of variance (ANOVA). A P-value was set at approach than the first-year students (P = 0.020). There was a significant decrease in surface strategy from the first to the fifth year (P = 0.003). No differences were found concerning deep approach or its subscales (deep strategy and deep motive) between the mean scores of the three cohorts. The results did not show the expected increased depth in learning approaches over the programme years. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The colloquial approach: An active learning technique

Science.gov (United States)

Arce, Pedro

1994-09-01

This paper addresses the very important problem of the effectiveness of teaching methodologies in fundamental engineering courses such as transport phenomena. An active learning strategy, termed the colloquial approach, is proposed in order to increase student involvement in the learning process. This methodology is a considerable departure from traditional methods that use solo lecturing. It is based on guided discussions, and it promotes student understanding of new concepts by directing the student to construct new ideas by building upon the current knowledge and by focusing on key cases that capture the essential aspects of new concepts. The colloquial approach motivates the student to participate in discussions, to develop detailed notes, and to design (or construct) his or her own explanation for a given problem. This paper discusses the main features of the colloquial approach within the framework of other current and previous techniques. Problem-solving strategies and the need for new textbooks and for future investigations based on the colloquial approach are also outlined.

Family, Learning Environments, Learning Approaches, and Student Outcomes in a Malaysian Private University

Science.gov (United States)

Kek, Megan A. Yih Chyn; Darmawan, I. Gusti Ngurah; Chen, Yu Sui

2007-01-01

This article presents the quantitative findings from a mixed methods study of students and faculty at a private medical university in Malaysia. In particular, the relationships among students' individual characteristics, general self-efficacy, family context, university and classroom learning environments, curriculum, approaches to learning, and…

Active Learning by Querying Informative and Representative Examples.

Science.gov (United States)

Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua

2014-10-01

Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.

A Novel Teaching Tool Combined With Active-Learning to Teach Antimicrobial Spectrum Activity.

Science.gov (United States)

MacDougall, Conan

2017-03-25

Objective. To design instructional methods that would promote long-term retention of knowledge of antimicrobial pharmacology, particularly the spectrum of activity for antimicrobial agents, in pharmacy students. Design. An active-learning approach was used to teach selected sessions in a required antimicrobial pharmacology course. Students were expected to review key concepts from the course reader prior to the in-class sessions. During class, brief concept reviews were followed by active-learning exercises, including a novel schematic method for learning antimicrobial spectrum of activity ("flower diagrams"). Assessment. At the beginning of the next quarter (approximately 10 weeks after the in-class sessions), 360 students (three yearly cohorts) completed a low-stakes multiple-choice examination on the concepts in antimicrobial spectrum of activity. When data for students was pooled across years, the mean number of correct items was 75.3% for the items that tested content delivered with the active-learning method vs 70.4% for items that tested content delivered via traditional lecture (mean difference 4.9%). Instructor ratings on student evaluations of the active-learning approach were high (mean scores 4.5-4.8 on a 5-point scale) and student comments were positive about the active-learning approach and flower diagrams. Conclusion. An active-learning approach led to modestly higher scores in a test of long-term retention of pharmacology knowledge and was well-received by students.

Identifying Green Infrastructure from Social Media and Crowdsourcing- An Image Based Machine-Learning Approach.

Science.gov (United States)

Rai, A.; Minsker, B. S.

2016-12-01

In this work we introduce a novel dataset GRID: GReen Infrastructure Detection Dataset and a framework for identifying urban green storm water infrastructure (GI) designs (wetlands/ponds, urban trees, and rain gardens/bioswales) from social media and satellite aerial images using computer vision and machine learning methods. Along with the hydrologic benefits of GI, such as reducing runoff volumes and urban heat islands, GI also provides important socio-economic benefits such as stress recovery and community cohesion. However, GI is installed by many different parties and cities typically do not know where GI is located, making study of its impacts or siting new GI difficult. We use object recognition learning methods (template matching, sliding window approach, and Random Hough Forest method) and supervised machine learning algorithms (e.g., support vector machines) as initial screening approaches to detect potential GI sites, which can then be investigated in more detail using on-site surveys. Training data were collected from GPS locations of Flickr and Instagram image postings and Amazon Mechanical Turk identification of each GI type. Sliding window method outperformed other methods and achieved an average F measure, which is combined metric for precision and recall performance measure of 0.78.

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…

Variability in University Students' Use of Technology: An "Approaches to Learning" Perspective

Science.gov (United States)

Mimirinis, Mike

2016-01-01

This study reports the results of a cross-case study analysis of how students' approaches to learning are demonstrated in blended learning environments. It was initially propositioned that approaches to learning as key determinants of the quality of student learning outcomes are demonstrated specifically in how students utilise technology in…

Contextual Teaching and Learning Approach of Mathematics in Primary Schools

Science.gov (United States)

Selvianiresa, D.; Prabawanto, S.

2017-09-01

The Contextual Teaching and Learning (CTL) approach is an approach involving active students in the learning process to discover the concepts learned through to knowledge and experience of the students. Similar to Piaget’s opinion that learning gives students an actives trying to do new things by relating their experiences and building their own minds. When students to connecting mathematics with real life, then students can looking between a conceptual to be learned with a concept that has been studied. So that, students can developing of mathematical connection ability. This research is quasi experiment with a primary school in the city of Kuningan. The result showed that CTL learning can be successful, when learning used a collaborative interaction with students, a high level of activity in the lesson, a connection to real-world contexts, and an integration of science content with other content and skill areas. Therefore, CTL learning can be applied by techer to mathematics learning in primary schools.

Harnessing the Power of Learning Management Systems: An E-Learning Approach for Professional Development.

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White, Meagan; Shellenbarger, Teresa

E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.

MOOC Design – Dissemination to the Masses or Facilitation of Social Learning and a Deep Approach to Learning?

DEFF Research Database (Denmark)

Christensen, Inger-Marie F.; Dam Laursen, Mette; Bøggild, Jacob

2016-01-01

This article accounts for the design of the massive open online course (MOOC) Hans Christian Andersen’s Fairy tales on FutureLearn and reports on the effectiveness of this design in terms of engaging learners in social learning and encouraging a deep approach to learning. A learning pathway...... and increased educator feedback. Course data show that that some learners use the space provided for social interaction and mutual support. A learning pathway that engages learners in discussion and progression from week to week facilitates a deep approach to learning. However, this requires more support from...

Development of radiation oncology learning system combined with multi-institutional radiotherapy database (ROGAD)

International Nuclear Information System (INIS)

Takemura, Akihiro; Iinuma, Masahiro; Kou, Hiroko; Harauchi, Hajime; Inamura, Kiyonari

1999-01-01

We have constructed and are operating a multi-institutional radiotherapy database ROGAD (Radiation Oncology Greater Area Database) since 1992. One of it's purpose is 'to optimize individual radiotherapy plans'. We developed Radiation oncology learning system combined with ROGAD' which conforms to that purpose. Several medical doctors evaluated our system. According to those evaluations, we are now confident that our system is able to contribute to improvement of radiotherapy results. Our final target is to generate a good cyclic relationship among three components: radiotherapy results according to ''Radiation oncology learning system combined with ROGAD.'; The growth of ROGAD; and radiation oncology learning system. (author)

Learning Behavior and Achievement Analysis of a Digital Game-Based Learning Approach Integrating Mastery Learning Theory and Different Feedback Models

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Yang, Kai-Hsiang

2017-01-01

It is widely accepted that the digital game-based learning approach has the advantage of stimulating students' learning motivation, but simply using digital games in the classroom does not guarantee satisfactory learning achievement, especially in the case of the absence of a teacher. Integrating appropriate learning strategies into a game can…

Student-Centred Learning Environments: An Investigation into Student Teachers' Instructional Preferences and Approaches to Learning

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Baeten, Marlies; Dochy, Filip; Struyven, Katrien; Parmentier, Emmeline; Vanderbruggen, Anne

2016-01-01

The use of student-centred learning environments in education has increased. This study investigated student teachers' instructional preferences for these learning environments and how these preferences are related to their approaches to learning. Participants were professional Bachelor students in teacher education. Instructional preferences and…

A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

International Nuclear Information System (INIS)

Wander, J D; Morris, D

2014-01-01

Continuous cardiac monitoring of healthy and unhealthy patients can help us understand the progression of heart disease and enable early treatment. Optical pulse sensing is an excellent candidate for continuous mobile monitoring of cardiovascular health indicators, but optical pulse signals are susceptible to corruption from a number of noise sources, including motion artifact. Therefore, before higher-level health indicators can be reliably computed, corrupted data must be separated from valid data. This is an especially difficult task in the presence of artifact caused by ambulation (e.g. walking or jogging), which shares significant spectral energy with the true pulsatile signal. In this manuscript, we present a machine-learning-based system for automated estimation of signal quality of optical pulse signals that performs well in the presence of periodic artifact. We hypothesized that signal processing methods that identified individual heart beats (segmenting approaches) would be more error-prone than methods that did not (non-segmenting approaches) when applied to data contaminated by periodic artifact. We further hypothesized that a fusion of segmenting and non-segmenting approaches would outperform either approach alone. Therefore, we developed a novel non-segmenting approach to signal quality estimation that we then utilized in combination with a traditional segmenting approach. Using this system we were able to robustly detect differences in signal quality as labeled by expert human raters (Pearson’s r = 0.9263). We then validated our original hypotheses by demonstrating that our non-segmenting approach outperformed the segmenting approach in the presence of contaminated signal, and that the combined system outperformed either individually. Lastly, as an example, we demonstrated the utility of our signal quality estimation system in evaluating the trustworthiness of heart rate measurements derived from optical pulse signals. (paper)

Self-Regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison between Professional Training and English Learning

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Tseng, Min-chen; Chen, Chia-cheng

2017-01-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between…

Learning Human Actions by Combining Global Dynamics and Local Appearance.

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Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

A New Design Approach to Game-Based learning

DEFF Research Database (Denmark)

Larsen, Lasse Juel

2012-01-01

to ground the student’s reason to learn. This paper proposes a different approach: using visualisation in immersive 3D worlds as both documentation of learning progress and as a reward system which motivates further learning. The overall design idea is to build a game based learning system from three......This paper puts forward a new design perspective for gamebased learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn – without the interference of teachers – whatever subject......-based learning system, but will also confront aspects of modern learning theory, especially the notion of reference between the content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way of tackling the common experience of the average...

BLENDED LEARNING AS AN INNOVATIVE FORM OF TEACHING AND LEARNING AT SCHOOL

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Olga Kuzmenko

2017-09-01

Full Text Available In the paper the theoretical background of blended learning is examined, traditional brick-and-mortar and blended learning are compared, the advantages of blended learning are outlined and it effectiveness in foreign language teaching is proven. The topicality of this research is determined by the prospect of implementing the blended learning models to achieve the goals set by the National Strategy for the Development of Education in Ukraine for 2012-2021, namely: improving the quality of education on an innovative basis, creating and providing opportunities for implementing various learning models, forms and means of getting education. In this context, a modern educational institution is required to set up a combination of traditional and innovative forms of learning, and constantly update its information and communication resources, which cause the need to introduce the blended learning approach. Blended learning is a relatively new approach in the field of education in Ukraine. The great prospect of blended learning consists in its potential to combine the best of traditional and online practices. This is a formal education program in which pupils learn partially through online learning with some element of self-control over time, place and pace; and partially in a traditional classroom setting. It provides more efficiency and flexibility in comparison with traditional learning as well as online or distance learning. Moreover, blended learning implies a mastery-based approach ensuring that pupils achieve the required level of mastery at the end of the course. It also prepares learners to collaborate in an online environment and meet the demands of the modern labour market. This is particularly important for schools, because modern pupils are tech-savvy and their motivation is determined by the need for autonomy, personalization, communicatively-oriented and mastery-based learning. For the teaching staff, blended learning can improve teaching

How to develop students’ approaches to learning: Experiences from a programme based on co-regulated learning

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Stančić Milan

2017-01-01

Full Text Available Starting from the insight that during their education students do not manage to learn how to learn, we created the programme called Blooming with the intention of enabling the students to reconsider their own approaches to learning by developing collaborative activities and relations in the classroom. The programme was realised in a secondary school class, and research goals were to explore the contribution of the programme to the change in students’ approach to learning - regarding the learning motivation and strategies - and to obtain an insight into students’ perspective of the benefits of the programme. The changes in learning strategies and students’ motivation were investigated using the MSLQ before and after programme attendance. The data on the programme benefits were obtained via focus groups with students and analysed by the thematic content analysis. It has been established that the students achieved a significant improvement when it comes to the mastering of the learning strategies that refer to self-regulation, critical thinking, peer learning and help seeking. In addition, the students pointed out as benefits a different method of work and pleasant atmosphere, the feeling of autonomy in classes, as well as the development of a different understanding of the nature of knowledge, the learning process and instruction. The results indicate that the use of Bloom’s taxonomy as the tool for co-regulated learning and self-evaluation of students can contribute to the change in students’ learning approaches. This finding is relevant for further considering of the possibility for this method to grow from a special programme into everyday teaching practice.

Machine learning and computer vision approaches for phenotypic profiling.

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Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Prediction of a service demand using combined forecasting approach

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Zhou, Ling

2017-08-01

Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast short-term logistic demand for a LTL carrier. Combined approach depends on several forecasting methods simultaneously, instead of a single method. It can offset the weakness of a forecasting method with the strength of another, which could improve the precision performance of prediction. Main issues of combined forecast modeling are how to select methods for combination, and how to find out weight coefficients among methods. The principles of method selection include that each method should apply to the problem of forecasting itself, also methods should differ in categorical feature as much as possible. Based on these principles, exponential smoothing, ARIMA and Neural Network are chosen to form the combined approach. Besides, least square technique is employed to settle the optimal weight coefficients among forecasting methods. Simulation results show the advantage of combined approach over the three single methods. The work done in the paper helps manager to select prediction method in practice.

Effects of the Digital Game-Development Approach on Elementary School Students' Learning Motivation, Problem Solving, and Learning Achievement

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Chu, Hui-Chun; Hung, Chun-Ming

2015-01-01

In this study, the game-based development approach is proposed for improving the learning motivation, problem solving skills, and learning achievement of students. An experiment was conducted on a learning activity of an elementary school science course to evaluate the performance of the proposed approach. A total of 59 sixth graders from two…

Superficial and deep learning approaches among medical students in an interdisciplinary integrated curriculum.

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Mirghani, Hisham M; Ezimokhai, Mutairu; Shaban, Sami; van Berkel, Henk J M

2014-01-01

Students' learning approaches have a significant impact on the success of the educational experience, and a mismatch between instructional methods and the learning approach is very likely to create an obstacle to learning. Educational institutes' understanding of students' learning approaches allows those institutes to introduce changes in their curriculum content, instructional format, and assessment methods that will allow students to adopt deep learning techniques and critical thinking. The objective of this study was to determine and compare learning approaches among medical students following an interdisciplinary integrated curriculum. This was a cross-sectional study in which an electronic questionnaire using the Biggs two-factor Study Process Questionnaire (SPQ) with 20 questions was administered. Of a total of 402 students at the medical school, 214 (53.2%) completed the questionnaire. There was a significant difference in the mean score of superficial approach, motive and strategy between students in the six medical school years. However, no significant difference was observed in the mean score of deep approach, motive and strategy. The mean score for years 1 and 2 showed a significantly higher surface approach, surface motive and surface strategy when compared with students in years 4-6 in medical school. The superficial approach to learning was mostly preferred among first and second year medical students, and the least preferred among students in the final clinical years. These results may be useful in creating future teaching, learning and assessment strategies aiming to enhance a deep learning approach among medical students. Future studies are needed to investigate the reason for the preferred superficial approach among medical students in their early years of study.

Learning approaches as predictors of academic performance in first year health and science students.

Science.gov (United States)

Salamonson, Yenna; Weaver, Roslyn; Chang, Sungwon; Koch, Jane; Bhathal, Ragbir; Khoo, Cheang; Wilson, Ian

2013-07-01

To compare health and science students' demographic characteristics and learning approaches across different disciplines, and to examine the relationship between learning approaches and academic performance. While there is increasing recognition of a need to foster learning approaches that improve the quality of student learning, little is known about students' learning approaches across different disciplines, and their relationships with academic performance. Prospective, correlational design. Using a survey design, a total of 919 first year health and science students studying in a university located in the western region of Sydney from the following disciplines were recruited to participate in the study - i) Nursing: n = 476, ii) Engineering: n = 75, iii) Medicine: n = 77, iv) Health Sciences: n = 204, and v) Medicinal Chemistry: n = 87. Although there was no statistically significant difference in the use of surface learning among the five discipline groups, there were wide variations in the use of deep learning approach. Furthermore, older students and those with English as an additional language were more likely to use deep learning approach. Controlling for hours spent in paid work during term-time and English language usage, both surface learning approach (β = -0.13, p = 0.001) and deep learning approach (β = 0.11, p = 0.009) emerged as independent and significant predictors of academic performance. Findings from this study provide further empirical evidence that underscore the importance for faculty to use teaching methods that foster deep instead of surface learning approaches, to improve the quality of student learning and academic performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Healthcare students' experiences when integrating e-learning and flipped classroom instructional approaches.

Science.gov (United States)

Telford, Mark; Senior, Emma

2017-06-08

This article describes the experiences of undergraduate healthcare students taking a module adopting a 'flipped classroom' approach. Evidence suggests that flipped classroom as a pedagogical tool has the potential to enhance student learning and to improve healthcare practice. This innovative approach was implemented within a healthcare curriculum and in a module looking at public health delivered at the beginning of year two of a 3-year programme. The focus of the evaluation study was on the e-learning resources used in the module and the student experiences of these; with a specific aim to evaluate this element of the flipped classroom approach. A mixed-methods approach was adopted and data collected using questionnaires, which were distributed across a whole cohort, and a focus group involving ten participants. Statistical analysis of the data showed the positive student experience of engaging with e-learning. The thematic analysis identified two key themes; factors influencing a positive learning experience and the challenges when developing e-learning within a flipped classroom approach. The study provides guidance for further developments and improvements when developing e-learning as part of the flipped classroom approach.

Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

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Akhmetova, Daniya Z.

2014-01-01

Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…

Implementing Project Based Learning Approach to Graphic Design Course

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Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.

2017-01-01

The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…

Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation

Directory of Open Access Journals (Sweden)

Wenjing Zhao

2018-01-01

Full Text Available SGK (sequential generalization of K-means dictionary learning denoising algorithm has the characteristics of fast denoising speed and excellent denoising performance. However, the noise standard deviation must be known in advance when using SGK algorithm to process the image. This paper presents a denoising algorithm combined with SGK dictionary learning and the principal component analysis (PCA noise estimation. At first, the noise standard deviation of the image is estimated by using the PCA noise estimation algorithm. And then it is used for SGK dictionary learning algorithm. Experimental results show the following: (1 The SGK algorithm has the best denoising performance compared with the other three dictionary learning algorithms. (2 The SGK algorithm combined with PCA is superior to the SGK algorithm combined with other noise estimation algorithms. (3 Compared with the original SGK algorithm, the proposed algorithm has higher PSNR and better denoising performance.

Integrating transformative learning and action learning approaches to enhance ethical leadership for supervisors in the hotel business

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Boonyuen Saranya

2016-01-01

Full Text Available Ethical leadership is now increasingly focused in leadership development. The main purpose of this study is to explore two methods of adult learning, action learning and transformative learning, and to use the methods to enhance ethical leadership. Building ethical leadership requires an approach that focuses on personal values, beliefs, or frames of references, which is transformative learning. Transformative learning requires a series of meetings to conduct critical discourse and to follow up the learning of learners. By organizing such action learning, human resource developers can optimize their time and effort more effectively. The authors have created a comprehensive model to integrate the two learning approaches in a general way that focuses not only on ethical leadership, but also on all kinds of behavioral transformation in the workplace in the hotel business or even other types of business.

Organizational Approach to the Ergonomic Examination of E-Learning Modules

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Lavrov, Evgeniy; Kupenko, Olena; Lavryk, Tetiana; Barchenko, Natalia

2013-01-01

With a significant increase in the number of e-learning resources the issue of quality is of current importance. An analysis of existing scientific and methodological literature shows the variety of approaches, methods and tools to evaluate e-learning materials. This paper proposes an approach based on the procedure for estimating parameters of…

The FITS model: an improved Learning by Design approach

OpenAIRE

Michels, Koen; Vries, de, Marc; Breukelen, van, Dave; Schure, Frank

2016-01-01

Learning by Design (LBD) is a project-based inquiry approach for interdisciplinary teaching that uses design contexts to learn skills and conceptual knowledge. Research around the year 2000 showed that LBD students achieved high skill performances but disappointing conceptual learning gains. A series of exploratory studies, previous to the study in this paper, indicated how to enhance concept learning. Small-scale tested modifications, based on explicit teaching and scaffolding, were promisin...

Meta-analysis of Jelajah Alam Sekitar (JAS Approach Implementation in Learning Procces

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S. Ngabekti

2017-04-01

Full Text Available The results of tracer studies on the approach of Jelajah Alam Sekitar (JAS or environment exploring learning has been detected is used in eight provinces in Indonesia and studied in the learning begin primary school to college. Then, how the effectiveness of the implementation of the JAS approach in improving the learning process. This study uses meta-analysis-data in the form of descriptive exploratory qualitative. Data was taken from the various thesis, and research faculty in the last 10 years. Data analysis was performed by calculating the percentage of the same findings for similar problems. The results showed a wide range of studies using different methods and approach such as qualitative descriptive, quasi-experimental, PTK and R and D to produce evidence that the approach JAS effective when applied in teaching, especially teaching biology in a variety of teaching materials. Various studies have shown the approach JAS managed to increase learning outcomes, can differentiate learning outcomes between treatment and control groups in which the treatment group had a mean score higher. Models/strategies/methods centered learning students are very relevant to implementation approach JAS making it seem more real, like a model of cooperative learning, think pair share, strategy role-playing, the investigation group, learning cycle 5e, hands-on activity, and so on, making it possible to continuously assessed and developed in the paradigm of competency-based curriculum developed.

Development of radiation oncology learning system combined with multi-institutional radiotherapy database (ROGAD)

Energy Technology Data Exchange (ETDEWEB)

Takemura, Akihiro; Iinuma, Masahiro; Kou, Hiroko [Kanazawa Univ. (Japan). School of Medicine; Harauchi, Hajime; Inamura, Kiyonari

1999-09-01

We have constructed and are operating a multi-institutional radiotherapy database ROGAD (Radiation Oncology Greater Area Database) since 1992. One of it's purpose is 'to optimize individual radiotherapy plans'. We developed Radiation oncology learning system combined with ROGAD' which conforms to that purpose. Several medical doctors evaluated our system. According to those evaluations, we are now confident that our system is able to contribute to improvement of radiotherapy results. Our final target is to generate a good cyclic relationship among three components: radiotherapy results according to ''Radiation oncology learning system combined with ROGAD.'; The growth of ROGAD; and radiation oncology learning system. (author)

A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

Science.gov (United States)

Avendi, M R; Kheradvar, Arash; Jafarkhani, Hamid

2016-05-01

Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms combined with deformable models to develop and evaluate a fully automatic LV segmentation tool from short-axis cardiac MRI datasets. The method employs deep learning algorithms to learn the segmentation task from the ground true data. Convolutional networks are employed to automatically detect the LV chamber in MRI dataset. Stacked autoencoders are used to infer the LV shape. The inferred shape is incorporated into deformable models to improve the accuracy and robustness of the segmentation. We validated our method using 45 cardiac MR datasets from the MICCAI 2009 LV segmentation challenge and showed that it outperforms the state-of-the art methods. Excellent agreement with the ground truth was achieved. Validation metrics, percentage of good contours, Dice metric, average perpendicular distance and conformity, were computed as 96.69%, 0.94, 1.81 mm and 0.86, versus those of 79.2-95.62%, 0.87-0.9, 1.76-2.97 mm and 0.67-0.78, obtained by other methods, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

IMPROVING TRUST THROUGH ETHICAL LEADERSHIP: MOVING BEYOND THE SOCIAL LEARNING THEORY TO A HISTORICAL LEARNING APPROACH

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Omoregie Charles Osifo

2016-12-01

Full Text Available The complex nature of trust and its evolving relative concepts require a more idealistic and simpler review. Ethical leadership is related to trust, honesty, transparency, compassion, empathy, results-orientedness, and many other behavioral attributes. Ethical leadership and good leadership are the same, because they represent practicing what one preaches or showing a way to the accomplishment of set goals. The outcomes and findings of many research papers on trust and ethical leadership report positive correlations between ethical leadership and trust. Improving trust from different rational standpoints requires moving and looking beyond the popular theoretical framework through which most results are derived in order to create a new thinking perspective. Social learning theory strongly emphasizes modelling while the new historical learning approach, proposed by the author, is defined as an approach that creates unique historical awareness among individuals, groups, institutions, societies, and nations to use previous experience(s or occurrence(s as a guide in developing positive opinion(s and framework(s in order to tackle the problems and issues of today and tomorrow. Social learning theory is seen as limited from the perspectives of balancing the equation between leadership and trust, the non-compatibility of the values of different generations at work, and other approaches and methods that support the historical approach. This paper is argumentative, adopts a writer´s perspective, and employs a logical analysis of the literature. The main contention is that a historical learning approach can inform an independent-learning to improve trust and its relatives (e.g. motivation and performance, because independent learning can positively shape the value of integrity, which is an integral part of ethical leadership. Historical learning can positively shape leadership in every perspective, because good leadership can develop based on history and

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

Science.gov (United States)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

Undergraduate Students' Earth Science Learning: Relationships among Conceptions, Approaches, and Learning Self-Efficacy in Taiwan

Science.gov (United States)

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-01-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to…

Workplace-based assessment and students' approaches to learning: a qualitative inquiry.

Science.gov (United States)

Al-Kadri, Hanan M; Al-Kadi, Mohammed T; Van Der Vleuten, Cees P M

2013-01-01

We have performed this research to assess the effect of work-place based assessment (WBA) practice on medical students' learning approaches. The research was conducted at the King Saud bin Abdulaziz University for Health Sciences, College of Medicine from 1 March to 31 July 2012. We conducted a qualitative, phenomenological research utilizing semi-structured individual interviews with medical students exposed to WBA. The audio-taped interviews were transcribed verbatim, analyzed, and themes were identified. We preformed investigators' triangulation, member checking with clinical supervisors and we triangulated the data with a similar research performed prior to the implementation of WBA. WBA results in variable learning approaches. Based on several affecting factors; clinical supervisors, faculty-given feedback, and assessment function, students may swing between surface, deep and effort and achievement learning approaches. Students' and supervisors' orientations on the process of WBA, utilization of peer feedback and formative rather than summative assessment facilitate successful implementation of WBA and lead to students' deeper approaches to learning. Interestingly, students and their supervisors have contradicting perceptions to WBA. A change in culture to unify students' and supervisors' perceptions of WBA, more accommodation of formative assessment, and feedback may result in students' deeper approach to learning.

Blending Online Learning with Traditional Approaches: Changing Practices

Science.gov (United States)

Condie, Rae; Livingston, Kay

2007-01-01

Considerable claims have been made for the development of e-learning, either as stand-alone programmes or alongside more traditional approaches to teaching and learning, for students across school and tertiary education. National initiatives have improved the position of schools in terms of access to hardware and electronic networking, software…

Arts-Based Learning: A New Approach to Nursing Education Using Andragogy.

Science.gov (United States)

Nguyen, Megan; Miranda, Joyal; Lapum, Jennifer; Donald, Faith

2016-07-01

Learner-oriented strategies focusing on learning processes are needed to prepare nursing students for complex practice situations. An arts-based learning approach uses art to nurture cognitive and emotional learning. Knowles' theory of andragogy aims to develop the skill of learning and can inform the process of implementing arts-based learning. This article explores the use and evaluation of andragogy-informed arts-based learning for teaching nursing theory at the undergraduate level. Arts-based learning activities were implemented and then evaluated by students and instructors using anonymous questionnaires. Most students reported that the activities promoted learning. All instructors indicated an interest in integrating arts-based learning into the curricula. Facilitators and barriers to mainstreaming arts-based learning were highlighted. Findings stimulate implications for prospective research and education. Findings suggest that arts-based learning approaches enhance learning by supporting deep inquiry and different learning styles. Further exploration of andragogy-informed arts-based learning in nursing and other disciplines is warranted. [J Nurs Educ. 2016;55(7):407-410.]. Copyright 2016, SLACK Incorporated.

Relationships between Learning Approach, Procrastination and Academic Achievement amongst First-Year University Students

Science.gov (United States)

Saele, Rannveig Grøm; Dahl, Tove Irene; Sørlie, Tore; Friborg, Oddgeir

2017-01-01

Individual differences in student learning influence academic performance, and two aspects influencing the learning process are the particular learning approach the students use and procrastination behaviour. We examined the relationships between learning approaches, procrastination and academic achievement (measured 1 year later as the grade…

Students' Conception of Learning Environment and Their Approach to Learning and Its Implication on Quality Education

Science.gov (United States)

Belaineh, Matheas Shemelis

2017-01-01

Quality of education in higher institutions can be affected by different factors. It partly rests on the learning environment created by teachers and the learning approach students are employing during their learning. The main purpose of this study is to examine the learning environment at Mizan Tepi University from students' perspective and their…

Game-Enhanced Simulation as an Approach to Experiential Learning in Business English

Science.gov (United States)

Punyalert, Sansanee

2017-01-01

This dissertation aims to integrate various learning approaches, i.e., multiple literacies, experiential learning, game-enhanced learning, and global simulation, into an extracurricular module, in which it remodels traditional ways of teaching input, specifically, the lexical- and grammatical-only approaches of business English at a private…

Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands

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Krzysztof Rataj

2018-05-01

Full Text Available The identification of subtype-selective GPCR (G-protein coupled receptor ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HT2BR versus 5-HT1BR selectivity. Our approach employs the hierarchical combination of machine learning methods, docking, and multiple scoring methods. First, we applied machine learning tools to filter a large database of druglike compounds by the new Neighbouring Substructures Fingerprint (NSFP. This two-dimensional fingerprint contains information on the connectivity of the substructural features of a compound. Preselected subsets of the database were then subjected to docking calculations. The main indicators of compounds’ selectivity were their different interactions with the secondary binding pockets of both target proteins, while binding modes within the orthosteric binding pocket were preserved. The combined methodology of ligand-based and structure-based methods was validated prospectively, resulting in the identification of hits with nanomolar affinity and ten-fold to ten thousand-fold selectivities.

Providing pervasive Learning eXperiences by Combining Internet of Things and e-Learning standards

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Aroua TAAMALLAH

2015-12-01

Full Text Available Nowadays, learning is more and more taking place anywhere and anytime. This implies that e-learning environments are expanded from only virtual learning environments to both virtual and physical ones. Thanks to the evolution of Internet, ICT (Information and Communication Technology and Internet of Things, new learning scenarios could be experienced by learners either individually or collaboratively. These learning scenarios are Pervasive in such a way that they allow to mix virtual and physical learning environments as well. They are therefore characterized by possible interactions of the learner with the physical environment, the Learner's contextual data detection as well as the adaptation of pedagogical strategies and services according to this context. This paper aims to take advantage of this trend and keep up also with existing e-Learning standards such as IMS LD and LOM. The solution proposed is therefore to extend these standards models with that of Internet of Things and to provide an adaptation approach of learning activities based on learner's context and her/his track using the eXperience API. In this context and in order to allow both reasoning capabilities and interoperability between the proposed models Ontological representations and implementation are therefore proposed. Moreover a technical architecture highlighting the required software components and their interactions is provided. And finally, a relevant pervasive learning scenario is implemented and experimented.

Using Flipped Classroom Approach to Explore Deep Learning in Large Classrooms

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Brenda Danker

2015-01-01

Full Text Available This project used two Flipped Classroom approaches to stimulate deep learning in large classrooms during the teaching of a film module as part of a Diploma in Performing Arts course at Sunway University, Malaysia. The flipped classes utilized either a blended learning approach where students first watched online lectures as homework, and then completed their assignments and practical work in class; or utilized a guided inquiry approach at the beginning of class using this same process. During the class the lecturers were present to help the students, and in addition, the students were advantaged by being able to help one another. The in-class learning activities also included inquiry-based learning, active learning, and peer-learning. This project used an action research approach to improve the in-class instructional design progressively to achieve its impact of deep learning among the students. The in-class learning activities that was included in the later flipped classes merged aspects of blended learning with an inquiry-based learning cycle which focused on the exploration of concepts. Data was gathered from questionnaires filled out by the students and from short interviews with the students, as well as from the teacher’s reflective journals. The findings verified that the flipped classrooms were able to remodel large lecture classes into active-learning classes. The results also support the possibility of individualised learning for the students as being high as a result of the teacher’s ability to provide one-on-one tutoring through technology-infused lessons. It is imperative that the in-class learning activities are purposefully designed as the inclusion of the exploratory learning through guided inquiry-based activities in the flipped classes was a successful way to engage students on a deeper level and increased the students’ curiosity and engaged them to develop higher-order thinking skills. This project also concluded that

Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

Science.gov (United States)

Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

2018-01-01

This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…

Transbasal versus endoscopic endonasal versus combined approaches for olfactory groove meningiomas: importance of approach selection.

Science.gov (United States)

Liu, James K; Silva, Nicole A; Sevak, Ilesha A; Eloy, Jean Anderson

2018-04-01

OBJECTIVE There has been much debate regarding the optimal surgical approach for resecting olfactory groove meningiomas (OGMs). In this paper, the authors analyzed the factors involved in approach selection and reviewed the surgical outcomes in a series of OGMs. METHODS A retrospective review of 28 consecutive OGMs from a prospective database was conducted. Each tumor was treated via one of 3 approaches: transbasal approach (n = 15), pure endoscopic endonasal approach (EEA; n = 5), and combined (endoscope-assisted) transbasal-EEA (n = 8). RESULTS The mean tumor volume was greatest in the transbasal (92.02 cm 3 ) and combined (101.15 cm 3 ) groups. Both groups had significant lateral dural extension over the orbits (transbasal 73.3%, p 95%) was achieved in 20% of transbasal and 37.5% of combined cases, all due to tumor adherence to the critical neurovascular structures. The rate of CSF leakage was 0% in the transbasal and combined groups, and there was 1 leak in the EEA group (20%), resulting in an overall CSF leakage rate of 3.6%. Olfaction was preserved in 66.7% in the transbasal group. There was no significant difference in length of stay or 30-day readmission rate between the 3 groups. The mean modified Rankin Scale score was 0.79 after the transbasal approach, 2.0 after EEA, and 2.4 after the combined approach (p = 0.0604). The mean follow-up was 14.5 months (range 1-76 months). CONCLUSIONS The transbasal approach provided the best clinical outcomes with the lowest rate of complications for large tumors (> 40 mm) and for smaller tumors (OGMs invading the sinonasal cavity. Careful patient selection using an individualized, tailored strategy is important to optimize surgical outcomes.

Translation in language learning: a ‘what for’ approach

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Paolo E. Balboni

2017-12-01

Full Text Available Literature about translation in language learning and teaching shows the prominence of the ‘for and against’ approach, while a ‘what for’ approach would be more profitable. In order to prevent the latter approach from becoming a random list of the potential benefits of the use of translation in language teaching, this essay suggests the use of a formal model of communicative competence, to see which of its components can profit of translation activities. The result is a map of the effects of translation in the wide range of competences and abilities which constitute language learning.

Learning Outcomes in Vocational Education: A Business Plan Development by Production-Based Learning Model Approach

Science.gov (United States)

Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia

2016-01-01

This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…

Benefiting from Customer and Competitor Knowledge: A Market-Based Approach to Organizational Learning

Science.gov (United States)

Hoe, Siu Loon

2008-01-01

Purpose: The purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market-based approach to organizational learning. Design/methodology/approach: The extant organizational learning…

A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

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Han Kyungsook

2010-06-01

Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for

The Use of a Hybrid Strategy Combining Problem-based Learning and Magisterial Lectures to Enhance Learning

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Carlos Alberto Acosta-Nassar

2014-09-01

Full Text Available This paper addresses the problem of capturing the attention of intermediate level students in the Thermodynamics 1 course from the Mechanical and Agricultural Engineering Program, with the purpose of helping students improve their learning process. A hybrid teaching strategy was proposed based on Problem-based Learning (PBL principles combined with magisterial lectures. Digital and traditional didactic resources were also used in order to find the best mean to minimize the lack of attention in learners. The strategy was developed by sensitizing students to get involved in their formation process. PowerPoint presentations, video clips, the traditional white board and an ultra slim digital tablet board were used to develop the theoretical issues and present the solutions to the problems chosen for the PBL strategy. Finally, the strategy was evaluated and results were analyzed, indicating that using a hybrid strategy combining PBL and traditional magisterial lectures is an optimal resource to improve the learning process of students taking Thermodynamics 1. In addition, it was also concluded that the ultra slim digital tablet board is the optimal didactic resource.

Teamwork: improved eQTL mapping using combinations of machine learning methods.

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Marit Ackermann

Full Text Available Expression quantitative trait loci (eQTL mapping is a widely used technique to uncover regulatory relationships between genes. A range of methodologies have been developed to map links between expression traits and genotypes. The DREAM (Dialogue on Reverse Engineering Assessments and Methods initiative is a community project to objectively assess the relative performance of different computational approaches for solving specific systems biology problems. The goal of one of the DREAM5 challenges was to reverse-engineer genetic interaction networks from synthetic genetic variation and gene expression data, which simulates the problem of eQTL mapping. In this framework, we proposed an approach whose originality resides in the use of a combination of existing machine learning algorithms (committee. Although it was not the best performer, this method was by far the most precise on average. After the competition, we continued in this direction by evaluating other committees using the DREAM5 data and developed a method that relies on Random Forests and LASSO. It achieved a much higher average precision than the DREAM best performer at the cost of slightly lower average sensitivity.

Gene prediction in metagenomic fragments: A large scale machine learning approach

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Morgenstern Burkhard

2008-04-01

Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

Combining accounting approaches to practice valuation.

Science.gov (United States)

Schwartzben, D; Finkler, S A

1998-06-01

Healthcare organizations that wish to acquire physician or ambulatory care practices can choose from a variety of practice valuation approaches. Basic accounting methods assess the value of a physician practice on the basis of a historical, balance-sheet description of tangible assets. Yet these methods alone are inadequate to determine the true financial value of a practice. By using a combination of accounting approaches to practice valuation that consider factors such as fair market value, opportunity cost, and discounted cash flow over a defined time period, organizations can more accurately assess a practice's actual value.

Iterative Perceptual Learning for Social Behavior Synthesis

NARCIS (Netherlands)

de Kok, I.A.; Poppe, Ronald Walter; Heylen, Dirk K.J.

We introduce Iterative Perceptual Learning (IPL), a novel approach for learning computational models for social behavior synthesis from corpora of human-human interactions. The IPL approach combines perceptual evaluation with iterative model refinement. Human observers rate the appropriateness of

Exploring students learning approaches in MOOCs

OpenAIRE

Faucon, Louis Pierre

2017-01-01

This study aims at understanding different students approaches for solving assignments in MOOCs. It makes use of a large dataset of logs from students interaction with the MOOC platform Coursera on a course about functional programming with Scala. In total more than 10.000 students participated in the assignments. Learning approaches are divided in two categories: starting with video lectures (V) and start- ing with the assignment (A); and students are divided in three groups: those applying ...

Assessing reflective thinking and approaches to learning.

Science.gov (United States)

Dunn, Louise; Musolino, Gina M

2011-01-01

Facilitation of reflective practice is critical for the ongoing demands of health care practitioners. Reflective thinking concepts, grounded in the work of Dewey and Schön, emphasize critical reflection to promote transformation in beliefs and learning necessary for reflective practice. The Reflective Thinking Questionnaire (QRT) and Revised Study Process Questionnaire (RSPQ-2F) assess skill aspects of professional reasoning, with promise for measuring changes over time. The purpose of this study was to examine the reliability and responsiveness and the model validity of reflective thinking and approaches to learning measures for U.S. health professions students enrolled in entry-level occupational (MOT) and physical therapy (DPT) programs. This measurement study addressed reliability and responsiveness of two measures, the QRT and RSPQ-2F, for graduate health professionals. A convenience sample of 125 MOT and DPT students participated in the two-measure, test-retest investigation, with electronic data collection. Outcomes support the stability of the four-scale QRT (ICC 0.63 to 0.82) and the two-scale RSPQ-2F (ICC 0.91 and 0.87). Descriptive data supporting responsiveness are presented. With noted limitations, the results support the use of the QRT and RSPQ-2F measures to assess changes in reflective thinking and approaches to learning. Measurement of these learning outcomes furthers our understanding and knowledge about instructional strategies, development of professional reasoning, and fostering of self-directed learning within MOT and DPT programs.

Cooperative learning combined with short periods of lecturing: A good alternative in teaching biochemistry.

Science.gov (United States)

Fernández-Santander, Ana

2008-01-01

The informal activities of cooperative learning and short periods of lecturing has been combined and used in the university teaching of biochemistry as part of the first year course of Optics and Optometry in the academic years 2004-2005 and 2005-2006. The lessons were previously elaborated by the teacher and included all that is necessary to understand the topic (text, figures, graphics, diagrams, pictures, etc.). Additionally, a questionnaire was prepared for every chapter. All lessons contained three parts: objectives, approach and development, and the assessment of the topic. Team work, responsibility, and communication skills were some of the abilities developed with this new methodology. Students worked collaboratively in small groups of two or three following the teacher's instructions with short periods of lecturing that clarified misunderstood concepts. Homework was minimized. On comparing this combined methodology with the traditional one (only lecture), students were found to exhibit a higher satisfaction with the new method. They were more involved in the learning process and had a better attitude toward the subject. The use of this new methodology showed a significant increase in the mean score of the students' academic results. The rate of students who failed the subject was significantly inferior in comparison with those who failed in the previous years when only lecturing was applied. This combined methodology helped the teacher to observe the apprenticeship process of students better and to act as a facilitator in the process of building students' knowledge. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Combining deep learning and satellite data to inform sustainable development

Science.gov (United States)

Lobell, D. B.

2017-12-01

Methods in machine learning, and in particular deep learning, are quickly advancing, in parallel with dramatic increases in the availability of fine resolution satellite data. The combination of both offers the possibility to improve understanding of some of the poorest regions of the world, where traditional data sources are limited. This talk will cover recent applications to track poverty at the village level in Africa, spot the onset of disease outbreaks in agriculture, and identify land use patterns and crop productivity.

Supporting Blended-Learning: Tool Requirements and Solutions with OWLish

Science.gov (United States)

Álvarez, Ainhoa; Martín, Maite; Fernández-Castro, Isabel; Urretavizcaya, Maite

2016-01-01

Currently, most of the educational approaches applied to higher education combine face-to-face (F2F) and computer-mediated instruction in a Blended-Learning (B-Learning) approach. One of the main challenges of these approaches is fully integrating the traditional brick-and-mortar classes with online learning environments in an efficient and…

Improving Problem Solving Skill and Self Regulated Learning of Senior High School Students through Scientific Approach using Quantum Learning strategy

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M Sudirman

2017-12-01

Full Text Available This research is quasi experiment with control group pretest-postest design. The sampel in this research using the techique of purposive sampling so the samples used were two classes of the 11th grade students of SMAN 14 Bandung in the academic year 2017/2018. The experiment group uses saintific approach using Quantum Learning strategy and control group uses saintific approach. In collecting the data the researcher will use the test of problem solving ability and self regulated learning as the instrument. The aims of this research are to:1find out the improvement of students mathematical problem solving through scientific approach using Quantum Learning study, 2 find out students self regulated learning through scientific approach using Quantum Learning.

Missing links between lean startup, design thinking, and experiential learning approaches in entrepreneurship education

DEFF Research Database (Denmark)

Ramsgaard, Michael Breum; Christensen, Marie Ernst

2016-01-01

Questions we care about • How do different pedagogical teaching approaches in entrepreneurship education construct learning outcome when comparing the underlying pedagogical models? • Where can unidentified fields and correlations of pedagogical insights between the approaches of lean startup......, design thinking, and experiential learning be identified? • How can new concepts of learning models, taking lean startup, design thinking and experiential learning approaches into account, be developed in entrepreneurship education? Approach This 3e conference paper begins as a conceptual paper...... highlighting the theories and underlying learning models behind three pedagogical approaches within entrepreneurship education, namely lean startup, design thinking and experiential learning. The paper builds this knowledge framework in order to set the design for an empirical investigation of the proposed...

Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

DEFF Research Database (Denmark)

Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

2013-01-01

Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

TIME-ON-TASK IN PRIMARY CLASSROOMS, DURING DIFFERENT TEACHING-LEARNING APPROACHES

OpenAIRE

Sachin Mohite; Meenal Dashputre

2017-01-01

The entire education system is moving from the teacher-centered teaching-learning approaches towards student-centered teaching-learning approaches, with anticipation that it would increase the learning outcomes. This empirical study was carried out to compare the traditional and non-traditional classrooms. It also tried to understand the effectiveness of the Alternate Instructions in the Mathematics and Primary Language (Marathi) classrooms. This study collected about 8000 snapshots from the ...

Learning Assessment in physical education: the relationship between assessment practices of teachers and learning approaches

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Marco Vinicio Gutiérrez

2015-02-01

Full Text Available This article shows the result of an investigation that studied teachers’ assessment practices in Physical Education in public schools from Suba in Bogota and the relationship between these practices with both superfluous and superficial learning approaches. It is organized into two sections; the first presents a classification of the evaluation practices, and the second establishes the relationship between these practices with the superficial and profound learning approaches. This article nourishes itself from a mixed-method research approach wherein the sample consisted of 68 teachers from whom data was collected using a survey. This data was then analyzed using the statistical software R. The results show the object, the purpose, procedures and ways in which teachers develop their assessment practice in physical education, and as well show a trend towards promoting meaningful and profound learning.

AN ANALYSIS ON THE ADVANTAGES OF COOPERATIVE LEARNING APPROACH IN TEACHING WRITING

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Chamisah Chamisah

2013-11-01

Full Text Available This article aims to explain an analysis of cooperative learning approach advantages in teaching writing. Accordingly, learning writing by using cooperative learning makes the students easier in developing the ideas to write. This approach is more than just putting students into groups, but the students can work together, share information, and they are responsible for completion of the tasks in group as well. Besides, in this approach, the students can transfer their information and knowledge to the others and help each other in getting the ideas to develop in written communication during teaching-learning process.

Classroom quality and academic skills: Approaches to learning as a moderator.

Science.gov (United States)

Meng, Christine

2015-12-01

The purpose of this study was to examine whether approaches to learning moderated the association between child care classroom environment and Head Start children's academic skills. The data came from the Head Start Family and Child Experiences Survey (FACES-2003 Cohort). The dataset is a nationally representative longitudinal study of Head Start children. The sample was selected using the stratified 4-stage sampling procedure. Data was collected in fall 2003, spring 2004, spring 2005, and spring 2006 in the first year of kindergarten. Participants included 3- and 4-year-old Head Start children (n = 786; 387 boys, 399 girls; 119 Hispanic children, 280 African American children, 312 Caucasian children). Head Start children's academic skills in letter-word identification, dictation/spelling, and mathematics at the 4 time points were measured by the Woodcock-Johnson Achievement Battery tests. Approaches to learning in fall 2003 was measured by the teacher report of the Preschool Learning Behaviors Scale. Child care classroom quality in fall 2003 was measured by the revised Early Childhood Environment Rating Scale. Results of the linear mixed effects models demonstrated that approaches to learning significantly moderated the effect of child care classroom quality on Head Start children's writing and spelling. Specifically, positive approaches to learning mitigated the negative effect of lower levels of classroom quality on dictation/spelling. Results underscore the important role of approaches to learning as a protective factor. Implications for early childhood educators with an emphasis on learning goals for disengaged children are discussed. (c) 2015 APA, all rights reserved).

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

KAUST Repository

McCabe, Matthew

2017-12-06

with inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

Science.gov (United States)

Houborg, Rasmus; McCabe, Matthew F.

2018-01-01

inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼ 21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

KAUST Repository

McCabe, Matthew; McCabe, Matthew

2017-01-01

with inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.

Integrating knowledge exchange and the assessment of dryland management alternatives - A learning-centered participatory approach.

Science.gov (United States)

Bautista, Susana; Llovet, Joan; Ocampo-Melgar, Anahí; Vilagrosa, Alberto; Mayor, Ángeles G; Murias, Cristina; Vallejo, V Ramón; Orr, Barron J

2017-06-15

The adoption of sustainable land management strategies and practices that respond to current climate and human pressures requires both assessment tools that can lead to better informed decision-making and effective knowledge-exchange mechanisms that facilitate new learning and behavior change. We propose a learning-centered participatory approach that links land management assessment and knowledge exchange and integrates science-based data and stakeholder perspectives on both biophysical and socio-economic attributes. We outline a structured procedure for a transparent assessment of land management alternatives, tailored to dryland management, that is based on (1) principles of constructivism and social learning, (2) the participation of stakeholders throughout the whole assessment process, from design to implementation, and (3) the combination of site-specific indicators, identified by local stakeholders as relevant to their particular objectives and context conditions, and science-based indicators that represent ecosystem services of drylands worldwide. The proposed procedure follows a pattern of eliciting, challenging, and self-reviewing stakeholder perspectives that aims to facilitate learning. The difference between the initial baseline perspectives and the final self-reviewed stakeholder perspectives is used as a proxy of learning. We illustrate the potential of this methodology by its application to the assessment of land uses in a Mediterranean fire-prone area in East Spain. The approach may be applied to a variety of socio-ecological systems and decision-making and governance scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Peer learning a pedagogical approach to enhance online learning: A qualitative exploration.

Science.gov (United States)

Raymond, Anita; Jacob, Elisabeth; Jacob, Darren; Lyons, Judith

2016-09-01

Flexible online programs are becoming increasingly popular method of education for students, allowing them to complete programs in their own time and cater for lifestyle differences. A mixture of delivery modes is one way which allows for enhanced learning. Peer learning is another method of learning which is shown to foster collaboration and prepare healthcare students for their future careers. This paper reports on a project to combine peer and online learning to teach pharmacology to nursing students. To explore undergraduate nursing student opinions of working in peer groups for online learning sessions in a pharmacology course. A qualitative study utilising a self-reported questionnaire. A rural campus of an Australian university. Second year nursing students enrolled in a Bachelor of Nursing Program. A hard copy questionnaire was distributed to all students who attended the final semester lecture for the course. Content analysis of open-ended survey questions was used to identify themes in the written data. Of the 61 students enrolled in the nursing subject, 35 students chose to complete the survey (57%). Students reported a mixed view of the benefits and disadvantages of peer online learning. Sixty 6% (66%) of students liked peer online learning, whilst 29% disliked it and 6% were undecided. Convenience and ease of completion were reported as the most common reason to like peer online learning, whilst Information Technology issues, communication and non-preferred learning method were reasons for not liking peer online learning. Peer online learning groups' acted as one further method to facilitate student learning experiences. Blending peer online learning with traditional face-to-face learning increases the variety of learning methods available to students to enhance their overall learning experience. Copyright © 2016 Elsevier Ltd. All rights reserved.

Investigating the relationships between approaches to learning, learner identities and academic achievement in higher education

DEFF Research Database (Denmark)

Herrmann, Kim Jesper; Bager-Elsborg, Anna; McCune, Velda

2017-01-01

This paper considers relationships between approaches to learning, learner identities, self-efficacy beliefs and academic achievement in higher education. In addition to already established survey instruments, a new scale, subject area affinity, was developed. The scale explores the extent to which...... students identify with their area of study and imagine being part of it in future. The new scale showed strong psychometric properties when it was tested on a sample of 4377 students at a research-intensive university. The new scale correlated positively with both the deep approach and self-efficacy scales....... The new scale also correlated negatively with the surface approach scale. K-means cluster analysis identified seven distinct groups of students who espoused interpretable combinations of approaches, self-efficacy and subject area affinity. Cluster membership was associated with differences in academic...

REVIEW OF MONITORING TOOLS FOR E-LEARNING PLATFORMS

OpenAIRE

Ali Alowayr; Atta Badii

2014-01-01

The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The...

A New Approach to Programming Language Education for Beginners with Top-Down Learning

Directory of Open Access Journals (Sweden)

Daisuke Saito

2013-12-01

Full Text Available There are two basic approaches in learning new programming language: a bottom-up approach and a top-down approach. It has been said that if a learner has already acquired one language, the top-down approach is more efficient to learn another while, for a person who has absolutely no knowledge of any programming languages; the bottom-up approach is preferable. The major problem of the bottom-up approach is that it requires longer period to acquire the language. For quicker learning, this paper applies a top-down approach for a beginners who has not yet acquired any programming languages.

Episodic reinforcement learning control approach for biped walking

Directory of Open Access Journals (Sweden)

Katić Duško

2012-01-01

Full Text Available This paper presents a hybrid dynamic control approach to the realization of humanoid biped robotic walk, focusing on the policy gradient episodic reinforcement learning with fuzzy evaluative feedback. The proposed structure of controller involves two feedback loops: a conventional computed torque controller and an episodic reinforcement learning controller. The reinforcement learning part includes fuzzy information about Zero-Moment- Point errors. Simulation tests using a medium-size 36-DOF humanoid robot MEXONE were performed to demonstrate the effectiveness of our method.

Deep and shallow approaches to learning mathematics are not mutually exclusive.

OpenAIRE

Mathias, J.; Newton, D.P.

2016-01-01

From time to time, students are characterised as having a deep or shallow approach to learning. A deep approach to learning tends to attract more approval than a shallow approach, at least in the West. Students on a university-based Foundation course to prepare them for undergraduate studies were divided into those likely to have a deep approach (26) and those likely to have a shallow approach (18). Their performance in a test of problem solving in an aspect of applied mathematics was compare...

Learning "Math on the Move": Effectiveness of a Combined Numeracy and Physical Activity Program for Primary School Children.

Science.gov (United States)

Vetter, Melanie; O'Connor, Helen; O'Dwyer, Nicholas; Orr, Rhonda

2018-03-27

Physically active learning that combines physical activity with core curriculum areas is emerging in school-based health interventions. This study investigates the effectiveness of learning an important numeracy skill of times tables (TT) while concurrently engaging in aerobic activity compared with a seated classroom approach. Grade-4 primary school students were randomly allocated to physical activity (P) or classroom (C) groups and received the alternate condition in the following term. P group received moderate to vigorous exercise (20 min, 3 times per week, 6 wk) while simultaneously learning selected TT. C group received similar learning, but seated. Changes in TT accuracy, general numeracy, aerobic fitness, and body mass index were assessed. Data were expressed as mean (SEM) and between-condition effect size (ES; 95% confidence interval). Participants [N = 85; 55% male, 9.8 (0.3) y, 36.4% overweight/obese] improved similarly on TT in both conditions [C group: 2.2% (1.1%); P group: 2.5% (1.3%); ES = 0.03; -0.30 to 0.36; P = .86]. Improvement in general numeracy was significantly greater for P group than C group [C group: 0.7% (1.2%); P group: 5.3% (1.4%); ES = 0.42; 0.08 to 0.75; P < .03]. An improvement in aerobic fitness for P group (P < .01) was not significantly greater than C group [C group: 0.8 (0.6); P group: 2.2 (0.5) mL·kg·min -1 ; ES = 0.32; -0.01 to 0.66; P = .06]. Body mass index was unchanged. Combined movement with learning TT was effective. Physically active learning paradigms may contribute to meeting daily physical activity guidelines while supporting or even boosting learning.

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

Directory of Open Access Journals (Sweden)

Pontil Massimiliano

2009-10-01

Full Text Available Abstract Background Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (ΔΔG measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots" at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. Results We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which ΔΔG ≥ 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. Conclusion We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been

Evolutionary and adaptive learning in complex markets: a brief summary

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Hommes, Cars H.

2007-06-01

We briefly review some work on expectations and learning in complex markets, using the familiar demand-supply cobweb model. We discuss and combine two different approaches on learning. According to the adaptive learning approach, agents behave as econometricians using time series observations to form expectations, and update the parameters as more observations become available. This approach has become popular in macro. The second approach has an evolutionary flavor and is sometimes referred to as reinforcement learning. Agents employ different forecasting strategies and evaluate these strategies based upon a fitness measure, e.g. past realized profits. In this framework, boundedly rational agents switch between different, but fixed behavioral rules. This approach has become popular in finance. We combine evolutionary and adaptive learning to model complex markets and discuss whether this theory can match empirical facts and forecasting behavior in laboratory experiments with human subjects.

Meta-Analysis of Jelajah Alam Sekitar (JAS) Approach Implementation in Learning Process

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Ngabekti, S.; Ridlo, S.; Peniati, E.; Martanto, R.

2017-01-01

The results of tracer studies on the approach of Jelajah Alam Sekitar (JAS) or environment exploring learning has been detected is used in eight provinces in Indonesia and studied in the learning begin primary school to college. Then, how the effectiveness of the implementation of the JAS approach in improving the learning process. This study uses…

Adult Learning in Health and Safety: Some Issues and Approaches.

Science.gov (United States)

O Fathaigh, Mairtin

This document, which was developed for presentation at a seminar on adult learning and safety, examines approaches to occupational safety and health (OSH) learning/training in the workplace. Section 1 examines selected factors affecting adults' learning in workplace OSH programs. The principal dimensions along which individual adult learners will…

Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

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Thota, Neena; Whitfield, Richard

2010-01-01

This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…

High school students educational usage of Internet and their learning approaches

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M. Betül Yılmaz, Feza Orhan

2010-08-01

Full Text Available This study examines the Internet usage of high school students for educational needs in respect to their learning approaches. The “learning approach” categorizes individuals as ‘surface learners’ and ‘deep learners’. Surface learners mainly choose to rehearse and memorize the course material they work on and they acquire the information they need to learn in a disconnected way, by memorization. On the other hand, deep learners want to grasp the meaning of the course material. In the study, adapted Turkish version of Learning Process Questionnaire (LPQ was used to determine high school students’ learning approaches. 921 secondary school students were subjected and the Cronbach alpha values were 0.73 for a deep approach and 0.66 for a surface approach. According to the data obtained, surface learners use the Internet more when compared to deep learners, though they use it for non-instructional purposes. The ratios of the Internet use of deep learners for educational needs are higher when compared to those of surface learners. Ratios of the Internet use for educational needs by the students who are given assignments requiring the use of the Internet are higher.

Learning Matlab a problem solving approach

CERN Document Server

Gander, Walter

2015-01-01

This comprehensive and stimulating introduction to Matlab, a computer language now widely used for technical computing, is based on an introductory course held at Qian Weichang College, Shanghai University, in the fall of 2014.  Teaching and learning a substantial programming language aren’t always straightforward tasks. Accordingly, this textbook is not meant to cover the whole range of this high-performance technical programming environment, but to motivate first- and second-year undergraduate students in mathematics and computer science to learn Matlab by studying representative problems, developing algorithms and programming them in Matlab. While several topics are taken from the field of scientific computing, the main emphasis is on programming. A wealth of examples are completely discussed and solved, allowing students to learn Matlab by doing: by solving problems, comparing approaches and assessing the proposed solutions.

A work-based learning approach for clinical support workers on mental health inpatient wards.

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Kemp, Philip; Gilding, Moorene; Seewooruttun, Khooseal; Walsh, Hannah

2016-09-14

Background With a rise in the number of unqualified staff providing health and social care, and reports raising concerns about the quality of care provided, there is a need to address the learning needs of clinical support workers. This article describes a qualitative evaluation of a service improvement project that involved a work-based learning approach for clinical support workers on mental health inpatient wards. Aim To investigate and identify insights in relation to the content and process of learning using a work-based learning approach for clinical support workers. Method This was a qualitative evaluation of a service improvement project involving 25 clinical support workers at the seven mental health inpatient units in South London and Maudsley NHS Foundation Trust. Three clinical skills tutors were appointed to develop, implement and evaluate the work-based learning approach. Four sources of data were used to evaluate this approach, including reflective journals, qualitative responses to questionnaires, three focus groups involving the clinical support workers and a group interview involving the clinical skills tutors. Data were analysed using thematic analysis. Findings The work-based learning approach was highly valued by the clinical support workers and enhanced learning in practice. Face-to-face learning in practice helped the clinical support workers to develop practice skills and reflective learning skills. Insights relating to the role of clinical support workers were also identified, including the benefits of face-to-face supervision in practice, particularly in relation to the interpersonal aspects of care. Conclusion A work-based learning approach has the potential to enhance care delivery by meeting the learning needs of clinical support workers and enabling them to apply learning to practice. Care providers should consider how the work-based learning approach can be used on a systematic, organisation-wide basis in the context of budgetary

Contract Learning as an Approach to Individualizing EFL Education in the Context of Assessment for Learning

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Zandi, Hamed; Kaivanpanah, Shiva; Alavi, Sayyed Mohammad

2015-01-01

Contract learning as an approach to individualizing education in the context of assessment for learning is relatively underexplored in English as a Foreign Language instruction. The present study used a mixed-methods design to investigate its efficacy to provide feedback to students and improve self-directed learning. Furthermore, it studied…

Individual Learning in Construction Projects: Professions and their Approaches

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Ingeborg Wasif

2010-10-01

Full Text Available New materials, use of sophisticated technologies and increased customer demands, in combination with growing competition among construction companies, have led to a high organizational boundaries. The results indicate that personal networks are the most common source of learning for all professions. While clients, architects, and designers also engage in reading and attending courses, site managers and workers are less engaged in these activities. Experimenting and organizing for learning appear to be underutilized strategies by all professions. This leads to the conclusion that attempts to increase learning have to address the differences in learning behaviours of the various groups. Further, focus on experimenting and organizing for learning is a possibility to change the learning behaviour from learning as a consequence of problems to learning for future improvement.degree of specialization. For successful integration of the different professional specialists, there is a need for shared learning between project co-workers. Based on twenty eight interviews in six different Swedish construction projects, this paper illustrates strategies for individual and shared learning, among different actors and across various

Service-Learning Instructional Design Considerations

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Maddrell, Jennifer

2014-01-01

This paper explores the design of "service-learning" experiences to engage college students in the real-world application of course subject matter. Service learning is an educational approach that combines community service, academic coursework, and work-based applied learning. Based on data gathered during a series of recent interviews…

Multi-Kernel Learning with Dartel Improves Combined MRI-PET Classification of Alzheimer’s Disease in AIBL Data: Group and Individual Analyses

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Vahab Youssofzadeh

2017-07-01

Full Text Available Magnetic resonance imaging (MRI and positron emission tomography (PET are neuroimaging modalities typically used for evaluating brain changes in Alzheimer’s disease (AD. Due to their complementary nature, their combination can provide more accurate AD diagnosis or prognosis. In this work, we apply a multi-modal imaging machine-learning framework to enhance AD classification and prediction of diagnosis of subject-matched gray matter MRI and Pittsburgh compound B (PiB-PET data related to 58 AD, 108 mild cognitive impairment (MCI and 120 healthy elderly (HE subjects from the Australian imaging, biomarkers and lifestyle (AIBL dataset. Specifically, we combined a Dartel algorithm to enhance anatomical registration with multi-kernel learning (MKL technique, yielding an average of >95% accuracy for three binary classification problems: AD-vs.-HE, MCI-vs.-HE and AD-vs.-MCI, a considerable improvement from individual modality approach. Consistent with t-contrasts, the MKL weight maps revealed known brain regions associated with AD, i.e., (parahippocampus, posterior cingulate cortex and bilateral temporal gyrus. Importantly, MKL regression analysis provided excellent predictions of diagnosis of individuals by r2 = 0.86. In addition, we found significant correlations between the MKL classification and delayed memory recall scores with r2 = 0.62 (p < 0.01. Interestingly, outliers in the regression model for diagnosis were mainly converter samples with a higher likelihood of converting to the inclined diagnostic category. Overall, our work demonstrates the successful application of MKL with Dartel on combined neuromarkers from different neuroimaging modalities in the AIBL data. This lends further support in favor of machine learning approach in improving the diagnosis and risk prediction of AD.

A Bayesian concept learning approach to crowdsourcing

DEFF Research Database (Denmark)

Viappiani, P.; Zilles, S.; Hamilton, H.J.

2011-01-01

techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing......We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...

systemic approach to teaching and learning chemistry

African Journals Online (AJOL)

unesco

2National Core Group in Chemistry, H.E.J Research Institute of Chemistry,. University of ... innovative way of teaching and learning through systemic approach (SATL) has been .... available to do useful work in a thermodynamic process.

Combining extreme learning machines using support vector machines for breast tissue classification.

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Daliri, Mohammad Reza

2015-01-01

In this paper, we present a new approach for breast tissue classification using the features derived from electrical impedance spectroscopy. This method is composed of a feature extraction method, feature selection phase and a classification step. The feature extraction phase derives the features from the electrical impedance spectra. The extracted features consist of the impedivity at zero frequency (I0), the phase angle at 500 KHz, the high-frequency slope of phase angle, the impedance distance between spectral ends, the area under spectrum, the normalised area, the maximum of the spectrum, the distance between impedivity at I0 and the real part of the maximum frequency point and the length of the spectral curve. The system uses the information theoretic criterion as a strategy for feature selection and the combining extreme learning machines (ELMs) for the classification phase. The results of several ELMs are combined using the support vector machines classifier, and the result of classification is reported as a measure of the performance of the system. The results indicate that the proposed system achieves high accuracy in classification of breast tissues using the electrical impedance spectroscopy.

The flipped learning approach in teaching degrees: students’ perceptions

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Déborah Martín R.

2017-05-01

Full Text Available In this paper, we analyze the students' perception of a university teaching-learning strategy, with a flipped learning approach, in the development of the subject Orientación educativa y plan de acción tutorial del Grado de Educación Primaria. The 21st century skills proposed by Fullan (2013 and known as the six Cs (Character, Communication, Collaboration, Citizenship, Critical Thinking and Creativity are used as a frame of reference. An experimental design of two groups, with a non-equivalent control group, has been used to analyze the students' perceptions of their learning in a conventional teaching environment and under a flipped environment based on m-learning. The differences found were statistically significant in all the analyzed dimensions, with favorable increases in the experimental methodology in all cases. The differences in Citizenship, Character, and Communication are of particular relevance. The analysis of the items reveals some difficulties in the functional literacy of students in the use of digital technology to improve their learning. Likewise, it is evident that the active methodologies improve, according to the perception of the students, the skills development, and learning. It is confirmed the hypothesis proposed in this study that the use of m-learning with a pedagogical approach centered on learning, with active methodologies, is a support that improves the development of the competences of the 21st century and, specifically, those described as the 6C's.

A Blended Learning Approach to Teach Fluid Mechanics in Engineering

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Rahman, Ataur

2017-01-01

This paper presents a case study on the teaching and learning of fluid mechanics at the University of Western Sydney (UWS), Australia, by applying a blended learning approach (BLA). In the adopted BLA, various flexible learning materials have been made available to the students such as online recorded lectures, online recorded tutorials, hand…

Exploring a Problem-Based Learning Approach in Pharmaceutics

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Barbara McKenzie

2017-09-01

Full Text Available Objective. The basis of this study was to explore the impact of the initiation of a Problem-Base Learning (PBL approach within a second-year pharmaceutics degree on a Master of Pharmacy programme, introduced as a way of improving deep learning and to foster independent learning. Design. A semi-structured interview was used to seek feedback from the students, and feedback from staff was secured though a focus group. A thematic approach was used for the analysis, once data saturation had been reached. Exam pass-rate statistics were also analysed. Assessment. Five parent themes were identified from the student interviews: Module structure, Promoting lifelong learning, Integration and future practice, Outcomes and Student experience. The third year exam pass rate improved by 12% in the year following the introduction of PBL in second year. Conclusions. Various recommendations were proposed to further improve the module, based on the findings of this study. These include improving feedback and support through tutorials, reducing the volume of directed study, as well as highlighting the relevance of pharmaceutics to the pharmacy degree. A long-term review would be needed to assess the full implications of PBL teaching within this course.

Using Flipped Classroom Approach to Explore Deep Learning in Large Classrooms

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Danker, Brenda

2015-01-01

This project used two Flipped Classroom approaches to stimulate deep learning in large classrooms during the teaching of a film module as part of a Diploma in Performing Arts course at Sunway University, Malaysia. The flipped classes utilized either a blended learning approach where students first watched online lectures as homework, and then…

Active Learning Innovations in Knowledge Management Education Generate Higher Quality Learning Outcomes

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Arthur Shelley

2014-01-01

Full Text Available Innovations in how a postgraduate course in knowledge management is delivered have generated better learning outcomes and made the course more engaging for learners. Course participant feedback has shown that collaborative active learning is preferred and provides them with richer insights into how knowledge is created and applied to generate innovation and value. The course applies an andragogy approach in which students collaborate in weekly dialogue of their experiences of the content, rather than learn the content itself. The approach combines systems thinking, learning praxis, and active learning to explore the interdependencies between topics and how they impact outcomes in real world situations. This has stimulated students to apply these ideas in their own workplaces.

The Trialogical Learning Approach to innovate teaching

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Nadia Sansone

2016-11-01

Full Text Available This article focuses on a case of implementing the Trialogical Learning Approach (TLA in two classes in the first year of a university school for future osteopaths (N = 36. The approach involves the creation of useful and tangible objects through alternation between individual and group activities, supported by digital technologies. The aim of the study is to observe the impact of TLA on the quality of learning products made by students and on teaching style, as well as to collect students’ views on activities. The collected data (individual and group products, notes inserted online, audio recordings of lessons, final questionnaires have been analyzed using a mixed qualitative and quantitative approach. The results show: a positive evolution in the quality of individual and group products; b progression from a transmissive teaching style towards one more oriented to collaboration and knowledge building; c general appreciation of the innovative method and its potential for fostering social skills useful for future employment.

Making Learning and Web 2.0 Technologies Work for Higher Learning Institutions in Africa

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Lwoga, Edda

2012-01-01

Purpose: This paper seeks to assess the extent to which learning and Web 2.0 technologies are utilised to support learning and teaching in Africa's higher learning institutions, with a specific focus on Tanzania's public universities. Design/methodology/approach: A combination of content analysis and semi-structured interviews was used to collect…

The E-Learning Setting Circle: First Steps toward Theory Development in E-Learning Research

Science.gov (United States)

Rüth, Marco; Kaspar, Kai

2017-01-01

E-learning projects and related research generate an increasing amount of evidence within and across various disciplines and contexts. The field is very heterogeneous as e-learning approaches are often characterized by rather unique combinations of situational factors that guide the design and realization of e-learning in a bottom-up fashion.…

Epistemological Belief and Learning Approaches of Students in Higher Institutions of Learning in Malaysia

Science.gov (United States)

Ismail, Habsah; Hassan, Aminuddin; Muhamad, Mohd. Mokhtar; Ali, Wan Zah Wan; Konting, Mohd. Majid

2013-01-01

This is an investigation of the students' beliefs about the nature of knowledge or epistemological beliefs, and the relation of these beliefs on their learning approaches. Students chosen as samples of the study were from both public and private higher institutions of learning in Malaysia. The instrument used in the study consists of 49 items…

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

Science.gov (United States)

Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

2015-01-01

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

E-learning paradigms and applications agent-based approach

CERN Document Server

Jain, Lakhmi

2014-01-01

Teaching and learning paradigms have attracted increased attention especially in the last decade. Immense developments of different ICT technologies and services have paved the way for alternative but effective approaches in educational processes. Many concepts of the agent technology, such as intelligence, autonomy, and cooperation, have had a direct positive impact on many of the requests imposed on modern e-learning systems and educational processes. This book presents the state-of-the-art of e-learning and tutoring systems, and discusses their capabilities and benefits that stem from integrating software agents. We hope that the presented work will be of a great use to our colleagues and researchers interested in the e-learning and agent technology.    

Blended learning tools for teaching and training

CERN Document Server

Allan, Barbara

2007-01-01

Offers a holistic blended learning approach, combining the best of traditional approaches to learning and teaching to make best use of the advantages of each while minimizing the disadvantages. It provides information professionals with a practical guide to the design and delivery of such training programmes.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

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Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

Multimodal approaches to use mobile, digital devices in learning practies

DEFF Research Database (Denmark)

Buhl, Mie

, anthropology, psychology and sociology) and outlines the prospect of a trans-disciplinary learning mode. The learning mode reflects the current society where knowledge production is social collaborative process and is produced in formal as well as informal and non-formal contexts. My discussion’s theoretical......In this paper, I discuss the potential of multimodal approaches to enhance learning processes. I draw on a case based on Danish Master Courses in ICT and didactic designs where multimodal approaches are in the center of students’ practical design experience as well as in generation of theoretical...... knowledge. The design of the master courses takes its starting point in the assumption that theoretical knowledge generates from practical experiences. Thus, the organization of the students’ learning processes revolves around practical multimodal experiences followed by iterative reflexive sessions...

Cultivating collaborative improvement: an action learning approach

NARCIS (Netherlands)

Middel, H.G.A.; McNichols, Timothy

2006-01-01

The process of implementing collaborative initiatives across disparate members of supply networks is fraught with difficulties. One approach designed to tackle the difficulties of organisational change and interorganisational improvement in practice is 'action learning'. This paper examines the

Function approximation using combined unsupervised and supervised learning.

Science.gov (United States)

Andras, Peter

2014-03-01

Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasing volume of data as the dimensionality of the data increases. At the same time, often the high-dimensional data is arranged around a much lower dimensional manifold. Here we propose the breaking of the function approximation task for high-dimensional data into two steps: (1) the mapping of the high-dimensional data onto a lower dimensional space corresponding to the manifold on which the data resides and (2) the approximation of the function using the mapped lower dimensional data. We use over-complete self-organizing maps (SOMs) for the mapping through unsupervised learning, and single hidden layer neural networks for the function approximation through supervised learning. We also extend the two-step procedure by considering support vector machines and Bayesian SOMs for the determination of the best parameters for the nonlinear neurons in the hidden layer of the neural networks used for the function approximation. We compare the approximation performance of the proposed neural networks using a set of functions and show that indeed the neural networks using combined unsupervised and supervised learning outperform in most cases the neural networks that learn the function approximation using the original high-dimensional data.

Influence of the Constructivist Learning Approach on Students' Levels of Learning Trigonometry and on Their Attitudes towards Mathematics

OpenAIRE

İNAN, CEMİL

2014-01-01

In this experimental study, the influence of the constructivist learning approach on students’ levels of learning trigonometry and on their attitudes towards mathematics was examined in comparison with the traditional methods of instruction. The constructivist learning approach was the independent variable, while mathematics achievement, the lessons of trigonometry and the attitudes towards mathematics constituted the dependent variables. The study was designed as the pretest-posttest control...

A Holistic Approach to Scoring in Complex Mobile Learning Scenarios

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Gebbe, Marcel; Teine, Matthias; Beutner, Marc

2016-01-01

Interactive dialogues are key elements for designing authentic and motivating learning situations, and in combination with learning analysis they provide educators and users with the opportunity to track information related to professional competences, but mind-sets as well. This paper offers exemplary insights into the project NetEnquiry that is…

Integrating transformative learning and action learning approaches to enhance ethical leadership for supervisors in the hotel business

OpenAIRE

Boonyuen Saranya; Charungkaittikul Suwithida; Ratana-ubol Archanya

2016-01-01

Ethical leadership is now increasingly focused in leadership development. The main purpose of this study is to explore two methods of adult learning, action learning and transformative learning, and to use the methods to enhance ethical leadership. Building ethical leadership requires an approach that focuses on personal values, beliefs, or frames of references, which is transformative learning. Transformative learning requires a series of meetings to conduct critical discourse and to follow ...

On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

NARCIS (Netherlands)

Melendez Rodriguez, J.C.; Ginneken, B. van; Maduskar, P.; Philipsen, R.H.H.M.; Ayles, H.; Sanchez, C.I.

2016-01-01

The major advantage of multiple-instance learning (MIL) applied to a computer-aided detection (CAD) system is that it allows optimizing the latter with case-level labels instead of accurate lesion outlines as traditionally required for a supervised approach. As shown in previous work, a MIL-based

The Semiotic Approach and Language Teaching and Learning

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Müfit Şenel

2007-04-01

Full Text Available This study investigates the relation of the Foreign Language Teaching with the SemioticApproach that gains more importance recently and tries to explain how this concept has beenused as Semiotic Approach in Foreign Language Teaching and Learning and teacher-learnerroles, strong-weak sides, types of activities, etc. have been handled.

Digging deeper on "deep" learning: A computational ecology approach.

Science.gov (United States)

Buscema, Massimo; Sacco, Pier Luigi

2017-01-01

We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of many different examples of a single situation, we opt for model-based learning and adaptive flexibility. Cross-fertilization of learning processes across multiple domains is the fundamental feature of human intelligence that must inform "new" artificial intelligence.

Study Circles in Online Learning Environment in the Spirit of Learning-Centered Approach

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Simándi Szilvia

2017-08-01

Full Text Available Introduction: In the era of information society and knowledge economy, learning in non-formal environments gets a highlighted role: it can supplement, replace or raise the knowledge and skills gained in the school system to a higher level (Forray & Juhász, 2008, as the so-called “valid” knowledge significantly changes due to the acceleration of development. With the appearance of information technology means and their booming development, the possibilities of gaining information have widened and, according to the forecasts, the role of learning communities will grow. Purpose: Our starting point is that today, with the involvement of community sites (e.g. Google+, Facebook etc. there is a new possibility for inspiring learning communities: by utilizing the power of community and the possibilities of network-based learning (Ollé & Lévai, 2013. Methods: We intend to make a synthesis based on former research and literature focusing on the learning-centered approach, online learning environment, learning communities and study circles (Noesgaard & Ørngreen, 2015; Biggs & Tang, 2007; Kindström, 2010 Conclusions: The online learning environment can be well utilized for community learning. In the online learning environment, the process of learning is built on activity-oriented work for which active participation, and an intensive, initiative communication are necessary and cooperative and collaborative learning get an important role.

Affective Underpinnings of Surface Approaches to Learning and Their Relationship with Sensation Seeking

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Robinson, Peter M.

2018-01-01

Surface approaches to learning materials and tasks are a commonplace challenge to teachers, and they prove difficult to shift, even among students who are otherwise talented or motivated to learn. The present study investigates a theory that surface approaches are triggered by a suboptimal, aversive response to learning stimuli, which overrides…

Developing a Competency-Based Assessment Approach for Student Learning

Science.gov (United States)

Dunning, Pamela T.

2014-01-01

Higher education accrediting bodies are increasing the emphasis on assessing student learning outcomes as opposed to teaching methodology. The purpose of this article is to describe the process used by Troy University's Master of Public Administration program to change their assessment approach from a course learning objective perspective to a…

ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

NARCIS (Netherlands)

Drachsler, Hendrik; Pecceu, Dries; Arts, Tanja; Hutten, Edwin; Rutledge, Lloyd; Van Rosmalen, Peter; Hummel, Hans; Koper, Rob

2009-01-01

Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. Presentation at the 2nd Workshop Mash-Up Personal Learning

ONLINE EDUCATION, ACTIVE LEARNING, AND ANDRAGOGY: An approach for Student Engagement

OpenAIRE

CARUTH, Gail D.

2015-01-01

Online learning opportunities have become essential for today’s colleges and universities. Online technology can support active learning approaches to learning. The purpose of the paper was to investigate why active learning in online classes has a positive effect on student engagement. A review of the literature revealed that research studies have been conducted to investigate the benefits of active learning. There exists extensive evidence to support the notion that active learning enhances...

Storytelling: a teaching-learning technique.

Science.gov (United States)

Geanellos, R

1996-03-01

Nurses' stories, arising from the practice world, reconstruct the essence of experience as lived and provide vehicles for learning about nursing. The learning process is forwarded by combining storytelling and reflection. Reflection represents an active, purposive, contemplative and deliberative approach to learning through which learners create meaning from the learning experience. The combination of storytelling and reflection allows the creation of links between the materials at hand and prior and future learning. As a teaching-learning technique storytelling engages learners; organizes information; allows exploration of shared lived experiences without the demands, responsibilities and consequences of practice; facilitates remembering; enhances discussion, problem posing and problem solving; and aids understanding of what it is to nurse and to be a nurse.

Manpower allocation in a cellular manufacturing system considering the impact of learning, training and combination of learning and training in operator skills

Directory of Open Access Journals (Sweden)

Masoud

2017-01-01

Full Text Available In this article, a manpower allocation and cell loading problem is studied, where demand is sto-chastic. The inter-cell and intra-cell movements are considered and attention is focused on as-signing operators with different skill levels to operations, because cell performance in addition to load cell is dependent on manpower. The purpose of this article is manpower allocation in cellu-lar manufacturing with consideration to learning and training policies. The manpower skill levels are determined in order to enhance production rate. The main contribution of this approach is the scenarios of training and learning in addition to the combination of training and learning being simulated. By using these three scenarios, the skill level of workers increase which reduces the processing time. In this regard cell layout is static where processing times and customer demand follow a normal distribution. As one of the significant costs of industrial unit is related to pro-duction cost, this study has attempted to reduce these costs by increasing the skill level of opera-tor which causes to reduce the processing time. Scenarios are evaluated by using a simulation method that finally attained results indicate this simulation provides better manpower assign-ments.

A Review of Adventure Learning

Directory of Open Access Journals (Sweden)

George Veletsianos

2009-12-01

Full Text Available Adventure learning (AL is an approach for the design of digitally-enhanced teaching and learning environments driven by a framework of guidelines grounded on experiential and inquiry-based education. The purpose of this paper is to review the adventure learning literature and to describe the status quo of the practice by identifying the current knowledge, misconceptions, and future opportunities in adventure learning. Specifically, the authors present an integrative analysis of the adventure learning literature, identify knowledge gaps, present future research directions, and discuss research methods and approaches that may improve the AL approach.The authors engaged in a systematic search strategy to identify adventure learning studies then applied a set of criteria to decide whether to include or exclude each study. Results from the systematic review were combined, analyzed, and critiqued inductively using the constant comparative method and weaved together using the qualitative metasynthesis approach.Results indicate the appeal and promise of the adventure learning approach. Nevertheless, the authors recommend further investigation of the approach. Along with studies that investigate learning outcomes, aspects of the AL approach that are engaging, and the nature of expert-learner collaboration, future adventure learning projects that focus on higher education and are (a small and (b diverse can yield significant knowledge into adventure learning. Research and design in this area will benefit by taking an activity theory and design-based research perspective.

Multi-modal Social Networks: A MRF Learning Approach

Science.gov (United States)

2016-06-20

Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

Learning from project experiences using a legacy-based approach

Science.gov (United States)

Cooper, Lynne P.; Majchrzak, Ann; Faraj, Samer

2005-01-01

As project teams become used more widely, the question of how to capitalize on the knowledge learned in project teams remains an open issue. Using previous research on shared cognition in groups, an approach to promoting post-project learning was developed. This Legacy Review concept was tested on four in tact project teams. The results from those test sessions were used to develop a model of team learning via group cognitive processes. The model and supporting propositions are presented.

A Challenge-Feedback Learning Approach to Teaching International Business

Science.gov (United States)

Sternad, Dietmar

2015-01-01

This article introduces a challenge-feedback learning (CFL) approach based on the goal-setting theory of human motivation, the deliberate practice theory of expert performance, and findings from the research on active and collaborative learning. The core of the teaching concept is the CFL cycle in which students repeatedly progress through four…

Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

Science.gov (United States)

Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

2017-11-01

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

Focusing on first year assessment: Surface or deep approaches to learning?

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Sharn Donnison

2012-08-01

Full Text Available This paper investigates the assessment and learning approaches that some first year students employ to assist them in their transition into their first year of study and extends our previous work on first year student engagement and timely academic support (Penn-Edwards & Donnison, 2011. It is situated within the First Year transition and student engagement literature and specifically speaks to concepts of learning within that body of literature. In this paper we argue that while students are in the transitional period of their studies, the use of assessment as a motivator for learning (surface approach is valid first year pedagogy and forms an initial learning stage in the student’s progress towards being lifelong learners. 

Personal computer versus personal computer/mobile device combination users' preclinical laboratory e-learning activity.

Science.gov (United States)

Kon, Haruka; Kobayashi, Hiroshi; Sakurai, Naoki; Watanabe, Kiyoshi; Yamaga, Yoshiro; Ono, Takahiro

2017-11-01

The aim of the present study was to clarify differences between personal computer (PC)/mobile device combination and PC-only user patterns. We analyzed access frequency and time spent on a complete denture preclinical website in order to maximize website effectiveness. Fourth-year undergraduate students (N=41) in the preclinical complete denture laboratory course were invited to participate in this survey during the final week of the course to track login data. Students accessed video demonstrations and quizzes via our e-learning site/course program, and were instructed to view online demonstrations before classes. When the course concluded, participating students filled out a questionnaire about the program, their opinions, and devices they had used to access the site. Combination user access was significantly more frequent than PC-only during supplementary learning time, indicating that students with mobile devices studied during lunch breaks and before morning classes. Most students had favorable opinions of the e-learning site, but a few combination users commented that some videos were too long and that descriptive answers were difficult on smartphones. These results imply that mobile devices' increased accessibility encouraged learning by enabling more efficient time use between classes. They also suggest that e-learning system improvements should cater to mobile device users by reducing video length and including more short-answer questions. © 2016 John Wiley & Sons Australia, Ltd.

Combining machine learning and matching techniques to improve causal inference in program evaluation.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2016-12-01

Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balance is assessed before estimating treatment effects. This paper introduces a novel analytic framework utilizing a machine learning algorithm called optimal discriminant analysis (ODA) for assessing covariate balance and estimating treatment effects, once the matching strategy has been implemented. This framework holds several key advantages over the conventional approach: application to any variable metric and number of groups; insensitivity to skewed data or outliers; and use of accuracy measures applicable to all prognostic analyses. Moreover, ODA accepts analytic weights, thereby extending the methodology to any study design where weights are used for covariate adjustment or more precise (differential) outcome measurement. One-to-one matching on the propensity score was used as the matching strategy. Covariate balance was assessed using standardized difference in means (conventional approach) and measures of classification accuracy (ODA). Treatment effects were estimated using ordinary least squares regression and ODA. Using empirical data, ODA produced results highly consistent with those obtained via the conventional methodology for assessing covariate balance and estimating treatment effects. When ODA is combined with matching techniques within a treatment effects framework, the results are consistent with conventional approaches. However, given that it provides additional dimensions and robustness to the analysis versus what can currently be achieved using conventional approaches, ODA offers an appealing alternative. © 2016 John Wiley & Sons, Ltd.

Dyslexia, authorial identity, and approaches to learning and writing: a mixed methods study.

Science.gov (United States)

Kinder, Julianne; Elander, James

2012-06-01

Dyslexia may lead to difficulties with academic writing as well as reading. The authorial identity approach aims to help students improve their academic writing and avoid unintentional plagiarism, and could help to understand dyslexic students' approaches to writing. (1) To compare dyslexic and non-dyslexic students' authorial identity and approaches to learning and writing; (2) to compare correlations between approaches to writing and approaches to learning among dyslexic and non-dyslexic students; (3) to explore dyslexic students' understandings of authorship and beliefs about dyslexia, writing and plagiarism. Dyslexic (n= 31) and non-dyslexic (n= 31) university students. Questionnaire measures of self-rated confidence in writing, understanding of authorship, knowledge to avoid plagiarism, and top-down, bottom-up and pragmatic approaches to writing (Student Authorship Questionnaire; SAQ), and deep, surface and strategic approaches to learning (Approaches and Study Skills Inventory for Students; ASSIST), plus qualitative interviews with dyslexic students with high and low SAQ scores. Dyslexic students scored lower for confidence in writing, understanding authorship, and strategic approaches to learning, and higher for surface approaches to learning. Correlations among SAQ and ASSIST scores were larger and more frequently significant among non-dyslexic students. Self-rated knowledge to avoid plagiarism was associated with a top-down approach to writing among dyslexic students and with a bottom-up approach to writing among non-dyslexic students. All the dyslexic students interviewed described how dyslexia made writing more difficult and reduced their confidence in academic writing, but they had varying views about whether dyslexia increased the risk of plagiarism. Dyslexic students have less strong authorial identities, and less congruent approaches to learning and writing. Knowledge to avoid plagiarism may be more salient for dyslexic students, who may benefit from

Factors Contributing to Changes in a Deep Approach to Learning in Different Learning Environments

Science.gov (United States)

Postareff, Liisa; Parpala, Anna; Lindblom-Ylänne, Sari

2015-01-01

The study explored factors explaining changes in a deep approach to learning. The data consisted of interviews with 12 students from four Bachelor-level courses representing different disciplines. We analysed and compared descriptions of students whose deep approach either increased, decreased or remained relatively unchanged during their courses.…

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Science.gov (United States)

Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan

2015-07-01

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.

Modeling the Relations among Students' Epistemological Beliefs, Motivation, Learning Approach, and Achievement

Science.gov (United States)

Kizilgunes, Berna; Tekkaya, Ceren; Sungur, Semra

2009-01-01

The authors proposed a model to explain how epistemological beliefs, achievement motivation, and learning approach related to achievement. The authors assumed that epistemological beliefs influence achievement indirectly through their effect on achievement motivation and learning approach. Participants were 1,041 6th-grade students. Results of the…

Regulating approaches to learning: Testing learning strategy convergences across a year at university.

Science.gov (United States)

Fryer, Luke K; Vermunt, Jan D

2018-03-01

Contemporary models of student learning within higher education are often inclusive of processing and regulation strategies. Considerable research has examined their use over time and their (person-centred) convergence. The longitudinal stability/variability of learning strategy use, however, is poorly understood, but essential to supporting student learning across university experiences. Develop and test a person-centred longitudinal model of learning strategies across the first-year university experience. Japanese university students (n = 933) completed surveys (deep and surface approaches to learning; self, external, and lack of regulation) at the beginning and end of their first year. Following invariance and cross-sectional tests, latent profile transition analysis (LPTA) was undertaken. Initial difference testing supported small but significant differences for self-/external regulation. Fit indices supported a four-group model, consistent across both measurement points. These subgroups were labelled Low Quality (low deep approaches and self-regulation), Low Quantity (low strategy use generally), Average (moderate strategy use), and High Quantity (intense use of all strategies) strategies. The stability of these groups ranged from stable to variable: Average (93% stayers), Low Quality (90% stayers), High Quantity (72% stayers), and Low Quantity (40% stayers). The three largest transitions presented joint shifts in processing/regulation strategy preference across the year, from adaptive to maladaptive and vice versa. Person-centred longitudinal findings presented patterns of learning transitions that different students experience during their first year at university. Stability/variability of students' strategy use was linked to the nature of initial subgroup membership. Findings also indicated strong connections between processing and regulation strategy changes across first-year university experiences. Implications for theory and practice are discussed. �

Effect of Work-Based Learning Approach Genius Scientific Judging of the Physics Learning Achievement of Knowledge Early SMPN 13 Balikpapan in 2012

Directory of Open Access Journals (Sweden)

Suliyono Suliyono

2014-06-01

Full Text Available Pengaruh Pendekatan Genius Learning Berbasis Kerja Ilmiah terhadap Prestasi Belajar Fisika Ditinjau dari  Pengetahuan Awal Siswa SMPN 13 Balikpapan Tahun 2012 Abstract: student mastery of the concepts of physics would be better if teachers implement instructional strategies that can make students more active and motivated, but still maintain a constructivist. Work-Based Learning Approach Scientific Genius (GLBKI is believed to be able to answer the demands of the development of education and facilitate students in learning physics concepts. The purpose of this study was to examine student achievement studying the Work-Based Learning Approach Genius Scientific and conventional learning. GLBKI approach to the treatment of experimental classes randomly selected and control classes conducted conventional learning. Learning achievement data collected by physics learning achievement tests. Results of the study are:  (1 there is a significant difference between student achievement through conventional learning and work-based learning approach scientific genius, (2 students who studied with GLBKI approach has physics learning achievement higher than the students who studied with conventional learning, ( 3 learning by using the Work-Based Learning Approach Scientific Genius can deliver improved student achievement is higher than the students who studied with conventional learning. Key words: work-based learning strategies genius of scientific, academic achievement, prior knowledge Abstrak: Penguasaan siswa terhadap konsep-konsep fisika akan lebih baik apabila pendidik menerap-kan strategi pembelajaran yang dapat membuat siswa lebih aktif dan termotivasi, namun tetap memper-tahankan konstruktivis. Pendekatan Genius Learning Berbasis Kerja Ilmiah (GLBKI diyakini mampu menjawab tuntutan perkembangan pendidikan dan mempermudah siswa dalam mempelajari konsep-konsep fisika. Tujuan penelitian ini adalah untuk menguji  prestasi belajar siswa yang belajar

Facilitating long-term changes in student approaches to learning science.

Science.gov (United States)

Buchwitz, Brian J; Beyer, Catharine H; Peterson, Jon E; Pitre, Emile; Lalic, Nevena; Sampson, Paul D; Wakimoto, Barbara T

2012-01-01

Undergraduates entering science curricula differ greatly in individual starting points and learning needs. The fast pace, high enrollment, and high stakes of introductory science courses, however, limit students' opportunities to self-assess and modify learning strategies. The University of Washington's Biology Fellows Program (BFP) intervenes through a 20-session, premajors course that introduces students to the rigor expected of bioscience majors and assists their development as science learners. This study uses quantitative and qualitative approaches to assess whether the 2007-2009 BFP achieved its desired short- and long-term impacts on student learning. Adjusting for differences in students' high school grade point average and Scholastic Aptitude Test scores, we found that participation in the BFP was associated with higher grades in two subsequent gateway biology courses, across multiple quarters and instructors. Two to 4 yr after participating in the program, students attributed changes in how they approached learning science to BFP participation. They reported having learned to "think like a scientist" and to value active-learning strategies and learning communities. In addition, they reported having developed a sense of belonging in bioscience communities. The achievement of long-term impacts for a short-term instructional investment suggests a practical means to prepare diverse students for the rigors of science curricula.

Educational environment and approaches to learning of undergraduate nursing students in an Indonesian school of nursing.

Science.gov (United States)

Rochmawati, Erna; Rahayu, Gandes Retno; Kumara, Amitya

2014-11-01

The aims of this study were to assess students' perceptions of their educational environment and approaches to learning, and determine if perceptions of learning environment associates with approaches to learning. A survey was conducted to collect data from a regional private university in Indonesia. A total of 232 nursing students completed two questionnaires that measured their perceptions of educational environment and approaches to learning. The measurement was based on Dundee Ready Education Environment Measurement (DREEM) and Approaches and Study Skills Inventory for Students (ASSIST). Five learning environments dimensions and three learning approaches dimensions from two measures were measured. The overall score of DREEM was 131.03/200 (SD 17.04), it was in the range considered to be favourable. The overall score is different significantly between years of study (p value = 0.01). This study indicated that the majority of undergraduate nursing students' adopt strategic approach (n = 139. 59.9%). The finding showed that perceived educational environment significantly associated with approaches to learning. This study implicated the need to maintain conducive learning environment. There is also a need to improve the management of learning activities that reflect the use of student-centered learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Examining the Roles of Blended Learning Approaches in Computer-Supported Collaborative Learning (CSCL) Environments: A Delphi Study

Science.gov (United States)

So, Hyo-Jeong; Bonk, Curtis J.

2010-01-01

In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…

The Development of Scientific Literacy through Nature of Science (NoS) within Inquiry Based Learning Approach

Science.gov (United States)

Widowati, A.; Widodo, E.; Anjarsari, P.; Setuju

2017-11-01

Understanding of science instructional leading to the formation of student scientific literacy, seems not yet fully understood well by science teachers. Because of this, certainly needs to be reformed because science literacy is a major goal in science education for science education reform. Efforts of development science literacy can be done by help students develop an information conception of the Nature of Science (NoS) and apply inquiry approach. It is expected that students’ science literacy can develop more optimal by combining NoS within inquiry approach. The purpose of this research is to produce scientific literacy development model of NoS within inquiry-based learning. The preparation of learning tools will be maked through Research and Development (R & D) following the 4-D model (Define, Design, Develop, and Disseminate) and Borg & Gall. This study is a follow-up of preliminary research results about the inquiry profile of junior high school students indicating that most categories are quite good. The design of the model NoS within inquiry approach for developing scientific literacy is using MER Model in development educational reconstruction. This research will still proceed to the next stage that is Develop.

Mathematical beauty in service of deep approach to learning

DEFF Research Database (Denmark)

Karamehmedovic, Mirza

2015-01-01

was hands-on MATLAB programming, where the algorithms were tested and applied to solve physical modelbased problems. To encourage a deep approach, and discourage a surface approach to learning, I introduced into the lectures a basic but rigorous mathematical treatment of crucial theoretical points...

Think Pair Share Using Realistic Mathematics Education Approach in Geometry Learning

Science.gov (United States)

Afthina, H.; Mardiyana; Pramudya, I.

2017-09-01

This research aims to determine the impact of mathematics learning applying Think Pair Share (TPS) using Realistic Mathematics Education (RME) viewed from mathematical-logical intelligence in geometry learning. Method that used in this research is quasi experimental research The result of this research shows that (1) mathematics achievement applying TPS using RME approach gives a better result than those applying direct learning model; (2) students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low one, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one; (3) there is no interaction between learning model and the level of students’ mathematical-logical intelligence in giving a mathematics achievement. The impact of this research is that TPS model using RME approach can be applied in mathematics learning so that students can learn more actively and understand the material more, and mathematics learning become more meaningful. On the other hand, internal factors of students must become a consideration toward the success of students’ mathematical achievement particularly in geometry material.

Learning intervention and the approach to study of engineering undergraduates

Science.gov (United States)

Solomonides, Ian Paul

The aim of the research was to: investigate the effect of a learning intervention on the Approach to Study of first year engineering degree students. The learning intervention was a local programme of learning to learn' workshops designed and facilitated by the author. The primary aim of these was to develop students' Approaches to Study. Fifty-three first year engineering undergraduates at The Nottingham Trent University participated in the workshops. Approaches to Study were quantified using data obtained from the Revised Approach to Study Inventory (RASI) which was also subjected to a validity and reliability study using local data. Quantitative outcomes were supplemented using a qualitative analysis of essays written by students during the workshops. These were analysed for detail regarding student Approach to Study. It was intended that any findings would inform the local system of Engineering Education, although more general findings also emerged, in particular in relation to the utility of the research instrument. It was concluded that the intervention did not promote the preferential Deep Approach and did not affect Approaches to Study generally as measured by the RASI. This concurred with previous attempts to change student Approaches to Study at the group level. It was also established that subsequent years of the Integrated Engineering degree course are associated with progressively deteriorating Approaches to Study. Students who were exposed to the intervention followed a similar pattern of deteriorating Approaches suggesting that the local course context and its demands had a greater influence over the Approach of students than the intervention did. It was found that academic outcomes were unrelated to the extent to which students took a Deep Approach to the local assessment demands. There appeared therefore to be a mis-match between the Approach students adopted to pass examinations and those that are required for high quality learning outcomes. It is

Elementary Students' Generalization and Representation of Functional Relationships: A Learning Progressions Approach

Science.gov (United States)

Stephens, Ana; Fonger, Nicole L.; Blanton, Maria; Knuth, Eric

2016-01-01

In this paper, we describe our learning progressions approach to early algebra research that involves the coordination of a curricular framework, an instructional sequence, written assessments, and levels of sophistication describing the development of students' thinking. We focus in particular on what we have learning through this approach about…

The Effect of Contextual Teaching and Learning Combined with Peer Tutoring towards Learning Achievement on Human Digestive System Concept

Directory of Open Access Journals (Sweden)

Farhah Abadiyah

2017-11-01

Full Text Available This research aims to know the influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept. This research was conducted at one of State Senior High School in South Tangerang in the academic year of 2016/2017. The research method was quasi experiment with nonequivalent pretest-postest control group design. The sample was taken by simple random sampling. The total of the sampels were 86 students which consisted of 44 students as a controlled group and 42 students as an experimental group. The research instrument was objective test which consisted of 25 multiple choice items of each pretest and posttest. The research also used observation sheets for teacher and students activity. The result of data analysis using t-test on the two groups show that the value of tcount was 2.40 and ttable was 1.99 on significant level α = 0,05, so that tcount > ttable.. This result indicated that there was influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept.

Combining Project-Based Learning and Community-Based Research in a Research Methodology Course: The Lessons Learned

Science.gov (United States)

Arantes do Amaral, João Alberto; Lino dos Santos, Rebeca Júlia Rodrigues

2018-01-01

In this article, we present our findings regarding the course "Research Methodology," offered to 22 first-year undergraduate students studying Administration at the Federal University of São Paulo, Osasco, Brazil. The course, which combined community-based research and project-based learning, was developed during the second semester of…

The development of learning material using learning goal orientation approach in digital electronics

Science.gov (United States)

Puspitaningayu, P.; Anifah, L.; Kholis, N.

2018-01-01

Mastery of digital electronics principles is essential for future engineers in the digital era. This article describes the use of simulations in an undergraduate electrical engineering course to promote the adoption of a learning-goal orientation. This study used experimental method. This was done by providing students with a simulation environment which students freely use to experiment with various circuit models. Students were then invited to reflect on how the simulation results compare with results from lab experiments. The module got 82% of positive rating from 28 students and all of them passed in the examination with 81.8 as the average score. Those majority students were motivated by the combination of two learning goals written in the module. Moreover, they also gain the ability to design more complex systems because of their combined experience. Additionally, the module also has been validated and got 83% of reliability. The final product of this research hereafter can be recommended to be used as teaching material.

The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent

Science.gov (United States)

Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie

2017-01-01

Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…

Localized Multiple Kernel Learning A Convex Approach

Science.gov (United States)

2016-11-22

data. All the aforementioned approaches to localized MKL are formulated in terms of non-convex optimization problems, and deep the- oretical...learning. IEEE Transactions on Neural Networks, 22(3):433–446, 2011. Jingjing Yang, Yuanning Li, Yonghong Tian, Lingyu Duan, and Wen Gao. Group-sensitive

Elemental representation and configural mappings: combining elemental and configural theories of associative learning.

Science.gov (United States)

McLaren, I P L; Forrest, C L; McLaren, R P

2012-09-01

In this article, we present our first attempt at combining an elemental theory designed to model representation development in an associative system (based on McLaren, Kaye, & Mackintosh, 1989) with a configural theory that models associative learning and memory (McLaren, 1993). After considering the possible advantages of such a combination (and some possible pitfalls), we offer a hybrid model that allows both components to produce the phenomena that they are capable of without introducing unwanted interactions. We then successfully apply the model to a range of phenomena, including latent inhibition, perceptual learning, the Espinet effect, and first- and second-order retrospective revaluation. In some cases, we present new data for comparison with our model's predictions. In all cases, the model replicates the pattern observed in our experimental results. We conclude that this line of development is a promising one for arriving at general theories of associative learning and memory.

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

Science.gov (United States)

Gentry, Diana

2017-01-01

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may

A Mobile Device Based Serious Gaming Approach for Teaching and Learning Java Programming

Directory of Open Access Journals (Sweden)

Tobias Jordine

2015-01-01

Full Text Available Most first year computer science students find that learning object-oriented programming is hard. Serious games have ever been used as one approach to handle this problem. But most of them cannot be played with mobile devices. This obviously does not suit the era of mobile computing that intends to allow students to learn programming skills in anytime anywhere. To enhance mobile teaching and learning, a research project started over a year ago and aims to create a mobile device based serious gaming approach along with a serious game for enhancing mobile teaching and learning for Java programming. So far the project has completed a literature review for understanding existing work and identifying problems in this area, conducted a survey for eliciting students’ requirements for mobile gaming approach, and then established a mobile-device based serious gaming approach with a developed prototype of the game. This paper introduces the project in details, and in particularly presents and discusses its current results. It is expected that the presented project will be helpful and useful to bring more efficient approaches with new mobile games into teaching object-oriented programming and to enhance students’ learning experiences.

Relational Analysis of College Chemistry-Major Students' Conceptions of and Approaches to Learning Chemistry

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Li, Wei-Ting; Liang, Jyh-Chong; Tsai, Chin-Chung

2013-01-01

The purpose of this research was to examine the relationships between conceptions of learning and approaches to learning in chemistry. Two questionnaires, conceptions of learning chemistry (COLC) and approaches to learning chemistry (ALC), were developed to identify 369 college chemistry-major students' (220 males and 149 females) conceptions of…

First-Year Students' Approaches to Learning, and Factors Related to Change or Stability in Their Deep Approach during a Pharmacy Course

Science.gov (United States)

Varunki, Maaret; Katajavuori, Nina; Postareff, Liisa

2017-01-01

Research shows that a surface approach to learning is more common among students in the natural sciences, while students representing the "soft" sciences are more likely to apply a deep approach. However, findings conflict concerning the stability of approaches to learning in general. This study explores the variation in students'…

Sequenced Integration and the Identification of a Problem-Solving Approach through a Learning Process

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Cormas, Peter C.

2016-01-01

Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…

A Self-Synthesis Approach to Perceptual Learning for Multisensory Fusion in Robotics

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Axenie, Cristian; Richter, Christoph; Conradt, Jörg

2016-01-01

Biological and technical systems operate in a rich multimodal environment. Due to the diversity of incoming sensory streams a system perceives and the variety of motor capabilities a system exhibits there is no single representation and no singular unambiguous interpretation of such a complex scene. In this work we propose a novel sensory processing architecture, inspired by the distributed macro-architecture of the mammalian cortex. The underlying computation is performed by a network of computational maps, each representing a different sensory quantity. All the different sensory streams enter the system through multiple parallel channels. The system autonomously associates and combines them into a coherent representation, given incoming observations. These processes are adaptive and involve learning. The proposed framework introduces mechanisms for self-creation and learning of the functional relations between the computational maps, encoding sensorimotor streams, directly from the data. Its intrinsic scalability, parallelisation, and automatic adaptation to unforeseen sensory perturbations make our approach a promising candidate for robust multisensory fusion in robotic systems. We demonstrate this by applying our model to a 3D motion estimation on a quadrotor. PMID:27775621

A Self-Synthesis Approach to Perceptual Learning for Multisensory Fusion in Robotics

Directory of Open Access Journals (Sweden)

Cristian Axenie

2016-10-01

Full Text Available Biological and technical systems operate in a rich multimodal environment. Due to the diversity of incoming sensory streams a system perceives and the variety of motor capabilities a system exhibits there is no single representation and no singular unambiguous interpretation of such a complex scene. In this work we propose a novel sensory processing architecture, inspired by the distributed macro-architecture of the mammalian cortex. The underlying computation is performed by a network of computational maps, each representing a different sensory quantity. All the different sensory streams enter the system through multiple parallel channels. The system autonomously associates and combines them into a coherent representation, given incoming observations. These processes are adaptive and involve learning. The proposed framework introduces mechanisms for self-creation and learning of the functional relations between the computational maps, encoding sensorimotor streams, directly from the data. Its intrinsic scalability, parallelisation, and automatic adaptation to unforeseen sensory perturbations make our approach a promising candidate for robust multisensory fusion in robotic systems. We demonstrate this by applying our model to a 3D motion estimation on a quadrotor.

Advanced methods in NDE using machine learning approaches

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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

A New Design Approach to game or play based learning

DEFF Research Database (Denmark)

Larsen, Lasse Juel

to ground the students sense of meaning. This paper proposes another approach: using visualization in immersive 3D-worlds as documentation of learning progress while at the same time constituting a reward system which motivate further learning. The overall design idea is to build a game based learning......Abstract: The present paper proposes a new design perspective for game based learning. The general idea is to abandon the long and sought after dream of designing a closed learning system, where students from elementary school to high school without teachers’ interference could learn whatever...... game based learning system, but also confront aspects of modern learning theory especially the notion of reference between content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way to tackle the common experience...

'Rapid Learning health care in oncology' - an approach towards decision support systems enabling customised radiotherapy'.

Science.gov (United States)

Lambin, Philippe; Roelofs, Erik; Reymen, Bart; Velazquez, Emmanuel Rios; Buijsen, Jeroen; Zegers, Catharina M L; Carvalho, Sara; Leijenaar, Ralph T H; Nalbantov, Georgi; Oberije, Cary; Scott Marshall, M; Hoebers, Frank; Troost, Esther G C; van Stiphout, Ruud G P M; van Elmpt, Wouter; van der Weijden, Trudy; Boersma, Liesbeth; Valentini, Vincenzo; Dekker, Andre

2013-10-01

An overview of the Rapid Learning methodology, its results, and the potential impact on radiotherapy. Rapid Learning methodology is divided into four phases. In the data phase, diverse data are collected about past patients, treatments used, and outcomes. Innovative information technologies that support semantic interoperability enable distributed learning and data sharing without additional burden on health care professionals and without the need for data to leave the hospital. In the knowledge phase, prediction models are developed for new data and treatment outcomes by applying machine learning methods to data. In the application phase, this knowledge is applied in clinical practice via novel decision support systems or via extensions of existing models such as Tumour Control Probability models. In the evaluation phase, the predictability of treatment outcomes allows the new knowledge to be evaluated by comparing predicted and actual outcomes. Personalised or tailored cancer therapy ensures not only that patients receive an optimal treatment, but also that the right resources are being used for the right patients. Rapid Learning approaches combined with evidence based medicine are expected to improve the predictability of outcome and radiotherapy is the ideal field to study the value of Rapid Learning. The next step will be to include patient preferences in the decision making. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Synergistic target combination prediction from curated signaling networks: Machine learning meets systems biology and pharmacology.

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Chua, Huey Eng; Bhowmick, Sourav S; Tucker-Kellogg, Lisa

2017-10-01

Given a signaling network, the target combination prediction problem aims to predict efficacious and safe target combinations for combination therapy. State-of-the-art in silico methods use Monte Carlo simulated annealing (mcsa) to modify a candidate solution stochastically, and use the Metropolis criterion to accept or reject the proposed modifications. However, such stochastic modifications ignore the impact of the choice of targets and their activities on the combination's therapeutic effect and off-target effects, which directly affect the solution quality. In this paper, we present mascot, a method that addresses this limitation by leveraging two additional heuristic criteria to minimize off-target effects and achieve synergy for candidate modification. Specifically, off-target effects measure the unintended response of a signaling network to the target combination and is often associated with toxicity. Synergy occurs when a pair of targets exerts effects that are greater than the sum of their individual effects, and is generally a beneficial strategy for maximizing effect while minimizing toxicity. mascot leverages on a machine learning-based target prioritization method which prioritizes potential targets in a given disease-associated network to select more effective targets (better therapeutic effect and/or lower off-target effects); and on Loewe additivity theory from pharmacology which assesses the non-additive effects in a combination drug treatment to select synergistic target activities. Our experimental study on two disease-related signaling networks demonstrates the superiority of mascot in comparison to existing approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

Vocation, Motivation and Approaches to Learning: A Comparative Study

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Arquero, Jose Luis; Fernández-Polvillo, Carmen; Hassall, Trevor; Joyce, John

2015-01-01

Purpose: The individual characteristics of students can have a strong influence on the success of the adopted innovations in terms of their transferability and sustainability. The purpose of this paper is to compare the motivations and approaches to learning on degrees with differing vocational components. Design/methodology/approach:…

Exploring the Behavioural Patterns of Entrepreneurial Learning: A Competency Approach

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Man, Thomas Wing Yan

2006-01-01

Purpose: The purpose of this study is to empirically explore the behavioural patterns involved in entrepreneurial learning through a conceptualization of entrepreneurial learning as a "competency". Design/methodology/approach: Semi-structured interviews to 12 entrepreneurs were conducted with a focus on the critical incidents in which…

Application of heuristic and machine-learning approach to engine model calibration

Science.gov (United States)

Cheng, Jie; Ryu, Kwang R.; Newman, C. E.; Davis, George C.

1993-03-01

Automation of engine model calibration procedures is a very challenging task because (1) the calibration process searches for a goal state in a huge, continuous state space, (2) calibration is often a lengthy and frustrating task because of complicated mutual interference among the target parameters, and (3) the calibration problem is heuristic by nature, and often heuristic knowledge for constraining a search cannot be easily acquired from domain experts. A combined heuristic and machine learning approach has, therefore, been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of a machine learning program called GID3* for automatic acquisition of heuristic rules for ordering target parameters.

A SOCIO-COGNITIVE APPROACH TO KNOWLEDGE CONSTRUCTION THROUGH BLENDED LEARNING

Directory of Open Access Journals (Sweden)

Tuba Kocaturk

2017-01-01

Full Text Available This paper results from an educational research project that was undertaken by the School of Architecture, at the University of Liverpool funded by the Higher Education Academy in UK. The research explored technology driven shifts in architectural design studio education, identified their cognitive effects on design learning and developed an innovative blended learning approach that was implemented at a masters level digital design studio. The contribution of the research and the proposed approach to the existing knowledge and practice are twofold. Firstly, it offers a new pedagogical framework which integrates social, technical and cognitive dimensions of knowledge construction. And secondly, it offers a unique operational model through the integration of both mediational and instrumental use of digital media. The proposed model provides a useful basis for the effective mobilization of next generation learning technologies which can effectively respond to the learning challenges specific to architectural design knowledge and its means of creation.

Surgical treatment of traumatic cervical facet dislocation: anterior, posterior or combined approaches?

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Catarina C. Lins

Full Text Available ABSTRACT Surgical treatment is well accepted for patients with traumatic cervical facet joint dislocations (CFD, but there is uncertainty over which approach is better: anterior, posterior or combined. We performed a systematic literature review to evaluate the indications for anterior and posterior approaches in the management of CFD. Anterior approaches can restore cervical lordosis, and cause less postoperative pain and less wound problems. Posterior approaches are useful for direct reduction of locked facet joints and provide stronger fixation from a biomechanical point of view. Combined approaches can be used in more complex cases. Although both anterior and posterior approaches can be used interchangeably, there are some patients who may benefit from one of them over the other, as discussed in this review. Surgeons who treat cervical spine trauma should be able to perform both procedures as well as combined approaches to adequately manage CFD and improve patients’ final outcomes.

Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

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Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

2017-12-01

Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

A new approach to theoretical investigations of high harmonics generation by means of fs laser interaction with overdense plasma layers. Combining particle-in-cell simulations with machine learning

International Nuclear Information System (INIS)

Mihailescu, A.

2016-01-01

Within the past decade, various experimental and theoretical investigations have been performed in the field of high-order harmonics generation (HHG) by means of femtosecond ( fs ) laser pulses interacting with laser produced plasmas. Numerous potential future applications thus arise. Beyond achieving higher conversion efficiency for higher harmonic orders and hence harmonic power and brilliance, there are more ambitious scientific goals such as attaining shorter harmonic wavelengths or reducing harmonic pulse durations towards the attosecond and even the zeptosecond range. High order harmonics are also an attractive diagnostic tool for the laser-plasma interaction process itself. Particle-in-Cell (PIC) simulations are known to be one of the most important numerical instruments employed in plasma physics and in laser-plasma interaction investigations. The novelty brought by this paper consists in combining the PIC method with several machine learning approaches. For predictive modelling purposes, a universal functional approximator is used, namely a multi-layer perceptron (MLP), in conjunction with a self-organizing map (SOM). The training sets have been retrieved from the PIC simulations and also from the available literature in the field. The results demonstrate the potential utility of machine learning in predicting optimal interaction scenarios for gaining higher order harmonics or harmonics with particular features such as a particular wavelength range, a particular harmonic pulse duration or a certain intensity. Furthermore, the author will show how machine learning can be used for estimations of electronic temperatures, proving that it can be a reliable tool for obtaining better insights into the fs laser interaction physics.

The Effect of Integrated Learning-Teaching Approach on Reading Comprehension and Narration Skills

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Ergün Hamzadayı

2010-12-01

Full Text Available This study investigated the effects of integrated learning-teaching approach on reading comprehension and narration skills. Considerations regarding how to overcome difficulties in the teaching of Turkish language through multi-theoretical perspectives have resulted in this approach to come into the existence. For the purpose of forming theoretical foundations of the research, behaviourist, cognitive and constructivist learning theories with their philosophical foundations were introduced, their principals and assumptions with regard to instructional design were compared, and their strengths and weakness were delineated. These considerations were then associated with the components of Turkish language program (content, objectives, teaching strategies and methods, assessment and that paved way for “integrative learning and teaching approach” to come into being. This study aimed to investigate whether there is a significant difference between the performance of the experimental group students who were exposed to integrative learning and teaching approach and that of control group students who were not exposed to integrative learning and teaching approach in terms of reading comprehension and written expression skills in Turkish language

A Combination of Machine Learning and Cerebellar Models for the Motor Control and Learning of a Modular Robot

DEFF Research Database (Denmark)

Baira Ojeda, Ismael; Tolu, Silvia; Pacheco, Moises

2017-01-01

We scaled up a bio-inspired control architecture for the motor control and motor learning of a real modular robot. In our approach, the Locally Weighted Projection Regression algorithm (LWPR) and a cerebellar microcircuit coexist, forming a Unit Learning Machine. The LWPR optimizes the input space...... and learns the internal model of a single robot module to command the robot to follow a desired trajectory with its end-effector. The cerebellar microcircuit refines the LWPR output delivering corrective commands. We contrasted distinct cerebellar circuits including analytical models and spiking models...

A Context-Aware Ubiquitous Learning Approach for Providing Instant Learning Support in Personal Computer Assembly Activities

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Hsu, Ching-Kun; Hwang, Gwo-Jen

2014-01-01

Personal computer assembly courses have been recognized as being essential in helping students understand computer structure as well as the functionality of each computer component. In this study, a context-aware ubiquitous learning approach is proposed for providing instant assistance to individual students in the learning activity of a…

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

Science.gov (United States)

Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

2017-01-01

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as

3 Colleges' Different Approaches Shape Learning in Econ 101

Science.gov (United States)

Berrett, Dan

2012-01-01

No matter the college, a class in the principles of microeconomics is likely to cover the discipline's greatest hits. The author attends three economics courses at three colleges, and finds three very different approaches. In this article, the author discusses three colleges' different approaches that shape learning in Econ 101.

Teaching Newton's 3rd law of motion using learning by design approach

Science.gov (United States)

Aquino, Jiezel G.; Caliguid, Mariel P.; Buan, Amelia T.; Magsayod, Joy R.; Lahoylahoy, Myrna E.

2018-01-01

This paper presents the process and implementation of Learning by Design Approach in teaching Newton's 3rd Law of Motion. A lesson activity from integrative STEM education was adapted, modified and enhanced through pilot testing. After revisions, the implementation was done to one class. The respondent's prior knowledge was first assessed by a pretest. PPIT (present the scenario, plan, implement and test) was the framework followed in the implementation of Learning by Design. Worksheets were then utilized to measure their conceptual understanding and perception. A score guide was also used to evaluate the student's output. Paired t-test analysis showed that there is a significant difference in the pretest and posttest achievement scores. This implies that the performance of the students have improved during the implementation of the Learning by Design. The Analysis of variance also depicts that the low, average and high benefited in the Learning by Design approach. The results of this study suggests that Learning by Design is an effective approach in teaching Newton's 3rd Law of Motion and thus be used in a Science classroom.

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

Science.gov (United States)

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-08-24

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

Directory of Open Access Journals (Sweden)

Jinmeng Rao

2017-08-01

Full Text Available The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

Science.gov (United States)

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-01-01

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

Transformative Learning Approaches for Public Relations Pedagogy

Science.gov (United States)

Motion, Judy; Burgess, Lois

2014-01-01

Public relations educators are frequently challenged by students' flawed perceptions of public relations. Two contrasting case studies are presented in this paper to illustrate how socially-oriented paradigms may be applied to a real-client project to deliver a transformative learning experience. A discourse-analytic approach is applied within the…

Designing e-learning solutions with a client centred approach

DEFF Research Database (Denmark)

Ørngreen, Rikke; Nielsen, Janni; Levinsen, Karin

2008-01-01

  This paper claims that the strategies applied in designing e-learning solutions tend to focus on how to proceed after the precondition, e.g., learners requirements, pedagogical choice, etc., have been decided upon. Investigating the HCI research field, we find that the methodological approaches...... as the organisation that has initiated the e-learning project and needs to manage the e-learning system after its development. Through the Client Centred Design and in close collaboration with the client, three strategic issues are uncovered and strategic models are presented for each. These models are complementary...... perspectives in a Client Centred framework that is useable as the starting point for others in developing large scale e-learning projects....

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

Science.gov (United States)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high

Restoring Proprioception via a Cortical Prosthesis: A Novel Learning-Based Approach

Science.gov (United States)

2015-10-01

AWARD NUMBER: W81XWH-14-1-0510 TITLE: Restoring Proprioception via a Cortical Prosthesis : A Novel Learning-Based Approach PRINCIPAL INVESTIGATOR...Proprioception via a Cortical Prosthesis : A Novel Learning-Based Approach 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Philip Sabes, PhD 5d...component of this lost sensation is proprioception, the feeling of where the body is in space. The importance of proprioception is often not appreciated

Evaluation of students' perception of their learning environment and approaches to learning

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Valyrakis, Manousos; Cheng, Ming

2015-04-01

This work presents the results of two case studies designed to assess the various approaches undergraduate and postgraduate students undertake for their education. The first study describes the results and evaluation of an undergraduate course in Water Engineering which aims to develop the fundamental background knowledge of students on introductory practical applications relevant to the practice of water and hydraulic engineering. The study assesses the effectiveness of the course design and learning environment from the perception of students using a questionnaire addressing several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning, and methods of communication and assessment. The second study investigates the effectiveness of supervisory arrangements based on the perceptions of engineering undergraduate and postgraduate students. Effective supervision requires leadership skills that are not taught in the University, yet there is rarely a chance to get feedback, evaluate this process and reflect. Even though the results are very encouraging there are significant lessons to learn in improving ones practice and develop an effective learning environment to student support and guidance. The findings from these studies suggest that students with high level of intrinsic motivation are deep learners and are also top performers in a student-centered learning environment. A supportive teaching environment with a plethora of resources and feedback made available over different platforms that address students need for direct communication and feedback has the potential to improve student satisfaction and their learning experience. Finally, incorporating a multitude of assessment methods is also important in promoting deep learning. These results have deep implications about student learning and can be used to further improve course design and delivery in the future.

[Efficacy of the program "Testas's (mis)adventures" to promote the deep approach to learning].

Science.gov (United States)

Rosário, Pedro; González-Pienda, Julio Antonio; Cerezo, Rebeca; Pinto, Ricardo; Ferreira, Pedro; Abilio, Lourenço; Paiva, Olimpia

2010-11-01

This paper provides information about the efficacy of a tutorial training program intended to enhance elementary fifth graders' study processes and foster their deep approaches to learning. The program "Testas's (mis)adventures" consists of a set of books in which Testas, a typical student, reveals and reflects upon his life experiences during school years. These life stories are nothing but an opportunity to present and train a wide range of learning strategies and self-regulatory processes, designed to insure students' deeper preparation for present and future learning challenges. The program has been developed along a school year, in a one hour weekly tutorial sessions. The training program had a semi-experimental design, included an experimental group (n=50) and a control one (n=50), and used pre- and posttest measures (learning strategies' declarative knowledge, learning approaches and academic achievement). Data suggest that the students enrolled in the training program, comparing with students in the control group, showed a significant improvement in their declarative knowledge of learning strategies and in their deep approach to learning, consequently lowering their use of a surface approach. In spite of this, in what concerns to academic achievement, no statistically significant differences have been found.

Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

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Niklas Berliner

Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.

A New Learning Approach: Flipped Classroom and Its Impacts

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Yildirim, Gürkan

2017-01-01

The aim of this study is to present opinions of undergraduate students towards Flipped Classroom (FC) practices and to determine their different aspects then traditional learning approaches. The case study approach is preferred to conduct the study. In this context, 34 volunteered students were included in the study group by purposive sampling…

Learning User Preferences in Ubiquitous Systems: A User Study and a Reinforcement Learning Approach

OpenAIRE

Zaidenberg , Sofia; Reignier , Patrick; Mandran , Nadine

2010-01-01

International audience; Our study concerns a virtual assistant, proposing services to the user based on its current perceived activity and situation (ambient intelligence). Instead of asking the user to define his preferences, we acquire them automatically using a reinforcement learning approach. Experiments showed that our system succeeded the learning of user preferences. In order to validate the relevance and usability of such a system, we have first conducted a user study. 26 non-expert s...

Using the Blended Learning Approach in a Quantitative Literacy Course

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Botts, Ryan T.; Carter, Lori; Crockett, Catherine

2018-01-01

The efforts to improve the quantitative reasoning (quantitative literacy) skills of college students in the United States have been gaining momentum in recent years. At the same time, the blended learning approach to course delivery has gained in popularity, promising better learning with flexible modalities and pace. This paper presents the…

Liquid-phase microextraction approaches combined with atomic detection: A critical review

International Nuclear Information System (INIS)

Pena-Pereira, Francisco; Lavilla, Isela; Bendicho, Carlos

2010-01-01

Liquid-phase microextraction (LPME) displays unique characteristics such as excellent preconcentration capability, simplicity, low cost, sample cleanup and integration of steps. Even though LPME approaches have the potential to be combined with almost every analytical technique, their use in combination with atomic detection techniques has not been exploited until recently. A comprehensive review dealing with the applications of liquid-phase microextraction combined with atomic detection techniques is presented. Theoretical features, possible strategies for these combinations as well as the effect of key experimental parameters influencing method development are addressed. Finally, a critical comparison of the different LPME approaches in terms of enrichment factors achieved, extraction efficiency, precision, selectivity and simplicity of operation is provided.

PENGEMBANGAN PENDIDIKAN KARAKTER DALAM MATA KULIAH EVALUASI PEMBELAJARAN MELALUI PENDEKATAN DEEP APPROACH TO LEARNING

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Nanik Suryani

2016-01-01

Full Text Available The objectives of this study are to find and to test the model of characters education in Learning Evaluation Subject through deep approach to learning. The subject of the study is the class of Learning Evaluation of Office Administration Program, Economics Education Department, Economics Faculty, Semarang State University. The data are collected by a test, and then analyzed by qualitative descriptive. The result of this study showed that the model of characters education through deep approach to learning could improve students’ self awareness in learning the subject.

PENGEMBANGAN PENDIDIKAN KARAKTER DALAM MATA KULIAH EVALUASI PEMBELAJARAN MELALUI PENDEKATAN DEEP APPROACH TO LEARNING

Directory of Open Access Journals (Sweden)

Nanik Suryani

2012-12-01

Full Text Available The objectives of this study are to find and to test the model of characters education in Learning Evaluation Subject through deep approach to learning. The subject of the study is the class of Learning Evaluation of Office Administration Program, Economics Education Department, Economics Faculty, Semarang State University. The data are collected by a test, and then analyzed by qualitative descriptive. The result of this study showed that the model of characters education through deep approach to learning could improve students’ self awareness in learning the subject.

A combination of HARMONIE short time direct normal irradiance forecasts and machine learning: The #hashtdim procedure

Science.gov (United States)

Gastón, Martín; Fernández-Peruchena, Carlos; Körnich, Heiner; Landelius, Tomas

2017-06-01

The present work describes the first approach of a new procedure to forecast Direct Normal Irradiance (DNI): the #hashtdim that treats to combine ground information and Numerical Weather Predictions. The system is centered in generate predictions for the very short time. It combines the outputs from the Numerical Weather Prediction Model HARMONIE with an adaptive methodology based on Machine Learning. The DNI predictions are generated with 15-minute and hourly temporal resolutions and presents 3-hourly updates. Each update offers forecasts to the next 12 hours, the first nine hours are generated with 15-minute temporal resolution meanwhile the last three hours present hourly temporal resolution. The system is proved over a Spanish emplacement with BSRN operative station in south of Spain (PSA station). The #hashtdim has been implemented in the framework of the Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies (DNICast) project, under the European Union's Seventh Programme for research, technological development and demonstration framework.

Student perceptions of independent versus facilitated small group learning approaches to compressed medical anatomy education.

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Whelan, Alexander; Leddy, John J; Mindra, Sean; Matthew Hughes, J D; El-Bialy, Safaa; Ramnanan, Christopher J

2016-01-01

The purpose of this study was to compare student perceptions regarding two, small group learning approaches to compressed (46.5 prosection-based laboratory hours), integrated anatomy education at the University of Ottawa medical program. In the facilitated active learning (FAL) approach, tutors engage students and are expected to enable and balance both active learning and progression through laboratory objectives. In contrast, the emphasized independent learning (EIL) approach stresses elements from the "flipped classroom" educational model: prelaboratory preparation, independent laboratory learning, and limited tutor involvement. Quantitative (Likert-style questions) and qualitative data (independent thematic analysis of open-ended commentary) from a survey of students who had completed the preclerkship curriculum identified strengths from the EIL (promoting student collaboration and communication) and FAL (successful progression through objectives) approaches. However, EIL led to student frustration related to a lack of direction and impaired completion of objectives, whereas active learning opportunities in FAL were highly variable and dependent on tutor teaching style. A "hidden curriculum" was also identified, where students (particularly EIL and clerkship students) commonly compared their compressed anatomy education or their anatomy learning environment with other approaches. Finally, while both groups highly regarded the efficiency of prosection-based learning and expressed value for cadaveric-based learning, student commentary noted that the lack of grade value dedicated to anatomy assessment limited student accountability. This study revealed critical insights into small group learning in compressed anatomy education, including the need to balance student active learning opportunities with appropriate direction and feedback (including assessment). © 2015 American Association of Anatomists.

PlayIt: Game Based Learning Approach for Teaching Programming Concepts

Science.gov (United States)

Mathrani, Anuradha; Christian, Shelly; Ponder-Sutton, Agate

2016-01-01

This study demonstrates a game-based learning (GBL) approach to engage students in learning and enhance their programming skills. The paper gives a detailed narrative of how an educational game was mapped with the curriculum of a prescribed programming course in a computing diploma study programme. Two separate student cohorts were invited to…

Combined Interhemispheric and Transsylvian Approach for Resection of Craniopharyngioma.

Science.gov (United States)

Inoue, Tomohiro; Ono, Hideaki; Tamura, Akira; Saito, Isamu

2018-04-01

We present a 37-year-old male case of cystic suprasellar huge craniopharyngioma, who presented with significant memory disturbance due to obstructive hydrocephalus. Combined interhemispheric and pterional approach was chosen to resect huge suprasellar tumor. Interhemispheric trans-lamina terminalis approach was quite effective to resect third ventricular tumor, while pterional approach was useful to dissect tumor out of basilar perforators and stalk. The link to the video can be found at: https://youtu.be/BoYIPa96kdo .

Learner differences and learning outcomes in an introductory biochemistry class: attitude toward images, visual cognitive skills, and learning approach.

Science.gov (United States)

Milner, Rachel E

2014-01-01

The practice of using images in teaching is widespread, and in science education images are used so extensively that some have argued they are now the "main vehicle of communication" (C. Ferreira, A. Arroio Problems Educ. 21st Century 2009, 16, 48-53). Although this phenomenon is especially notable in the field of biochemistry, we know little about the role and importance of images in communicating concepts to students in the classroom. This study reports the development of a scale to assess students' attitude toward biochemical images, particularly their willingness and ability to use the images to support their learning. In addition, because it is argued that images are central in the communication of biochemical concepts, we investigated three "learner differences" which might impact learning outcomes in this kind of classroom environment: attitude toward images, visual cognitive skills, and learning approach. Overall, the students reported a positive attitude toward the images, the majority agreeing that they liked images and considered them useful. However, the participants also reported that verbal explanations were more important than images in helping them to understand the concepts. In keeping with this we found that there was no relationship between learning outcomes and the students' self-reported attitude toward images or visual cognitive skills. In contrast, learning outcomes were significantly correlated with the students' self-reported approach to learning. These findings suggest that images are not necessarily the main vehicle of communication in a biochemistry classroom and that verbal explanations and encouragement of a deep learning approach are important considerations in improving our pedagogical approach. © 2013 International Union of Biochemistry and Molecular Biology, Inc.

Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

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Kaya, Mehmet; Alhajj, Reda

2005-04-01

Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.