Sample records for active learning techniques

  1. Journaling; an active learning technique. (United States)

    Blake, Tim K


    Journaling is a method frequently discussed in nursing literature and educational literature as an active learning technique that is meant to enhance reflective practice. Reflective practice is a means of self-examination that involves looking back over what has happened in practice in an effort to improve, or encourage professional growth. Some of the benefits of reflective practice include discovering meaning, making connections between experiences and the classroom, instilling values of the profession, gaining the perspective of others, reflection on professional roles, and development of critical thinking. A review of theory and research is discussed, as well as suggestions for implementation of journaling into coursework.

  2. Active learning techniques for librarians practical examples

    CERN Document Server

    Walsh, Andrew


    A practical work outlining the theory and practice of using active learning techniques in library settings. It explains the theory of active learning and argues for its importance in our teaching and is illustrated using a large number of examples of techniques that can be easily transferred and used in teaching library and information skills to a range of learners within all library sectors. These practical examples recognise that for most of us involved in teaching library and information skills the one off session is the norm, so we need techniques that allow us to quickly grab and hold our

  3. Stimulating Deep Learning Using Active Learning Techniques (United States)

    Yew, Tee Meng; Dawood, Fauziah K. P.; a/p S. Narayansany, Kannaki; a/p Palaniappa Manickam, M. Kamala; Jen, Leong Siok; Hoay, Kuan Chin


    When students and teachers behave in ways that reinforce learning as a spectator sport, the result can often be a classroom and overall learning environment that is mostly limited to transmission of information and rote learning rather than deep approaches towards meaningful construction and application of knowledge. A group of college instructors…

  4. The colloquial approach: An active learning technique (United States)

    Arce, Pedro


    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.

  5. Opportunities to Create Active Learning Techniques in the Classroom (United States)

    Camacho, Danielle J.; Legare, Jill M.


    The purpose of this article is to contribute to the growing body of research that focuses on active learning techniques. Active learning techniques require students to consider a given set of information, analyze, process, and prepare to restate what has been learned--all strategies are confirmed to improve higher order thinking skills. Active…

  6. Effect of active learning techniques on students' choice of approach ...

    African Journals Online (AJOL)

    The purpose of this article is to report on empirical work, related to a techniques module, undertaken with the dental students of the University of the Western Cape, South Africa. I will relate how a range of different active learning techniques (tutorials; question papers and mock tests) assisted students to adopt a deep ...

  7. Active Learning Techniques Applied to an Interdisciplinary Mineral Resources Course. (United States)

    Aird, H. M.


    An interdisciplinary active learning course was introduced at the University of Puget Sound entitled 'Mineral Resources and the Environment'. Various formative assessment and active learning techniques that have been effective in other courses were adapted and implemented to improve student learning, increase retention and broaden knowledge and understanding of course material. This was an elective course targeted towards upper-level undergraduate geology and environmental majors. The course provided an introduction to the mineral resources industry, discussing geological, environmental, societal and economic aspects, legislation and the processes involved in exploration, extraction, processing, reclamation/remediation and recycling of products. Lectures and associated weekly labs were linked in subject matter; relevant readings from the recent scientific literature were assigned and discussed in the second lecture of the week. Peer-based learning was facilitated through weekly reading assignments with peer-led discussions and through group research projects, in addition to in-class exercises such as debates. Writing and research skills were developed through student groups designing, carrying out and reporting on their own semester-long research projects around the lasting effects of the historical Ruston Smelter on the biology and water systems of Tacoma. The writing of their mini grant proposals and final project reports was carried out in stages to allow for feedback before the deadline. Speakers from industry were invited to share their specialist knowledge as guest lecturers, and students were encouraged to interact with them, with a view to employment opportunities. Formative assessment techniques included jigsaw exercises, gallery walks, placemat surveys, think pair share and take-home point summaries. Summative assessment included discussion leadership, exams, homeworks, group projects, in-class exercises, field trips, and pre-discussion reading exercises

  8. Figure analysis: A teaching technique to promote visual literacy and active Learning. (United States)

    Wiles, Amy M


    Learning often improves when active learning techniques are used in place of traditional lectures. For many of these techniques, however, students are expected to apply concepts that they have already grasped. A challenge, therefore, is how to incorporate active learning into the classroom of courses with heavy content, such as molecular-based biology courses. An additional challenge is that visual literacy is often overlooked in undergraduate science education. To address both of these challenges, a technique called figure analysis was developed and implemented in three different levels of undergraduate biology courses. Here, students learn content while gaining practice in interpreting visual information by discussing figures with their peers. Student groups also make connections between new and previously learned concepts on their own while in class. The instructor summarizes the material for the class only after students grapple with it in small groups. Students reported a preference for learning by figure analysis over traditional lecture, and female students in particular reported increased confidence in their analytical abilities. There is not a technology requirement for this technique; therefore, it may be utilized both in classrooms and in nontraditional spaces. Additionally, the amount of preparation required is comparable to that of a traditional lecture. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(4):336-344, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.


    Directory of Open Access Journals (Sweden)

    Juri. S. Ezrokh


    Full Text Available The research is aimed at specifying and developing the modern control system of current academic achievements of junior university students; and the main task is to find the adequate ways for stimulating the junior students’ learning activities, and estimating their individual achievements.Methods: The author applies his own assessment method for estimating and stimulating students’ learning outcomes, based on the rating-point system of gradually obtained points building up a student’s integrated learning outcomes.Results: The research findings prove that implementation of the given method can increase the motivational, multiplicative and controlling components of the learning process.Scientific novelty: The method in question is based on the new original game approach to controlling procedures and stimulation of learning motivation of the economic profile students.Practical significance: The recommended technique can intensify the incentivebased training activities both in and outside a classroom, developing thereby students’ professional and personal qualities.

  10. Status of the Usage of Active Learning and Teaching Method and Techniques by Social Studies Teachers (United States)

    Akman, Özkan


    The purpose of this study was to determine the active learning and teaching methods and techniques which are employed by the social studies teachers working in state schools of Turkey. This usage status was assessed using different variables. This was a case study, wherein the research was limited to 241 social studies teachers. These teachers…

  11. Cultivating ICT Students' Interpersonal Soft Skills in Online Learning Environments Using Traditional Active Learning Techniques (United States)

    Myers, Trina S.; Blackman, Anna; Andersen, Trevor; Hay, Rachel; Lee, Ickjai; Gray, Heather


    Flexible online delivery of tertiary ICT programs is experiencing rapid growth. Creating an online environment that develops team building and interpersonal skills is difficult due to factors such as student isolation and the individual-centric model of online learning that encourages discrete study rather than teamwork. Incorporating teamwork…

  12. A Severe Weather Laboratory Exercise for an Introductory Weather and Climate Class Using Active Learning Techniques (United States)

    Grundstein, Andrew; Durkee, Joshua; Frye, John; Andersen, Theresa; Lieberman, Jordan


    This paper describes a new severe weather laboratory exercise for an Introductory Weather and Climate class, appropriate for first and second year college students (including nonscience majors), that incorporates inquiry-based learning techniques. In the lab, students play the role of meteorologists making forecasts for severe weather. The…

  13. Is There a Relationship between the Usage of Active and Collaborative Learning Techniques and International Students' Study Anxiety? (United States)

    Khoshlessan, Rezvan


    This study was designed to explore the relationships between the international students' perception of professors' instructional practices (the usage of active and collaborative learning techniques in class) and the international students' study anxiety. The dominant goal of this research was to investigate whether the professors' usage of active…

  14. High Classification Rates for Continuous Cow Activity Recognition using Low-cost GPS Positioning Sensors and Standard Machine Learning Techniques

    DEFF Research Database (Denmark)

    Godsk, Torben; Kjærgaard, Mikkel Baun


    activities. By preprocessing the raw cow position data, we obtain high classification rates using standard machine learning techniques to recognize cow activities. Our objectives were to (i) determine to what degree it is possible to robustly recognize cow activities from GPS positioning data, using low...... and their activities manually logged to serve as ground truth. For our dataset we managed to obtain an average classification success rate of 86.2% of the four activities: eating/seeking (90.0%), walking (100%), lying (76.5%), and standing (75.8%) by optimizing both the preprocessing of the raw GPS data...

  15. Active Learning in PhysicsTechnology and Research-based Techniques Emphasizing Interactive Lecture Demonstrations (United States)

    Thornton, Ronald


    Physics education research has shown that learning environments that engage students and allow them to take an active part in their learning can lead to large conceptual gains compared to traditional instruction. Examples of successful curricula and methods include Peer Instruction, Just in Time Teaching, RealTime Physics, Workshop Physics, Scale-Up, and Interactive Lecture Demonstrations (ILDs). An active learning environment is often difficult to achieve in lecture sessions. This presentation will demonstrate the use of sequences of Interactive Lecture Demonstrations (ILDs) that use real experiments often involving real-time data collection and display combined with student interaction to create an active learning environment in large or small lecture classes. Interactive lecture demonstrations will be done in the area of mechanics using real-time motion probes and the Visualizer. A video tape of students involved in interactive lecture demonstrations will be shown. The results of a number of research studies at various institutions (including international) to measure the effectiveness of ILDs and guided inquiry conceptual laboratories will be presented.

  16. Learning from the experts: exploring playground experience and activities using a write and draw technique. (United States)

    Knowles, Zoe Rebecca; Parnell, Daniel; Stratton, Gareth; Ridgers, Nicola Diane


    Qualitative research into the effect of school recess on children's physical activity is currently limited. This study used a write and draw technique to explore children's perceptions of physical activity opportunities during recess. 299 children age 7-11 years from 3 primary schools were enlisted. Children were grouped into Years 3 & 4 and Years 5 & 6 and completed a write and draw task focusing on likes and dislikes. Pen profiles were used to analyze the data. Results indicated 'likes' focused on play, positive social interaction, and games across both age groups but showed an increasing dominance of games with an appreciation for being outdoors with age. 'Dislikes' focused on dysfunctional interactions linked with bullying, membership, equipment, and conflict for playground space. Football was a dominant feature across both age groups and 'likes/dislikes' that caused conflict and dominated the physically active games undertaken. Recess was important for the development of conflict management and social skills and contributed to physical activity engagement. The findings contradict suggestions that time spent in recess should be reduced because of behavioral issues.

  17. Storytelling: a teaching-learning technique. (United States)

    Geanellos, R


    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.

  18. The Effect of Active Learning Techniques on Class Teacher Candidates' Success Rates and Attitudes toward Their Museum Theory and Application Unit in Their Visual Arts Course (United States)

    Dilmac, Oguz


    The purpose of this study is to examine the effect that using active learning techniques during museum and gallery visits has on teacher candidates' academic success rates in and attitudes toward their Visual Arts Course. In this study, the importance and requirement of education to take place in museums and art galleries is emphasized. The…

  19. Interpretable Active Learning


    Phillips, Richard L.; Chang, Kyu Hyun; Friedler, Sorelle A.


    Active learning has long been a topic of study in machine learning. However, as increasingly complex and opaque models have become standard practice, the process of active learning, too, has become more opaque. There has been little investigation into interpreting what specific trends and patterns an active learning strategy may be exploring. This work expands on the Local Interpretable Model-agnostic Explanations framework (LIME) to provide explanations for active learning recommendations. W...

  20. m-Learning and holography: Compatible techniques? (United States)

    Calvo, Maria L.


    Since the last decades, cell phones have become increasingly popular and are nowadays ubiquitous. New generations of cell phones are now equipped with text messaging, internet, and camera features. They are now making their way into the classroom. This is creating a new teaching and learning technique, the so called m-Learning (or mobile-Learning). Because of the many benefits that cell phones offer, teachers could easily use them as a teaching and learning tool. However, an additional work from the teachers for introducing their students into the m-Learning in the classroom needs to be defined and developed. As an example, optical techniques, based upon interference and diffraction phenomena, such as holography, appear to be convenient topics for m-Learning. They can be approached with simple examples and experiments within the cell phones performances and classroom accessibility. We will present some results carried out at the Faculty of Physical Sciences in UCM to obtain very simple holographic recordings via cell phones. The activities were carried out inside the course on Optical Coherence and Laser, offered to students in the fourth course of the Grade in Physical Sciences. Some open conclusions and proposals will be presented.

  1. Active Learning Methods (United States)

    Zayapragassarazan, Z.; Kumar, Santosh


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

  2. Incorporating active-learning techniques into the photonics-related teaching in the Erasmus Mundus Master in "Color in Informatics and Media Technology" (United States)

    Pozo, Antonio M.; Rubiño, Manuel; Hernández-Andrés, Javier; Nieves, Juan L.


    In this work, we present a teaching methodology using active-learning techniques in the course "Devices and Instrumentation" of the Erasmus Mundus Master's Degree in "Color in Informatics and Media Technology" (CIMET). A part of the course "Devices and Instrumentation" of this Master's is dedicated to the study of image sensors and methods to evaluate their image quality. The teaching methodology that we present consists of incorporating practical activities during the traditional lectures. One of the innovative aspects of this teaching methodology is that students apply the concepts and methods studied in class to real devices. For this, students use their own digital cameras, webcams, or cellphone cameras in class. These activities provide students a better understanding of the theoretical subject given in class and encourage the active participation of students.

  3. Optimization of the Kinetic Activation-Relaxation Technique, an off-lattice and self-learning kinetic Monte-Carlo method

    International Nuclear Information System (INIS)

    Joly, Jean-François; Béland, Laurent Karim; Brommer, Peter; Mousseau, Normand; El-Mellouhi, Fedwa


    We present two major optimizations for the kinetic Activation-Relaxation Technique (k-ART), an off-lattice self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search THAT has been successfully applied to study a number of semiconducting and metallic systems. K-ART is parallelized in a non-trivial way: A master process uses several worker processes to perform independent event searches for possible events, while all bookkeeping and the actual simulation is performed by the master process. Depending on the complexity of the system studied, the parallelization scales well for tens to more than one hundred processes. For dealing with large systems, we present a near order 1 implementation. Techniques such as Verlet lists, cell decomposition and partial force calculations are implemented, and the CPU time per time step scales sublinearly with the number of particles, providing an efficient use of computational resources.

  4. Minimax bounds for active learning

    NARCIS (Netherlands)

    Castro, R.M.; Nowak, R.; Bshouty, N.H.; Gentile, C.


    This paper aims to shed light on achievable limits in active learning. Using minimax analysis techniques, we study the achievable rates of classification error convergence for broad classes of distributions characterized by decision boundary regularity and noise conditions. The results clearly

  5. Challenges of Using Learning Analytics Techniques to Support Mobile Learning (United States)

    Arrigo, Marco; Fulantelli, Giovanni; Taibi, Davide


    Evaluation of Mobile Learning remains an open research issue, especially as regards the activities that take place outside the classroom. In this context, Learning Analytics can provide answers, and offer the appropriate tools to enhance Mobile Learning experiences. In this poster we introduce a task-interaction framework, using learning analytics…

  6. Techniques for active passivation (United States)

    Roscioli, Joseph R.; Herndon, Scott C.; Nelson, Jr., David D.


    In one embodiment, active (continuous or intermittent) passivation may be employed to prevent interaction of sticky molecules with interfaces inside of an instrument (e.g., an infrared absorption spectrometer) and thereby improve response time. A passivation species may be continuously or intermittently applied to an inlet of the instrument while a sample gas stream is being applied. The passivation species may have a highly polar functional group that strongly binds to either water or polar groups of the interfaces, and once bound presents a non-polar group to the gas phase in order to prevent further binding of polar molecules. The instrument may be actively used to detect the sticky molecules while the passivation species is being applied.

  7. Active learning of Pareto fronts. (United States)

    Campigotto, Paolo; Passerini, Andrea; Battiti, Roberto


    This paper introduces the active learning of Pareto fronts (ALP) algorithm, a novel approach to recover the Pareto front of a multiobjective optimization problem. ALP casts the identification of the Pareto front into a supervised machine learning task. This approach enables an analytical model of the Pareto front to be built. The computational effort in generating the supervised information is reduced by an active learning strategy. In particular, the model is learned from a set of informative training objective vectors. The training objective vectors are approximated Pareto-optimal vectors obtained by solving different scalarized problem instances. The experimental results show that ALP achieves an accurate Pareto front approximation with a lower computational effort than state-of-the-art estimation of distribution algorithms and widely known genetic techniques.

  8. Machine Learning Techniques in Clinical Vision Sciences. (United States)

    Caixinha, Miguel; Nunes, Sandrina


    This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

  9. From learning objects to learning activities

    DEFF Research Database (Denmark)

    Dalsgaard, Christian


    This paper discusses and questions the current metadata standards for learning objects from a pedagogical point of view. From a social constructivist approach, the paper discusses how learning objects can support problem based, self-governed learning activities. In order to support this approach......, it is argued that it is necessary to focus on learning activities rather than on learning objects. Further, it is argued that descriptions of learning objectives and learning activities should be separated from learning objects. The paper presents a new conception of learning objects which supports problem...... based, self-governed activities. Further, a new way of thinking pedagogy into learning objects is introduced. It is argued that a lack of pedagogical thinking in learning objects is not solved through pedagogical metadata. Instead, the paper suggests the concept of references as an alternative...

  10. Theoretical Foundations of Active Learning (United States)


    I study the informational complexity of active learning in a statistical learning theory framework. Specifically, I derive bounds on the rates of...convergence achievable by active learning , under various noise models and under general conditions on the hypothesis class. I also study the theoretical...advantages of active learning over passive learning, and develop procedures for transforming passive learning algorithms into active learning algorithms

  11. Machine learning techniques in optical communication

    DEFF Research Database (Denmark)

    Zibar, Darko; Piels, Molly; Jones, Rasmus Thomas


    Machine learning techniques relevant for nonlinearity mitigation, carrier recovery, and nanoscale device characterization are reviewed and employed. Markov Chain Monte Carlo in combination with Bayesian filtering is employed within the nonlinear state-space framework and demonstrated for parameter...

  12. Machine learning techniques in optical communication

    DEFF Research Database (Denmark)

    Zibar, Darko; Piels, Molly; Jones, Rasmus Thomas


    Techniques from the machine learning community are reviewed and employed for laser characterization, signal detection in the presence of nonlinear phase noise, and nonlinearity mitigation. Bayesian filtering and expectation maximization are employed within nonlinear state-space framework...

  13. Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach (United States)

    McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine


    Background: Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Methods: Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Results: Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. Conclusions: The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction. PMID:29707649

  14. Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach. (United States)

    McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine


    Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction.

  15. Minimax bounds for active learning

    NARCIS (Netherlands)

    Castro, R.M.; Nowak, R.


    This paper analyzes the potential advantages and theoretical challenges of "active learning" algorithms. Active learning involves sequential sampling procedures that use information gleaned from previous samples in order to focus the sampling and accelerate the learning process relative to "passive

  16. Is Peer Interaction Necessary for Optimal Active Learning? (United States)

    Linton, Debra L.; Farmer, Jan Keith; Peterson, Ernie


    Meta-analyses of active-learning research consistently show that active-learning techniques result in greater student performance than traditional lecture-based courses. However, some individual studies show no effect of active-learning interventions. This may be due to inexperienced implementation of active learning. To minimize the effect of…

  17. Using Breakout Groups as an Active Learning Technique in a Large Undergraduate Nutrition Classroom at the University of Guelph

    Directory of Open Access Journals (Sweden)

    Genevieve Newton


    Full Text Available Breakout groups have been widely used under many different conditions, but the lack of published information related to their use in undergraduate settings highlights the need for research related to their use in this context. This paper describes a study investigating the use of breakout groups in undergraduate education as it specifically relates to teaching a large 4th year undergraduate Nutrition class in a physically constrained lecture space. In total, 220 students completed a midterm survey and 229 completed a final survey designed to measure student satisfaction. Survey results were further analyzed to measure relationships between student perception of breakout group effectiveness and (1 gender and (2 cumulative GPA. Results of both surveys revealed that over 85% of students either agreed or strongly agreed that using breakout groups enhanced their learning experience, with females showing a significantly greater level of satisfaction and higher final course grade than males. Although not stratified by gender, a consistent finding between surveys was a lower perception of breakout group effectiveness by students with a cumulative GPA above 90%. The majority of respondents felt that despite the awkward room space, the breakout groups were easy to create and participate in, which suggests that breakout groups can be successfully used in a large undergraduate classroom despite physical constraints. The findings of this work are relevant given the applicability of breakout groups to a wide range of disciplines, and the relative ease of integration into a traditional lecture format.Les enseignants ont recours aux petits groupes dans de nombreuses conditions différentes, cependant, le manque d’information publiée sur leur utilisation au premier cycle confirme la nécessité d’effectuer des recherches sur ce format dans ce contexte. Le présent article rend compte d’une étude portant sur l’utilisation des petits groupes au premier

  18. Active Math Learning

    DEFF Research Database (Denmark)

    The presentation is concerned with general course planning philosophy and a specific case study (boomerang flight geometro-dynamics) for active learning of mathematics via computer assisted and hands-on unfolding of first principles - in this case the understanding of rotations and Eulers equatio...

  19. Flipped Classroom, active Learning?

    DEFF Research Database (Denmark)

    Andersen, Thomas Dyreborg; Levinsen, Henrik; Philipps, Morten


    Action research is conducted in three physics classes over a period of eighteen weeks with the aim of studying the effect of flipped classroom on the pupils agency and learning processes. The hypothesis is that flipped classroom teaching will potentially allocate more time to work actively...

  20. Learning Activity Package, Algebra. (United States)

    Evans, Diane

    A set of ten teacher-prepared Learning Activity Packages (LAPs) in beginning algebra and nine in intermediate algebra, these units cover sets, properties of operations, number systems, open expressions, solution sets of equations and inequalities in one and two variables, exponents, factoring and polynomials, relations and functions, radicals,…

  1. Grooming. Learning Activity Package. (United States)

    Stark, Pamela

    This learning activity package on grooming for health workers is one of a series of 12 titles developed for use in health occupations education programs. Materials in the package include objectives, a list of materials needed, information sheets, reviews (self evaluations) of portions of the content, and answers to reviews. These topics are…

  2. Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques.

    Directory of Open Access Journals (Sweden)

    Shirin Enshaeifar

    Full Text Available The number of people diagnosed with dementia is expected to rise in the coming years. Given that there is currently no definite cure for dementia and the cost of care for this condition soars dramatically, slowing the decline and maintaining independent living are important goals for supporting people with dementia. This paper discusses a study that is called Technology Integrated Health Management (TIHM. TIHM is a technology assisted monitoring system that uses Internet of Things (IoT enabled solutions for continuous monitoring of people with dementia in their own homes. We have developed machine learning algorithms to analyse the correlation between environmental data collected by IoT technologies in TIHM in order to monitor and facilitate the physical well-being of people with dementia. The algorithms are developed with different temporal granularity to process the data for long-term and short-term analysis. We extract higher-level activity patterns which are then used to detect any change in patients' routines. We have also developed a hierarchical information fusion approach for detecting agitation, irritability and aggression. We have conducted evaluations using sensory data collected from homes of people with dementia. The proposed techniques are able to recognise agitation and unusual patterns with an accuracy of up to 80%.

  3. Three visual techniques to enhance interprofessional learning. (United States)

    Parsell, G; Gibbs, T; Bligh, J


    Many changes in the delivery of healthcare in the UK have highlighted the need for healthcare professionals to learn to work together as teams for the benefit of patients. Whatever the profession or level, whether for postgraduate education and training, continuing professional development, or for undergraduates, learners should have an opportunity to learn about and with, other healthcare practitioners in a stimulating and exciting way. Learning to understand how people think, feel, and react, and the parts they play at work, both as professionals and individuals, can only be achieved through sensitive discussion and exchange of views. Teaching and learning methods must provide opportunities for this to happen. This paper describes three small-group teaching techniques which encourage a high level of learner collaboration and team-working. Learning content is focused on real-life health-care issues and strong visual images are used to stimulate lively discussion and debate. Each description includes the learning objectives of each exercise, basic equipment and resources, and learning outcomes.

  4. Learning Physics through Project-Based Learning Game Techniques (United States)

    Baran, Medine; Maskan, Abdulkadir; Yasar, Seyma


    The aim of the present study, in which Project and game techniques are used together, is to examine the impact of project-based learning games on students' physics achievement. Participants of the study consist of 34 9th grade students (N = 34). The data were collected using achievement tests and a questionnaire. Throughout the applications, the…


    Directory of Open Access Journals (Sweden)



    Full Text Available The classical tools used in data analysis are not enough in order to benefit of all advantages of big data. The amount of information is too large for a complete investigation, and the possible connections and relations between data could be missed, because it is difficult or even impossible to verify all assumption over the information. Machine learning is a great solution in order to find concealed correlations or relationships between data, because it runs at scale machine and works very well with large data sets. The more data we have, the more the machine learning algorithm is useful, because it “learns” from the existing data and applies the found rules on new entries. In this paper, we present some machine learning algorithms and techniques used in big data.

  6. Active Learning Using Hint Information. (United States)

    Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien


    The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

  7. Active Learning with Statistical Models. (United States)


    Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

  8. Active inference and learning. (United States)

    Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O Doherty, John; Pezzulo, Giovanni


    This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Toward accelerating landslide mapping with interactive machine learning techniques (United States)

    Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne


    Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also

  10. Learning curve estimation techniques for nuclear industry

    International Nuclear Information System (INIS)

    Vaurio, Jussi K.


    Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on actuarial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

  11. Machine learning techniques for optical communication system optimization

    DEFF Research Database (Denmark)

    Zibar, Darko; Wass, Jesper; Thrane, Jakob

    In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.......In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction....

  12. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning (United States)

    Firdausiah Mansur, Andi Besse; Yusof, Norazah


    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  13. Re-imagining Active Learning

    DEFF Research Database (Denmark)

    Dall'Alba, Gloria; Bengtsen, Søren Smedegaard


    is largely lacking in the literature on active learning. In this article, we explore the possibility of re-imagining, or at least extending, the meaning of active learning by drawing out dimensions that are neither readily visible nor instrumental, as much of this literature implies. Drawing from educational......Ample attention is being paid in the higher education literature to promoting active learning among students. Where studies on active learning report student outcomes, they indicate improved or equivalent outcomes when compared with traditional lectures, which are considered more passive...... philosophy and, in particular, existential philosophies, we argue that active learning may also be partly invisible, unfocused, unsettling, and not at all instrumentalsometimes even leaving the learner more confused and (temporarily) incompetent. However, such forms of undisclosed or ‘dark’ learning, we...

  14. Machine learning techniques for the verification of refueling activities in CANDU-type nuclear power plants (NPPs) with direct applications in nuclear safeguards

    International Nuclear Information System (INIS)

    Budzinski, J.


    This dissertation deals with the problem of automated classification of the signals obtained from certain radiation monitoring systems, specifically from the Core Discharge Monitor (CDM) systems, that are successfully operated by the International Atomic Energy Agency (IAEA) at various CANDU-type nuclear power plants around the world. In order to significantly reduce the costly and error-prone manual evaluation of the large amounts of the collected CDM signals, a reliable and efficient algorithm for the automated data evaluation is necessary, which might ensure real-time performance with maximum of 0.01 % misclassification ratio. This thesis describes the research behind finding a successful prototype implementation of such automated analysis software. The finally adopted methodology assumes a nonstationary data-generating process that has a finite number of states or basic fueling activities, each of which can emit observable data patterns having particular stationary characteristics. To find out the underlying state sequences, a unified probabilistic approach known as the hidden Markov model (HMM) is used. Each possible fueling sequence is modeled by a distinct HMM having a left-right profile topology with explicit insert and delete states. Given an unknown fueling sequence, a dynamic programming algorithm akin to the Viterbi search is used to find the maximum likelihood state path through each model and eventually the overall best-scoring path is picked up as the recognition hypothesis. Machine learning techniques are applied to estimate the observation densities of the states, because the densities are not simply parameterizable. Unlike most present applications of continuous monitoring systems that rely on heuristic approaches to the recognition of possibly risky events, this research focuses on finding techniques that make optimal use of prior knowledge and computer simulation in the recognition task. Thus, a suitably modified, approximate n-best variant of

  15. Nuclear activation techniques in the life sciences

    Energy Technology Data Exchange (ETDEWEB)



    The analysis of the elemental composition of biological materials is presently undertaken on a large scale in many countries around the world One recent estimate puts the number of such analyses at six thousand million single-element determinations per year, of which about sixteen million are for the so-called trace elements. Since many of these elements are known to play an important role in relation to health and disease, there is considerable interest in learning more about the ways in which they function in living organisms. Nuclear activation techniques, generally referred to collectively as 'activation analysis' constitute an important group of methods for the analysis of the elemental composition of biological materials. Generally they rely on the use of a research nuclear reactor as a source of neutrons for bombarding small samples of biological material, followed by a measurement of the induced radioactivity to provide an estimate of the concentrations of elements. Other methods of activation with Bremsstrahlung and charged particles may also be used, and have their own special applications. These methods of in vitro analysis are particularly suitable for the study of trace elements. Another important group of methods makes use of neutrons from isotopic neutron sources or neutron generators to activate the whole body, or a part of the body, of a living patient. They are generally used for the study of major elements such as Ca, Na and N. All these techniques have previously been the subject of two symposia organised by the IAEA in 1967 and 1972. The present meeting was held to review some of the more recent developments in this field and also to provide a viewpoint on the current status of nuclear activation techniques vis-a-vis other competing non-nuclear methods of analysis.

  16. Active learning methods for interactive image retrieval. (United States)

    Gosselin, Philippe Henri; Cord, Matthieu


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

  17. Student Perceptions of Active Learning (United States)

    Lumpkin, Angela; Achen, Rebecca M.; Dodd, Regan K.


    A paradigm shift from lecture-based courses to interactive classes punctuated with engaging, student-centered learning activities has begun to characterize the work of some teachers in higher education. Convinced through the literature of the values of using active learning strategies, we assessed through an action research project in five college…

  18. Exploring the Earth Using Deep Learning Techniques (United States)

    Larraondo, P. R.; Evans, B. J. K.; Antony, J.


    Research using deep neural networks have significantly matured in recent times, and there is now a surge in interest to apply such methods to Earth systems science and the geosciences. When combined with Big Data, we believe there are opportunities for significantly transforming a number of areas relevant to researchers and policy makers. In particular, by using a combination of data from a range of satellite Earth observations as well as computer simulations from climate models and reanalysis, we can gain new insights into the information that is locked within the data. Global geospatial datasets describe a wide range of physical and chemical parameters, which are mostly available using regular grids covering large spatial and temporal extents. This makes them perfect candidates to apply deep learning methods. So far, these techniques have been successfully applied to image analysis through the use of convolutional neural networks. However, this is only one field of interest, and there is potential for many more use cases to be explored. The deep learning algorithms require fast access to large amounts of data in the form of tensors and make intensive use of CPU in order to train its models. The Australian National Computational Infrastructure (NCI) has recently augmented its Raijin 1.2 PFlop supercomputer with hardware accelerators. Together with NCI's 3000 core high performance OpenStack cloud, these computational systems have direct access to NCI's 10+ PBytes of datasets and associated Big Data software technologies (see and To effectively use these computing infrastructures requires that both the data and software are organised in a way that readily supports the deep learning software ecosystem. Deep learning software, such as the open source TensorFlow library, has allowed us to demonstrate the possibility of generating geospatial models by combining information from

  19. Active Learning through Online Instruction (United States)

    Gulbahar, Yasemin; Kalelioglu, Filiz


    This article explores the use of proper instructional techniques in online discussions that lead to meaningful learning. The research study looks at the effective use of two instructional techniques within online environments, based on qualitative measures. "Brainstorming" and "Six Thinking Hats" were selected and implemented…

  20. CRDM motion analysis using machine learning technique

    International Nuclear Information System (INIS)

    Nishimura, Takuya; Nakayama, Hiroyuki; Saitoh, Mayumi; Yaguchi, Seiji


    Magnetic jack type Control Rod Drive Mechanism (CRDM) for pressurized water reactor (PWR) plant operates control rods in response to electrical signals from a reactor control system. CRDM operability is evaluated by quantifying armature's response of closed/opened time which means interval time between coil energizing/de-energizing points and armature closed/opened points. MHI has already developed an automatic CRDM motion analysis and applied it to actual plants so far. However, CRDM operational data has wide variation depending on their characteristics such as plant condition, plant, etc. In the existing motion analysis, there is an issue of analysis accuracy for applying a single analysis technique to all plant conditions, plants, etc. In this study, MHI investigated motion analysis using machine learning (Random Forests) which is flexibly accommodated to CRDM operational data with wide variation, and is improved analysis accuracy. (author)

  1. Learning and Active Aging (United States)

    Boulton-Lewis, Gillian M.; Buys, Laurie; Lovie-Kitchin, Jan


    Learning is an important aspect of aging productively. This paper describes results from 2645 respondents (aged from 50 to 74+ years) to a 165-variable postal survey in Australia. The focus is on learning and its relation to work; social, spiritual, and emotional status; health; vision; home; life events; and demographic details. Clustering…

  2. Agnostic Active Learning Without Constraints


    Beygelzimer, Alina; Hsu, Daniel; Langford, John; Zhang, Tong


    We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate hypotheses is maintained throughout learning, and only hypotheses from this set are ever returned. By avoiding this version space approach, our algorithm sheds the computational burden and brittleness associated with maintaining version spaces, yet still allows for substantial improvements over supervised learning f...

  3. Application of Machine Learning Techniques in Aquaculture


    Rahman, Akhlaqur; Tasnim, Sumaira


    In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.

  4. Automatic Earthquake Detection by Active Learning (United States)

    Bergen, K.; Beroza, G. C.


    In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

  5. Active Learning and Teaching: Improving Postsecondary Library Instruction. (United States)

    Allen, Eileen E.


    Discusses ways to improve postsecondary library instruction based on theories of active learning. Topics include a historical background of active learning; student achievement and attitudes; cognitive development; risks; active teaching; and instructional techniques, including modified lectures, brainstorming, small group work, cooperative…

  6. Active Learning Using Arbitrary Binary Valued Queries (United States)


    active learning in the sense that the learner has complete choice in the information received. Specifically, we allow the learner to ask arbitrary questions. We consider both active learning under a fixed distribution and distribution-free active learning . In the case of active learning , the...a concept class is actively learnable iff it is finite, so that active learning is in fact less powerful than the usual passive learning model. We

  7. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques (United States)

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili


    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  8. Learning plan applicability through active mental entities

    International Nuclear Information System (INIS)

    Baroni, Pietro; Fogli, Daniela; Guida, Giovanni


    This paper aims at laying down the foundations of a new approach to learning in autonomous mobile robots. It is based on the assumption that robots can be provided with built-in action plans and with mechanisms to modify and improve such plans. This requires that robots are equipped with some form of high-level reasoning capabilities. Therefore, the proposed learning technique is embedded in a novel distributed control architecture featuring an explicit model of robot's cognitive activity. In particular, cognitive activity is obtained by the interaction of active mental entities, such as intentions, persuasions and expectations. Learning capabilities are implemented starting from the interaction of such mental entities. The proposal is illustrated through an example concerning a robot in charge of reaching a target in an unknown environment cluttered with obstacles

  9. Active Learning Through Discussion in E-Learning


    Daru Wahyuningsih


    Active learning is generally made by a lecturer in learning face to face. In the face to face learning, lecturer can implement a variety of teaching methods to make students actively involved in learning. This is different from learning that is actuating in e-learning. The main characteristic of e-learning is learning that can take place anytime and anywhere. Special strategies are needed so that lecturer can make students play an active role in the course of e-learning. Research in order to ...

  10. Pulsed neutron activation calibration technique

    International Nuclear Information System (INIS)

    Kehler, P.


    A pulsed neutron activation (PNA) for measurement of two-phase flow consists of a pulsed source of fast neutron to activate the oxygen in a steam-water mixture. Flow is measured downstream by an NaI detector. Measured counts are sorted by a multiscaler into different time channels. A counts vs. time distribution typical for two-phase flow with slip between the two phases is obtained. Proper evaluation for the counts/time distribution leads to flow-regime independent equations for the average of the inverse transil time and the average density. After calculation of the average mass flow velocity, the true mass flow is derived


    Directory of Open Access Journals (Sweden)

    T. Hamsapriya


    Full Text Available E-mail is one of the most popular and frequently used ways of communication due to its worldwide accessibility, relatively fast message transfer, and low sending cost. The flaws in the e-mail protocols and the increasing amount of electronic business and financial transactions directly contribute to the increase in e-mail-based threats. Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Spam emails are invading users without their consent and filling their mail boxes. They consume more network capacity as well as time in checking and deleting spam mails. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. While most of the users want to do right think to avoid and get rid of spam, they need clear and simple guidelines on how to behave. In spite of all the measures taken to eliminate spam, they are not yet eradicated. Also when the counter measures are over sensitive, even legitimate emails will be eliminated. Among the approaches developed to stop spam, filtering is the one of the most important technique. Many researches in spam filtering have been centered on the more sophisticated classifier-related issues. In recent days, Machine learning for spam classification is an important research issue. The effectiveness of the proposed work is explores and identifies the use of different learning algorithms for classifying spam messages from e-mail. A comparative analysis among the algorithms has also been presented.

  12. Experiential Learning and Learning Environments: The Case of Active Listening Skills (United States)

    Huerta-Wong, Juan Enrique; Schoech, Richard


    Social work education research frequently has suggested an interaction between teaching techniques and learning environments. However, this interaction has never been tested. This study compared virtual and face-to-face learning environments and included active listening concepts to test whether the effectiveness of learning environments depends…

  13. eLearning techniques supporting problem based learning in clinical simulation. (United States)

    Docherty, Charles; Hoy, Derek; Topp, Helena; Trinder, Kathryn


    This paper details the results of the first phase of a project using eLearning to support students' learning within a simulated environment. The locus was a purpose built clinical simulation laboratory (CSL) where the School's philosophy of problem based learning (PBL) was challenged through lecturers using traditional teaching methods. a student-centred, problem based approach to the acquisition of clinical skills that used high quality learning objects embedded within web pages, substituting for lecturers providing instruction and demonstration. This encouraged student nurses to explore, analyse and make decisions within the safety of a clinical simulation. Learning was facilitated through network communications and reflection on video performances of self and others. Evaluations were positive, students demonstrating increased satisfaction with PBL, improved performance in exams, and increased self-efficacy in the performance of nursing activities. These results indicate that eLearning techniques can help students acquire clinical skills in the safety of a simulated environment within the context of a problem based learning curriculum.

  14. The International Active Learning Space

    DEFF Research Database (Denmark)

    Manners, Ian James


    -Danish students receive the basic international and intercultural skills and knowledge they need in current society. The English-language masters’ seminars I teach at the Department of Political Science are international in terms of students and teacher, but they are also Active Learning seminars......-Danish students (and sometimes teachers) rarely speak to each other or learn each other’s names. In the international AL spaces I create, students must work together on joint tasks which require interaction to address tasks and integration in order to benefit from the multinational activity groups. Planning AL...... that complete the seminar soon become vocal advocates of international AL. Ultimately, enriching student learning through immersing Danish and international students in an international AL space is, for me, the best way of ensuring an internationalised learning outcome, rather than just international mobility....

  15. Active Learning for Player Modeling

    DEFF Research Database (Denmark)

    Shaker, Noor; Abou-Zleikha, Mohamed; Shaker, Mohammad


    Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player...... experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a case study and we employ the random forest method to learn mod- els of player experience through the active learning approach. The results obtained suggest that only part of the dataset (up to half the size...... that the method can be used online during the content generation process where the mod- els can improve and better content can be presented as the game is being played....

  16. Active Learning in ASTR 101 Lectures (United States)

    Deming, Grace L.


    The lecture is the most common teaching method used at colleges and universities, but does this format facilitate student learning? Lectures can be brilliantly delivered, but they are received by a passive audience. As time passes during a lecture, student attention and effective notetaking diminish. Many students become more interested in a subject and retain information longer in courses that rely on active rather than passive teaching methods. Interactive teaching strategies such as the think-pair-share-(write), the 3-minute paper, and the misconception confrontation can be used to actively engage students during lecture. As a cooperative learning strategy, the think-pair-share-(write) technique requires active discussion by everyone in the class. The "write" component structures individual accountability into the activity. The 3-minute paper is an expansion of the standard 1-minute paper feedback technique, but is required of all students rather than voluntary or anonymous. The misconception confrontation technique allows students to focus on how their pre- conceived notions differ from the scientific explanation. These techniques can be easily adopted by anyone currently using a standard lecture format for introductory astronomy. The necessary components are a commitment by the instructor to require active participation by all students and a willingness to try new teaching methods.



    Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed


    Machine Learning approaches are good in solving problems that have less information. In most cases, the software domain problems characterize as a process of learning that depend on the various circumstances and changes accordingly. A predictive model is constructed by using machine learning approaches and classified them into defective and non-defective modules. Machine learning techniques help developers to retrieve useful information after the classification and enable them to analyse data...

  18. IoT Security Techniques Based on Machine Learning


    Xiao, Liang; Wan, Xiaoyue; Lu, Xiaozhen; Zhang, Yanyong; Wu, Di


    Internet of things (IoT) that integrate a variety of devices into networks to provide advanced and intelligent services have to protect user privacy and address attacks such as spoofing attacks, denial of service attacks, jamming and eavesdropping. In this article, we investigate the attack model for IoT systems, and review the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning. We focus on the machine le...

  19. Active Learning versus Traditional Teaching

    Directory of Open Access Journals (Sweden)

    L.A. Azzalis


    Full Text Available In traditional teaching most of the class time is spent with the professor lecturing and the students watching and listening. The students work individually, and cooperation is discouraged. On the other hand,  active learning  changes the focus of activity from the teacher to the learners, in which students solve problems, answer questions, formulate questions of their own, discuss, explain, debate during class;  moreover, students work in teams on problems and projects under conditions that assure positive interdependence and individual accountability. Although student-centered methods have repeatedly been shown to be superior to the traditional teacher-centered approach to instruction, the literature regarding the efficacy of various teaching methods is inconclusive. The purpose of this study was to compare the student perceptions of course and instructor effectiveness, course difficulty, and amount learned between the active learning and lecture sections  in Health Sciences´ courses by statistical data from Anhembi Morumbi University. Results indicated significant  difference between active  learning and traditional  teaching. Our conclusions were that strategies promoting  active  learning to  traditional lectures could increase knowledge and understanding.

  20. Techniques to Promote Reflective Practice and Empowered Learning. (United States)

    Nguyen-Truong, Connie Kim Yen; Davis, Andra; Spencer, Cassius; Rasmor, Melody; Dekker, Lida


    Health care environments are fraught with fast-paced critical demands and ethical dilemmas requiring decisive nursing actions. Nurse educators must prepare nursing students to practice skills, behaviors, and attitudes needed to meet the challenges of health care demands. Evidence-based, innovative, multimodal techniques with novice and seasoned nurses were incorporated into a baccalaureate (BSN) completion program (RN to-BSN) to deepen learning, complex skill building, reflective practice, teamwork, and compassion toward the experiences of others. Principles of popular education for engaged teaching-learning were applied. Nursing students experience equitable access to content through co-constructing knowledge with four creative techniques. Four creative techniques include poem reading aloud to facilitate connectedness; mindfulness to cultivate self-awareness; string figure activities to demonstrate indigenous knowledge and teamwork; and cartooning difficult subject matter. Nursing school curricula can promote a milieu for developing organizational skills to manage simultaneous priorities, practice reflectively, and develop empathy and the authenticity that effective nursing requires. [J Nurs Educ. 2018;57(2):115-120.]. Copyright 2018, SLACK Incorporated.

  1. Study of CT image texture using deep learning techniques (United States)

    Dutta, Sandeep; Fan, Jiahua; Chevalier, David


    For CT imaging, reduction of radiation dose while improving or maintaining image quality (IQ) is currently a very active research and development topic. Iterative Reconstruction (IR) approaches have been suggested to be able to offer better IQ to dose ratio compared to the conventional Filtered Back Projection (FBP) reconstruction. However, it has been widely reported that often CT image texture from IR is different compared to that from FBP. Researchers have proposed different figure of metrics to quantitate the texture from different reconstruction methods. But there is still a lack of practical and robust method in the field for texture description. This work applied deep learning method for CT image texture study. Multiple dose scans of a 20cm diameter cylindrical water phantom was performed on Revolution CT scanner (GE Healthcare, Waukesha) and the images were reconstructed with FBP and four different IR reconstruction settings. The training images generated were randomly allotted (80:20) to a training and validation set. An independent test set of 256-512 images/class were collected with the same scan and reconstruction settings. Multiple deep learning (DL) networks with Convolution, RELU activation, max-pooling, fully-connected, global average pooling and softmax activation layers were investigated. Impact of different image patch size for training was investigated. Original pixel data as well as normalized image data were evaluated. DL models were reliably able to classify CT image texture with accuracy up to 99%. Results show that the deep learning techniques suggest that CT IR techniques may help lower the radiation dose compared to FBP.

  2. Machine Learning Techniques in Optimal Design (United States)

    Cerbone, Giuseppe


    Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution

  3. Is Active Learning Like Broccoli? Student Perceptions of Active Learning in Large Lecture Classes (United States)

    Smith, C. Veronica; Cardaciotto, LeeAnn


    Although research suggests that active learning is associated with positive outcomes (e.g., memory, test performance), use of such techniques can be difficult to implement in large lecture-based classes. In the current study, 1,091 students completed out-of-class group exercises to complement course material in an Introductory Psychology class.…

  4. Active learning for Corsika

    Energy Technology Data Exchange (ETDEWEB)

    Baack, Dominik; Temme, Fabian; Buss, Jens; Noethe, Max; Bruegge, Kai [TU Dortmund, Dortmund (Germany); Collaboration: FACT-Collaboration


    Modern Cosmic-Ray experiments need a huge amount of simulated data. In many cases, only a portion of the data is actually needed for following steps in the analysis chain, for example training of different machine learning algorithms. The other parts are thrown away by the trigger simulation of the experiment or so not increase the quality of following analysis steps. In this talk, I present a new developed package for the air shower simulation software CORSIKA. This extension includes different approaches to reduce the amount of unnecessary computation. One approach is a new internal particle stack implementation that allows to priorize the processing of special intermediate shower particles and the removal of not needed shower particles. The second approach is the possibility to sent various information of the initial particle and parameters of the status of the partial simulated event to an external application to approximate the information gain of the current simulator event. If the information gain is to low, the current event simulation gets terminated and all information get stored into a central database. For the Simulation - Server communication a simple network protocol has been developed.

  5. Data Mining Practical Machine Learning Tools and Techniques

    CERN Document Server

    Witten, Ian H; Hall, Mark A


    Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

  6. Maximizing Reading Narrative Text Ability by Probing Prompting Learning Technique

    Directory of Open Access Journals (Sweden)

    Wiwied Pratiwi


    Full Text Available The objective of this research was to know whether Probing Prompting Learning Technique can be used to get the maximum effect of students’ reading narrative ability in teaching and learning process. This research was applied collaborative action reEsearch, this research was done in two cycle. The subject of this research was 23 students at tenth grade of SMA Kartikatama Metro. The result of the research showed that the Probing Prompting Learning Technique is useful and effective to help students get maximum effect of their reading. Based on the results of the questionnaire obtained an average percentage of 95%, it indicated that application of Probing Prompting Learning Technique in teaching l reading was appropriately applied. In short that students’ responses toward Probing Prompting Learning Technique in teaching reading was positive. In conclusion, Probing Prompting Learning Technique can get maximum effect of students’ reading ability. In relation to the result of the reserach, some suggestion are offered to english teacher, that  the use of Probing Prompting learning Technique in teaching reading will get the maximum effect of students’ reading abilty.

  7. Machine learning of molecular properties: Locality and active learning (United States)

    Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V.


    In recent years, the machine learning techniques have shown great potent1ial in various problems from a multitude of disciplines, including materials design and drug discovery. The high computational speed on the one hand and the accuracy comparable to that of density functional theory on another hand make machine learning algorithms efficient for high-throughput screening through chemical and configurational space. However, the machine learning algorithms available in the literature require large training datasets to reach the chemical accuracy and also show large errors for the so-called outliers—the out-of-sample molecules, not well-represented in the training set. In the present paper, we propose a new machine learning algorithm for predicting molecular properties that addresses these two issues: it is based on a local model of interatomic interactions providing high accuracy when trained on relatively small training sets and an active learning algorithm of optimally choosing the training set that significantly reduces the errors for the outliers. We compare our model to the other state-of-the-art algorithms from the literature on the widely used benchmark tests.

  8. Lectures Abandoned: Active Learning by Active Seminars

    DEFF Research Database (Denmark)

    Christensen, Henrik Bærbak; Corry, Aino Vonge


    Traditional lecture-based courses are widely criticised for be- ing less eective in teaching. The question is of course what should replace the lectures and various active learning tech- niques have been suggested and studied. In this paper, we report on our experiences of redesigning a software ......- tive seminars as a replacement of traditional lectures, an activity template for the contents of active seminars, an ac- count on how storytelling supported the seminars, as well as reports on our and the students' experiences....

  9. Active Learning in Introductory Climatology. (United States)

    Dewey, Kenneth F.; Meyer, Steven J.


    Introduces a software package available for the climatology curriculum that determines possible climatic events according to a long-term climate history. Describes the integration of the software into the curriculum and presents examples of active learning. (Contains 19 references.) (YDS)

  10. Oral Hygiene. Learning Activity Package. (United States)

    Hime, Kirsten

    This learning activity package on oral hygiene is one of a series of 12 titles developed for use in health occupations education programs. Materials in the package include objectives, a list of materials needed, a list of definitions, information sheets, reviews (self evaluations) of portions of the content, and answers to reviews. These topics…

  11. Learning by Doing: Twenty Successful Active Learning Exercises for Information Systems Courses

    Directory of Open Access Journals (Sweden)

    Alanah Mitchell


    Full Text Available Aim/Purpose: This paper provides a review of previously published work related to active learning in information systems (IS courses. Background: There are a rising number of strategies in higher education that offer promise in regards to getting students’ attention and helping them learn, such as flipped classrooms and offering courses online. These learning strategies are part of the pedagogical technique known as active learning. Active learning is a strategy that became popular in the early 1990s and has proven itself as a valid tool for helping students to be engaged with learning. Methodology: This work follows a systematic method for identifying and coding previous research based on an aspect of interest. The authors identified and assessed research through a search of ABI/Inform scholarly journal abstracts and keywords, as well as additional research databases, using the search terms “active learning” and “information systems” from 2000 through June 2016. Contribution: This synthesis of active learning exercises provides guidance for information technology faculty looking to implement active learning strategies in their classroom by demonstrating how IS faculty might begin to introduce more active learning techniques in their teaching as well as by presenting a sample teaching agenda for a class that uses a mix of active and passive learning techniques to engage student learning. Findings: Twenty successful types of active learning exercises in IS courses are presented. Recommendations for Practitioners\t: This paper offers a “how to” resource of successful active learning strategies for IS faculty interested in implementing active learning in the classroom. Recommendation for Researchers: This work provides an example of a systematic literature review as a means to assess successful implementations of active learning in IS. Impact on Society: An updated definition of active learning is presented as well as a meaningful

  12. Engaging Students' Learning Through Active Learning

    Directory of Open Access Journals (Sweden)

    Margaret Fitzsimons


    Full Text Available This paper discusses a project carried out with thirty six final year undergraduate students, studying the Bachelor of Science in Business and Management and taking the module Small Business Management during the academic year 2012 and 2013 in Dublin Institute of Technology. The research had two separate objectives, 1 to engage in active learning by having students work on a consulting project in groups for a real life business and 2 to improve student learning. The Small Business Management previously had a group assignment that was to choose an article related to entrepreneurship and critic it and present it to the class. Anecdotally, from student feedback, it was felt that this process did not engage students and also did not contribute to the key competencies necessary in order to be an entrepreneur. The desire was for students on successful completion of this module to have better understood how business is conducted and equip them with core skills such as innovation, critical thinking, problem solving and decision making .Student buy in was achieved by getting the students to select their own groups and also work out between each group from a one page brief provided by the businesses which business they would like to work with. It was important for the businesses to also feel their time spent with students was worthwhile so they were presented with a report from the students at the end of the twelve weeks and invited into the College to hear the presentations from students. Students were asked to provide a reflection on their three key learning points from the assignment and to answer specific questions designed to understand what they learnt and how and their strengths and weaknesses. A survey was sent to the businesses that took part to understand their experiences. The results were positive with student engagement and learning rating very highly and feedback from the businesses demonstrated an appreciation of having a different

  13. E-learning systems intelligent techniques for personalization

    CERN Document Server

    Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C


    This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .

  14. A Comparative Analysis of Machine Learning Techniques for Credit Scoring


    Nwulu, Nnamdi; Oroja, Shola; İlkan, Mustafa


    Abstract Credit Scoring has become an oft researched topic in light of the increasing volatility of the global economy and the recent world financial crisis. Amidst the many methods used for credit scoring, machine learning techniques are becoming increasingly popular due to their efficient and accurate nature and relative simplicity. Furthermore machine learning techniques minimize the risk of human bias and error and maximize speed as they are able to perform computation...

  15. Precision Learning Assessment: An Alternative to Traditional Assessment Techniques. (United States)

    Caltagirone, Paul J.; Glover, Christopher E.


    A continuous and curriculum-based assessment method, Precision Learning Assessment (PLA), which integrates precision teaching and norm-referenced techniques, was applied to a math computation curriculum for 214 third graders. The resulting districtwide learning curves defining average annual progress through the computation curriculum provided…

  16. The ICAP Active Learning Framework Predicts the Learning Gains Observed in Intensely Active Classroom Experiences

    Directory of Open Access Journals (Sweden)

    Benjamin L. Wiggins


    Full Text Available STEM classrooms (science, technology, engineering, and mathematics in postsecondary education are rapidly improved by the proper use of active learning techniques. These techniques occupy a descriptive spectrum that transcends passive teaching toward active, constructive, and, finally, interactive methods. While aspects of this framework have been examined, no large-scale or actual classroom-based data exist to inform postsecondary education STEM instructors about possible learning gains. We describe the results of a quasi-experimental study to test the apex of the ICAP framework (interactive, constructive, active, and passive in this ecological classroom environment. Students in interactive classrooms demonstrate significantly improved learning outcomes relative to students in constructive classrooms. This improvement in learning is relatively subtle; similar experimental designs without repeated measures would be unlikely to have the power to observe this significance. We discuss the importance of seemingly small learning gains that might propagate throughout a course or departmental curriculum, as well as improvements with the necessity for faculty to develop and implement similar activities.

  17. Active Learning with Irrelevant Examples (United States)

    Wagstaff, Kiri; Mazzoni, Dominic


    An improved active learning method has been devised for training data classifiers. One example of a data classifier is the algorithm used by the United States Postal Service since the 1960s to recognize scans of handwritten digits for processing zip codes. Active learning algorithms enable rapid training with minimal investment of time on the part of human experts to provide training examples consisting of correctly classified (labeled) input data. They function by identifying which examples would be most profitable for a human expert to label. The goal is to maximize classifier accuracy while minimizing the number of examples the expert must label. Although there are several well-established methods for active learning, they may not operate well when irrelevant examples are present in the data set. That is, they may select an item for labeling that the expert simply cannot assign to any of the valid classes. In the context of classifying handwritten digits, the irrelevant items may include stray marks, smudges, and mis-scans. Querying the expert about these items results in wasted time or erroneous labels, if the expert is forced to assign the item to one of the valid classes. In contrast, the new algorithm provides a specific mechanism for avoiding querying the irrelevant items. This algorithm has two components: an active learner (which could be a conventional active learning algorithm) and a relevance classifier. The combination of these components yields a method, denoted Relevance Bias, that enables the active learner to avoid querying irrelevant data so as to increase its learning rate and efficiency when irrelevant items are present. The algorithm collects irrelevant data in a set of rejected examples, then trains the relevance classifier to distinguish between labeled (relevant) training examples and the rejected ones. The active learner combines its ranking of the items with the probability that they are relevant to yield a final decision about which item



    Arshdeep Singh Syal*1 & Abhinav Gupta2


    A human face provides a lot of information that allows another person to identify characteristics such as age, sex, etc. Therefore, the challenge is to develop an age group prediction system using the automatic learning method. The task of estimating the age group of the human from their frontal facial images is very captivating, but also challenging because of the pattern of personalized and non-linear aging that differs from one person to another. This paper examines the problem of predicti...

  19. Prostate Cancer Probability Prediction By Machine Learning Technique. (United States)

    Jović, Srđan; Miljković, Milica; Ivanović, Miljan; Šaranović, Milena; Arsić, Milena


    The main goal of the study was to explore possibility of prostate cancer prediction by machine learning techniques. In order to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results. Machine learning techniques are the most common techniques for the creation of the predictive models. Therefore in this study several machine techniques were applied and compared. The obtained results were analyzed and discussed. It was concluded that the machine learning techniques could be used for the relevant prediction of prostate cancer.

  20. StreamAR: incremental and active learning with evolving sensory data for activity recognition


    Abdallah, Z.; Gaber, M.; Srinivasan, B.; Krishnaswamy, S.


    Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition Systems, termed StreamAR. The system incorporates incremental and active learning for mining user ...

  1. Using IMS Learning Design to model collaborative learning activities

    NARCIS (Netherlands)

    Tattersall, Colin


    IMS Learning Design provides a counter to the trend towards designing for lone-learners reading from screens. It guides staff and educational developers to start not with content, but with learning activities and the achievement of learning objectives. It recognises that learning can happen without

  2. Modern machine learning techniques and their applications in cartoon animation research

    CERN Document Server

    Yu, Jun


    The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations

  3. Modelling tick abundance using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Kjær, Lene Jung; Korslund, L.; Kjelland, V.

    satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution (presence/absence of ticks) and relative tick abundance of nymphs and larvae in southern Scandinavia. For nymphs, the predicted abundance had a positive correlation with observed abundance...... the predicted distribution of larvae was mostly even throughout Denmark, it was primarily around the coastlines in Norway and Sweden. Abundance was fairly low overall except in some fragmented patches corresponding to forested habitats in the region. Machine learning techniques allow us to predict for larger...... the collected ticks for pathogens and using the same machine learning techniques to develop prevalence maps of the ScandTick region....

  4. Enhancing E-Learning with VRML Techniques


    Sangeetha Senthilkumar; E. Kirubakaran


    Virtual Reality (VR) is a computer-generated three-dimensional space that is multi-sensorial, interactive and engaging. Virtual reality is an artificial environment that is created with software and presented to the user in such a way that the user suspends belief and accepts it as a real environment. On a computer, virtual reality is primarily experienced through two of the five senses: sight and sound. This research paper is focused on enhancing E-Learning using the three dimensional Web Te...

  5. Instructional Utility and Learning Efficacy of Common Active Learning Strategies (United States)

    McConell, David A.; Chapman, LeeAnna; Czaijka, C. Douglas; Jones, Jason P.; Ryker, Katherine D.; Wiggen, Jennifer


    The adoption of active learning instructional practices in college science, technology, engineering, and mathematics (STEM) courses has been shown to result in improvements in student learning, contribute to increased retention rates, and reduce the achievement gap among different student populations. Descriptions of active learning strategies…


    National Aeronautics and Space Administration — IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING ISAAC PERSING AND VINCENT NG Abstract. Active learning has been successfully applied to many natural language...

  7. History and Evolution of Active Learning Spaces (United States)

    Beichner, Robert J.


    This chapter examines active learning spaces as they have developed over the years. Consistently well-designed classrooms can facilitate active learning even though the details of implementing pedagogies may differ.

  8. Machine learning techniques to examine large patient databases. (United States)

    Meyfroidt, Geert; Güiza, Fabian; Ramon, Jan; Bruynooghe, Maurice


    Computerization in healthcare in general, and in the operating room (OR) and intensive care unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific properties. Machine learning techniques are able to examine and to extract knowledge from large databases in an automatic way. Although the number of potential applications for these techniques in medicine is large, few medical doctors are familiar with their methodology, advantages and pitfalls. A general overview of machine learning techniques, with a more detailed discussion of some of these algorithms, is presented in this review.

  9. Active Learning for Text Classification


    Hu, Rong


    Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

  10. Learning Programming Technique through Visual Programming Application as Learning Media with Fuzzy Rating (United States)

    Buditjahjanto, I. G. P. Asto; Nurlaela, Luthfiyah; Ekohariadi; Riduwan, Mochamad


    Programming technique is one of the subjects at Vocational High School in Indonesia. This subject contains theory and application of programming utilizing Visual Programming. Students experience some difficulties to learn textual learning. Therefore, it is necessary to develop media as a tool to transfer learning materials. The objectives of this…


    Directory of Open Access Journals (Sweden)

    Dr. Issy Yuliasri


    Full Text Available This paper is based on the results of pre-test post-test, feedback questionnaire and observation during a community service program entitled ―Training on English Teaching using Cooperative Learning Techniques for Elementary and Junior High School Teachers of Sekolah Alam Arridho Semarang‖. It was an English teaching training program intended to equip the teachers with the knowledge and skills of using the different cooperative learning techniques such as jigsaw, think-pair-share, three-step interview, roundrobin braistorming, three-minute review, numbered heads together, team-pair-solo, circle the sage, dan partners. This program was participated by 8 teachers of different subjects (not only English, but most of them had good mastery of English. The objectives of this program was to improve teachers‘ skills in using the different cooperative learning techniques to vary their teaching, so that students would be more motivated to learn and improve their English skill. Besides, the training also gave the teachers the knowledge and skills to adjust their techniques with the basic competence and learning objectives to be achieved as well as with the teaching materials to be used. This was also done through workshops using cooperative learning techniques, so that the participants had real experiences of using cooperative learning techniques (learning by doing. The participants were also encouraged to explore the applicability of the techniques in their classroom contexts, in different areas of their teaching. This community service program showed very positive results. The pre-test and post-test results showed that before the training program all the participants did not know the nine cooperative techniques to be trained, but after the program they mastered the techniques as shown from the teaching-learning scenarios they developed following the test instructions. In addition, the anonymous questionnaires showed that all the participants

  12. Machine learning techniques for razor triggers

    CERN Document Server

    Kolosova, Marina


    My project was focused on the development of a neural network which can predict if an event passes or not a razor trigger. Using synthetic data containing jets and missing transverse energy we built and trained a razor network by supervised learning. We accomplished a ∼ 91% agreement between the output of the neural network and the target while the other 10% was due to the noise of the neural network. We could apply such networks during the L1 trigger using neuromorhic hardware. Neuromorphic chips are electronic systems that function in a way similar to an actual brain, they are faster than GPUs or CPUs, but they can only be used with spiking neural networks.

  13. Predicting radiotherapy outcomes using statistical learning techniques

    International Nuclear Information System (INIS)

    El Naqa, Issam; Bradley, Jeffrey D; Deasy, Joseph O; Lindsay, Patricia E; Hope, Andrew J


    Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

  14. The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement (United States)

    Makahinda, T.


    The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

  15. Incorporation of Socio-scientific Content into Active Learning Activities (United States)

    King, D. B.; Lewis, J. E.; Anderson, K.; Latch, D.; Sutheimer, S.; Webster, G.; Moog, R.


    Active learning has gained increasing support as an effective pedagogical technique to improve student learning. One way to promote active learning in the classroom is the use of in-class activities in place of lecturing. As part of an NSF-funded project, a set of in-class activities have been created that use climate change topics to teach chemistry content. These activities use the Process Oriented Guided Inquiry Learning (POGIL) methodology. In this pedagogical approach a set of models and a series of critical thinking questions are used to guide students through the introduction to or application of course content. Students complete the activities in their groups, with the faculty member as a facilitator of learning. Through assigned group roles and intentionally designed activity structure, process skills, such as teamwork, communication, and information processing, are developed during completion of the activity. Each of these climate change activities contains a socio-scientific component, e.g., social, ethical and economic data. In one activity, greenhouse gases are used to explain the concept of dipole moment. Data about natural and anthropogenic production rates, global warming potential and atmospheric lifetimes for a list of greenhouse gases are presented. The students are asked to identify which greenhouse gas they would regulate, with a corresponding explanation for their choice. They are also asked to identify the disadvantages of regulating the gas they chose in the previous question. In another activity, where carbon sequestration is used to demonstrate the utility of a phase diagram, students use economic and environmental data to choose the best location for sequestration. Too often discussions about climate change (both in and outside the classroom) consist of purely emotional responses. These activities force students to use data to support their arguments and hypothesize about what other data could be used in the corresponding discussion to

  16. Create a good learning environment and motivate active learning enthusiasm (United States)

    Bi, Weihong; Fu, Guangwei; Fu, Xinghu; Zhang, Baojun; Liu, Qiang; Jin, Wa


    In view of the current poor learning initiative of undergraduates, the idea of creating a good learning environment and motivating active learning enthusiasm is proposed. In practice, the professional tutor is allocated and professional introduction course is opened for college freshman. It can promote communication between the professional teachers and students as early as possible, and guide students to know and devote the professional knowledge by the preconceived form. Practice results show that these solutions can improve the students interest in learning initiative, so that the active learning and self-learning has become a habit in the classroom.


    Directory of Open Access Journals (Sweden)

    Sergio Zepeda-Hernández


    Full Text Available Teachers who currently use the traditional method teacher-centered learning, are having various difficulties with the new generations of students. New learning methods are required to allow students to focus more positive attitudes towards their learning. In this paper, we show how the evaluation and activities based on Active Learning and Gamification, can be an alternative to generate a more positive attitude of students and create a more friendly environment in the classroom. This research was conducted using the qualitative research and ethnographic method as technique.

  18. Quality assurance techniques for activation analysis

    International Nuclear Information System (INIS)

    Becker, D.A.


    The principles and techniques of quality assurance are applied to the measurement method of activation analysis. Quality assurance is defined to include quality control and quality assessment. Plans for quality assurance include consideration of: personnel; facilities; analytical design; sampling and sample preparation; the measurement process; standards; and documentation. Activation analysis concerns include: irradiation; chemical separation; counting/detection; data collection, and analysis; and calibration. Types of standards discussed include calibration materials and quality assessment materials

  19. Promoting Cooperative Learning in the Classroom: Comparing Explicit and Implicit Training Techniques

    Directory of Open Access Journals (Sweden)

    Anne Elliott


    Full Text Available In this study, we investigated whether providing 4th and 5th-grade students with explicit instruction in prerequisite cooperative-learning skills and techniques would enhance their academic performance and promote in them positive attitudes towards cooperative learning. Overall, students who received explicit training outperformed their peers on both the unit project and test and presented more favourable attitudes towards cooperative learning. The findings of this study support the use of explicitly instructing students about the components of cooperative learning prior to engaging in collaborative activities. Implications for teacher-education are discussed.

  20. Analysing CMS transfers using Machine Learning techniques

    CERN Document Server

    Diotalevi, Tommaso


    LHC experiments transfer more than 10 PB/week between all grid sites using the FTS transfer service. In particular, CMS manages almost 5 PB/week of FTS transfers with PhEDEx (Physics Experiment Data Export). FTS sends metrics about each transfer (e.g. transfer rate, duration, size) to a central HDFS storage at CERN. The work done during these three months, here as a Summer Student, involved the usage of ML techniques, using a CMS framework called DCAFPilot, to process this new data and generate predictions of transfer latencies on all links between Grid sites. This analysis will provide, as a future service, the necessary information in order to proactively identify and maybe fix latency issued transfer over the WLCG.

  1. Learning activism, acting with phronesis (United States)

    Lee, Yew-Jin


    The article "Socio-political development of private school children mobilising for disadvantaged others" by Darren Hoeg, Natalie Lemelin, and Lawrence Bencze described a language-learning curriculum that drew on elements of Socioscientific issues and Science, Technology, Society and Environment. Results showed that with a number of enabling factors acting in concert, learning about and engagement in practical action for social justice and equity are possible. An alternative but highly compatible framework is now introduced—phronetic social research—as an action-oriented, wisdom-seeking research stance for the social sciences. By so doing, it is hoped that forms of phronetic social research can gain wider currency among those that promote activism as one of many valued outcomes of an education in science.

  2. Developing metacognition: a basis for active learning

    NARCIS (Netherlands)

    Vos, Henk; de Graaff, E.


    The reasons to introduce formats of Active Learning in Engineering (ALE) like project work, problem based learning, use of cases, etc., are mostly based on practical experience and sometimes from applied research on teaching and learning. Such research shows that students learn more and different

  3. Contemporary machine learning: techniques for practitioners in the physical sciences (United States)

    Spears, Brian


    Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  4. Event Streams Clustering Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Hanen Bouali


    Full Text Available Data streams are usually of unbounded lengths which push users to consider only recent observations by focusing on a time window, and ignore past data. However, in many real world applications, past data must be taken in consideration to guarantee the efficiency, the performance of decision making and to handle data streams evolution over time. In order to build a selectively history to track the underlying event streams changes, we opt for the continuously data of the sliding window which increases the time window based on changes over historical data. In this paper, to have the ability to access to historical data without requiring any significant storage or multiple passes over the data. In this paper, we propose a new algorithm for clustering multiple data streams using incremental support vector machine and data representative points’ technique. The algorithm uses a sliding window model for the most recent clustering results and data representative points to model the old data clustering results. Our experimental results on electromyography signal show a better clustering than other present in the literature

  5. Active vibration control by robust control techniques

    International Nuclear Information System (INIS)

    Lohar, F.A.


    This paper studies active vibration control of multi-degree-of-freedom system. The control techniques considered are LTR, H/sup 2/ and H/sup infinite/. The results show that LTR controls the vibration but its respective settling time is higher than that of the other techniques. The control performance of H/sup infinite/ control is similar to that of H/sup 2/ control in the case of it weighting functions. However, H/sup infinite/ control is superior to H/sup 2/ control with respect to robustness, steady state error and settling time. (author)

  6. Reinforcement learning or active inference? (United States)

    Friston, Karl J; Daunizeau, Jean; Kiebel, Stefan J


    This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.

  7. Reinforcement learning or active inference?

    Directory of Open Access Journals (Sweden)

    Karl J Friston


    Full Text Available This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.

  8. Research on Mobile Learning Activities Applying Tablets (United States)

    Kurilovas, Eugenijus; Juskeviciene, Anita; Bireniene, Virginija


    The paper aims to present current research on mobile learning activities in Lithuania while implementing flagship EU-funded CCL project on application of tablet computers in education. In the paper, the quality of modern mobile learning activities based on learning personalisation, problem solving, collaboration, and flipped class methods is…

  9. Active Learning in the Middle Grades (United States)

    Edwards, Susan


    What is active learning and what does it look like in the classroom? If students are participating in active learning, they are playing a more engaged role in the learning process and are not overly reliant on the teacher (Bransford, Brown, & Cocking, 2003; Petress, 2008). The purpose of this article is to propose a framework to describe and…

  10. Incorporating active learning in psychiatry education. (United States)

    Kumar, Sonia; McLean, Loyola; Nash, Louise; Trigwell, Keith


    We aim to summarise the active learning literature in higher education and consider its relevance for postgraduate psychiatry trainees, to inform the development of a new Formal Education Course (FEC): the Master of Medicine (Psychiatry) at the University of Sydney. We undertook a literature search on 'active learning', 'flipped classroom', 'problem-based learning' and 'psychiatry education'. The effectiveness of active learning pedagogy in higher education is well supported by evidence; however, there have been few psychiatry-specific studies. A new 'flipped classroom' format was developed for the Master of Medicine (Psychiatry). Postgraduate psychiatry training is an active learning environment; the pedagogical approach to FECs requires further evaluation.

  11. Active load control techniques for wind turbines.

    Energy Technology Data Exchange (ETDEWEB)

    van Dam, C.P. (University of California, Davis, CA); Berg, Dale E.; Johnson, Scott J. (University of California, Davis, CA)


    This report provides an overview on the current state of wind turbine control and introduces a number of active techniques that could be potentially used for control of wind turbine blades. The focus is on research regarding active flow control (AFC) as it applies to wind turbine performance and loads. The techniques and concepts described here are often described as 'smart structures' or 'smart rotor control'. This field is rapidly growing and there are numerous concepts currently being investigated around the world; some concepts already are focused on the wind energy industry and others are intended for use in other fields, but have the potential for wind turbine control. An AFC system can be broken into three categories: controls and sensors, actuators and devices, and the flow phenomena. This report focuses on the research involved with the actuators and devices and the generated flow phenomena caused by each device.

  12. Machine learning techniques for persuasion dectection in conversation


    Ortiz, Pedro.


    Approved for public release; distribution is unlimited We determined that it is possible to automatically detect persuasion in conversations using three traditional machine learning techniques, naive bayes, maximum entropy, and support vector machine. These results are the first of their kind and serve as a baseline for all future work in this field. The three techniques consistently outperformed the baseline F-score, but not at a level that would be useful for real world applications. The...

  13. Instructional Television: Visual Production Techniques and Learning Comprehension. (United States)

    Silbergleid, Michael Ian

    The purpose of this study was to determine if increasing levels of complexity in visual production techniques would increase the viewer's learning comprehension and the degree of likeness expressed for a college level instructional television program. A total of 119 mass communications students at the University of Alabama participated in the…

  14. Generating a Spanish Affective Dictionary with Supervised Learning Techniques (United States)

    Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora


    Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…

  15. Applications of neutron activation analysis technique

    International Nuclear Information System (INIS)

    Jonah, S. A.


    The technique was developed as far back as 1936 by G. Hevesy and H. Levy for the analysis of Dy using an isotopic source. Approximately 40 elements can be analyzed by instrumental neutron activation analysis (INNA) technique with neutrons from a nuclear reactor. By applying radiochemical separation, the number of elements that can be analysed may be increased to almost 70. Compared with other analytical methods used in environmental and industrial research, NAA has some unique features. These are multi-element capability, rapidity, reproducibility of results, complementarity to other methods, freedom from analytical blank and independency of chemical state of elements. There are several types of neutron sources namely: nuclear reactors, accelerator-based and radioisotope-based sources, but nuclear reactors with high fluxes of neutrons from the fission of 235 U give the most intense irradiation, and hence the highest available sensitivities for NAA. In this paper, the applications of NAA of socio-economic importance are discussed. The benefits of using NAA and related nuclear techniques for on-line applications in industrial process control are highlighted. A brief description of the NAA set-ups at CERT is enumerated. Finally, NAA is compared with other leading analytical techniques

  16. Computer-aided auscultation learning system for nursing technique instruction. (United States)

    Hou, Chun-Ju; Chen, Yen-Ting; Hu, Ling-Chen; Chuang, Chih-Chieh; Chiu, Yu-Hsien; Tsai, Ming-Shih


    Pulmonary auscultation is a physical assessment skill learned by nursing students for examining the respiratory system. Generally, a sound simulator equipped mannequin is used to group teach auscultation techniques via classroom demonstration. However, nursing students cannot readily duplicate this learning environment for self-study. The advancement of electronic and digital signal processing technologies facilitates simulating this learning environment. This study aims to develop a computer-aided auscultation learning system for assisting teachers and nursing students in auscultation teaching and learning. This system provides teachers with signal recording and processing of lung sounds and immediate playback of lung sounds for students. A graphical user interface allows teachers to control the measuring device, draw lung sound waveforms, highlight lung sound segments of interest, and include descriptive text. Effects on learning lung sound auscultation were evaluated for verifying the feasibility of the system. Fifteen nursing students voluntarily participated in the repeated experiment. The results of a paired t test showed that auscultative abilities of the students were significantly improved by using the computer-aided auscultation learning system.

  17. Practising What We Teach: Vocational Teachers Learn to Research through Applying Action Learning Techniques (United States)

    Lasky, Barbara; Tempone, Irene


    Action learning techniques are well suited to the teaching of organisation behaviour students because of their flexibility, inclusiveness, openness, and respect for individuals. They are no less useful as a tool for change for vocational teachers, learning, of necessity, to become researchers. Whereas traditional universities have always had a…

  18. Simulation-based optimization parametric optimization techniques and reinforcement learning

    CERN Document Server

    Gosavi, Abhijit


    Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to converg...

  19. Active Learning to Improve Fifth Grade Mathematics Achievement in Banten

    Directory of Open Access Journals (Sweden)

    Andri Suherman


    Full Text Available Teaching for active learning is a pedagogical technique that has been actively promoted in Indonesian education through government reform efforts and international development assistance projects for decades. Recently, elementary schools in Banten province received training in active learning instructional strategies from the USAID-funded project, Decentralized Basic Education 2. Post-training evaluations conducted by lecturers from the University of Sultan Ageng Tirtayasa (UNTIRTA: Universitas Sultan Ageng Tirtayasa suggested that teachers were successfully employing active learning strategies in some subjects, but not mathematics. In order to understand the difficulties teachers were having in teaching for active learning in mathematics, and to assist them in using active learning strategies, a team of lecturers from UNTIRTA designed and carried out an action research project to train teachers in an elementary school in the city of Cilegon to use a technique called Magic Fingers in teaching Grade 5 multiplication. During the course of the project the research team discovered that teachers were having problems transferring knowledge gained from training in one context and subject to other school subjects and contexts. Key Words: Mathematics, Teaching for Active Learning, Indonesia, Banten

  20. Exploring Machine Learning Techniques Using Patient Interactions in Online Health Forums to Classify Drug Safety (United States)

    Chee, Brant Wah Kwong


    This dissertation explores the use of personal health messages collected from online message forums to predict drug safety using natural language processing and machine learning techniques. Drug safety is defined as any drug with an active safety alert from the US Food and Drug Administration (FDA). It is believed that this is the first…

  1. Machine Learning Techniques for Stellar Light Curve Classification (United States)

    Hinners, Trisha A.; Tat, Kevin; Thorp, Rachel


    We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB of Kepler light curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature engineering approaches. Studies using machine learning in the field have been primarily done on simulated data, making our study one of the first to use real light-curve data for machine learning approaches. We tuned our data using previous work with simulated data as a template and achieved mixed results between the two approaches. Representation learning using a long short-term memory recurrent neural network produced no successful predictions, but our work with feature engineering was successful for both classification and regression. In particular, we were able to achieve values for stellar density, stellar radius, and effective temperature with low error (∼2%–4%) and good accuracy (∼75%) for classifying the number of transits for a given star. The results show promise for improvement for both approaches upon using larger data sets with a larger minority class. This work has the potential to provide a foundation for future tools and techniques to aid in the analysis of astrophysical data.

  2. The Effect of Group Investigation Learning Model with Brainstroming Technique on Students Learning Outcomes

    Directory of Open Access Journals (Sweden)

    Astiti Kade kAyu


    Full Text Available This study aims to determine the effect of group investigation (GI learning model with brainstorming technique on student physics learning outcomes (PLO compared to jigsaw learning model with brainstroming technique. The learning outcome in this research are the results of learning in the cognitive domain. The method used in this research is experiment with Randomised Postest Only Control Group Design. Population in this research is all students of class XI IPA SMA Negeri 9 Kupang year lesson 2015/2016. The selected sample are 40 students of class XI IPA 1 as the experimental class and 38 students of class XI IPA 2 as the control class using simple random sampling technique. The instrument used is 13 items description test. The first hypothesis was tested by using two tailed t-test. From that, it is obtained that H0 rejected which means there are differences of students physics learning outcome. The second hypothesis was tested using one tailed t-test. It is obtained that H0 rejected which means the students PLO in experiment class were higher than control class. Based on the results of this study, researchers recommend the use of GI learning models with brainstorming techniques to improve PLO, especially in the cognitive domain.

  3. Architecture for Collaborative Learning Activities in Hybrid Learning Environments


    Ibáñez, María Blanca; Maroto, David; García Rueda, José Jesús; Leony, Derick; Delgado Kloos, Carlos


    3D virtual worlds are recognized as collaborative learning environments. However, the underlying technology is not sufficiently mature and the virtual worlds look cartoonish, unlinked to reality. Thus, it is important to enrich them with elements from the real world to enhance student engagement in learning activities. Our approach is to build learning environments where participants can either be in the real world or in its mirror world while sharing the same hybrid space in a collaborative ...

  4. Doing physical activity – not learning

    DEFF Research Database (Denmark)

    Jensen, Jens-Ole


    Introduction In recent years there have been a raising critique concerning PE as a subject which is more concerned with keeping pupils physically active than insuring that they learn something (Annerstedt, 2008). In Denmark, this issue has been actualized in a new sense. In 2014, a new school...... reform with 45 minutes of daily physical activity was introduced to enhance the pupils’ health, well-being and learning capabilities. Instead of focusing on learning bodily skills, physical activities has become an instrument to improve learning in the academic subjects. Physical activities.......g. Biesta, 2010; Standal, 2015) I will argue that the focus on learning outcome and effects on physical activity has gone too far in order to reach the objectives. If the notion of ‘keeping pupils physically active’ is understood as a representation of the core quality of physical activity, it seems...

  5. Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques (United States)

    Segura, Alejandra; Vidal, Christian; Menendez, Victor; Zapata, Alfredo; Prieto, Manuel

    Learning object repositories provide a platform for the sharing of Web-based educational resources. As these repositories evolve independently, it is difficult for users to have a clear picture of the kind of contents they give access to. Metadata can be used to automatically extract a characterization of these resources by using machine learning techniques. This paper presents an exploratory study carried out in the contents of four public repositories that uses clustering and association rule mining algorithms to extract characterizations of repository contents. The results of the analysis include potential relationships between different attributes of learning objects that may be useful to gain an understanding of the kind of resources available and eventually develop search mechanisms that consider repository descriptions as a criteria in federated search.

  6. Data mining practical machine learning tools and techniques

    CERN Document Server

    Witten, Ian H


    As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same

  7. Using Machine Learning Techniques in the Analysis of Oceanographic Data (United States)

    Falcinelli, K. E.; Abuomar, S.


    Acoustic Doppler Current Profilers (ADCPs) are oceanographic tools capable of collecting large amounts of current profile data. Using unsupervised machine learning techniques such as principal component analysis, fuzzy c-means clustering, and self-organizing maps, patterns and trends in an ADCP dataset are found. Cluster validity algorithms such as visual assessment of cluster tendency and clustering index are used to determine the optimal number of clusters in the ADCP dataset. These techniques prove to be useful in analysis of ADCP data and demonstrate potential for future use in other oceanographic applications.

  8. Action Research to Improve the Learning Space for Diagnostic Techniques

    Directory of Open Access Journals (Sweden)

    Ellen Ariel


    Full Text Available The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of “knowledge” and “understanding.” The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001, it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed.

  9. Action Research to Improve the Learning Space for Diagnostic Techniques. (United States)

    Ariel, Ellen; Owens, Leigh


    The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of "knowledge" and "understanding." The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001), it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed. Journal of Microbiology & Biology Education.

  10. Student Activity and Learning Outcomes in a Virtual Learning Environment (United States)

    Romanov, Kalle; Nevgi, Anne


    The aim of the study was to explore the relationship between degree of participation and learning outcomes in an e-learning course on medical informatics. Overall activity in using course materials and degree of participation in the discussion forums of an online course were studied among 39 medical students. Students were able to utilise the…

  11. Captivate: Building Blocks for Implementing Active Learning (United States)

    Kitchens, Brent; Means, Tawnya; Tan, Yinliang


    In this study, the authors propose a set of key elements that impact the success of an active learning implementation: content delivery, active learning methods, physical environment, technology enhancement, incentive alignment, and educator investment. Through a range of metrics the authors present preliminary evidence that students in courses…

  12. Faculty Perceptions about Barriers to Active Learning (United States)

    Michael, Joel


    Faculty may perceive many barriers to active learning in their classrooms. Four groups of participants in a faculty development workshop were asked to list their perceived barriers to active learning. Many of the problems identified were present on more than one list. The barriers fall into three categories: student characteristics, issues…

  13. Active teaching methods, studying responses and learning

    DEFF Research Database (Denmark)

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


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

  14. Active Ageing, Active Learning: Policy and Provision in Hong Kong (United States)

    Tam, M.


    This paper discusses the relationship between ageing and learning, previous literature having confirmed that participation in continued learning in old age contributes to good health, satisfaction with life, independence and self-esteem. Realizing that learning is vital to active ageing, the Hong Kong government has implemented policies and…

  15. Enhancing learning in geosciences and water engineering via lab activities (United States)

    Valyrakis, Manousos; Cheng, Ming


    This study focuses on the utilisation of lab based activities to enhance the learning experience of engineering students studying Water Engineering and Geosciences. In particular, the use of modern highly visual and tangible presentation techniques within an appropriate laboratory based space are used to introduce undergraduate students to advanced engineering concepts. A specific lab activity, namely "Flood-City", is presented as a case study to enhance the active engagement rate, improve the learning experience of the students and better achieve the intended learning objectives of the course within a broad context of the engineering and geosciences curriculum. Such activities, have been used over the last few years from the Water Engineering group @ Glasgow, with success for outreach purposes (e.g. Glasgow Science Festival and demos at the Glasgow Science Centre and Kelvingrove museum). The activity involves a specific setup of the demonstration flume in a sand-box configuration, with elements and activities designed so as to gamely the overall learning activity. Social media platforms can also be used effectively to the same goals, particularly in cases were the students already engage in these online media. To assess the effectiveness of this activity a purpose designed questionnaire is offered to the students. Specifically, the questionnaire covers several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning (also assessed by follow-up quizzes), and methods of communication and assessment. The results, analysed to assess the effectiveness of the learning activity as the students perceive it, offer a promising potential for the use of such activities in outreach and learning.

  16. Scene recognition based on integrating active learning with dictionary learning (United States)

    Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen


    Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

  17. Memorization techniques: Using mnemonics to learn fifth grade science terms (United States)

    Garcia, Juan O.

    The purpose of this study was to determine whether mnemonic instruction could assist students in learning fifth-grade science terminology more effectively than traditional-study methods of recall currently in practice The task was to examine if fifth-grade students were able to learn a mnemonic and then use it to understand science vocabulary; subsequently, to determine if students were able to remember the science terms after a period of time. The problem is that in general, elementary school students are not being successful in science achievement at the fifth grade level. In view of this problem, if science performance is increased at the elementary level, then it is likely that students will be successful when tested at the 8th and 10th grade in science with the Texas Assessment of Knowledge and Skills (TAKS) in the future. Two research questions were posited: (1) Is there a difference in recall achievement when a mnemonic such as method of loci, pegword method, or keyword method is used in learning fifth-grade science vocabulary as compared to the traditional-study method? (2) If using a mnemonic in learning fifth-grade science vocabulary was effective on recall achievement, would this achievement be maintained over a span of time? The need for this study was to assist students in learning science terms and concepts for state accountability purposes. The first assumption was that memorization techniques are not commonly applied in fifth-grade science classes in elementary schools. A second assumption was that mnemonic devices could be used successfully in learning science terms and increase long term retention. The first limitation was that the study was conducted on one campus in one school district in South Texas which limited the generalization of the study. The second limitation was that it included random assigned intact groups as opposed to random student assignment to fifth-grade classroom groups.

  18. Applying perceptual and adaptive learning techniques for teaching introductory histopathology

    Directory of Open Access Journals (Sweden)

    Sally Krasne


    Full Text Available Background: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem. Methods: We adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses that appear during a learning session based on each learner′s accuracy and response time (RT. We developed a perceptual and adaptive learning module (PALM that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a "Score" that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness. Results: Accuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1 st -year students, but not significantly so for 2 nd -year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1 st and 2 nd year students suggesting good retention of pattern recognition. Student evaluations were very favorable. Conclusion: A web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students.

  19. A Studi on High Plant Systems Course with Active Learning in Higher Education Through Outdoor Learning to Increase Student Learning Activities


    Nur Rokhimah Hanik, Anwari Adi Nugroho


    Biology learning especially high plant system courses needs to be applied to active learning centered on the student (Active Learning In Higher Education) to enhance the students' learning activities so that the quality of learning for the better. Outdoor Learning is one of the active learning invites students to learn outside of the classroom by exploring the surrounding environment. This research aims to improve the students' learning activities in the course of high plant systems through t...

  20. Learning-curve estimation techniques for nuclear industry

    Energy Technology Data Exchange (ETDEWEB)

    Vaurio, J.K.


    Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on acturial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year.

  1. Learning curve estimation techniques for the nuclear industry

    International Nuclear Information System (INIS)

    Vaurio, J.K.


    Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on actuarial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

  2. Learning-curve estimation techniques for nuclear industry

    International Nuclear Information System (INIS)

    Vaurio, J.K.


    Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on acturial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

  3. Students’ mathematical learning in modelling activities

    DEFF Research Database (Denmark)

    Kjeldsen, Tinne Hoff; Blomhøj, Morten


    Ten years of experience with analyses of students’ learning in a modelling course for first year university students, led us to see modelling as a didactical activity with the dual goal of developing students’ modelling competency and enhancing their conceptual learning of mathematical concepts i...... create and help overcome hidden cognitive conflicts in students’ understanding; that reflections within modelling can play an important role for the students’ learning of mathematics. These findings are illustrated with a modelling project concerning the world population....

  4. Comparison of Machine Learning Techniques in Inferring Phytoplankton Size Classes

    Directory of Open Access Journals (Sweden)

    Shuibo Hu


    Full Text Available The size of phytoplankton not only influences its physiology, metabolic rates and marine food web, but also serves as an indicator of phytoplankton functional roles in ecological and biogeochemical processes. Therefore, some algorithms have been developed to infer the synoptic distribution of phytoplankton cell size, denoted as phytoplankton size classes (PSCs, in surface ocean waters, by the means of remotely sensed variables. This study, using the NASA bio-Optical Marine Algorithm Data set (NOMAD high performance liquid chromatography (HPLC database, and satellite match-ups, aimed to compare the effectiveness of modeling techniques, including partial least square (PLS, artificial neural networks (ANN, support vector machine (SVM and random forests (RF, and feature selection techniques, including genetic algorithm (GA, successive projection algorithm (SPA and recursive feature elimination based on support vector machine (SVM-RFE, for inferring PSCs from remote sensing data. Results showed that: (1 SVM-RFE worked better in selecting sensitive features; (2 RF performed better than PLS, ANN and SVM in calibrating PSCs retrieval models; (3 machine learning techniques produced better performance than the chlorophyll-a based three-component method; (4 sea surface temperature, wind stress, and spectral curvature derived from the remote sensing reflectance at 490, 510, and 555 nm were among the most sensitive features to PSCs; and (5 the combination of SVM-RFE feature selection techniques and random forests regression was recommended for inferring PSCs. This study demonstrated the effectiveness of machine learning techniques in selecting sensitive features and calibrating models for PSCs estimations with remote sensing.

  5. The Activity Theory Approach to Learning

    Directory of Open Access Journals (Sweden)

    Ritva Engeström


    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.

  6. Comparative Performance Analysis of Machine Learning Techniques for Software Bug Detection


    Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed


    Machine learning techniques can be used to analyse data from different perspectives and enable developers to retrieve useful information. Machine learning techniques are proven to be useful in terms of software bug prediction. In this paper, a comparative performance analysis of different machine learning techniques is explored f or software bug prediction on public available data sets. Results showed most of the mac ...

  7. Child Development: An Active Learning Approach (United States)

    Levine, Laura E.; Munsch, Joyce


    Within each chapter of this innovative topical text, the authors engage students by demonstrating the wide range of real-world applications of psychological research connected to child development. In particular, the distinctive Active Learning features incorporated throughout the book foster a dynamic and personal learning process for students.…

  8. Discussing Active Learning from the Practitioner's Perspective (United States)

    Bamba, Priscilla


    The purpose of this paper is to present an overview of how active learning took place in a class containing specific readings,cooperative and collaborative group work, and a writing assignment for college students at a Northern Virginia Community College campus (NVCC). Requisite knowledge, skills, learner characteristics, brain-based learning, and…

  9. Learning models of activities involving interacting objects

    DEFF Research Database (Denmark)

    Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.


    We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...

  10. Deep Learning Techniques for Top-Quark Reconstruction

    CERN Document Server

    Naderi, Kiarash


    Top quarks are unique probes of the standard model (SM) predictions and have the potential to be a window for physics beyond the SM (BSM). Top quarks decay to a $Wb$ pair, and the $W$ can decay in leptons or jets. In a top pair event, assigning jets to their correct source is a challenge. In this study, I studied different methods for improving top reconstruction. The main motivation was to use Deep Learning Techniques in order to enhance the precision of top reconstruction.

  11. Learning outcomes between Socioscientific Issues-Based Learning and Conventional Learning Activities


    Piyaluk Wongsri; Prasart Nuangchalerm


    Problem statement: Socioscientific issues-based learning activity is essential for scientific reasoning skills and it could be used for analyzing problems be applied to each situation for more successful and suitable. The purposes of this research aimed to compare learning achievement, analytical thinking and moral reasoning of seventh grade students who were organized between socioscientific issues-based learning and conventional learning activities. Approach: The samples used in research we...

  12. [Learning experience of acupuncture technique from professor ZHANG Jin]. (United States)

    Xue, Hongsheng; Zhang, Jin


    As a famous acupuncturist in the world, professor ZHANG Jin believes the key of acupuncture technique is the use of force, and the understanding of the "concentrating the force into needle body" is essential to understand the essence of acupuncture technique. With deep study of Huangdi Neijing ( The Inner Canon of Huangdi ) and Zhenjiu Dacheng ( Compendium of Acupuncture and Moxibustion ), the author further learned professor ZHANG Jin 's theory and operation specification of "concentrating force into needle body, so the force arriving before and together with needle". The whole-body force should be subtly focused on the tip of needle, and gentle force at tip of needle could get significant reinforcing and reducing effect. In addition, proper timing at tip of needle could start reinforcing and reducing effect, lead qi to disease location, and achieve superior clinical efficacy.

  13. Machine-learning techniques applied to antibacterial drug discovery. (United States)

    Durrant, Jacob D; Amaro, Rommie E


    The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. © 2015 John Wiley & Sons A/S.

  14. Learning outcomes and effective communication techniques for hazard recognition learning programmes in the transportation thrust area.

    CSIR Research Space (South Africa)

    Krige, PD


    Full Text Available on South African mines ............................................ 32 4.3 People development and training techniques associated with confidence, attitudes and leadership............................................ 34 Page 4 4.4 Recommended learning... to rules and procedures, safety commitment of management, supervision style, organising for safety, equipment design and maintenance. Only the last two are engineering issues. The trend is clear. Improvements in engineering design have significantly...

  15. E-Learning System Using Segmentation-Based MR Technique for Learning Circuit Construction (United States)

    Takemura, Atsushi


    This paper proposes a novel e-Learning system using the mixed reality (MR) technique for technical experiments involving the construction of electronic circuits. The proposed system comprises experimenters' mobile computers and a remote analysis system. When constructing circuits, each learner uses a mobile computer to transmit image data from the…

  16. A New Profile Learning Model for Recommendation System based on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Shereen H. Ali


    Full Text Available Recommender systems (RSs have been used to successfully address the information overload problem by providing personalized and targeted recommendations to the end users. RSs are software tools and techniques providing suggestions for items to be of use to a user, hence, they typically apply techniques and methodologies from Data Mining. The main contribution of this paper is to introduce a new user profile learning model to promote the recommendation accuracy of vertical recommendation systems. The proposed profile learning model employs the vertical classifier that has been used in multi classification module of the Intelligent Adaptive Vertical Recommendation (IAVR system to discover the user’s area of interest, and then build the user’s profile accordingly. Experimental results have proven the effectiveness of the proposed profile learning model, which accordingly will promote the recommendation accuracy.

  17. Point-of-Purchase Advertising. Learning Activity. (United States)

    Shackelford, Ray


    In this technology education activity, students learn the importance of advertising, conduct a day-long survey of advertising strategies, and design and produce a tabletop point-of-purchase advertisement. (JOW)

  18. Activating teaching methods, studying responses and learning


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


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

  19. Learning Activities in a Sociable Smart City

    Directory of Open Access Journals (Sweden)

    Dimitrios Ringas


    Full Text Available We present our approach on how smart city technologies may enhance the learning process. We have developed the CLIO urban computing system, which invites people to share personal memories and interact the collective city memory. Various educational scenarios and activities were performed exploiting CLIO; in this paper we present the methodology we followed and the experience we gained. Learning has always been the cognitive process of acquiring skills or knowledge, while teachers are often eager to experiment with novel technological means and methods; our aim was to explore the effect that urban computing could have to the learning process. We applied our methodology in the city of Corfu inviting schools to engage their students in learning through the collective city memory while exploiting urban computing. Results from our experience demonstrate the potential of exploiting urban computing in the learning process and the benefits of learning out of the classroom.

  20. Dopamine, reward learning, and active inference

    Directory of Open Access Journals (Sweden)

    Thomas eFitzgerald


    Full Text Available Temporal difference learning models propose phasic dopamine signalling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behaviour. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.

  1. Dopamine, reward learning, and active inference. (United States)

    FitzGerald, Thomas H B; Dolan, Raymond J; Friston, Karl


    Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.

  2. People with Learning Disabilities and "Active Ageing" (United States)

    Foster, Liam; Boxall, Kathy


    Background: People (with and without learning disabilities) are living longer. Demographic ageing creates challenges and the leading policy response to these challenges is "active ageing". "Active" does not just refer to the ability to be physically and economically active, but also includes ongoing social and civic engagement…

  3. Teaching Engineering with Autonomous Learning Activities (United States)

    Otero, Beatriz; Rodríguez, Eva; Royo, Pablo


    This paper proposes several activities that encourage self-learning in engineering courses. For each activity, the context and the pedagogical issues addressed are described emphasizing strengths and weaknesses. Specifically, this work describes and implements five activities, which are: questionnaires, conceptual maps, videos, jigsaw and…

  4. Improving face image extraction by using deep learning technique (United States)

    Xue, Zhiyun; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.


    The National Library of Medicine (NLM) has made a collection of over a 1.2 million research articles containing 3.2 million figure images searchable using the Open-iSM multimodal (text+image) search engine. Many images are visible light photographs, some of which are images containing faces ("face images"). Some of these face images are acquired in unconstrained settings, while others are studio photos. To extract the face regions in the images, we first applied one of the most widely-used face detectors, a pre-trained Viola-Jones detector implemented in Matlab and OpenCV. The Viola-Jones detector was trained for unconstrained face image detection, but the results for the NLM database included many false positives, which resulted in a very low precision. To improve this performance, we applied a deep learning technique, which reduced the number of false positives and as a result, the detection precision was improved significantly. (For example, the classification accuracy for identifying whether the face regions output by this Viola- Jones detector are true positives or not in a test set is about 96%.) By combining these two techniques (Viola-Jones and deep learning) we were able to increase the system precision considerably, while avoiding the need to manually construct a large training set by manual delineation of the face regions.

  5. Introduction of active learning method in learning physiology by MBBS students. (United States)

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


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

  6. Active Learning and Cooperative Learning in the Organic Chemistry Lecture Class (United States)

    Paulson, Donald R.


    Faculty in the physical sciences are one of the academic groups least receptive to the use of active learning strategies and cooperative learning in their classrooms. This is particularly so in traditional lecture classes. It is the objective of this paper to show how effective these techniques can be in improving student performance in classes. The use of active learning strategies and cooperative learning groups in my organic chemistry lecture classes has increased the overall pass rate in my classes by an astounding 20-30% over the traditional lecture mode. This has been accomplished without any reduction in "standards". The actual methods employed are presented as well as a discussion of how I came to radically change the way I teach my classes.

  7. Manifold Regularized Experimental Design for Active Learning. (United States)

    Zhang, Lining; Shum, Hubert P H; Shao, Ling


    Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.


    African Journals Online (AJOL)


    Pulmonary Function Responses to Active Cycle. Breathing ... Key Words: Heart Failure, Active Cycle of Breathing ... cough, fatigue, reduced respiratory muscle mass, and. [5] ... an amount of exercise which is said to lower disease. [9].

  9. Quantum Speedup for Active Learning Agents

    Directory of Open Access Journals (Sweden)

    Giuseppe Davide Paparo


    Full Text Available Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.

  10. Locomotion training of legged robots using hybrid machine learning techniques (United States)

    Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.


    In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible

  11. Learning, Learning Analytics, Activity Visualisation and Open learner Model

    DEFF Research Database (Denmark)

    Bull, Susan; Kickmeier-Rust, Michael; Vatrapu, Ravi


    This paper draws on visualisation approaches in learning analytics, considering how classroom visualisations can come together in practice. We suggest an open learner model in situations where many tools and activity visualisations produce more visual information than can be readily interpreted....

  12. A Learning Activity Design Framework for Supporting Mobile Learning

    Directory of Open Access Journals (Sweden)

    Jalal Nouri


    Full Text Available This article introduces the Learning Activity Design (LEAD framework for the development and implementation of mobile learning activities in primary schools. The LEAD framework draws on methodological perspectives suggested by design-based research and interaction design in the specific field of technology-enhanced learning (TEL. The LEAD framework is grounded in four design projects conducted over a period of six years. It contributes a new understanding of the intricacies and multifaceted aspects of the design-process characterizing the development and implementation of mobile devices (i.e. smart phones and tablets in curricular activities conducted in Swedish primary schools. This framework is intended to provide both designers and researchers with methodological tools that take account of the pedagogical foundations of technologically-based educational interventions, usability issues related to the interaction with the mobile application developed, multiple data streams generated during the design project, multiple stakeholders involved in the design process and sustainability aspects of the mobile learning activities implemented in the school classroom.

  13. Variation in behavioral engagement during an active learning activity leads to differential knowledge gains in college students. (United States)

    LaDage, Lara D; Tornello, Samantha L; Vallejera, Jennilyn M; Baker, Emily E; Yan, Yue; Chowdhury, Anik


    There are many pedagogical techniques used by educators in higher education; however, some techniques and activities have been shown to be more beneficial to student learning than others. Research has demonstrated that active learning and learning in which students cognitively engage with the material in a multitude of ways result in better understanding and retention. The aim of the present study was to determine which of three pedagogical techniques led to improvement in learning and retention in undergraduate college students. Subjects partook in one of three different types of pedagogical engagement: hands-on learning with a model, observing someone else manipulate the model, and traditional lecture-based presentation. Students were then asked to take an online quiz that tested their knowledge of the new material, both immediately after learning the material and 2 wk later. Students who engaged in direct manipulation of the model scored higher on the assessment immediately after learning the material compared with the other two groups. However, there were no differences among the three groups when assessed after a 2-wk retention interval. Thus active learning techniques that involve direct interaction with the material can lead to learning benefits; however, how these techniques benefit long-term retention of the information is equivocal.

  14. Oral Hygiene. Instructor's Packet. Learning Activity Package. (United States)

    Hime, Kirsten

    This instructor's packet accompanies the learning activity package (LAP) on oral hygiene. Contents included in the packet are a time sheet, suggested uses for the LAP, an instruction sheet, final LAP reviews, a final LAP review answer key, suggested activities, additional resources (student handouts), student performance checklists for both…

  15. Building Maintenance. Math Learning Activity Packet. (United States)

    Grant, Shelia I.

    This collection of learning activities is intended for use in reinforcing mathematics instruction as it relates to building maintenance. Fifty activity sheets are provided. These are organized into units on the following topics: numeration, adding whole numbers, subtracting whole numbers, multiplying whole numbers, dividing whole numbers,…

  16. Grooming. Instructor's Packet. Learning Activity Package. (United States)

    Stark, Pamela

    This instructor's packet accompanies the learning activity package (LAP) on grooming. Contents included in the packet are a time sheet, suggested uses for the LAP, an instruction sheet, final LAP reviews, a final LAP review answer key, suggested activities, an additional resources list, and student completion cards to issue to students as an…

  17. Activating Teaching for Quality Learning

    DEFF Research Database (Denmark)

    Zhurbenko, Vitaliy


    Activating teaching is an educational concept which is based on active participation of students in the study process. It is becoming an alternative to more typical approach where the teacher will just lecture and the students will take notes. The study described in this paper considers student...... activating teaching methods focusing on those based on knowledge dissemination. The practical aspects of the implemented teaching method are considered, and employed assessment methods and tools are discussed....

  18. Active learning in practice: Implementation of the principles of active learning in an engineering course

    DEFF Research Database (Denmark)

    Rützou, C.


    The most common form of teaching is still the form where a teacher presents the subject of the lecture to a listening audience. During teaching history this has proved to be an effective way of teaching, however the probability of students being inactive is high and the learning outcome may...... through the same curriculum as usual during a term? • Will Active Learning reduce failure rate? • Will Active Learning give a higher learning outcome than traditional teaching? This paper deals with the results of this experiment, answers the mentioned questions and presents a way to implement Active...


    Directory of Open Access Journals (Sweden)

    M.ª José Mayorga Fernández


    Full Text Available This  article  presents  an  innovative  experience  carried  out  in  the  subject Pedagogical Bases of Special Education, a 4.5 credit core subject taught at the second year of the Degree in Physical Education Teacher Training (to be extinguish, based on the use of a methodological strategic in accordance with the new demands of the EEES. With the experience we pursue a double purpose: firstly, to present the technique of jigsaw or puzzle as a useful methodological strategy for university learning and, on the other hand, to show whether this strategy improves students results. Comparing the results with students previous year results shows that the performance of students who participated in the innovative experience has improved considerably, increasing their motivation and involvement towards the task.

  20. Classifying Structures in the ISM with Machine Learning Techniques (United States)

    Beaumont, Christopher; Goodman, A. A.; Williams, J. P.


    The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

  1. Developing an instrument to measure emotional behaviour abilities of meaningful learning through the Delphi technique. (United States)

    Cadorin, Lucia; Bagnasco, Annamaria; Tolotti, Angela; Pagnucci, Nicola; Sasso, Loredana


    To identify items for a new instrument that measures emotional behaviour abilities of meaningful learning, according to Fink's Taxonomy. Meaningful learning is an active process that promotes a wider and deeper understanding of concepts. It is the result of an interaction between new and previous knowledge and produces a long-term change of knowledge and skills. To measure meaningful learning capability, it is very important in the education of health professionals to identify problems or special learning needs. For this reason, it is necessary to create valid instruments. A Delphi Study technique was implemented in four phases by means of e-mail. The study was conducted from April-September 2015. An expert panel consisting of ten researchers with experience in Fink's Taxonomy was established to identify the items of the instrument. Data were analysed for conceptual description and item characteristics and attributes were rated. Expert consensus was sought in each of these phases. An 87·5% consensus cut-off was established. After four rounds, consensus was obtained for validation of the content of the instrument 'Assessment of Meaningful learning Behavioural and Emotional Abilities'. This instrument consists of 56 items evaluated on a 6-point Likert-type scale. Foundational Knowledge, Application, Integration, Human Dimension, Caring and Learning How to Learn were the six major categories explored. This content validated tool can help educators (teachers, trainers and tutors) to identify and improve the strategies to support students' learning capability, which could increase their awareness of and/or responsibility in the learning process. © 2017 John Wiley & Sons Ltd.

  2. Using machine learning techniques to differentiate acute coronary syndrome

    Directory of Open Access Journals (Sweden)

    Sougand Setareh


    Full Text Available Backgroud: Acute coronary syndrome (ACS is an unstable and dynamic process that includes unstable angina, ST elevation myocardial infarction, and non-ST elevation myocardial infarction. Despite recent technological advances in early diognosis of ACS, differentiating between different types of coronary diseases in the early hours of admission is controversial. The present study was aimed to accurately differentiate between various coronary events, using machine learning techniques. Such methods, as a subset of artificial intelligence, include algorithms that allow computers to learn and play a major role in treatment decisions. Methods: 1902 patients diagnosed with ACS and admitted to hospital were selected according to Euro Heart Survey on ACS. Patients were classified based on decision tree J48. Bagging aggregation algorithms was implemented to increase the efficiency of algorithm. Results: The performance of classifiers was estimated and compared based on their accuracy computed from confusion matrix. The accuracy rates of decision tree and bagging algorithm were calculated to be 91.74% and 92.53%, respectively. Conclusion: The proposed methods used in this study proved to have the ability to identify various ACS. In addition, using matrix of confusion, an acceptable number of subjects with acute coronary syndrome were identified in each class.

  3. Reinforcement learning techniques for controlling resources in power networks (United States)

    Kowli, Anupama Sunil

    As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

  4. Classification of Phishing Email Using Random Forest Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Andronicus A. Akinyelu


    Full Text Available Phishing is one of the major challenges faced by the world of e-commerce today. Thanks to phishing attacks, billions of dollars have been lost by many companies and individuals. In 2012, an online report put the loss due to phishing attack at about $1.5 billion. This global impact of phishing attacks will continue to be on the increase and thus requires more efficient phishing detection techniques to curb the menace. This paper investigates and reports the use of random forest machine learning algorithm in classification of phishing attacks, with the major objective of developing an improved phishing email classifier with better prediction accuracy and fewer numbers of features. From a dataset consisting of 2000 phishing and ham emails, a set of prominent phishing email features (identified from the literature were extracted and used by the machine learning algorithm with a resulting classification accuracy of 99.7% and low false negative (FN and false positive (FP rates.

  5. Estimation of Alpine Skier Posture Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Bojan Nemec


    Full Text Available High precision Global Navigation Satellite System (GNSS measurements are becoming more and more popular in alpine skiing due to the relatively undemanding setup and excellent performance. However, GNSS provides only single-point measurements that are defined with the antenna placed typically behind the skier’s neck. A key issue is how to estimate other more relevant parameters of the skier’s body, like the center of mass (COM and ski trajectories. Previously, these parameters were estimated by modeling the skier’s body with an inverted-pendulum model that oversimplified the skier’s body. In this study, we propose two machine learning methods that overcome this shortcoming and estimate COM and skis trajectories based on a more faithful approximation of the skier’s body with nine degrees-of-freedom. The first method utilizes a well-established approach of artificial neural networks, while the second method is based on a state-of-the-art statistical generalization method. Both methods were evaluated using the reference measurements obtained on a typical giant slalom course and compared with the inverted-pendulum method. Our results outperform the results of commonly used inverted-pendulum methods and demonstrate the applicability of machine learning techniques in biomechanical measurements of alpine skiing.

  6. Driver drowsiness detection using behavioral measures and machine learning techniques: A review of state-of-art techniques

    CSIR Research Space (South Africa)

    Ngxande, Mkhuseli


    Full Text Available This paper presents a literature review of driver drowsiness detection based on behavioral measures using machine learning techniques. Faces contain information that can be used to interpret levels of drowsiness. There are many facial features...

  7. Personal recommender systems for learners in lifelong learning: requirements, techniques and model

    NARCIS (Netherlands)

    Drachsler, Hendrik; Hummel, Hans; Koper, Rob


    Drachsler, H., Hummel, H. G. K., & Koper, R. (2008). Personal recommender systems for learners in lifelong learning: requirements, techniques and model. International Journal of Learning Technology, 3(4), 404-423.

  8. Exploring Representativeness and Informativeness for Active Learning. (United States)

    Du, Bo; Wang, Zengmao; Zhang, Lefei; Zhang, Liangpei; Liu, Wei; Shen, Jialie; Tao, Dacheng


    How can we find a general way to choose the most suitable samples for training a classifier? Even with very limited prior information? Active learning, which can be regarded as an iterative optimization procedure, plays a key role to construct a refined training set to improve the classification performance in a variety of applications, such as text analysis, image recognition, social network modeling, etc. Although combining representativeness and informativeness of samples has been proven promising for active sampling, state-of-the-art methods perform well under certain data structures. Then can we find a way to fuse the two active sampling criteria without any assumption on data? This paper proposes a general active learning framework that effectively fuses the two criteria. Inspired by a two-sample discrepancy problem, triple measures are elaborately designed to guarantee that the query samples not only possess the representativeness of the unlabeled data but also reveal the diversity of the labeled data. Any appropriate similarity measure can be employed to construct the triple measures. Meanwhile, an uncertain measure is leveraged to generate the informativeness criterion, which can be carried out in different ways. Rooted in this framework, a practical active learning algorithm is proposed, which exploits a radial basis function together with the estimated probabilities to construct the triple measures and a modified best-versus-second-best strategy to construct the uncertain measure, respectively. Experimental results on benchmark datasets demonstrate that our algorithm consistently achieves superior performance over the state-of-the-art active learning algorithms.

  9. From Tootsie Rolls to Composites: Assessing a Spectrum of Active Learning Activities in Engineering Mechanics (United States)


    The introduction of active learning exercises into a traditional lecture has been shown to improve students’ learning. Hands-on learning...opportunities in labs and projects provide are additional tools in the active learning toolbox. This paper presents a series of innovative hands-on active ... learning activities for mechanics of materials topics. These activities are based on a Methodology for Developing Hands-on Active Learning Activities, a

  10. Suitable activated carbon-13 tracer techniques

    International Nuclear Information System (INIS)

    Zhang Weicheng; Peng Xiuru; Wang Yuhua


    Feasibility and applicability studies of the proton induced gamma ray emission (PIGE) have been performed. The graphite was firstly bombarded at various proton energies to determine gamma ray yield (and, thus, sensitivities) for the reaction of interest. The accuracy for the determination of 13 C abundance was checked, and the precision with which this value and ratios 13 C/ 12 C may be obtained was established by repetitive analysis samples. The performance of different standards in this determination was assessed. The mathematical treatment was developed for the determination of 13 C abundance in tracer studies, and to derive the equations that govern this method of analysis from first principles, to arrive finally at a simple expression by virtue of the observed regularities. The system was calibrated by measuring the gamma ray yield form the 12 C (p, γ) 13 N and 13 C(p,γ) 14 N reaction as a function of known 13 C enrichment. Using this experimentally determined calibration curve, unknown materials can be assayed. This technique is applicable to the analysis of samples with 13 C enrichments between 0.1% and 90%. The samples of human breath natural samples were analyzed against graphite and Cylinder CO 2 standards. Relative standard deviations were 13 C abundance, an increase in 13 C per cent isotopic abundance from the natural 1.11% (average) to only 1.39% may be ascertained. Finally, PIGE is compared with more classical techniques for analysis of 13 C tracer experiments. Ease and speed are important advantages of this technique over mass spectrometry, and its error is compatible with the natural variation of biological results. (9 refs., 11 figs., 9 tabs.)

  11. Mind and activity. Psychic mechanism of learning

    Directory of Open Access Journals (Sweden)

    Zoya A. Reshetova


    Full Text Available The paper is devoted to the issue of mechanisms of learning for understanding the nature of the human mind. Learning is regarded as a special activity that is important for developing the human mind in a specific cultural and historical setting and indirect activity. The author’s understanding of the ideas developed by the psychological theory of activity for establishing the principles of developing the human mind is highlighted. Interpretation of dialectical connections of brain processes and mind, and also the objective activity that emerges them is provided. According to the activity theory, the causes of the students’ psychological difficulties and the low efficacy of learning within predominant reproductive method or the use of the trial and error method are revealed. Thus, a new understanding of the renowned didactic principles of scientific rigour, accessibility, objectivity, the connection of learning with life and others is offered. The contribution of the psychological theory in organizing and managing the studies, increasing teaching activity and awareness, and the growth of the internal causes of motivation are shown. Particular attention is paid to the issue of intellectual development and creative abilities. The author believes the creative abilities of the student and the way the latter are taught are interconnected. At the same time, the developers and educators should make efforts to develop in the students a systemic orientation in the subject, primarily mastering the method of system analysis. Once the method of system analysis has been mastered, it becomes a general intellectual and developing tool through which activities are organized to solve any teaching problems with whatever type of content and difficulty level. Summing up, the organization and disclosure to the student of the process of learning as an activity with its social, consciously transformative and sense shaping meaning, the conditions of its development

  12. Signs of learning in kinaesthetic science activities

    DEFF Research Database (Denmark)

    Bruun, Jesper; Johannsen, Bjørn Friis

    that students use bodily explorations to construct meaning and understanding from kinaesthetic learning that is relevant to school physics? To answer the question, we employ a semiotics perspective to analyse data from a 1-hour lesson for 8-9th graders which introduced students to kinaesthetic activities, where......?”). The analysis is conducted by searching the data to find episodes that illustrate student activity which can serve as a sign of the object that the ‘experiential gestalt of causation’ is employed in the construction of the intended learning outcome. In essence, we study a chaotic but authentic teaching...

  13. Astronomy Learning Activities for Tablets (United States)

    Pilachowski, Catherine A.; Morris, Frank


    Four web-based tools allow students to manipulate astronomical data to learn concepts in astronomy. The tools are HTML5, CSS3, Javascript-based applications that provide access to the content on iPad and Android tablets. The first tool “Three Color” allows students to combine monochrome astronomical images taken through different color filters or in different wavelength regions into a single color image. The second tool “Star Clusters” allows students to compare images of stars in clusters with a pre-defined template of colors and sizes in order to produce color-magnitude diagrams to determine cluster ages. The third tool adapts Travis Rector’s “NovaSearch” to allow students to examine images of the central regions of the Andromeda Galaxy to find novae. After students find a nova, they are able to measure the time over which the nova fades away. A fourth tool, Proper Pair, allows students to interact with Hipparcos data to evaluate close double stars are physical binaries or chance superpositions. Further information and access to these web-based tools are available at

  14. High-frequency TRNS reduces BOLD activity during visuomotor learning.

    Directory of Open Access Journals (Sweden)

    Catarina Saiote

    Full Text Available Transcranial direct current stimulation (tDCS and transcranial random noise stimulation (tRNS consist in the application of electrical current of small intensity through the scalp, able to modulate perceptual and motor learning, probably by changing brain excitability. We investigated the effects of these transcranial electrical stimulation techniques in the early and later stages of visuomotor learning, as well as associated brain activity changes using functional magnetic resonance imaging (fMRI. We applied anodal and cathodal tDCS, low-frequency and high-frequency tRNS (lf-tRNS, 0.1-100 Hz; hf-tRNS 101-640 Hz, respectively and sham stimulation over the primary motor cortex (M1 during the first 10 minutes of a visuomotor learning paradigm and measured performance changes for 20 minutes after stimulation ceased. Functional imaging scans were acquired throughout the whole experiment. Cathodal tDCS and hf-tRNS showed a tendency to improve and lf-tRNS to hinder early learning during stimulation, an effect that remained for 20 minutes after cessation of stimulation in the late learning phase. Motor learning-related activity decreased in several regions as reported previously, however, there was no significant modulation of brain activity by tDCS. In opposition to this, hf-tRNS was associated with reduced motor task-related-activity bilaterally in the frontal cortex and precuneous, probably due to interaction with ongoing neuronal oscillations. This result highlights the potential of lf-tRNS and hf-tRNS to differentially modulate visuomotor learning and advances our knowledge on neuroplasticity induction approaches combined with functional imaging methods.

  15. A novel technique for active vibration control, based on optimal

    Indian Academy of Sciences (India)

    In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously ...

  16. Application of activation techniques to biological analysis

    International Nuclear Information System (INIS)

    Bowen, H.J.M.


    Applications of activation analysis in the biological sciences are reviewed for the period of 1970 to 1979. The stages and characteristics of activation analysis are described, and its advantages and disadvantages enumerated. Most applications involve activation by thermal neutrons followed by either radiochemical or instrumental determination. Relatively little use has been made of activation by fast neutrons, photons, or charged particles. In vivo analyses are included, but those based on prompt gamma or x-ray emission are not. Major applications include studies of reference materials, and the elemental analysis of plants, marine biota, animal and human tissues, diets, and excreta. Relatively little use of it has been made in biochemistry, microbiology, and entomology, but it has become important in toxicology and environmental science. The elements most often determined are Ag, As, Au, Br, Ca, Cd, Cl, Co, Cr, Cs, Cu, Fe, Hg, I, K, Mn, Mo, Na, Rb, Sb, Sc, Se, and Zn, while few or no determinations of B, Be, Bi, Ga, Gd, Ge, H, In, Ir, Li, Nd, Os, Pd, Pr, Pt, Re, Rh, Ru, Te, Tl, or Y have been made in biological materials

  17. Respirometry techniques and activated sludge models

    NARCIS (Netherlands)

    Benes, O.; Spanjers, H.; Holba, M.


    This paper aims to explain results of respirometry experiments using Activated Sludge Model No. 1. In cases of insufficient fit of ASM No. 1, further modifications to the model were carried out and the so-called "Enzymatic model" was developed. The best-fit method was used to determine the effect of

  18. Less is more: Sampling chemical space with active learning (United States)

    Smith, Justin S.; Nebgen, Ben; Lubbers, Nicholas; Isayev, Olexandr; Roitberg, Adrian E.


    The development of accurate and transferable machine learning (ML) potentials for predicting molecular energetics is a challenging task. The process of data generation to train such ML potentials is a task neither well understood nor researched in detail. In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials. It is based on the concept of active learning (AL) via Query by Committee (QBC), which uses the disagreement between an ensemble of ML potentials to infer the reliability of the ensemble's prediction. QBC allows the presented AL algorithm to automatically sample regions of chemical space where the ML potential fails to accurately predict the potential energy. AL improves the overall fitness of ANAKIN-ME (ANI) deep learning potentials in rigorous test cases by mitigating human biases in deciding what new training data to use. AL also reduces the training set size to a fraction of the data required when using naive random sampling techniques. To provide validation of our AL approach, we develop the COmprehensive Machine-learning Potential (COMP6) benchmark (publicly available on GitHub) which contains a diverse set of organic molecules. Active learning-based ANI potentials outperform the original random sampled ANI-1 potential with only 10% of the data, while the final active learning-based model vastly outperforms ANI-1 on the COMP6 benchmark after training to only 25% of the data. Finally, we show that our proposed AL technique develops a universal ANI potential (ANI-1x) that provides accurate energy and force predictions on the entire COMP6 benchmark. This universal ML potential achieves a level of accuracy on par with the best ML potentials for single molecules or materials, while remaining applicable to the general class of organic molecules composed of the elements CHNO.

  19. Using Oceanography to Support Active Learning (United States)

    Byfield, V.


    Teachers are always on the lookout for material to give their brightest students, in order to keep them occupied, stimulated and challenged, while the teacher gets on with helping the rest. They are also looking for material that can inspire and enthuse those who think that school is 'just boring!' Oceanography, well presented, has the capacity to do both. As a relatively young science, oceanography is not a core curriculum subject (possibly an advantage), but it draws on the traditional sciences of biology, chemistry, physic and geology, and can provide wonderful examples for teaching concepts in school sciences. It can also give good reasons for learning science, maths and technology. Exciting expeditions (research cruises) to far-flung places; opportunities to explore new worlds, a different angle on topical debates such as climate change, pollution, or conservation can bring a new life to old subjects. Access to 'real' data from satellites or Argo floats can be used to develop analytical and problem solving skills. The challenge is to make all this available in a form that can easily be used by teachers and students to enhance the learning experience. We learn by doing. Active teaching methods require students to develop their own concepts of what they are learning. This stimulates new neural connections in the brain - the physical manifestation of learning. There is a large body of evidence to show that active learning is much better remembered and understood. Active learning develops thinking skills through analysis, problem solving, and evaluation. It helps learners to use their knowledge in realistic and useful ways, and see its importance and relevance. Most importantly, properly used, active learning is fun. This paper presents experiences from a number of education outreach projects that have involved the National Oceanography Centre in Southampton, UK. All contain some element of active learning - from quizzes and puzzles to analysis of real data from

  20. Machine Learning Techniques for Arterial Pressure Waveform Analysis

    Directory of Open Access Journals (Sweden)

    João Cardoso


    Full Text Available The Arterial Pressure Waveform (APW can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1 a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2 the acquired position and amplitude of onset, Systolic Peak (SP, Point of Inflection (Pi and Dicrotic Wave (DW were used for the computation of some morphological attributes; (3 pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4 classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic, J48 (decision tree and RIPPER (rule-based induction; and (5 we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx. Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95% and high area under the curve (AUC of a Receiver Operating Characteristic (ROC curve (0.961. Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation.

  1. The Effects of Apprenticeship of Observation on Teachers Attitudes towards Active Learning Instruction


    Kuzhabekova Aliya; Zhaparova Raina


    Active learning instruction is promoted by the most recent version of the National Program for the Development of Education in Kazakhstan as it is believed to provide more meaningful learning and deeper understanding compared to traditional instruction. In order to achieve greater utilization of the instructional approach at schools, teachers must be aware of active learning techniques and know how to use them. This paper studies whether ‘apprenticeship of observation’ during a graduate cours...

  2. Active Learning in Engineering Education: A (Re)Introduction (United States)

    Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth


    The informal network "Active Learning in Engineering Education" (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE are centred on the vision that learners…

  3. Sequence learning in differentially activated dendrites

    DEFF Research Database (Denmark)

    Nielsen, Bjørn Gilbert


    . It is proposed that the neural machinery required in such a learning/retrieval mechanism could involve the NMDA receptor, in conjunction with the ability of dendrites to maintain differentially activated regions. In particular, it is suggested that such a parcellation of the dendrite allows the neuron......Differentially activated areas of a dendrite permit the existence of zones with distinct rates of synaptic modification, and such areas can be individually accessed using a reference signal which localizes synaptic plasticity and memory trace retrieval to certain subregions of the dendrite...... to participate in multiple sequences, which can be learned without suffering from the 'wash-out' of synaptic efficacy associated with superimposition of training patterns. This is a biologically plausible solution to the stability-plasticity dilemma of learning in neural networks....

  4. Bidirectional Active Learning: A Two-Way Exploration Into Unlabeled and Labeled Data Set. (United States)

    Zhang, Xiao-Yu; Wang, Shupeng; Yun, Xiaochun


    In practical machine learning applications, human instruction is indispensable for model construction. To utilize the precious labeling effort effectively, active learning queries the user with selective sampling in an interactive way. Traditional active learning techniques merely focus on the unlabeled data set under a unidirectional exploration framework and suffer from model deterioration in the presence of noise. To address this problem, this paper proposes a novel bidirectional active learning algorithm that explores into both unlabeled and labeled data sets simultaneously in a two-way process. For the acquisition of new knowledge, forward learning queries the most informative instances from unlabeled data set. For the introspection of learned knowledge, backward learning detects the most suspiciously unreliable instances within the labeled data set. Under the two-way exploration framework, the generalization ability of the learning model can be greatly improved, which is demonstrated by the encouraging experimental results.

  5. Active Collaborative Learning through Remote Tutoring (United States)

    Gehret, Austin U.; Elliot, Lisa B.; MacDonald, Jonathan H. C.


    An exploratory case study approach was used to describe remote tutoring in biochemistry and general chemistry with students who are deaf or hard of hearing (D/HH). Data collected for analysis were based on the observations of the participant tutor. The research questions guiding this study included (1) How is active learning accomplished in…

  6. Active Learning Strategies in Physics Teaching (United States)

    Karamustafaoglu, Orhan


    The purpose of this study was to determine physics teachers' opinions about student-centered activities applicable in physics teaching and learning in context. A case study approach was used in this research. First, semi-structured interviews were carried out with 6 physics teachers. Then, a questionnaire was developed based on the data obtained…

  7. World War II Memorial Learning Activities. (United States)

    Tennessee State Dept. of Education, Nashville.

    These learning activities can help students get the most out of a visit to the Tennessee World War II Memorial, a group of ten pylons located in Nashville (Tennessee). Each pylon contains informational text about the events of World War II. The ten pylons are listed as: (1) "Pylon E-1--Terror: America Enters the War against Fascism, June…

  8. Active Learning Strategies for the Mathematics Classroom (United States)

    Kerrigan, John


    Active learning involves students engaging with course content beyond lecture: through writing, applets, simulations, games, and more (Prince, 2004). As mathematics is often viewed as a subject area that is taught using more traditional methods (Goldsmith & Mark, 1999), there are actually many simple ways to make undergraduate mathematics…

  9. Windowed active sampling for reliable neural learning

    NARCIS (Netherlands)

    Barakova, E.I; Spaanenburg, L

    The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive pre-processing to bridge the representation gap between process measurement and neural presentation. In contrast, windowed active sampling attempts to solve these

  10. Accounting for Sustainability: An Active Learning Assignment (United States)

    Gusc, Joanna; van Veen-Dirks, Paula


    Purpose: Sustainability is one of the newer topics in the accounting courses taught in university teaching programs. The active learning assignment as described in this paper was developed for use in an accounting course in an undergraduate program. The aim was to enhance teaching about sustainability within such a course. The purpose of this…

  11. Predicting the Failure of Dental Implants Using Supervised Learning Techniques

    Directory of Open Access Journals (Sweden)

    Chia-Hui Liu


    Full Text Available Prosthodontic treatment has been a crucial part of dental treatment for patients with full mouth rehabilitation. Dental implant surgeries that replace conventional dentures using titanium fixtures have become the top choice. However, because of the wide-ranging scope of implant surgeries, patients’ body conditions, surgeons’ experience, and the choice of implant system should be considered during treatment. The higher price charged by dental implant treatments compared to conventional dentures has led to a rush among medical staff; therefore, the future impact of surgeries has not been analyzed in detail, resulting in medial disputes. Previous literature on the success factors of dental implants is mainly focused on single factors such as patients’ systemic diseases, operation methods, or prosthesis types for statistical correlation significance analysis. This study developed a prediction model for providing an early warning mechanism to reduce the chances of dental implant failure. We collected the clinical data of patients who received artificial dental implants at the case hospital for a total of 8 categories and 20 variables. Supervised learning techniques such as decision tree (DT, support vector machines, logistic regressions, and classifier ensembles (i.e., Bagging and AdaBoost were used to analyze the prediction of the failure of dental implants. The results show that DT with both Bagging and Adaboost techniques possesses the highest prediction performance for the failure of dental implant (area under the receiver operating characteristic curve, AUC: 0.741; the analysis also revealed that the implant systems affect dental implant failure. The model can help clinical surgeons to reduce medical failures by choosing the optimal implant system and prosthodontics treatments for their patients.

  12. Active learning machine learns to create new quantum experiments. (United States)

    Melnikov, Alexey A; Poulsen Nautrup, Hendrik; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J


    How useful can machine learning be in a quantum laboratory? Here we raise the question of the potential of intelligent machines in the context of scientific research. A major motivation for the present work is the unknown reachability of various entanglement classes in quantum experiments. We investigate this question by using the projective simulation model, a physics-oriented approach to artificial intelligence. In our approach, the projective simulation system is challenged to design complex photonic quantum experiments that produce high-dimensional entangled multiphoton states, which are of high interest in modern quantum experiments. The artificial intelligence system learns to create a variety of entangled states and improves the efficiency of their realization. In the process, the system autonomously (re)discovers experimental techniques which are only now becoming standard in modern quantum optical experiments-a trait which was not explicitly demanded from the system but emerged through the process of learning. Such features highlight the possibility that machines could have a significantly more creative role in future research.

  13. Active Learning to Develop Motor Skills and Teamwork

    Directory of Open Access Journals (Sweden)

    Johanna Lorena Aristizabal-Almanza


    Full Text Available This action-research project was conducted to determine how the use of principles of active learning, specifically collaboration, had an effect on psychomotor performance and achievement in teamwork. The research setting included 20 students of first grade from a private school located in Bogota, Colombia. The students were selected through not randomized sampling based on criteria. The methodological process included observation, interviews, and a scale based on standardized tests to measure skills; the latter was applied before and after the intervention. Data analysis was performed using a triangulation of qualitative data, and through comparative analysis of the initial and final student profile for quantitative inputs. The results showed that, after the intervention with collaborative techniques based on action learning, students achieved a positive variation in their performance. Being part of a team positively affected the achievement of the objectives. Systematical reflection on their practices fostered their capacity to identify strengths and weaknesses to build knowledge in interaction with others. Knowledge construction was nurtured based in their previous experiences. Students showed more accountability and self-directed learning behaviors, according to their age. Overall the experience showed the importance of research and innovation in the classroom in order to provide meaningful data, so teachers and researchers can engage in providing learning experiences based in active learning.

  14. Effective, Active Learning Strategies for the Oceanography Classroom (United States)

    Dmochowski, J. E.; Marinov, I.


    A decline in enrollment in STEM fields at the university level has prompted extensive research on alternative ways of teaching and learning science. Inquiry-based learning as well as the related "flipped" or "active" lectures, and similar teaching methods and philosophies have been proposed as more effective ways to disseminate knowledge in science classes than the traditional lecture. We will provide a synopsis of our experiences in implementing some of these practices into our Introductory Oceanography, Global Climate Change, and Ocean Atmosphere Dynamics undergraduate courses at the University of Pennsylvania, with both smaller and larger enrollments. By implementing tools such as at-home modules; computer labs; incorporation of current research; pre- and post-lecture quizzes; reflective, qualitative writing assignments; peer review; and a variety of in-class learning strategies, we aim to increase the science literacy of the student population and help students gain a more comprehensive knowledge of the topic, enhance their critical thinking skills, and correct misconceptions. While implementing these teaching techniques with college students is not without complications, we argue that a blended class that flexibly and creatively accounts for class size and science level improves the learning experience and the acquired knowledge. We will present examples of student assignments and activities as well as describe the lessons we have learned, and propose ideas for moving forward to best utilize innovative teaching tools in order to increase science literacy in oceanography and other climate-related courses.

  15. Functional discrimination of membrane proteins using machine learning techniques

    Directory of Open Access Journals (Sweden)

    Yabuki Yukimitsu


    Full Text Available Abstract Background Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. Results We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane showed the accuracy of 82%. Conclusion The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.

  16. Using the 5E Learning Cycle with Metacognitive Technique to Enhance Students’ Mathematical Critical Thinking Skills

    Directory of Open Access Journals (Sweden)

    Runisah Runisah


    Full Text Available This study aims to describe enhancement and achievement of mathematical critical thinking skills of students who received the 5E Learning Cycle with Metacognitive technique, the 5E Learning Cycle, and conventional learning. This study use experimental method with pretest-posttest control group design. Population are junior high school students in Indramayu city, Indonesia. Sample are three classes of eighth grade students from high level school and three classes from medium level school. The study reveal that in terms of overall, mathematical critical thinking skills enhancement and achievement of students who received the 5E Learning Cycle with Metacognitive technique is better than students who received the 5E Learning Cycle and conventional learning. Mathematical critical thinking skills of students who received the 5E Learning Cycle is better than students who received conventional learning. There is no interaction effect between learning model and school level toward enhancement and achievement of students’ mathematical critical thinking skills.

  17. The double-loop feedback for active learning with understanding

    DEFF Research Database (Denmark)

    Christensen, Hans Peter


    Learning is an active process, and in engineering education authentic projects is often used to activate the students and promote learning. However, it is not all activity that leads to deep learning; and in a rapid changing society deep understanding is necessary for life-long learning. Empirical...... findings at DTU question the direct link between high activity and a deep approach to learning. Active learning is important to obtain engineering competencies, but active learning requires more than activity. Feedback and reflection is crucial to the learning process, since new knowledge is built...... on the student’s existing understanding. A model for an active learning process with a double-loop feedback is suggested - the first loop gives the student experience through experimentation, the second conceptual understanding through reflection. Students often miss the second loop, so it is important...

  18. Active learning in optics for girls (United States)

    Ali, R.; Ashraf, I.


    Active learning in Optics (ALO) is a self-funded program under the umbrella of the Abdus Salam International Centre for Theoretical Physics (ICTP) and Quaid-i-Azam University (QAU) to bring physical sciences to traditionally underserved Girls high schools and colleges in Pakistan. There is a significant gender disparity in physical Sciences in Pakistan. In Department of Physics at QAU, approximately 10 to 20% of total students were used to be females from past many decades, but now this percentage is increasing. To keep it up at same pace, we started ALO in January 2016 as a way to provide girls an enriching science experiences, in a very friendly atmosphere. We have organized many one-day activities, to support and encourage girls' students of government high schools and colleges to pursue careers in sciences. In this presentation we will describe our experience and lesson learned in these activities.

  19. Comparative exploration of learning styles and teaching techniques between Thai and Vietnamese EFL students and instructors

    Directory of Open Access Journals (Sweden)

    Supalak Nakhornsri


    Full Text Available Learning styles have been a particular focus of a number of researchers over the past decades. Findings from various studies researching into how students learn highlight significant relationships between learners’ styles of learning and their language learning processes and achievement. This research focuses on a comparative analysis of the preferences of English learning styles and teaching techniques perceived by students from Thailand and Vietnam, and the teaching styles and techniques practiced by their instructors. The purposes were 1 to investigate the learning styles and teaching techniques students from both countries preferred, 2 to investigate the compatibility of the teaching styles and techniques practiced by instructors and those preferred by the students, 3 to specify the learning styles and teaching techniques students with high level of English proficiency preferred, and 4 to investigate the similarities of Thai and Vietnamese students’ preferences for learning styles and teaching techniques. The sample consisted of two main groups: 1 undergraduate students from King Mongkut’s University of Technology North Bangkok (KMUTNB, Thailand and Thai Nguyen University (TNU, Vietnam and 2 English instructors from both institutions. The instruments employed comprised the Students’ Preferred English Learning Style and Teaching Technique Questionnaire and the Teachers’ Practiced English Teaching Style and Technique Questionnaire. The collected data were analyzed using arithmetic means and standard deviation. The findings can contribute to the curriculum development and assist teachers to teach outside their comfort level to match the students’ preferred learning styles. In addition, the findings could better promote the courses provided for students. By understanding the learning style make-up of the students enrolled in the courses, faculty can adjust their modes of content delivery to match student preferences and maximize

  20. Development of Innovation by Constructivist Theory with using Cooperative Learning Technique STAD of Mathayomsuksa 3 Students at Anuban Mahasarakham School

    Directory of Open Access Journals (Sweden)

    Apinya Phonpinyo


    Full Text Available The purposes of the this research: 1. were study the problems and needed science activities learning 2. to improve students activities 3. study the activities; 3.1 to improve the learning of course to pass the standard in 70 percentage 3.2 to improve basic science process skills to pass in 70 percentage 3.3 to study on attitude in science. the Target group was mathayomsuksa 3 students in the class 1 of Anuban Mahasarakham school by using purposive sampling technique that totally were 32 persons. The research instruments were an interview of teacher, the questionnaires of students who were managed in science learning activities and learning management based, the evaluation of learning achievement that had 4 choices were totally 30 items are have discrimination levels from 0.20 - 0.64 and all reliability levels were 0.74, the test of science process skills on basic level that had 4 choices with 30 items had discrimination levels from 0.28 - 0.83 and all reliability levels were 0.73. The evaluation of attitude to science course had 5-scale levels scale 5 levels, 20-item and difficulty levels from 0.20 - 0.71. The reliability levels were 0.69. The statistics used was percentage, mean and standard division. The research found as follows; 1. Study of the problems and needed science activities learning was found that concerning learning activities management focused on description, note by student non-action with learning activities, it non-evaluating science process skills and attitude in science. The knowledge of most student on science was lower. The motivated students students in learning activities in science were at high level ( = 3.81 2. Learning activities management was developed by 5 stages as follow; 1 introduction stage, 2 review old idea stage, 3 improvement and change concept stage, 4 applying a new idea stage, 5 conclusion stage and appropriately learning activities plan was at high level ( = 4.30 3. the Effects of learning activities

  1. Predicting Solar Activity Using Machine-Learning Methods (United States)

    Bobra, M.


    Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

  2. Assessing Student Behaviors and Motivation for Actively Learning Biology (United States)

    Moore, Michael Edward


    Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is…

  3. The Validation of the Active Learning in Health Professions Scale (United States)

    Kammer, Rebecca; Schreiner, Laurie; Kim, Young K.; Denial, Aurora


    There is a need for an assessment tool for evaluating the effectiveness of active learning strategies such as problem-based learning in promoting deep learning and clinical reasoning skills within the dual environments of didactic and clinical settings in health professions education. The Active Learning in Health Professions Scale (ALPHS)…

  4. Active Learning Environment with Lenses in Geometric Optics (United States)

    Tural, Güner


    Geometric optics is one of the difficult topics for students within physics discipline. Students learn better via student-centered active learning environments than the teacher-centered learning environments. So this study aimed to present a guide for middle school teachers to teach lenses in geometric optics via active learning environment…

  5. Competitive debate classroom as a cooperative learning technique for the human resources subject

    Directory of Open Access Journals (Sweden)

    Guillermo A. SANCHEZ PRIETO


    Full Text Available The paper shows an academic debate model as a cooperative learning technique for teaching human resources at University. The general objective of this paper is to conclude if academic debate can be included in the category of cooperative learning. The Specific objective it is presenting a model to implement this technique. Thus the first part of the paper shows the concept of cooperative learning and its main characteristics. The second part presents the debate model believed to be labelled as cooperative learning. Last part concludes with the characteristics of the model that match different aspects or not of the cooperative learning.

  6. Trainee Perspectives of the Effectiveness of Active Learning in a Legal Education Context

    Directory of Open Access Journals (Sweden)

    Rachael Hession


    Full Text Available This article explores whether active learning techniques can be effectively introduced to large group lectures in the context of legal professional training. It is limited to the perspective of the students (trainee solicitors. It is evident from research literature that a student-centred approach in the form of active learning techniques engages students and is considered a more effective form of teaching than the traditional lecturing style generally adopted at higher level education. There is a distinctive gap in the research literature relating to professional education. This article discusses a small scale qualitative study which adopted an action research methodology to determine the effectiveness of active learning techniques in this particular context. The study was confined to the introduction of two particular techniques, an in-class computation exercise and a re-cap technique, to the traditional lecture format. The views of a small focus group of trainee solicitors from the Law Society’s of Ireland Professional Practice Course were engaged. Findings from this study indicate that active learning techniques are effective in achieving learning outcomes from a trainees’ perspective. The author concludes that limitations of the use of the techniques can be overcome. Important directions for future research include in-depth analysis of the effectiveness of the techniques in preparing trainee solicitors for the professional role.

  7. Generalized query-based active learning to identify differentially methylated regions in DNA. (United States)

    Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J


    Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

  8. Adaptive Landmark-Based Navigation System Using Learning Techniques

    DEFF Research Database (Denmark)

    Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin


    The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal. In...... hexapod robots. As a result, it allows the robots to successfully learn to navigate to distal goals in complex environments.......The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal....... Inspired by this, we develop an adaptive landmark-based navigation system based on sequential reinforcement learning. In addition, correlation-based learning is also integrated into the system to improve learning performance. The proposed system has been applied to simulated simple wheeled and more complex...

  9. Who is that masked educator? Deconstructing the teaching and learning processes of an innovative humanistic simulation technique. (United States)

    McAllister, Margaret; Searl, Kerry Reid; Davis, Susan


    Simulation learning in nursing has long made use of mannequins, standardized actors and role play to allow students opportunity to practice technical body-care skills and interventions. Even though numerous strategies have been developed to mimic or amplify clinical situations, a common problem that is difficult to overcome in even the most well-executed simulation experiences, is that students may realize the setting is artificial and fail to fully engage, remember or apply the learning. Another problem is that students may learn technical competence but remain uncertain about communicating with the person. Since communication capabilities are imperative in human service work, simulation learning that only achieves technical competence in students is not fully effective for the needs of nursing education. Furthermore, while simulation learning is a burgeoning space for innovative practices, it has been criticized for the absence of a basis in theory. It is within this context that an innovative simulation learning experience named "Mask-Ed (KRS simulation)", has been deconstructed and the active learning components examined. Establishing a theoretical basis for creative teaching and learning practices provides an understanding of how, why and when simulation learning has been effective and it may help to distinguish aspects of the experience that could be improved. Three conceptual theoretical fields help explain the power of this simulation technique: Vygotskian sociocultural learning theory, applied theatre and embodiment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Active Learning in Engineering Education: a (re)introduction

    DEFF Research Database (Denmark)

    Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth


    The informal network ‘Active Learning in Engineering Education’ (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE...... were reviewed by the European Journal of Engineering Education community and this theme issue ended up with eight contributions, which are different both in their research and Active Learning approaches. These different Active Learning approaches are aligned with the different approaches that can...

  11. The application of different techniques to determine activated sludge ...

    African Journals Online (AJOL)

    The application of different techniques to determine activated sludge kinetic parameters in a food industry wastewater. ... method) and a respirometric technique based on oxygen consumption measurements, were used to compare microbial parameters using a wastewater model system of a potato processing plant.

  12. Thin layer activation techniques in research and industry

    International Nuclear Information System (INIS)

    Conlon, T.W.


    The following key application of thin layer activation technique (TLA) are discussed: ion-erosion in fusion tokamaks, bio-engineering technology, automobile industry. Future developments of the techniques, such as fission fragment TLA, multi-layer TLA and recoil implantation are discussed as well. 7 refs, 6 figs, 1 tab

  13. Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin


    Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically request user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.

  14. Approaching Assessment from a Learning Perspective: Elevating Assessment beyond Technique (United States)

    Simms, Michele; George, Beena


    Assessment is a key process in assuring quality education but how is it linked to the scholarship of teaching and learning (SoTL)? How can we join teaching and learning to the assessment process rather than view it as a stand-alone component in course and/or program development? This paper explores the relationship between assessment and the SoTL…

  15. Learning Faults Detection by AIS Techniques in CSCL Environments (United States)

    Zedadra, Amina; Lafifi, Yacine


    By the increase of e-learning platforms, huge data sets are made from different kinds of the collected traces. These traces differ from one learner to another according to their characteristics (learning styles, preferences, performed actions, etc.). Learners' traces are very heterogeneous and voluminous, so their treatments and exploitations are…

  16. Neutron activation analysis: an emerging technique for conservation/preservation

    International Nuclear Information System (INIS)

    Sayre, E.V.


    The diverse applications of neutron activation in analysis, preservation, and documentation of art works and artifacts are described with illustrations for each application. The uses of this technique to solve problems of attribution and authentication, to reveal the inner structure and composition of art objects, and, in some instances to recreate details of the objects are described. A brief discussion of the theory and techniques of neutron activation analysis is also included

  17. Debate preparation/participation: an active, effective learning tool. (United States)

    Koklanaris, Nikki; MacKenzie, Andrew P; Fino, M Elizabeth; Arslan, Alan A; Seubert, David E


    Passive educational techniques (such as lectures) are thought to be less productive than active learning. We examined whether preparing for and participating in a debate would be an effective, active way to learn about a controversial topic. We compared quiz performance in residents who attended a lecture to residents who prepared for/participated in a debate. Twelve residents each participated in one lecture session and one debate session. Learning was evaluated via a quiz. Quizzes were given twice: before the debate/lecture and 1 week after the debate/lecture. Quiz scores were compared using repeated measures analysis of variance, with a p value of debating was given to all participants. There was a statistically significant difference in the pretest mean quiz score between the debate and lecture groups: 78.3% and 52.5%, respectively (p = .02). Similarly, on posttest quizzes, the average debater scored 85.8%, versus 61.7% for the lecture group (p = .003). Although no one in the debate group scored lower on a follow-up quiz, 3 residents in the lecture group did worse on follow-up. When learning about a controversial topic, residents who prepared for/participated in a debate achieved higher quiz scores and were better at retaining information than those who attended a lecture. When faced with teaching a controversial topic, organizing a debate may be more effective than giving a lecture.

  18. Changing University Students' Alternative Conceptions of Optics by Active Learning (United States)

    Hadžibegovic, Zalkida; Sliško, Josip


    Active learning is individual and group participation in effective activities such as in-class observing, writing, experimenting, discussion, solving problems, and talking about to-be-learned topics. Some instructors believe that active learning is impossible, or at least extremely difficult to achieve in large lecture sessions. Nevertheless, the…

  19. Faculty motivations to use active learning among pharmacy educators. (United States)

    Rockich-Winston, Nicole; Train, Brian C; Rudolph, Michael J; Gillette, Chris


    Faculty motivations to use active learning have been limited to surveys evaluating faculty perceptions within active learning studies. Our objective in this study was to evaluate the relationship between faculty intrinsic motivation, extrinsic motivation, and demographic variables and the extent of active learning use in the classroom. An online survey was administered to individual faculty members at 137 colleges and schools of pharmacy across the United States. The survey assessed intrinsic and extrinsic motivations, active learning strategies, classroom time dedicated to active learning, and faculty development resources. Bivariate associations and multivariable stepwise linear regression were used to analyze the results. In total, 979 faculty members completed the questionnaire (23.6% response rate). All motivation variables were significantly correlated with percent active learning use (p active learning methods used in the last year (r = 0.259, p active learning use. Our results suggest that faculty members who are intrinsically motivated to use active learning are more likely to dedicate additional class time to active learning. Furthermore, intrinsic motivation may be positively associated with encouraging faculty members to attend active learning workshops and supporting faculty to use various active learning strategies in the classroom. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Active Learning: The Importance of Developing a Comprehensive Measure (United States)

    Carr, Rodney; Palmer, Stuart; Hagel, Pauline


    This article reports on an investigation into the validity of a widely used scale for measuring the extent to which higher education students employ active learning strategies. The scale is the active learning scale in the Australasian Survey of Student Engagement. This scale is based on the Active and Collaborative Learning scale of the National…

  1. Weed identification using an automated active shape matching (AASM) technique

    DEFF Research Database (Denmark)

    C. Swain, Kishore; Nørremark, Michael; Jørgensen, Rasmus Nyholm


    Weed identification and control is a challenge for intercultural operations in agriculture. As an alternative to chemical pest control, a smart weed identification technique followed by mechanical weed control system could be developed. The proposed smart identification technique works on the con......Weed identification and control is a challenge for intercultural operations in agriculture. As an alternative to chemical pest control, a smart weed identification technique followed by mechanical weed control system could be developed. The proposed smart identification technique works...... on the concept of ‘active shape modelling’ to identify weed and crop plants based on their morphology. The automated active shape matching system (AASM) technique consisted of, i) a Pixelink camera ii) an LTI (Lehrstuhlfuer technische informatik) image processing library, iii) a laptop pc with the Linux OS. A 2...

  2. MUMAL: Multivariate analysis in shotgun proteomics using machine learning techniques

    Directory of Open Access Journals (Sweden)

    Cerqueira Fabio R


    Full Text Available Abstract Background The shotgun strategy (liquid chromatography coupled with tandem mass spectrometry is widely applied for identification of proteins in complex mixtures. This method gives rise to thousands of spectra in a single run, which are interpreted by computational tools. Such tools normally use a protein database from which peptide sequences are extracted for matching with experimentally derived mass spectral data. After the database search, the correctness of obtained peptide-spectrum matches (PSMs needs to be evaluated also by algorithms, as a manual curation of these huge datasets would be impractical. The target-decoy database strategy is largely used to perform spectrum evaluation. Nonetheless, this method has been applied without considering sensitivity, i.e., only error estimation is taken into account. A recently proposed method termed MUDE treats the target-decoy analysis as an optimization problem, where sensitivity is maximized. This method demonstrates a significant increase in the retrieved number of PSMs for a fixed error rate. However, the MUDE model is constructed in such a way that linear decision boundaries are established to separate correct from incorrect PSMs. Besides, the described heuristic for solving the optimization problem has to be executed many times to achieve a significant augmentation in sensitivity. Results Here, we propose a new method, termed MUMAL, for PSM assessment that is based on machine learning techniques. Our method can establish nonlinear decision boundaries, leading to a higher chance to retrieve more true positives. Furthermore, we need few iterations to achieve high sensitivities, strikingly shortening the running time of the whole process. Experiments show that our method achieves a considerably higher number of PSMs compared with standard tools such as MUDE, PeptideProphet, and typical target-decoy approaches. Conclusion Our approach not only enhances the computational performance, and

  3. Machine learning in Python essential techniques for predictive analysis

    CERN Document Server

    Bowles, Michael


    Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, d

  4. Evaluation and Implementation of Distance Learning: Technologies, Tools and Techniques

    Directory of Open Access Journals (Sweden)

    Figen UNAL


    Full Text Available This book is published by Idea Group Publishing. The book consistsof seven chapters, a bibliography and references section, fourappendices, an index, and author biography. In appendix A, thereare three data forms those can used by distance learning coursedesigners. In appendix B, under the title of ‘definitions’, there is a dictionary consists of Internet and e-learning terms. In appendixC, there is a table relevant to infrastructure survey and upgraderequirements. Finally appendix D contains a list of web sites thatoffer discussions of distance learning issues and concepts.

  5. Annotating smart environment sensor data for activity learning. (United States)

    Szewcyzk, S; Dwan, K; Minor, B; Swedlove, B; Cook, D


    The pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track the activities that people perform at home. Machine learning techniques can perform this task, but the software algorithms rely upon large amounts of sample data that is correctly labeled with the corresponding activity. Labeling, or annotating, sensor data with the corresponding activity can be time consuming, may require input from the smart home resident, and is often inaccurate. Therefore, in this paper we investigate four alternative mechanisms for annotating sensor data with a corresponding activity label. We evaluate the alternative methods along the dimensions of annotation time, resident burden, and accuracy using sensor data collected in a real smart apartment.

  6. Educating patients: understanding barriers, learning styles, and teaching techniques. (United States)

    Beagley, Linda


    Health care delivery and education has become a challenge for providers. Nurses and other professionals are challenged daily to assure that the patient has the necessary information to make informed decisions. Patients and their families are given a multitude of information about their health and commonly must make important decisions from these facts. Obstacles that prevent easy delivery of health care information include literacy, culture, language, and physiological barriers. It is up to the nurse to assess and evaluate the patient's learning needs and readiness to learn because everyone learns differently. This article will examine how each of these barriers impact care delivery along with teaching and learning strategies will be examined. Copyright © 2011 American Society of PeriAnesthesia Nurses. Published by Elsevier Inc. All rights reserved.

  7. Machine learning techniques applied to system characterization and equalization

    DEFF Research Database (Denmark)

    Zibar, Darko; Thrane, Jakob; Wass, Jesper


    Linear signal processing algorithms are effective in combating linear fibre channel impairments. We demonstrate the ability of machine learning algorithms to combat nonlinear fibre channel impairments and perform parameter extraction from directly detected signals.......Linear signal processing algorithms are effective in combating linear fibre channel impairments. We demonstrate the ability of machine learning algorithms to combat nonlinear fibre channel impairments and perform parameter extraction from directly detected signals....

  8. Interactive Multimedia Instruction for Training Self-Directed Learning Techniques (United States)


    feedback and input on the content, format, and pedagogical approach of the lesson. This survey could be e-mailed to the principal ARI researcher for...peers in self-directed learning. Some examples of the metaphorical relationships and common examples woven into this IMI are identified in Table 1...20 Table 1 Metaphorical Relationships and Illustrations Used in Self-Directed Learning Training Military or Common Example Self-Directed

  9. Active Learning in the Era of Big Data

    Energy Technology Data Exchange (ETDEWEB)

    Jamieson, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Davis, IV, Warren L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)


    Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.

  10. Mobile Robot Navigation Based on Q-Learning Technique

    Directory of Open Access Journals (Sweden)

    Lazhar Khriji


    Full Text Available This paper shows how Q-learning approach can be used in a successful way to deal with the problem of mobile robot navigation. In real situations where a large number of obstacles are involved, normal Q-learning approach would encounter two major problems due to excessively large state space. First, learning the Q-values in tabular form may be infeasible because of the excessive amount of memory needed to store the table. Second, rewards in the state space may be so sparse that with random exploration they will only be discovered extremely slowly. In this paper, we propose a navigation approach for mobile robot, in which the prior knowledge is used within Q-learning. We address the issue of individual behavior design using fuzzy logic. The strategy of behaviors based navigation reduces the complexity of the navigation problem by dividing them in small actions easier for design and implementation. The Q-Learning algorithm is applied to coordinate between these behaviors, which make a great reduction in learning convergence times. Simulation and experimental results confirm the convergence to the desired results in terms of saved time and computational resources.

  11. An empirical study on the performance of spectral manifold learning techniques

    DEFF Research Database (Denmark)

    Mysling, Peter; Hauberg, Søren; Pedersen, Kim Steenstrup


    In recent years, there has been a surge of interest in spectral manifold learning techniques. Despite the interest, only little work has focused on the empirical behavior of these techniques. We construct synthetic data of variable complexity and observe the performance of the techniques as they ...

  12. Active noise control technique and its application on ships

    Directory of Open Access Journals (Sweden)

    CHEN Kean


    Full Text Available Due to the rapid development during past three decades, Active Noise Control(ANC has become a highly complementary noise control approach in comparison with traditional approaches, and has formed a complete system including basic theory, investigation approach, key techniques and system implementation. Meanwhile, substantial progress has been achieved in such fields as the practical application, industrialization development and commercial popularization of ANC, and this developed technique provides a practical and feasible choice for the active control of ship noise. In this review paper, its sound field analysis, system setup and key techniques are summarized, typical examples of ANC-based engineering applications including control of cabin noise and duct noise are briefly described, and a variety of forefronts and problems associated with the applications of ANC in ship noise control, such as active sound absorption, active sound insulation and smart acoustic structure, are subsequently discussed.


    Directory of Open Access Journals (Sweden)

    D. V. Tugay


    Full Text Available Purpose. The goal is to develop technique of the phase inductance power reactors selection for parallel active filter based on the account both low-frequency and high-frequency components of the electromagnetic processes in a power circuit. Methodology. We have applied concepts of the electrical circuits theory, vector analysis, mathematical simulation in Matlab package. Results. We have developed a new technique of the phase reactors inductance selection for parallel power active filter. It allows us to obtain the smallest possible value of THD network current. Originality. We have increased accuracy of methods of the phase reactor inductance selection for power active filter. Practical value. The proposed technique can be used in the design and manufacture of the active power filter for real objects of energy supply.

  14. Understanding Fatty Acid Metabolism through an Active Learning Approach (United States)

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


    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…

  15. Active Learning Increases Children's Physical Activity across Demographic Subgroups. (United States)

    Bartholomew, John B; Jowers, Esbelle M; Roberts, Gregory; Fall, Anna-Mária; Errisuriz, Vanessa L; Vaughn, Sharon


    Given the need to find more opportunities for physical activity within the elementary school day, this study was designed to asses the impact of I-CAN!, active lessons on: 1) student physical activity (PA) outcomes via accelerometry; and 2) socioeconomic status (SES), race, sex, body mass index (BMI), or fitness as moderators of this impact. Participants were 2,493 fourth grade students (45.9% male, 45.8% white, 21.7% low SES) from 28 central Texas elementary schools randomly assigned to intervention (n=19) or control (n=9). Multilevel regression models evaluated the effect of I-CAN! on PA and effect sizes were calculated. The moderating effects of SES, race, sex, BMI, and fitness were examined in separate models. Students in treatment schools took significantly more steps than those in control schools (β = 125.267, SE = 41.327, p = .002, d = .44). I-CAN! had a significant effect on MVPA with treatment schools realizing 80% (β = 0.796, SE =0.251, p = .001; d = .38) more MVPA than the control schools. There were no significant school-level differences on sedentary behavior (β = -0.177, SE = 0.824, p = .83). SES, race, sex, BMI, and fitness level did not moderate the impact of active learning on step count and MVPA. Active learning increases PA within elementary students, and does so consistently across demographic sub-groups. This is important as these sub-groups represent harder to reach populations for PA interventions. While these lessons may not be enough to help children reach daily recommendations of PA, they can supplement other opportunities for PA. This speaks to the potential of schools to adopt policy change to require active learning.

  16. The regeneration of polluted active carbon by radiation techniques

    International Nuclear Information System (INIS)

    Bao Borong; Wu Minghong; Hu Longxin; Zhou Riumin; Zhu Jinliang


    In this paper, we investigated the regeneration of polluted active carbon from monosodium glutamate factory by combination of radiation and acid-alkali chemical techniques. The experimental results show that the polluted active carbon will be highly regenerated on the conditions of process concentration 3%, process time 0.5 hour and the adjustment process concentration 2%, time 0.5 hour, radiation dose 5kGy. As regeneration times increase, the regenerated active carbon behaves with good repetition and stable property

  17. Face-to-Face Activities in Blended Learning

    DEFF Research Database (Denmark)

    Kjærgaard, Annemette

    While blended learning combines online and face-to-face teaching, research on blended learning has primarily focused on the role of technology and the opportunities it creates for engaging students. Less focus has been put on face-to-face activities in blended learning. This paper argues...... that it is not only the online activities in blended learning that provide new opportunities for rethinking pedagogy in higher education, it is also imperative to reconsider the face-to-face activities when part of the learning is provided online. Based on a review of blended learning in business and management...... education, we identify what forms of teaching and learning are suggested to take place face-to-face when other activities are moved online. We draw from the Community of Inquiry framework to analyze how face-to-face activities contribute to a blended learning pedagogy and discuss the implications...

  18. Active Metric Learning from Relative Comparisons


    Xiong, Sicheng; Rosales, Rómer; Pei, Yuanli; Fern, Xiaoli Z.


    This work focuses on active learning of distance metrics from relative comparison information. A relative comparison specifies, for a data point triplet $(x_i,x_j,x_k)$, that instance $x_i$ is more similar to $x_j$ than to $x_k$. Such constraints, when available, have been shown to be useful toward defining appropriate distance metrics. In real-world applications, acquiring constraints often require considerable human effort. This motivates us to study how to select and query the most useful ...

  19. Active Discriminative Dictionary Learning for Weather Recognition

    Directory of Open Access Journals (Sweden)

    Caixia Zheng


    Full Text Available Weather recognition based on outdoor images is a brand-new and challenging subject, which is widely required in many fields. This paper presents a novel framework for recognizing different weather conditions. Compared with other algorithms, the proposed method possesses the following advantages. Firstly, our method extracts both visual appearance features of the sky region and physical characteristics features of the nonsky region in images. Thus, the extracted features are more comprehensive than some of the existing methods in which only the features of sky region are considered. Secondly, unlike other methods which used the traditional classifiers (e.g., SVM and K-NN, we use discriminative dictionary learning as the classification model for weather, which could address the limitations of previous works. Moreover, the active learning procedure is introduced into dictionary learning to avoid requiring a large number of labeled samples to train the classification model for achieving good performance of weather recognition. Experiments and comparisons are performed on two datasets to verify the effectiveness of the proposed method.

  20. Strategies for active learning in online continuing education. (United States)

    Phillips, Janet M


    Online continuing education and staff development is on the rise as the benefits of access, convenience, and quality learning are continuing to take shape. Strategies to enhance learning call for learner participation that is self-directed and independent, thus changing the educator's role from expert to coach and facilitator. Good planning of active learning strategies promotes optimal learning whether the learning content is presented in a course or a just-in-time short module. Active learning strategies can be used to enhance online learning during all phases of the teaching-learning process and can accommodate a variety of learning styles. Feedback from peers, educators, and technology greatly influences learner satisfaction and must be harnessed to provide effective learning experiences. Outcomes of active learning can be assessed online and implemented conveniently and successfully from the initiation of the course or module planning to the end of the evaluation process. Online learning has become accessible and convenient and allows the educator to track learner participation. The future of online education will continue to grow, and using active learning strategies will ensure that quality learning will occur, appealing to a wide variety of learning needs.

  1. Impacts of Vocabulary Acquisition Techniques Instruction on Students' Learning (United States)

    Orawiwatnakul, Wiwat


    The objectives of this study were to determine how the selected vocabulary acquisition techniques affected the vocabulary ability of 35 students who took EN 111 and investigate their attitudes towards the techniques instruction. The research study was one-group pretest and post-test design. The instruments employed were in-class exercises…

  2. Active Learning Not Associated with Student Learning in a Random Sample of College Biology Courses (United States)

    Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.


    Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373

  3. STEM learning activity among home-educating families (United States)

    Bachman, Jennifer


    Science, technology, engineering, and mathematics (STEM) learning was studied among families in a group of home-educators in the Pacific Northwest. Ethnographic methods recorded learning activity (video, audio, fieldnotes, and artifacts) which was analyzed using a unique combination of Cultural-Historical Activity Theory (CHAT) and Mediated Action (MA), enabling analysis of activity at multiple levels. Findings indicate that STEM learning activity is family-led, guided by parents' values and goals for learning, and negotiated with children to account for learner interests and differences, and available resources. Families' STEM education practice is dynamic, evolves, and influenced by larger societal STEM learning activity. Parents actively seek support and resources for STEM learning within their home-school community, working individually and collectively to share their funds of knowledge. Home-schoolers also access a wide variety of free-choice learning resources: web-based materials, museums, libraries, and community education opportunities (e.g. afterschool, weekend and summer programs, science clubs and classes, etc.). A lesson-heuristic, grounded in Mediated Action, represents and analyzes home STEM learning activity in terms of tensions between parental goals, roles, and lesson structure. One tension observed was between 'academic' goals or school-like activity and 'lifelong' goals or everyday learning activity. Theoretical and experiential learning was found in both activity, though parents with academic goals tended to focus more on theoretical learning and those with lifelong learning goals tended to be more experiential. Examples of the National Research Council's science learning strands (NRC, 2009) were observed in the STEM practices of all these families. Findings contribute to the small but growing body of empirical CHAT research in science education, specifically to the empirical base of family STEM learning practices at home. It also fills a

  4. Enhancing Learning Outcomes through Application Driven Activities in Marketing (United States)

    Stegemann, Nicole; Sutton-Brady, Catherine


    This paper introduces an activity used in class to allow students to apply previously acquired information to a hands-on task. As the authors have previously shown active learning is a way to effectively facilitate and improve students' learning outcomes. As a result to improve learning outcomes we have overtime developed a series of learning…

  5. Improving active Mealy machine learning for protocol conformance testing

    NARCIS (Netherlands)

    Aarts, F.; Kuppens, H.; Tretmans, J.; Vaandrager, F.; Verwer, S.


    Using a well-known industrial case study from the verification literature, the bounded retransmission protocol, we show how active learning can be used to establish the correctness of protocol implementation I relative to a given reference implementation R. Using active learning, we learn a model M

  6. Telling Active Learning Pedagogies Apart: From Theory to Practice (United States)

    Cattaneo, Kelsey Hood


    Designing learning environments to incorporate active learning pedagogies is difficult as definitions are often contested and intertwined. This article seeks to determine whether classification of active learning pedagogies (i.e., project-based, problem-based, inquiry-based, case-based, and discovery-based), through theoretical and practical…

  7. Effects of Sharing Clickers in an Active Learning Environment (United States)

    Daniel, Todd; Tivener, Kristin


    Scientific research into learning enhancement gained by the use of clickers in active classrooms has largely focused on the use of individual clickers. In this study, we compared the learning experiences of participants in active learning groups in which an entire small group shared a single clicker to groups in which each member of the group had…

  8. Comparing visualization techniques for learning second language prosody

    DEFF Research Database (Denmark)

    Niebuhr, Oliver; Alm, Maria Helena; Schümchen, Nathalie


    We tested the usability of prosody visualization techniques for second language (L2) learners. Eighteen Danish learners realized target sentences in German based on different visualization techniques. The sentence realizations were annotated by means of the phonological Kiel Intonation Model...... and then analyzed in terms of (a) prosodic-pattern consistency and (b) correctness of the prosodic patterns. In addition, the participants rated the usability of the visualization techniques. The results from the phonological analysis converged with the usability ratings in showing that iconic techniques......, in particular the stylized “hat pattern” visualization, performed better than symbolic techniques, and that marking prosodic information beyond intonation can be more confusing than instructive. In discussing our findings, we also provide a description of the new Danish-German learner corpus we created: DANGER...

  9. Are students' impressions of improved learning through active learning methods reflected by improved test scores? (United States)

    Everly, Marcee C


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

  10. The use of an active learning approach in a SCALE-UP learning space improves academic performance in undergraduate General Biology. (United States)

    Hacisalihoglu, Gokhan; Stephens, Desmond; Johnson, Lewis; Edington, Maurice


    Active learning is a pedagogical approach that involves students engaging in collaborative learning, which enables them to take more responsibility for their learning and improve their critical thinking skills. While prior research examined student performance at majority universities, this study focuses on specifically Historically Black Colleges and Universities (HBCUs) for the first time. Here we present work that focuses on the impact of active learning interventions at Florida A&M University, where we measured the impact of active learning strategies coupled with a SCALE-UP (Student Centered Active Learning Environment with Upside-down Pedagogies) learning environment on student success in General Biology. In biology sections where active learning techniques were employed, students watched online videos and completed specific activities before class covering information previously presented in a traditional lecture format. In-class activities were then carefully planned to reinforce critical concepts and enhance critical thinking skills through active learning techniques such as the one-minute paper, think-pair-share, and the utilization of clickers. Students in the active learning and control groups covered the same topics, took the same summative examinations and completed identical homework sets. In addition, the same instructor taught all of the sections included in this study. Testing demonstrated that these interventions increased learning gains by as much as 16%, and students reported an increase in their positive perceptions of active learning and biology. Overall, our results suggest that active learning approaches coupled with the SCALE-UP environment may provide an added opportunity for student success when compared with the standard modes of instruction in General Biology.

  11. An Exploration of Prospective Teachers' Learning of Clinical Interview Techniques (United States)

    Groth, Randall E.; Bergner, Jennifer A.; Burgess, Claudia R.


    The present study followed four prospective teachers through the process of learning to interview during an undergraduate research project experience. Participants conducted and video recorded a series of interviews with children. They also carried out guided analyses of the videos and written artefacts from the interviews to formulate conjectures…

  12. Cooperative Learning Technique through Internet Based Education: A Model Proposal (United States)

    Ozkan, Hasan Huseyin


    Internet is gradually becoming the most valuable learning environment for the people which form the information society. That the internet provides written, oral and visual communication between the participants who are at different places, that it enables the students' interaction with other students and teachers, and that it does these so fast…

  13. Software Engineering Techniques for Computer-Aided Learning. (United States)

    Ibrahim, Bertrand


    Describes the process for developing tutorials for computer-aided learning (CAL) using a programing language rather than an authoring system. The workstation used is described, the use of graphics is discussed, the role of a local area network (LAN) is explained, and future plans are discussed. (five references) (LRW)

  14. Using Deep Learning Techniques to Forecast Environmental Consumption Level

    Directory of Open Access Journals (Sweden)

    Donghyun Lee


    Full Text Available Artificial intelligence is a promising futuristic concept in the field of science and technology, and is widely used in new industries. The deep-learning technology leads to performance enhancement and generalization of artificial intelligence technology. The global leader in the field of information technology has declared its intention to utilize the deep-learning technology to solve environmental problems such as climate change, but few environmental applications have so far been developed. This study uses deep-learning technologies in the environmental field to predict the status of pro-environmental consumption. We predicted the pro-environmental consumption index based on Google search query data, using a recurrent neural network (RNN model. To verify the accuracy of the index, we compared the prediction accuracy of the RNN model with that of the ordinary least square and artificial neural network models. The RNN model predicts the pro-environmental consumption index better than any other model. We expect the RNN model to perform still better in a big data environment because the deep-learning technologies would be increasingly sophisticated as the volume of data grows. Moreover, the framework of this study could be useful in environmental forecasting to prevent damage caused by climate change.

  15. Using the Technique of Journal Writing to Learn Emergency Psychiatry (United States)

    Bhuvaneswar, Chaya; Stern, Theodore; Beresin, Eugene


    Objective: The authors discuss journal writing in learning emergency psychiatry. Methods: The journal of a psychiatry intern rotating through an emergency department is used as sample material for analysis that could take place in supervision or a resident support group. A range of articles are reviewed that illuminate the relevance of journal…

  16. A comparison of machine learning techniques for predicting downstream acid mine drainage

    CSIR Research Space (South Africa)

    van Zyl, TL


    Full Text Available windowing approach over historical values to generate a prediction for the current value. We evaluate a number of Machine Learning techniques as regressors including Support Vector Regression, Random Forests, Stochastic Gradient Decent Regression, Linear...

  17. Application of machine learning techniques to lepton energy reconstruction in water Cherenkov detectors (United States)

    Drakopoulou, E.; Cowan, G. A.; Needham, M. D.; Playfer, S.; Taani, M.


    The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found that applying these techniques leads to an improvement of more than 50% in the energy resolution for all lepton energies compared to an approach based upon lookup tables. Machine learning techniques can be easily applied to different detector configurations and the results are comparable to likelihood-function based techniques that are currently used.

  18. "Heart Shots": a classroom activity to instigate active learning. (United States)

    Abraham, Reem Rachel; Vashe, Asha; Torke, Sharmila


    The present study aimed to provide undergraduate medical students at Melaka Manipal Medical College (Manipal Campus), Manipal University, in Karnataka, India, an opportunity to apply their knowledge in cardiovascular concepts to real-life situations. A group activity named "Heart Shots" was implemented for a batch of first-year undergraduate students (n = 105) at the end of a block (teaching unit). Students were divided into 10 groups each having 10-11 students. They were requested to make a video/PowerPoint presentation about the application of cardiovascular principles to real-life situations. The presentation was required to be of only pictures/photos and no text material, with a maximum duration of 7 min. More than 95% of students considered that the activity helped them to apply their knowledge in cardiovascular concepts to real-life situations and understand the relevance of physiology in medicine and to revise the topic. More than 90% of students agreed that the activity helped them to apply their creativity in improving their knowledge and to establish a link between concepts rather than learning them as isolated facts. Based on the feedback, we conclude that the activity was student centered and that it facilitated learning. Copyright © 2015 The American Physiological Society.

  19. Active Learning for Directed Exploration of Complex Systems (United States)

    Burl, Michael C.; Wang, Esther


    Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fidelity representation of system behavior, but are often so slow to run that insight into the system is limited. For example, conducting an exhaustive sweep over a d-dimensional input parameter space with k-steps along each dimension requires k(sup d) simulation trials (translating into k(sup d) CPU-days for one of our current simulations). An alternative is directed exploration in which the next simulation trials are cleverly chosen at each step. Given the results of previous trials, supervised learning techniques (SVM, KDE, GP) are applied to build up simplified predictive models of system behavior. These models are then used within an active learning framework to identify the most valuable trials to run next. Several active learning strategies are examined including a recently-proposed information-theoretic approach. Performance is evaluated on a set of thirteen synthetic oracles, which serve as surrogates for the more expensive simulations and enable the experiments to be replicated by other researchers.

  20. Active Affordance Learning in Continuous State and Action Spaces

    NARCIS (Netherlands)

    Wang, C.; Hindriks, K.V.; Babuska, R.


    Learning object affordances and manipulation skills is essential for developing cognitive service robots. We propose an active affordance learning approach in continuous state and action spaces without manual discretization of states or exploratory motor primitives. During exploration in the action

  1. Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support (United States)

    Wong, Lung-Hsiang; Looi, Chee-Kit


    The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

  2. Clustering: An Interactive Technique to Enhance Learning in Biology. (United States)

    Ambron, Joanna


    Explains an interdisciplinary approach to biology and writing which increases students' mastery of vocabulary, scientific concepts, creativity, and expression. Describes modifications of the clustering technique used to summarize lectures, integrate reading and understand textbook material. (RT)

  3. An Analysis of Learning Activities in a Technology Education Textbook for Teachers : Learning Process Based on Contents Framework and Learning Scene to Develop Technological Literacy


    Yata, Chikahiko; Hamamoto, Kengo; Oguri, Takenori


    This study analyzed the learning activities in a textbook on technology education for teachers, in order to examine the learning processes and learning scenes detailed therein. Results of analyzing learning process, primary learning activity found each contents framework. Other learning activities designated to be related to complementary in learning process. Results of analyzing learning scene, 14 learning scenes, among them "Scene to recognize the impact on social life and progress of techn...

  4. Lifeguard Final Exam—Encouraging the Use of Active Learning


    Griswold, Elise N.; Klionsky, Daniel J.


    To anyone familiar with the extensive literature on teaching and learning, there is little question that active learning is more effective than passive learning. Thus, we are not directing this letter to that particular audience. Instead, we are attempting to address the question of the best way to convince instructors who have not tried to incorporate elements of active learning into their courses to make such an attempt. There are numerous examples where it becomes immediately clear that ac...

  5. Student’s Perceptions on Simulation as Part of Experiential Learning in Approaches, Methods, and Techniques (AMT Course

    Directory of Open Access Journals (Sweden)

    Marselina Karina Purnomo


    Full Text Available Simulation is a part of Experiential Learning which represents certain real-life events. In this study, simulation is used as a learning activity in Approaches, Methods, and Techniques (AMT course which is one of the courses in English Language Education Study Program (ELESP of Sanata Dharma University. Since simulation represents the real-life events, it encourages students to apply the approaches, methods, and techniques being studied based on the real-life classroom. Several experts state that students are able to involve their personal experiences through simulation which additionally is believed to create a meaningful learning in the class. This study aimed to discover ELESP students’ perceptions toward simulation as a part of Experiential Learning in AMT course. From the findings, it could be inferred that students agreed that simulation in class was important for students’ learning for it formed a meaningful learning in class.  DOI:

  6. Does using active learning in thermodynamics lectures improve students’ conceptual understanding and learning experiences?

    International Nuclear Information System (INIS)

    Georgiou, H; Sharma, M D


    Encouraging ‘active learning’ in the large lecture theatre emerges as a credible recommendation for improving university courses, with reports often showing significant improvements in learning outcomes. However, the recommendations are based predominantly on studies undertaken in mechanics. We set out to examine those claims in the thermodynamics module of a large first year physics course with an established technique, called interactive lecture demonstrations (ILDs). The study took place at The University of Sydney, where four parallel streams of the thermodynamics module were divided into two streams that experienced the ILDs and two streams that did not. The programme was first implemented in 2011 to gain experience and refine logistical matters and repeated in 2012 with approximately 500 students. A validated survey, the thermal concepts survey, was used as pre-test and post-test to measure learning gains while surveys and interviews provided insights into what the ‘active learning’ meant from student experiences. We analysed lecture recordings to capture the time devoted to different activities in a lecture, including interactivity. The learning gains were in the ‘high gain’ range for the ILD streams and ‘medium gain’ for the other streams. The analysis of the lecture recordings showed that the ILD streams devoted significantly more time to interactivity while surveys and interviews showed that students in the ILD streams were thinking in deep ways. Our study shows that ILDs can make a difference in students’ conceptual understanding as well as their experiences, demonstrating the potential value-add that can be provided by investing in active learning to enhance lectures. (paper)

  7. Predicting breast screening attendance using machine learning techniques. (United States)

    Baskaran, Vikraman; Guergachi, Aziz; Bali, Rajeev K; Naguib, Raouf N G


    Machine learning-based prediction has been effectively applied for many healthcare applications. Predicting breast screening attendance using machine learning (prior to the actual mammogram) is a new field. This paper presents new predictor attributes for such an algorithm. It describes a new hybrid algorithm that relies on back-propagation and radial basis function-based neural networks for prediction. The algorithm has been developed in an open source-based environment. The algorithm was tested on a 13-year dataset (1995-2008). This paper compares the algorithm and validates its accuracy and efficiency with different platforms. Nearly 80% accuracy and 88% positive predictive value and sensitivity were recorded for the algorithm. The results were encouraging; 40-50% of negative predictive value and specificity warrant further work. Preliminary results were promising and provided ample amount of reasons for testing the algorithm on a larger scale.

  8. Enhanced Quality Control in Pharmaceutical Applications by Combining Raman Spectroscopy and Machine Learning Techniques (United States)

    Martinez, J. C.; Guzmán-Sepúlveda, J. R.; Bolañoz Evia, G. R.; Córdova, T.; Guzmán-Cabrera, R.


    In this work, we applied machine learning techniques to Raman spectra for the characterization and classification of manufactured pharmaceutical products. Our measurements were taken with commercial equipment, for accurate assessment of variations with respect to one calibrated control sample. Unlike the typical use of Raman spectroscopy in pharmaceutical applications, in our approach the principal components of the Raman spectrum are used concurrently as attributes in machine learning algorithms. This permits an efficient comparison and classification of the spectra measured from the samples under study. This also allows for accurate quality control as all relevant spectral components are considered simultaneously. We demonstrate our approach with respect to the specific case of acetaminophen, which is one of the most widely used analgesics in the market. In the experiments, commercial samples from thirteen different laboratories were analyzed and compared against a control sample. The raw data were analyzed based on an arithmetic difference between the nominal active substance and the measured values in each commercial sample. The principal component analysis was applied to the data for quantitative verification (i.e., without considering the actual concentration of the active substance) of the difference in the calibrated sample. Our results show that by following this approach adulterations in pharmaceutical compositions can be clearly identified and accurately quantified.

  9. Use of machine learning techniques for modeling of snow depth

    Directory of Open Access Journals (Sweden)

    G. V. Ayzel


    Full Text Available Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France, Sodankyla (Finland, and Snoquamie Pass (USA.Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

  10. Machine learning and evolutionary techniques in interplanetary trajectory design


    Izzo, Dario; Sprague, Christopher; Tailor, Dharmesh


    After providing a brief historical overview on the synergies between artificial intelligence research, in the areas of evolutionary computations and machine learning, and the optimal design of interplanetary trajectories, we propose and study the use of deep artificial neural networks to represent, on-board, the optimal guidance profile of an interplanetary mission. The results, limited to the chosen test case of an Earth-Mars orbital transfer, extend the findings made previously for landing ...

  11. Machine learning techniques for gait biometric recognition using the ground reaction force

    CERN Document Server

    Mason, James Eric; Woungang, Isaac


    This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...

  12. Cooperative activity and its potential for learning in tertiary education

    Directory of Open Access Journals (Sweden)

    Cirila Peklaj


    Full Text Available A learning situation can be structured in different ways, as an individual, competitive, or cooperative activity. Each of these structures can be used for different purposes and can lead to different learning outcomes. This paper focuses on cooperative activity and its potential for learning in tertiary education. After defining cooperative activity (or, in a broader sense, learning in interaction and introducing the CAMS theoretical framework to analyse cooperative activity, the main discussion focuses on the theoretical reasons for the usefulness of group learning and on the research of effects of cooperative learning on cognitive (metacognitive, affective-motivational and social processes in university students. The key elements that should be established for successful cooperation are also discussed. At the end, a new direction in using cooperative activity in learning—computer supported collaborative learning (CSCL, which emerged with rapid technology development in the last two decades—is presented and discussed.

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

    Directory of Open Access Journals (Sweden)

    Chinmoy Pal


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

  14. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights (United States)

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


    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.

  15. Students' Satisfaction on Their Learning Process in Active Learning and Traditional Classrooms (United States)

    Hyun, Jung; Ediger, Ruth; Lee, Donghun


    Studies have shown Active Learning Classrooms [ALCs] help increase student engagement and improve student performance. However, remodeling all traditional classrooms to ALCs entails substantial financial burdens. Thus, an imperative question for institutions of higher education is whether active learning pedagogies can improve learning outcomes…

  16. Active-Learning versus Teacher-Centered Instruction for Learning Acids and Bases (United States)

    Sesen, Burcin Acar; Tarhan, Leman


    Background and purpose: Active-learning as a student-centered learning process has begun to take more interest in constructing scientific knowledge. For this reason, this study aimed to investigate the effectiveness of active-learning implementation on high-school students' understanding of "acids and bases". Sample: The sample of this…

  17. Bonding techniques for hybrid active pixel sensors (HAPS)

    Energy Technology Data Exchange (ETDEWEB)

    Bigas, M. [Centre Nacional de Microelectronica, CNM-IMB (CSIC), Campus Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)]. E-mail:; Cabruja, E. [Centre Nacional de Microelectronica, CNM-IMB (CSIC), Campus Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)]. E-mail:; Lozano, M. [Centre Nacional de Microelectronica, CNM-IMB (CSIC), Campus Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)


    A hybrid active pixel sensor (HAPS) consists of an array of sensing elements which is connected to an electronic read-out unit. The most used way to connect these two different devices is bump bonding. This interconnection technique is very suitable for these systems because it allows a very fine pitch and a high number of I/Os. However, there are other interconnection techniques available such as direct bonding. This paper, as a continuation of a review [M. Lozano, E. Cabruja, A. Collado, J. Santander, M. Ullan, Nucl. Instr. and Meth. A 473 (1-2) (2001) 95-101] published in 2001, presents an update of the different advanced bonding techniques available for manufacturing a hybrid active pixel detector.

  18. Active structural control with stable fuzzy PID techniques

    CERN Document Server

    Yu, Wen


    This book presents a detailed discussion of intelligent techniques to measure the displacement of buildings when they are subjected to vibration. It shows how these techniques are used to control active devices that can reduce vibration 60–80% more effectively than widely used passive anti-seismic systems. After introducing various structural control devices and building-modeling and active structural control methods, the authors propose offset cancellation and high-pass filtering techniques to solve some common problems of building-displacement measurement using accelerometers. The most popular control algorithms in industrial settings, PD/PID controllers, are then analyzed and then combined with fuzzy compensation. The stability of this combination is proven with standard weight-training algorithms. These conditions provide explicit methods for selecting PD/PID controllers. Finally, fuzzy-logic and sliding-mode control are applied to the control of wind-induced vibration. The methods described are support...

  19. Development and Experimental Evaluation of Machine-Learning Techniques for an Intelligent Hairy Scalp Detection System

    Directory of Open Access Journals (Sweden)

    Wei-Chien Wang


    Full Text Available Deep learning has become the most popular research subject in the fields of artificial intelligence (AI and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made progress in voice and image recognition, image classification, and natural language processing. Prior to deep learning, decision tree, linear discriminant analysis (LDA, support vector machines (SVM, k-nearest neighbors algorithm (K-NN, and ensemble learning were popular in solving classification problems. In this paper, we applied the previously mentioned and deep learning techniques to hairy scalp images. Hairy scalp problems are usually diagnosed by non-professionals in hair salons, and people with such problems may be advised by these non-professionals. Additionally, several common scalp problems are similar; therefore, non-experts may provide incorrect diagnoses. Hence, scalp problems have worsened. In this work, we implemented and compared the deep-learning method, the ImageNet-VGG-f model Bag of Words (BOW, with machine-learning classifiers, and histogram of oriented gradients (HOG/pyramid histogram of oriented gradients (PHOG with machine-learning classifiers. The tools from the classification learner apps were used for hairy scalp image classification. The results indicated that deep learning can achieve an accuracy of 89.77% when the learning rate is 1 × 10−4, and this accuracy is far higher than those achieved by BOW with SVM (80.50% and PHOG with SVM (53.0%.

  20. Lifeguard Final Exam—Encouraging the Use of Active Learning

    Directory of Open Access Journals (Sweden)

    Elise N. Griswold


    Full Text Available To anyone familiar with the extensive literature on teaching and learning, there is little question that active learning is more effective than passive learning. Thus, we are not directing this letter to that particular audience. Instead, we are attempting to address the question of the best way to convince instructors who have not tried to incorporate elements of active learning into their courses to make such an attempt. There are numerous examples where it becomes immediately clear that active learning is preferable to a lecture/note-taking approach. Here, we provide a question for group discussion that can be used as one such illustration.

  1. Active learning for semi-supervised clustering based on locally linear propagation reconstruction. (United States)

    Chang, Chin-Chun; Lin, Po-Yi


    The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. A Comparison of Professional-Level Faculty and Student Perceptions of Active Learning: Its Current Use, Effectiveness, and Barriers (United States)

    Miller, Cynthia J.; Metz, Michael J.


    Active learning is an instructional method in which students become engaged participants in the classroom through the use of in-class written exercises, games, problem sets, audience-response systems, debates, class discussions, etc. Despite evidence supporting the effectiveness of active learning strategies, minimal adoption of the technique has…

  3. Empathy and feedback processing in active and observational learning. (United States)

    Rak, Natalia; Bellebaum, Christian; Thoma, Patrizia


    The feedback-related negativity (FRN) and the P300 have been related to the processing of one's own and other individuals' feedback during both active and observational learning. The aim of the present study was to elucidate the role of trait-empathic responding with regard to the modulation of the neural correlates of observational learning in particular. Thirty-four healthy participants completed an active and an observational learning task. On both tasks, the participants' aim was to maximize their monetary gain by choosing from two stimuli the one that showed the higher probability of reward. Participants gained insight into the stimulus-reward contingencies according to monetary feedback presented after they had made an active choice or by observing the choices of a virtual partner. Participants showed a general improvement in learning performance on both learning tasks. P200, FRN, and P300 amplitudes were larger during active, as compared with observational, learning. Furthermore, nonreward elicited a significantly more negative FRN than did reward in the active learning task, while only a trend was observed for observational learning. Distinct subcomponents of trait cognitive empathy were related to poorer performance and smaller P300 amplitudes for observational learning only. Taken together, both the learning performance and event-related potentials during observational learning are affected by different aspects of trait cognitive empathy, and certain types of observational learning may actually be disrupted by a higher tendency to understand and adopt other people's perspectives.

  4. Applying effective teaching and learning techniques to nephrology education. (United States)

    Rondon-Berrios, Helbert; Johnston, James R


    The interest in nephrology as a career has declined over the last several years. Some of the reasons cited for this decline include the complexity of the specialty, poor mentoring and inadequate teaching of nephrology from medical school through residency. The purpose of this article is to introduce the reader to advances in the science of adult learning, illustrate best teaching practices in medical education that can be extrapolated to nephrology and introduce the basic teaching methods that can be used on the wards, in clinics and in the classroom.

  5. Involving postgraduate's students in undergraduate small group teaching promotes active learning in both (United States)

    Kalra, Ruchi; Modi, Jyoti Nath; Vyas, Rashmi


    Background: Lecture is a common traditional method for teaching, but it may not stimulate higher order thinking and students may also be hesitant to express and interact. The postgraduate (PG) students are less involved with undergraduate (UG) teaching. Team based small group active learning method can contribute to better learning experience. Aim: To-promote active learning skills among the UG students using small group teaching methods involving PG students as facilitators to impart hands-on supervised training in teaching and managerial skills. Methodology: After Institutional approval under faculty supervision 92 UGs and 8 PGs participated in 6 small group sessions utilizing the jigsaw technique. Feedback was collected from both. Observations: Undergraduate Feedback (Percentage of Students Agreed): Learning in small groups was a good experience as it helped in better understanding of the subject (72%), students explored multiple reading resources (79%), they were actively involved in self-learning (88%), students reported initial apprehension of performance (71%), identified their learning gaps (86%), team enhanced their learning process (71%), informal learning in place of lecture was a welcome change (86%), it improved their communication skills (82%), small group learning can be useful for future self-learning (75%). Postgraduate Feedback: Majority performed facilitation for first time, perceived their performance as good (75%), it was helpful in self-learning (100%), felt confident of managing students in small groups (100%), as facilitator they improved their teaching skills, found it more useful and better identified own learning gaps (87.5%). Conclusions: Learning in small groups adopting team based approach involving both UGs and PGs promoted active learning in both and enhanced the teaching skills of the PGs. PMID:26380201

  6. "PowerPoint[R] Engagement" Techniques to Foster Deep Learning (United States)

    Berk, Ronald A.


    The purpose of this article is to describe a bunch of strategies with which teachers may already be familiar and, perhaps, use regularly, but not always in the context of a formal PowerPoint[R] presentation. Here are the author's top 10 engagement techniques that fit neatly within any version of PowerPoint[R]. Some of these may also be used with…

  7. Integrative Teaching Techniques and Improvement of German Speaking Learning Skills (United States)

    Litualy, Samuel Jusuf


    This research ist a Quasi-Experimental research which only applied to one group without comparison group. It aims to prove whether the implementation of integrative teaching technique has influenced the speaking skill of the students in German Education Study Program of FKIP, Pattimura University. The research was held in the German Education…

  8. The learning technique. Theoretical considerations for planning lessons wit h a strategic learning approach

    Directory of Open Access Journals (Sweden)

    Dania Regueira Martínez


    Full Text Available This article presents the learning task considered as the unit of smaller organization level in the teaching-learning process that conditions in its systemic structuring, the learning actions, for the students acquisition of the content, by means of the development of the reflection and the metacognitiv e regulation when they conscious ly or partially plan different types of learning strategies in the ir realization, with the objective to solv e the pedagogic professional problems that are p resented in the disciplines they receive and in its research task during the direction o f the teaching-learning process.

  9. Do International Students Appreciate Active Learning in Lectures?

    Directory of Open Access Journals (Sweden)

    Mauricio Marrone


    Full Text Available Active learning has been linked with increased student motivation, engagement and understanding of course material. It promotes deep learning, helping to develop critical thinking and writing skills in students. Less well understood, however, are the responses of international students to active learning. Using social constructivist theory, the purpose of this study is to examine domestic and international student perceptions of active learning introduced into large undergraduate Accounting Information Systems lectures. Several active learning strategies were implemented over one semester and examined through the use of semi-structured interviews as well as pre- and post- implementation surveys. Our results suggest broad improvements for international students in student engagement and understanding of unit material when implementing active learning strategies. Other key implications include international student preference for active learning compared with passive learning styles, and that international students may receive greater benefits from active learning strategies than domestic students due to social factors. Based on these findings this paper proposes that educators should seek to implement active learning to better assist and integrate students of diverse backgrounds.

  10. The impact of machine learning techniques in the study of bipolar disorder: A systematic review. (United States)

    Librenza-Garcia, Diego; Kotzian, Bruno Jaskulski; Yang, Jessica; Mwangi, Benson; Cao, Bo; Pereira Lima, Luiza Nunes; Bermudez, Mariane Bagatin; Boeira, Manuela Vianna; Kapczinski, Flávio; Passos, Ives Cavalcante


    Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to January 2017. We found 757 abstracts and included 51 studies in our review. Most of the included studies used multiple levels of biological data to distinguish the diagnosis of bipolar disorder from other psychiatric disorders or healthy controls. We also found studies that assessed the prediction of clinical outcomes and studies using unsupervised machine learning to build more consistent clinical phenotypes of bipolar disorder. We concluded that given the clinical heterogeneity of samples of patients with BD, machine learning techniques may provide clinicians and researchers with important insights in fields such as diagnosis, personalized treatment and prognosis orientation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. The Use of "Socrative" in ESL Classrooms: Towards Active Learning (United States)

    El Shaban, Abir


    The online student response system (SRS) is a technological tool that can be effectively implemented in English language classroom contexts and be used to promote students' active learning. In this qualitative study, "Socrative", a Web 2.0 software, was integrated with active learning activities and used as an SRS to explore English…

  12. Machine Learning Techniques for Prediction of Early Childhood Obesity. (United States)

    Dugan, T M; Mukhopadhyay, S; Carroll, A; Downs, S


    This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. Analyses of six different machine learning methods: RandomTree, RandomForest, J48, ID3, Naïve Bayes, and Bayes trained on CHICA data show that an accurate, sensitive model can be created. Of the methods analyzed, the ID3 model trained on the CHICA dataset proved the best overall performance with accuracy of 85% and sensitivity of 89%. Additionally, the ID3 model had a positive predictive value of 84% and a negative predictive value of 88%. The structure of the tree also gives insight into the strongest predictors of future obesity in children. Many of the strongest predictors seen in the ID3 modeling of the CHICA dataset have been independently validated in the literature as correlated with obesity, thereby supporting the validity of the model. This study demonstrated that data from a production clinical decision support system can be used to build an accurate machine learning model to predict obesity in children after age two.

  13. Is engagement with a purpose the essence of active learning?


    Álvarez Mesa, Mauricio


    In the 2009 edition of the conference on “Active Learning in Engineering Education”, there were several and fruitful discussions within a small workgroup about the essence of active learning. At the end we came with an attempt to sum up our whole discussion with one question. Our question is the same as the title of this essay. Taking this question as a starting point this article propose a specific purpose from which active learning can be based. Peer Reviewed

  14. Generation of Tutorial Dialogues: Discourse Strategies for Active Learning (United States)


    AND SUBTITLE Generation of Tutorial Dialogues: Discourse Strategies for active Learning AUTHORS Dr. Martha Evens 7. PERFORMING ORGANI2ATION NAME...time the student starts in on a new topic. Michael and Rovick constantly attempt to promote active learning . They regularly use hints and only resort...Controlling active learning : How tutors decide when to generate hints. Proceedings of FLAIRS 󈨣. Melbourne Beach, FL. 157-161. Hume, G., Michael

  15. The application of machine learning techniques in the clinical drug therapy. (United States)

    Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan


    The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at

  16. Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks (United States)

    Zhang, Huibin; Wang, Yuqiao; Chen, Haoran; Zhao, Yongli; Zhang, Jie


    In software defined optical networks (SDON), the centralized control plane may encounter numerous intrusion threatens which compromise the security level of provisioned services. In this paper, the issue of control plane security is studied and two machine-learning-based control plane intrusion detection techniques are proposed for SDON with properly selected features such as bandwidth, route length, etc. We validate the feasibility and efficiency of the proposed techniques by simulations. Results show an accuracy of 83% for intrusion detection can be achieved with the proposed machine-learning-based control plane intrusion detection techniques.

  17. Practical applications of activation analysis and other nuclear techniques

    International Nuclear Information System (INIS)

    Lyon, W.S.


    Neeutron activation analysis (NAA) is a versatile, sensitive multielement, usually nondestructive analytical technique used to determine elemental concentrations in a variety of materials. Samples are irradiated with neutrons in a nuclear reactor, removed, and for the nondestructive technique, the induced radioactivity measured. This measurement of γ rays emitted from specific radionuclides makes possible the quantitative determination of elements present. The method is described, advantages and disadvantages listed and a number of examples of its use given. Two other nuclear methods, particle induced x-ray emission and synchrotron produced x-ray fluorescence are also briefly discussed

  18. An investigation of tungsten by neutron activation techniques

    International Nuclear Information System (INIS)

    Svetsreni, R.


    This investigation used neutron from Plutonium-Beryllium source (5 curie) to analyse the amount of tungsten in tungsten oxide which was extracted from tungsten ores, slag and tungsten alloy of tungsten iron and carbon. The technique of neutron activation analysis with NaI(Tl) gamma detector 3'' x 3'' and 1024 multichannel analyzer. The dilution technique was used by mixing Fe 2 O 3 or pure sand into the sample before irradiation. In this study self shielding effect in the analysis of tungsten was solved and the detection limit of the tungsten in the sample was about 0.5%

  19. Performance in Physiology Evaluation: Possible Improvement by Active Learning Strategies (United States)

    Montrezor, Luís H.


    The evaluation process is complex and extremely important in the teaching/learning process. Evaluations are constantly employed in the classroom to assist students in the learning process and to help teachers improve the teaching process. The use of active methodologies encourages students to participate in the learning process, encourages…

  20. Teacher Feedback during Active Learning: Current Practices in Primary Schools (United States)

    van den Bergh, Linda; Ros, Anje; Beijaard, Douwe


    Background: Feedback is one of the most powerful tools, which teachers can use to enhance student learning. It appears dif?cult for teachers to give qualitatively good feedback, especially during active learning. In this context, teachers should provide facilitative feedback that is focused on the development of meta-cognition and social learning.…

  1. Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques. (United States)

    Cook, Diane J; Schmitter-Edgecombe, Maureen; Dawadi, Prafulla


    One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study, we use smart home and wearable sensors to collect data, while ( n = 84) older adults perform complex activities of daily living. We analyze the data using machine learning techniques and reveal that differences between healthy older adults and adults with Parkinson disease not only exist in their activity patterns, but that these differences can be automatically recognized. Our machine learning classifiers reach an accuracy of 0.97 with an area under the ROC curve value of 0.97 in distinguishing these groups. Our permutation-based testing confirms that the sensor-based differences between these groups are statistically significant.

  2. Assessing Student Behaviors and Motivation for Actively Learning Biology (United States)

    Moore, Michael Edward

    Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is why active learning is such an effective instructional tool and the limits of this instructional method’s ability to influence performance. This dissertation builds a case in three steps for why active learning is an effective instructional tool. In step one, I assessed the influence of different types of active learning (clickers, group activities, and whole class discussions) on student engagement behavior in one semester of two different introductory biology courses and found that active learning positively influenced student engagement behavior significantly more than lecture. For step two, I examined over four semesters whether student engagement behavior was a predictor of performance and found participation (engagement behavior) in the online (video watching) and in-class course activities (clicker participation) that I measure were significant predictors of performance. In the third, I assessed whether certain active learning satisfied the psychological needs that lead to students’ intrinsic motivation to participate in those activities when compared over two semesters and across two different institutions of higher learning. Findings from this last step show us that student’s perceptions of autonomy, competency, and relatedness in doing various types of active learning are significantly higher than lecture and consistent across two institutions of higher learning. Lastly, I tie everything together, discuss implications of the research, and address future directions for research on biology student motivation and behavior.

  3. Sentiment Analysis in Geo Social Streams by using Machine Learning Techniques


    Twanabasu, Bikesh


    Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi: SIW013. Curs acadèmic 2017-2018 Massive amounts of sentiment rich data are generated on social media in the form of Tweets, status updates, blog post, reviews, etc. Different people and organizations are using these user generated content for decision making. Symbolic techniques or Knowledge base approaches and Machine learning techniques are two main techniques used for analysis sentiment...

  4. Pedagogical Distance: Explaining Misalignment in Student-Driven Online Learning Activities Using Activity Theory (United States)

    Westberry, Nicola; Franken, Margaret


    This paper provides an Activity Theory analysis of two online student-driven interactive learning activities to interrogate assumptions that such groups can effectively learn in the absence of the teacher. Such an analysis conceptualises learning tasks as constructed objects that drive pedagogical activity. The analysis shows a disconnect between…

  5. An Innovative Teaching Method To Promote Active Learning: Team-Based Learning (United States)

    Balasubramanian, R.


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

  6. Root activity evaluation in tree crops using isotopic techniques

    International Nuclear Information System (INIS)

    Calvache, Marcelo


    This paper discusses the methdology used to evalute root activity of the crops utilizing the technique of soil injection with solutions marked with isotopes. Some of the experimental data obtained with coffee, citrus and oil palm are also presented. Ovel all, these tree crops present a higher root activity in soil layers close to the surface (0-20 cm) and to a distance from the trunk which varies with age, season and variety. The most important conclusions are: 1. The isotope injection technique using 3 2 P , 1 5 N , or 8 5 R b, allow direct and reliable determination of root activity in these tree crops. 2. Root activity of three crops depends on age of the tree, variety, moisture content of the soil and soil type. 3. Soil moisture is the most influencial factor affecting root activity. This is turn depends on the irrigation method employed. 4. From the practical view point, the best distance from the trunk to apply fertilizer in the one wich has highest root activity closest to the soil surface

  7. Active neutron technique for detecting attempted special nuclear material diversion

    International Nuclear Information System (INIS)

    Smith, G.W.; Rice, L.G. III.


    The identification of special nuclear material (SNM) diversion is necessary if SNM inventory control is to be maintained at nuclear facilities. (Special nuclear materials are defined for this purpose as either 235 U of 239 Pu.) Direct SNM identification by the detection of natural decay or fission radiation is inadequate if the SNM is concealed by appropriate shielding. The active neutron interrogation technique described combines direct SNM identification by delayed fission neutron (DFN) detection with implied SNM detection by the identification of materials capable of shielding SNM from direct detection. This technique is being developed for application in an unattended material/equipment portal through which items such as electronic instruments, packages, tool boxes, etc., will pass. The volume of this portal will be 41-cm wide, 53-cm high and 76-cm deep. The objective of this technique is to identify an attempted diversion of at least 20 grams of SNM with a measurement time of 30 seconds

  8. Sharing the learning activity using intelligent CAD

    DEFF Research Database (Denmark)

    Duffy, S. M.; Duffy, Alex


    In this paper the need for Intelligent Computer Aided Design (Int.CAD) to jointly support design and learning assistance is introduced. The paper focuses on presenting and exploring the possibility of realizing ''learning'' assistance in Int.CAD by introducing a new concept called Shared Learning...

  9. The control of tonic pain by active relief learning. (United States)

    Zhang, Suyi; Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W; Seymour, Ben


    Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. © 2018, Zhang et al.

  10. The control of tonic pain by active relief learning (United States)

    Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W


    Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty (‘associability’) signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. PMID:29482716

  11. Administrator skills: a study with academics of the administration course in the context of active learning

    Directory of Open Access Journals (Sweden)

    Sabrina Gorges


    Full Text Available The constant oscillations in society and the labor market require the management professional to evolve and develop their competencies, organizations are looking for people who are capable and flexible, who adapt quickly to changes. In this way, developing competencies has become paramount in the learning process, and higher education institutions play an important role in this construction, applying learning strategies that provide the academic with the competencies demanded by the market. Thus, it is feasible to use active learning in the Administration course, since it allows the integration between theory and practice and the experience of real situations in the classroom. Active learning is a set of pedagogical practices that address the issue of student learning from a different perspective of the classic learning techniques. In active learning, it is understood that the student should not be merely a receiver of information, but must actively engage in the acquisition of knowledge. This article aims to identify and analyze the skills of the Administrator desired and developed by the undergraduate students in Administration in the context of Active Learning. In this study, a descriptive research was carried out in a sample of 54 students from the Administration courses of three universities in Santa Catarina. Among the results, the research revealed that for students, the most important competences to be developed are: self-criticism and strategic thinking regarding opportunities.

  12. Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction


    Lopes, Manuel; Montesano, Luis


    In this survey we present different approaches that allow an intelligent agent to explore autonomous its environment to gather information and learn multiple tasks. Different communities proposed different solutions, that are in many cases, similar and/or complementary. These solutions include active learning, exploration/exploitation, online-learning and social learning. The common aspect of all these approaches is that it is the agent to selects and decides what information to gather next. ...

  13. Use of the Learning together technique associated to the theory of significative learning

    Directory of Open Access Journals (Sweden)

    Ester López Donoso


    Full Text Available This article deals with an experimental research, regarding a qualitative and quantitative design, applied to a group of students of General Physics course during the first semester of the university career of Engineering. Historically, students of this course present learning difficulties that directly affect their performance, conceptualization and permanence in the university. The present methodology integrates the collaborative learning, denominated Learning Together", with the theory of significant learning to avoid the above-written difficulties. Results of this research show that the proposed methodology works properly, especially to improve the conceptualization.

  14. Classification of Phishing Email Using Random Forest Machine Learning Technique


    Akinyelu, Andronicus A.; Adewumi, Aderemi O.


    Phishing is one of the major challenges faced by the world of e-commerce today. Thanks to phishing attacks, billions of dollars have been lost by many companies and individuals. In 2012, an online report put the loss due to phishing attack at about $1.5 billion. This global impact of phishing attacks will continue to be on the increase and thus requires more efficient phishing detection techniques to curb the menace. This paper investigates and reports the use of random forest machine learnin...

  15. Two-phase flow measurement by pulsed neutron activation techniques

    International Nuclear Information System (INIS)

    Kehler, P.


    The Pulsed Neutron Activation (PNA) technique for measuring the mass flow velocity and the average density of two-phase mixtures is described. PNA equipment can be easily installed at different loops, and PNA techniques are non-intrusive and independent of flow regimes. These features of the PNA technique make it suitable for in-situ measurement of two-phase flows, and for calibration of more conventional two-phase flow measurement devices. Analytic relations governing the various PNA methods are derived. The equipment and procedures used in the first air-water flow measurement by PNA techniques are discussed, and recommendations are made for improvement of future tests. In the present test, the mass flow velocity was determined with an accuracy of 2 percent, and average densities were measured down to 0.08 g/cm 3 with an accuracy of 0.04 g/cm 3 . Both the accuracy of the mass flow velocity measurement and the lower limit of the density measurement are functions of the injected activity and of the total number of counts. By using a stronger neutron source and a larger number of detectors, the measurable density can be decreased by a factor of 12 to .007 g/cm 3 for 12.5 cm pipes, and to even lower ranges for larger pipes

  16. Some problems of calibration technique in charged particle activation analysis

    International Nuclear Information System (INIS)

    Krasnov, N.N.; Zatolokin, B.V.; Konstantinov, I.O.


    It is shown that three different approaches to calibration technique based on the use of average cross-section, equivalent target thickness and thick target yield are adequate. Using the concept of thick target yield, a convenient charged particle activation equation is obtained. The possibility of simultaneous determination of two impurities, from which the same isotope is formed, is pointed out. The use of the concept of thick target yield facilitates the derivation of a simple formula for an absolute and comparative methods of analysis. The methodical error does not exceed 10%. Calibration technique and determination of expected sensitivity based on the thick target yield concept is also very convenient because experimental determination of thick target yield values is a much simpler procedure than getting activation curve or excitation function. (T.G.)

  17. Subliminal Cues While Teaching: HCI Technique for Enhanced Learning

    Directory of Open Access Journals (Sweden)

    Pierre Chalfoun


    Full Text Available This paper presents results from an empirical study conducted with a subliminal teaching technique aimed at enhancing learner's performance in Intelligent Systems through the use of physiological sensors. This technique uses carefully designed subliminal cues (positive and miscues (negative and projects them under the learner's perceptual visual threshold. A positive cue, called answer cue, is a hint aiming to enhance the learner's inductive reasoning abilities and projected in a way to help them figure out the solution faster but more importantly better. A negative cue, called miscue, is also used and aims at obviously at the opposite (distract the learner or lead them to the wrong conclusion. The latest obtained results showed that only subliminal cues, not miscues, could significantly increase learner performance and intuition in a logic-based problem-solving task. Nonintrusive physiological sensors (EEG for recording brainwaves, blood volume pressure to compute heart rate and skin response to record skin conductivity were used to record affective and cerebral responses throughout the experiment. The descriptive analysis, combined with the physiological data, provides compelling evidence for the positive impact of answer cues on reasoning and intuitive decision making in a logic-based problem-solving paradigm.

  18. Fusion alpha loss diagnostic for ITER using activation technique

    Czech Academy of Sciences Publication Activity Database

    Bonheure, G.; Hult, M.; González de Orduña, R.; Vermaercke, P.; Murari, A.; Popovichev, S.; Mlynář, Jan


    Roč. 86, 6-8 (2011), s. 1298-1301 ISSN 0920-3796. [Symposium on Fusion Technology (SOFT) /26th./. Port o, 27.09.2010-01.10.2010] Institutional research plan: CEZ:AV0Z20430508 Keywords : ITER * fusion product * burning plasma diagnostics * alpha losses * activation technique Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 1.490, year: 2011

  19. Active learning: a step towards automating medical concept extraction. (United States)

    Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony


    This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robustness of incremental active learning framework across different selection criteria and data sets are determined. The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional random fields as the supervised method, and least confidence and information density as 2 selection criteria for active learning framework were used. The effect of incremental learning vs standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. The following 2 clinical data sets were used for evaluation: the Informatics for Integrating Biology and the Bedside/Veteran Affairs (i2b2/VA) 2010 natural language processing challenge and the Shared Annotated Resources/Conference and Labs of the Evaluation Forum (ShARe/CLEF) 2013 eHealth Evaluation Lab. The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared with the random sampling baseline, the saving is at least doubled. Incremental active learning is a promising approach for building effective and robust medical concept extraction models while significantly reducing the burden of manual annotation. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email:

  20. Enhancing students' learning in problem based learning: validation of a self-assessment scale for active learning and critical thinking

    NARCIS (Netherlands)

    Khoiriyah, U.; Roberts, C.; Jorm, C.; Vleuten, C.P. van der


    BACKGROUND: Problem based learning (PBL) is a powerful learning activity but fidelity to intended models may slip and student engagement wane, negatively impacting learning processes, and outcomes. One potential solution to solve this degradation is by encouraging self-assessment in the PBL

  1. Group-Based Active Learning of Classification Models. (United States)

    Luo, Zhipeng; Hauskrecht, Milos


    Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

  2. Application of Learning Engineering Techniques Thinking Aloud Pair Problem Solving in Learning Mathematics Students Class VII SMPN 15 Padang (United States)

    Widuri, S. Y. S.; Almash, L.; Zuzano, F.


    The students activity and responsible in studying mathematic is still lack. It gives an effect for the bad result in studying mathematic. There is one of learning technic to increase students activity in the classroom and the result of studying mathematic with applying a learning technic. It is “Thinking Aloud Pair Problem Solving (TAPPS)”. The purpose of this research is to recognize the developing of students activity in mathematic subject during applying that technic “TAPPS” in seven grade at SMPN 15 Padang and compare the students proportion in learning mathematic with TAPPS between learning process without it in seven grade at SMPN 15 Padang. Students activity for indicators 1, 2, 3, 4, 5, 6 at each meeting is likely to increase and students activity for indicator 7 at each meeting is likely to decrease. The finding of this research is χ 2 = 9,42 and the value of p is 0,0005 < p < 0,005. Therefore p < 0,05 has means H 0 was rejected and H 1 was accepted. Thus, it was concluded that the activities and result in studying mathematic increased after applying learning technic the TAPPS.

  3. Assessing the Effectiveness of Inquiry-based Learning Techniques Implemented in Large Classroom Settings (United States)

    Steer, D. N.; McConnell, D. A.; Owens, K.


    assessments of knowledge-level learning included evaluations of student responses to pre- and post-instruction conceptual test questions, short group exercises and content-oriented exam questions. Higher level thinking skills were assessed when students completed exercises that required the completion of Venn diagrams, concept maps and/or evaluation rubrics both during class periods and on exams. Initial results indicate that these techniques improved student attendance significantly and improved overall retention in the course by 8-14% over traditional lecture formats. Student scores on multiple choice exam questions were slightly higher (1-3%) for students taught in the active learning environment and short answer questions showed larger gains (7%) over students' scores in a more traditional class structure.

  4. Sculpting with people – An experiential learning technique

    DEFF Research Database (Denmark)

    Andersen, Helle Elisabeth; Larsen, Kirsten Vendelbo


    At Department of Nursing, University College Lillebaelt in Denmark we use an experiential technique called sculpting in our simulation program. Sculpting is a kind of non-verbal role play in which participants are given a certain character and create a 'sculpture' by arranging family members......, social circles and professionals in ways which reflect the quality of the relationships of the people involved. The aim of this study is to further describe the sculpting exercise and present a small scale evaluation study using a qualitative descriptive design. An evaluation sheet was formulated...... by the authors and filled out by 114 Danish third-year nursing students. The results show that sculpting is experienced as emotionally demanding, but in a good way. It is experienced as an eye-opener that helps to identify the possible complex and emotional dynamics in a family experiencing critical illness...

  5. Collegewide Promotion of E-Learning/Active Learning and Faculty Development (United States)

    Ogawa, Nobuyuki; Shimizu, Akira


    Japanese National Institutes of Technology have revealed a plan to strongly promote e-Learning and active learning under the common schematization of education in over 50 campuses nationwide. Our e-Learning and ICT-driven education practiced for more than fifteen years were highly evaluated, and is playing a leading role in promoting e-Learning…


    Directory of Open Access Journals (Sweden)

    Meike Imelda Wachyu


    Full Text Available This study is aimed at finding out the impacts of the use of Know-Want-Learn technique in improving the reading comprehension to teach analytical exposition among eleventh grade students of SMA N 2 Indramayu in the academic year of 2017/2018. The study was action research in two research cycles. In the study, the researcher collaborated with the English teachers and the students. The data of this study were qualitative in nature supported by quantitative data. Qualitative data were obtained from the results of classroom observation and collaborators‘ discussion. Quantitative data were obtained from pre-test and post test results. The instruments for collecting the data were observation guides, interview guides, and the pre-test and posttest. The data were in the form of field notes, interview transcripts, and the scores of the students‘ pre-test and posttest. The results of the two cycles show that the use of Know-WantLearn technique is effective to improve the students‘ reading comprehension. It is supported by the qualitative data which show that (1 Know-Want-Learn technique can help the teacher to scaffold the students‘ comprehension of the text by focusing on the steps before, during, and after reading; (2 Know-Want-Learn technique can help the students to preview the text, assess what they have learned after reading, and motivate their interest in reading; (3 The kind of activities given such as preeteaching vocabulary, using skimming and scanning, using fix-up strategies, and guessing meaning can help the students to read the text efficiently.

  7. Examining factors affecting beginning teachers' transfer of learning of ICT-enhanced learning activities in their teaching practice

    NARCIS (Netherlands)

    Agyei, D.D.; Voogt, J.


    This study examined 100 beginning teachers’ transfer of learning when utilising Information Communication Technology-enhanced activity-based learning activities. The beginning teachers had participated in a professional development program that was characterised by ‘learning technology by

  8. Applying machine learning techniques for forecasting flexibility of virtual power plants

    DEFF Research Database (Denmark)

    MacDougall, Pamela; Kosek, Anna Magdalena; Bindner, Henrik W.


    network as well as the multi-variant linear regression. It is found that it is possible to estimate the longevity of flexibility with machine learning. The linear regression algorithm is, on average, able to estimate the longevity with a 15% error. However, there was a significant improvement with the ANN...... approach to investigating the longevity of aggregated response of a virtual power plant using historic bidding and aggregated behaviour with machine learning techniques. The two supervised machine learning techniques investigated and compared in this paper are, multivariate linear regression and single...... algorithm achieving, on average, a 5.3% error. This is lowered 2.4% when learning for the same virtual power plant. With this information it would be possible to accurately offer residential VPP flexibility for market operations to safely avoid causing further imbalances and financial penalties....

  9. An experimental result of estimating an application volume by machine learning techniques. (United States)

    Hasegawa, Tatsuhito; Koshino, Makoto; Kimura, Haruhiko


    In this study, we improved the usability of smartphones by automating a user's operations. We developed an intelligent system using machine learning techniques that periodically detects a user's context on a smartphone. We selected the Android operating system because it has the largest market share and highest flexibility of its development environment. In this paper, we describe an application that automatically adjusts application volume. Adjusting the volume can be easily forgotten because users need to push the volume buttons to alter the volume depending on the given situation. Therefore, we developed an application that automatically adjusts the volume based on learned user settings. Application volume can be set differently from ringtone volume on Android devices, and these volume settings are associated with each specific application including games. Our application records a user's location, the volume setting, the foreground application name and other such attributes as learning data, thereby estimating whether the volume should be adjusted using machine learning techniques via Weka.

  10. Orchestration Framework for Learning Activities in Augmented Reality Environments


    Ibáñez, María Blanca; Delgado Kloos, Carlos; Di Serio, Angela


    Proceedings of: Across Spaces11 Workshop in conjunction with the EC-TEL2011, Palermo, Italy, September 21, 2011 In this paper we show how Augmented Reality (AR) technology restricted to the use of mobiles or PCs, can be used to develop learning activities with the minimun level of orchestation required by meaningful learning sequences. We use Popcode as programming language to deploy orchestrated learning activities specified with an AR framework. Publicado

  11. Learning mediastinoscopy: the need for education, experience and modern techniques--interdependency of the applied technique and surgeon's training level. (United States)

    Walles, Thorsten; Friedel, Godehard; Stegherr, Tobias; Steger, Volker


    Mediastinoscopy represents the gold standard for invasive mediastinal staging. While learning and teaching the surgical technique are challenging due to the limited accessibility of the operation field, both benefited from the implementation of video-assisted techniques. However, it has not been established yet whether video-assisted mediastinoscopy improves the mediastinal staging in itself. Retrospective single-centre cohort analysis of 657 mediastinoscopies performed at a specialized tertiary care thoracic surgery unit from 1994 to 2006. The number of specimens obtained per procedure and per lymph node station (2, 4, 7, 8 for mediastinoscopy and 2-9 for open lymphadenectomy), the number of lymph node stations examined, sensitivity and negative predictive value with a focus on the technique employed (video-assisted vs standard technique) and the surgeon's experience were calculated. Overall sensitivity was 60%, accuracy was 90% and negative predictive value 88%. With the conventional technique, experience alone improved sensitivity from 49 to 57% and it was predominant at the paratracheal right region (from 62 to 82%). But with the video-assisted technique, experienced surgeons rose sensitivity from 57 to 79% in contrast to inexperienced surgeons who lowered sensitivity from 49 to 33%. We found significant differences concerning (i) the total number of specimens taken, (ii) the amount of lymph node stations examined, (iii) the number of specimens taken per lymph node station and (iv) true positive mediastinoscopies. The video-assisted technique can significantly improve the results of mediastinoscopy. A thorough education on the modern video-assisted technique is mandatory for thoracic surgeons until they can fully exhaust its potential.

  12. Incorporating Service-Learning, Technology, and Research Supportive Teaching Techniques into the University Chemistry Classroom (United States)

    Saitta, E. K. H.; Bowdon, M. A.; Geiger, C. L.


    Technology was integrated into service-learning activities to create an interactive teaching method for undergraduate students at a large research institution. Chemistry students at the University of Central Florida partnered with high school students at Crooms Academy of Information Technology in interactive service learning projects. The…

  13. Teaching for Engagement: Part 3: Designing for Active Learning (United States)

    Hunter, William J.


    In the first two parts of this series, ("Teaching for Engagement: Part 1: Constructivist Principles, Case-Based Teaching, and Active Learning") and ("Teaching for Engagement: Part 2: Technology in the Service of Active Learning"), William J. Hunter sought to outline the theoretical rationale and research basis for such active…

  14. Engaging Students in Large Health Classes with Active Learning Strategies (United States)

    Elliott, Steven; Combs, Sue; Huelskamp, Amelia; Hritz, Nancy


    Creative K-12 health teachers can engage students in large classes by utilizing active learning strategies. Active learning involves engaging students in higher-order tasks, such as analysis and synthesis, which is a crucial element of the movement toward what is commonly called "learner-centered" teaching. Health education teachers who…

  15. Introducing E-Learning in a Norwegian Service Company with Participatory Design and Evolutionary Prototyping Techniques


    Mørch , Anders I.; Engen , Bård Ketil; Hansen Åsand , Hege-René; Brynhildsen , Camilla; Tødenes , Ida


    Over a 2-year period, we have participated in the introduction of e-learning in a Norwegian service company, a gas station division of an oil company. This company has an advanced computer network infrastructure for communication and information sharing, but the primary task of the employees is serving customers. We identify some challenges to introducing e-learning in this kind of environment. A primary emphasis has been on using participatory design techniques during the planning stages and...

  16. A framework for detection of malicious software in Android handheld systems using machine learning techniques


    Torregrosa García, Blas


    The present study aims at designing and developing new approaches to detect malicious applications in Android-based devices. More precisely, MaLDroide (Machine Learning-based Detector for Android malware), a framework for detection of Android malware based on machine learning techniques, is introduced here. It is devised to identify malicious applications. Este trabajo tiene como objetivo el diseño y el desarrollo de nuevas formas de detección de aplicaciones maliciosas en los dispositivos...

  17. A Comprehensive Review and meta-analysis on Applications of Machine Learning Techniques in Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Manojit Chattopadhyay


    Full Text Available Securing a machine from various cyber-attacks has been of serious concern for researchers, statutory bodies such as governments, business organizations and users in both wired and wireless media. However, during the last decade, the amount of data handling by any device, particularly servers, has increased exponentially and hence the security of these devices has become a matter of utmost concern. This paper attempts to examine the challenges in the application of machine learning techniques to intrusion detection. We review different inherent issues in defining and applying the machine learning techniques to intrusion detection. We also attempt to identify the best technological solution for changing usage pattern by comparing different machine learning techniques on different datasets and summarizing their performance using various performance metrics. This paper highlights the research challenges and future trends of intrusion detection in dynamic scenarios of intrusion detection problems in diverse network technologies.

  18. Challenges Encountered in Creating Personalised Learning Activities to Suit Students Learning Preferences


    O'Donnell, Eileen; Wade, Vincent; Sharp, Mary; O'Donnell, Liam


    This book chapter reviews some of the challenges encountered by educators in creating personalised e-learning activities to suit students learning preferences. Technology-enhanced learning (TEL) alternatively known as e-learning has not yet reached its full potential in higher education. There are still many potential uses as yet undiscovered and other discovered uses which are not yet realisable by many educators. TEL is still predominantly used for e-dissemination and e-administration. This...


    Directory of Open Access Journals (Sweden)

    R. Priya


    Full Text Available Diabetic retinopathy (DR is an eye disease caused by the complication of diabetes and we should detect it early for effective treatment. As diabetes progresses, the vision of a patient may start to deteriorate and lead to diabetic retinopathy. As a result, two groups were identified, namely non-proliferative diabetic retinopathy (NPDR and proliferative diabetic retinopathy (PDR. In this paper, to diagnose diabetic retinopathy, three models like Probabilistic Neural network (PNN, Bayesian Classification and Support vector machine (SVM are described and their performances are compared. The amount of the disease spread in the retina can be identified by extracting the features of the retina. The features like blood vessels, haemmoraghes of NPDR image and exudates of PDR image are extracted from the raw images using the image processing techniques and fed to the classifier for classification. A total of 350 fundus images were used, out of which 100 were used for training and 250 images were used for testing. Experimental results show that PNN has an accuracy of 89.6 % Bayes Classifier has an accuracy of 94.4% and SVM has an accuracy of 97.6%. This infers that the SVM model outperforms all other models. Also our system is also run on 130 images available from “DIARETDB0: Evaluation Database and Methodology for Diabetic Retinopathy” and the results show that PNN has an accuracy of 87.69% Bayes Classifier has an accuracy of 90.76% and SVM has an accuracy of 95.38%.

  20. Considerations for Task Analysis Methods and Rapid E-Learning Development Techniques

    Directory of Open Access Journals (Sweden)

    Dr. Ismail Ipek


    Full Text Available The purpose of this paper is to provide basic dimensions for rapid training development in e-learning courses in education and business. Principally, it starts with defining task analysis and how to select tasks for analysis and task analysis methods for instructional design. To do this, first, learning and instructional technologies as visions of the future were discussed. Second, the importance of task analysis methods in rapid e-learning was considered, with learning technologies as asynchronous and synchronous e-learning development. Finally, rapid instructional design concepts and e-learning design strategies were defined and clarified with examples, that is, all steps for effective task analysis and rapid training development techniques based on learning and instructional design approaches were discussed, such as m-learning and other delivery systems. As a result, the concept of task analysis, rapid e-learning development strategies and the essentials of online course design were discussed, alongside learner interface design features for learners and designers.

  1. Active learning for noisy oracle via density power divergence. (United States)

    Sogawa, Yasuhiro; Ueno, Tsuyoshi; Kawahara, Yoshinobu; Washio, Takashi


    The accuracy of active learning is critically influenced by the existence of noisy labels given by a noisy oracle. In this paper, we propose a novel pool-based active learning framework through robust measures based on density power divergence. By minimizing density power divergence, such as β-divergence and γ-divergence, one can estimate the model accurately even under the existence of noisy labels within data. Accordingly, we develop query selecting measures for pool-based active learning using these divergences. In addition, we propose an evaluation scheme for these measures based on asymptotic statistical analyses, which enables us to perform active learning by evaluating an estimation error directly. Experiments with benchmark datasets and real-world image datasets show that our active learning scheme performs better than several baseline methods. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Development of active learning modules in pharmacology for small group teaching. (United States)

    Tripathi, Raakhi K; Sarkate, Pankaj V; Jalgaonkar, Sharmila V; Rege, Nirmala N


    Current teaching in pharmacology in undergraduate medical curriculum in India is primarily drug centered and stresses imparting factual knowledge rather than on pharmacotherapeutic skills. These skills would be better developed through active learning by the students. Hence modules that will encourage active learning were developed and compared with traditional methods within the Seth GS Medical College, Mumbai. After Institutional Review Board approval, 90 second year undergraduate medical students who consented were randomized into six sub-groups, each with 15 students. Pre-test was administered. The three sub-groups were taught a topic using active learning modules (active learning groups), which included problems on case scenarios, critical appraisal of prescriptions and drug identification. The remaining three sub-groups were taught the same topic in a conventional tutorial mode (tutorial learning groups). There was crossover for the second topic. Performance was assessed using post-test. Questionnaires with Likert-scaled items were used to assess feedback on teaching technique, student interaction and group dynamics. The active and tutorial learning groups differed significantly in their post-test scores (11.3 ± 1.9 and 15.9 ± 2.7, respectively, P active learning session as interactive (vs. 37/90 students in tutorial group) and enhanced their understanding vs. 56/90 in tutorial group), aroused intellectual curiosity (47/90 students of active learning group vs. 30/90 in tutorial group) and provoked self-learning (41/90 active learning group vs. 14/90 in tutorial group). Sixty-four students in the active learning group felt that questioning each other helped in understanding the topic, which was the experience of 25/90 students in tutorial group. Nevertheless, students (55/90) preferred tutorial mode of learning to help them score better in their examinations. In this study, students preferred an active learning environment, though to pass examinations, they

  3. Activities at Forschungszentrum Juelich in Safeguards Analytical Techniques and Measurements

    International Nuclear Information System (INIS)

    Duerr, M.; Knott, A.; Middendorp, R.; Niemeyer, I.; Kueppers, S.; Zoriy, M.; Froning, M.; Bosbach, D.


    The application of safeguards by the IAEA involves analytical measurements of samples taken during inspections. The development and advancement of analytical techniques with support from the Member States contributes to strengthened and more efficient verification of compliance with non-proliferation obligations. Since recently, a cooperation agreement has been established between Forschungszentrum Juelich and the IAEA in the field of analytical services. The current working areas of Forschungszentrum Juelich are: (i) Production of synthetic micro-particles as calibration standard and reference material for particle analysis, (ii) qualification of the Forschungszentrum Juelich as a member of the IAEA network of analytical laboratories for safeguards (NWAL), and (iii) analysis of impurities in nuclear material samples. With respect to the synthesis of particles, a dedicated setup for the production of uranium particles is being developed, which addresses the urgent need for material tailored for its use in quality assurance and quality control measures for particle analysis of environmental swipe samples. Furthermore, Forschungszentrum Juelich has been nominated as a candidate laboratory for membership in the NWAL network. To this end, analytical capabilities at Forschungszentrum Juelich have been joined to form an analytical service within a dedicated quality management system. Another activity is the establishment of analytical techniques for impurity analysis of uranium-oxide, mainly focusing on inductively coupled mass spectrometry. This contribution will present the activities at Forschungszentrum Juelich in the area of analytical measurements and techniques for nuclear verification. (author)

  4. Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques. (United States)

    Uhlig, Johannes; Uhlig, Annemarie; Kunze, Meike; Beissbarth, Tim; Fischer, Uwe; Lotz, Joachim; Wienbeck, Susanne


    The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers. Five machine learning techniques, including random forests, back propagation neural networks (BPN), extreme learning machines, support vector machines, and K-nearest neighbors, were used to train diagnostic models on a clinical breast CBCT dataset with internal validation by repeated 10-fold cross-validation. Two independent blinded human readers with profound experience in breast imaging and breast CBCT analyzed the same CBCT dataset. Diagnostic performance was compared using AUC, sensitivity, and specificity. The clinical dataset comprised 35 patients (American College of Radiology density type C and D breasts) with 81 suspicious breast lesions examined with contrast-enhanced breast CBCT. Forty-five lesions were histopathologically proven to be malignant. Among the machine learning techniques, BPNs provided the best diagnostic performance, with AUC of 0.91, sensitivity of 0.85, and specificity of 0.82. The diagnostic performance of the human readers was AUC of 0.84, sensitivity of 0.89, and specificity of 0.72 for reader 1 and AUC of 0.72, sensitivity of 0.71, and specificity of 0.67 for reader 2. AUC was significantly higher for BPN when compared with both reader 1 (p = 0.01) and reader 2 (p Machine learning techniques provide a high and robust diagnostic performance in the prediction of malignancy in breast lesions identified at CBCT. BPNs showed the best diagnostic performance, surpassing human readers in terms of AUC and specificity.

  5. Minimal-Learning-Parameter Technique Based Adaptive Neural Sliding Mode Control of MEMS Gyroscope

    Directory of Open Access Journals (Sweden)

    Bin Xu


    Full Text Available This paper investigates an adaptive neural sliding mode controller for MEMS gyroscopes with minimal-learning-parameter technique. Considering the system uncertainty in dynamics, neural network is employed for approximation. Minimal-learning-parameter technique is constructed to decrease the number of update parameters, and in this way the computation burden is greatly reduced. Sliding mode control is designed to cancel the effect of time-varying disturbance. The closed-loop stability analysis is established via Lyapunov approach. Simulation results are presented to demonstrate the effectiveness of the method.

  6. Active Inference and Learning in the Cerebellum. (United States)

    Friston, Karl; Herreros, Ivan


    This letter offers a computational account of Pavlovian conditioning in the cerebellum based on active inference and predictive coding. Using eyeblink conditioning as a canonical paradigm, we formulate a minimal generative model that can account for spontaneous blinking, startle responses, and (delay or trace) conditioning. We then establish the face validity of the model using simulated responses to unconditioned and conditioned stimuli to reproduce the sorts of behavior that are observed empirically. The scheme's anatomical validity is then addressed by associating variables in the predictive coding scheme with nuclei and neuronal populations to match the (extrinsic and intrinsic) connectivity of the cerebellar (eyeblink conditioning) system. Finally, we try to establish predictive validity by reproducing selective failures of delay conditioning, trace conditioning, and extinction using (simulated and reversible) focal lesions. Although rather metaphorical, the ensuing scheme can account for a remarkable range of anatomical and neurophysiological aspects of cerebellar circuitry-and the specificity of lesion-deficit mappings that have been established experimentally. From a computational perspective, this work shows how conditioning or learning can be formulated in terms of minimizing variational free energy (or maximizing Bayesian model evidence) using exactly the same principles that underlie predictive coding in perception.

  7. Reconstructing Causal Biological Networks through Active Learning.

    Directory of Open Access Journals (Sweden)

    Hyunghoon Cho

    Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.

  8. Resting alpha activity predicts learning ability in alpha neurofeedback

    Directory of Open Access Journals (Sweden)

    Wenya eNan


    Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

  9. Mapping Learning Outcomes and Assignment Tasks for SPIDER Activities

    Directory of Open Access Journals (Sweden)

    Lyn Brodie


    Full Text Available Modern engineering programs have to address rapidly changing technical content and have to enable students to develop transferable skills such as critical evaluation, communication skills and lifelong learning. This paper introduces a combined learning and assessment activity that provides students with opportunities to develop and practice their soft skills, but also extends their theoretical knowledge base. Key tasks included self directed inquiry, oral and written communication as well as peer assessment. To facilitate the SPIDER activities (Select, Prepare and Investigate, Discuss, Evaluate, Reflect, a software tool has been implemented in the learning management system Moodle. Evidence shows increased student engagement and better learning outcomes for both transferable as well as technical skills. The study focuses on generalising the relationship between learning outcomes and assignment tasks as well as activities that drive these tasks. Trail results inform the approach. Staff evaluations and their views of assignments and intended learning outcomes also supported this analysis.

  10. Postnatal TLR2 activation impairs learning and memory in adulthood. (United States)

    Madar, Ravit; Rotter, Aviva; Waldman Ben-Asher, Hiba; Mughal, Mohamed R; Arumugam, Thiruma V; Wood, W H; Becker, K G; Mattson, Mark P; Okun, Eitan


    Neuroinflammation in the central nervous system is detrimental for learning and memory, as evident form epidemiological studies linking developmental defects and maternal exposure to harmful pathogens. Postnatal infections can also induce neuroinflammatory responses with long-term consequences. These inflammatory responses can lead to motor deficits and/or behavioral disabilities. Toll like receptors (TLRs) are a family of innate immune receptors best known as sensors of microbial-associated molecular patterns, and are the first responders to infection. TLR2 forms heterodimers with either TLR1 or TLR6, is activated in response to gram-positive bacterial infections, and is expressed in the brain during embryonic development. We hypothesized that early postnatal TLR2-mediated neuroinflammation would adversely affect cognitive behavior in the adult. Our data indicate that postnatal TLR2 activation affects learning and memory in adult mice in a heterodimer-dependent manner. TLR2/6 activation improved motor function and fear learning, while TLR2/1 activation impaired spatial learning and enhanced fear learning. Moreover, developmental TLR2 deficiency significantly impairs spatial learning and enhances fear learning, stressing the involvement of the TLR2 pathway in learning and memory. Analysis of the transcriptional effects of TLR2 activation reveals both common and unique transcriptional programs following heterodimer-specific TLR2 activation. These results imply that adult cognitive behavior could be influenced in part, by activation or alterations in the TLR2 pathway at birth. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. An Interactive Learning Environment for Teaching the Imperative and Object-Oriented Programming Techniques in Various Learning Contexts (United States)

    Xinogalos, Stelios

    The acquisition of problem-solving and programming skills in the era of knowledge society seems to be particularly important. Due to the intrinsic difficulty of acquiring such skills various educational tools have been developed. Unfortunately, most of these tools are not utilized. In this paper we present the programming microworlds Karel and objectKarel that support the procedural-imperative and Object-Oriented Programming (OOP) techniques and can be used for supporting the teaching and learning of programming in various learning contexts and audiences. The paper focuses on presenting the pedagogical features that are common to both environments and mainly on presenting the potential uses of these environments.

  12. An Active Learning Classifier for Further Reducing Diabetic Retinopathy Screening System Cost

    Directory of Open Access Journals (Sweden)

    Yinan Zhang


    Full Text Available Diabetic retinopathy (DR screening system raises a financial problem. For further reducing DR screening cost, an active learning classifier is proposed in this paper. Our approach identifies retinal images based on features extracted by anatomical part recognition and lesion detection algorithms. Kernel extreme learning machine (KELM is a rapid classifier for solving classification problems in high dimensional space. Both active learning and ensemble technique elevate performance of KELM when using small training dataset. The committee only proposes necessary manual work to doctor for saving cost. On the publicly available Messidor database, our classifier is trained with 20%–35% of labeled retinal images and comparative classifiers are trained with 80% of labeled retinal images. Results show that our classifier can achieve better classification accuracy than Classification and Regression Tree, radial basis function SVM, Multilayer Perceptron SVM, Linear SVM, and K Nearest Neighbor. Empirical experiments suggest that our active learning classifier is efficient for further reducing DR screening cost.

  13. Development of active neutron interrogation techniques at Harwell

    International Nuclear Information System (INIS)

    Armitage, B.H.; Chard, P.M.J.; Packer, T.W.; Swinhoe, M.T.; Syme, D.B.


    Active neutron interrogation techniques capable of measuring the fissile content of a range of waste drum sizes and contents have been developed at Harwell. This paper describes measurements which have been made to investigate the behaviour of these assay systems for the difficult case of concreted waste in a heterogeneous matrix. The drums have been measured using a Cf shuffler and a differential die-away system, with supporting information obtained from a segmented gamma-scanner. Good correspondence has been observed between the two different neutron interrogation techniques. It was concluded that the measurement of highly heterogeneous wastes is likely to be more effective if calibration can be undertaken with representative artificial matrices. Further measurement and analysis remains to be undertaken

  14. Aseptic minimum volume vitrification technique for porcine parthenogenetically activated blastocyst. (United States)

    Lin, Lin; Yu, Yutao; Zhang, Xiuqing; Yang, Huanming; Bolund, Lars; Callesen, Henrik; Vajta, Gábor


    Minimum volume vitrification may provide extremely high cooling and warming rates if the sample and the surrounding medium contacts directly with the respective liquid nitrogen and warming medium. However, this direct contact may result in microbial contamination. In this work, an earlier aseptic technique was applied for minimum volume vitrification. After equilibration, samples were loaded on a plastic film, immersed rapidly into factory derived, filter-sterilized liquid nitrogen, and sealed into sterile, pre-cooled straws. At warming, the straw was cut, the filmstrip was immersed into a 39 degree C warming medium, and the sample was stepwise rehydrated. Cryosurvival rates of porcine blastocysts produced by parthenogenetical activation did not differ from control, vitrified blastocysts with Cryotop. This approach can be used for minimum volume vitrification methods and may be suitable to overcome the biological dangers and legal restrictions that hamper the application of open vitrification techniques.

  15. Automated flare forecasting using a statistical learning technique (United States)

    Yuan, Yuan; Shih, Frank Y.; Jing, Ju; Wang, Hai-Min


    We present a new method for automatically forecasting the occurrence of solar flares based on photospheric magnetic measurements. The method is a cascading combination of an ordinal logistic regression model and a support vector machine classifier. The predictive variables are three photospheric magnetic parameters, i.e., the total unsigned magnetic flux, length of the strong-gradient magnetic polarity inversion line, and total magnetic energy dissipation. The output is true or false for the occurrence of a certain level of flares within 24 hours. Experimental results, from a sample of 230 active regions between 1996 and 2005, show the accuracies of a 24-hour flare forecast to be 0.86, 0.72, 0.65 and 0.84 respectively for the four different levels. Comparison shows an improvement in the accuracy of X-class flare forecasting.

  16. Automated flare forecasting using a statistical learning technique

    International Nuclear Information System (INIS)

    Yuan Yuan; Shih, Frank Y.; Jing Ju; Wang Haimin


    We present a new method for automatically forecasting the occurrence of solar flares based on photospheric magnetic measurements. The method is a cascading combination of an ordinal logistic regression model and a support vector machine classifier. The predictive variables are three photospheric magnetic parameters, i.e., the total unsigned magnetic flux, length of the strong-gradient magnetic polarity inversion line, and total magnetic energy dissipation. The output is true or false for the occurrence of a certain level of flares within 24 hours. Experimental results, from a sample of 230 active regions between 1996 and 2005, show the accuracies of a 24-hour flare forecast to be 0.86, 0.72, 0.65 and 0.84 respectively for the four different levels. Comparison shows an improvement in the accuracy of X-class flare forecasting. (research papers)

  17. Teacher feedback during active learning: current practices in primary schools. (United States)

    van den Bergh, Linda; Ros, Anje; Beijaard, Douwe


    Feedback is one of the most powerful tools, which teachers can use to enhance student learning. It appears difficult for teachers to give qualitatively good feedback, especially during active learning. In this context, teachers should provide facilitative feedback that is focused on the development of meta-cognition and social learning. The purpose of the present study is to contribute to the existing knowledge about feedback and to give directions to improve teacher feedback in the context of active learning. The participants comprised 32 teachers who practiced active learning in the domain of environmental studies in the sixth, seventh, or eighth grade of 13 Dutch primary schools. A total of 1,465 teacher-student interactions were examined. Video observations were made of active learning lessons in the domain of environmental studies. A category system was developed based on the literature and empirical data. Teacher-student interactions were assessed using this system. Results. About half of the teacher-student interactions contained feedback. This feedback was usually focused on the tasks that were being performed by the students and on the ways in which these tasks were processed. Only 5% of the feedback was explicitly related to a learning goal. In their feedback, the teachers were directing (rather than facilitating) the learning processes. During active learning, feedback on meta-cognition and social learning is important. Feedback should be explicitly related to learning goals. In practice, these kinds of feedback appear to be scarce. Therefore, giving feedback during active learning seems to be an important topic for teachers' professional development. © 2012 The British Psychological Society.

  18. Learning To Learn: 15 Vocabulary Acquisition Activities. Tips and Hints. (United States)

    Holden, William R.


    This article describes a variety of ways learners can help themselves remember new words, choosing the ones that best suit their learning styles. It is asserted that repeated exposure to new lexical items using a variety of means is the most consistent predictor of retention. The use of verbal, visual, tactile, textual, kinesthetic, and sonic…

  19. Using the Internet to Study the Internet: An Active Learning Component. (United States)

    Kohut, Dave; Sternberg, Joel


    Describes the Internet component of an undergraduate course at St. Xavier University (Illinois) in which a librarian helps mass communications students survey state-of-the-art technologies and predict future possibilities. Active learning techniques are discussed and examples of class exercises and the final assignment are included. (Author/LRW)

  20. 3-Dimensional and Interactive Istanbul University Virtual Laboratory Based on Active Learning Methods (United States)

    Ince, Elif; Kirbaslar, Fatma Gulay; Yolcu, Ergun; Aslan, Ayse Esra; Kayacan, Zeynep Cigdem; Alkan Olsson, Johanna; Akbasli, Ayse Ceylan; Aytekin, Mesut; Bauer, Thomas; Charalambis, Dimitris; Gunes, Zeliha Ozsoy; Kandemir, Ceyhan; Sari, Umit; Turkoglu, Suleyman; Yaman, Yavuz; Yolcu, Ozgu


    The purpose of this study is to develop a 3-dimensional interactive multi-user and multi-admin IUVIRLAB featuring active learning methods and techniques for university students and to introduce the Virtual Laboratory of Istanbul University and to show effects of IUVIRLAB on students' attitudes on communication skills and IUVIRLAB. Although there…

  1. Active Learning to Improve Presentation Skills: The Use of Pecha Kucha in Undergraduate Sales Management Classes (United States)

    McDonald, Robert E.; Derby, Joseph M.


    Recruiters seek candidates with certain business skills that are not developed in the typical lecture-based classroom. Instead, active-learning techniques have been shown to be effective in honing these skills. One skill that is particularly important in sales careers is the ability to make a powerful and effective presentation. To help students…

  2. FísicActiva: Applying Active Learning Strategies to a Large Engineering Lecture (United States)

    Auyuanet, Adriana; Modzelewski, Helena; Loureiro, Silvia; Alessandrini, Daniel; Míguez, Marina


    This paper presents and analyses the results obtained by applying Active Learning techniques in overcrowded Physics lectures at the University of the Republic, Uruguay. The course referred to is Physics 1, the first Physics course that all students of the Faculty of Engineering take in their first semester for all the Engineering-related careers.…

  3. Learning Activity Package, Physical Science. LAP Numbers 1, 2, 3, and 4. (United States)

    Williams, G. J.

    These four units of the Learning Activity Packages (LAPs) for individualized instruction in physical science cover measuring techniques, operations of instruments, metric system heat, matter, energy, elements, atomic numbers, isotopes, molecules, mixtures, compounds, physical and chemical properties, liquids, solids, and gases. Each unit contains…

  4. Learning Choices, Older Australians and Active Ageing (United States)

    Boulton-Lewis, Gillian M.; Buys, Laurie


    This paper reports on the findings of qualitative, semistructured interviews conducted with 40 older Australian participants who either did or did not engage in organized learning. Phenomenology was used to guide the interviews and analysis to explore the lived learning experiences and perspectives of these older people. Their experiences of…

  5. Robust satellite techniques for remote sensing of seismically active areas

    Energy Technology Data Exchange (ETDEWEB)

    Tramutoli, V; Di Bello, G [Potenza Univ., Potenza (Italy). Dipt. di Ingegneria e Fisica dell' Ambiente; Pergola, N; Piscitelli, S [Consiglio Nazionale delle Ricerche, Istituto di Metodologie Avanzate di Analisi Ambientale, Potenza (Italy)


    Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity) whose variable contributions to the investigated signal can be so high as to completely mask (or simulate) the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT) has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks) which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observation field also in the presence of highly variable contributions from atmospheric (transmittance), surface (emissivity and morphology) and observational (time/season, but also solar and satellite zenithal angles) conditions. This work presents the first preliminary results, based on several years of NOA A/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications) as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.

  6. Robust satellite techniques for remote sensing of seismically active areas

    Directory of Open Access Journals (Sweden)

    S. Piscitelli


    Full Text Available Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity whose variable contributions to the investigated signal can be so high as to completely mask (or simulate the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observational field also in the presence of highly variable contributions from atmospheric (transmittance, surface (emissivity and morphology and observational (time/season, but also solar and satellite zenithal angles conditions.This work presents the first preliminary results, based on several years of NOAA/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.

  7. Penerapan Model Active Learning untuk Meremediasi Miskonsepsi Siswa pada Materi Gerak Lurus di SMP


    Yulindar, Arvitri; Djudin, Tomo; Hamdani


    This study aims to determine effectiveness of remediation application of active learning models that have misconceptions on rectilinear motion in class VIII SMP Negeri 2 Pontianak. This research is the form of pre-experiment using a one group pretest-postest. The study sample consisted of 38 students of class VIII B SMP Negeri 2 Pontianak. Data collection technique used in the form of a measurement technique using multiple choice diagnostic tests with reason that have total 10 questions. The ...

  8. Active learning reduces annotation time for clinical concept extraction. (United States)

    Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony


    To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Using active learning strategies to investigate student learning and attitudes in a large enrollment, introductory geology course (United States)

    Berry, Stacy Jane

    There has been an increased emphasis for college instruction to incorporate more active and collaborative involvement of students in the learning process. These views have been asserted by The Association of American Colleges (AAC), the National Science Foundation (NSF), and The National Research Counsel (NRC), which are advocating for the modification of traditional instructional techniques to allow students the opportunity to be more cooperative (Task Group on General Education, 1988). This has guided educators and facilitators into shifting teaching paradigms from a teacher centered to a more student-centered curriculum. The present study investigated achievement outcomes and attitudes of learners in a large enrollment (n ~ 200), introductory geology course using a student centered learning cycle format of instruction versus another similar section that used a traditional lecture format. Although the course is a recruiting class for majors, over 95% of the students that enroll are non-majors. Measurements of academic evaluation were through four unit exams, classroom communication systems, weekly web-based homework, in-class activities, and a thematic collaborative poster/paper project and presentation. The qualitative methods to investigate the effectiveness of the teaching design included: direct observation, self-reporting about learning, and open-ended interviews. By disaggregating emerging data, we tried to concentrate on patterns and causal relationships between achievement performance and attitudes regarding learning geology. Statistical analyses revealed positive relationships between student engagement in supplemental activities and achievement mean scores within and between the two sections. Completing weekly online homework had the most robust relationship with overall achievement performance. Contrary to expectations, a thematic group project only led to modest gains in achievement performance, although the social and professional gains could be

  10. The training and learning process of transseptal puncture using a modified technique. (United States)

    Yao, Yan; Ding, Ligang; Chen, Wensheng; Guo, Jun; Bao, Jingru; Shi, Rui; Huang, Wen; Zhang, Shu; Wong, Tom


    As the transseptal (TS) puncture has become an integral part of many types of cardiac interventional procedures, its technique that was initial reported for measurement of left atrial pressure in 1950s, continue to evolve. Our laboratory adopted a modified technique which uses only coronary sinus catheter as the landmark to accomplishing TS punctures under fluoroscopy. The aim of this study is prospectively to evaluate the training and learning process for TS puncture guided by this modified technique. Guided by the training protocol, TS puncture was performed in 120 consecutive patients by three trainees without previous personal experience in TS catheterization and one experienced trainer as a controller. We analysed the following parameters: one puncture success rate, total procedure time, fluoroscopic time, and radiation dose. The learning curve was analysed using curve-fitting methodology. The first attempt at TS crossing was successful in 74 (82%), a second attempt was successful in 11 (12%), and 5 patients failed to puncture the interatrial septal finally. The average starting process time was 4.1 ± 0.8 min, and the estimated mean learning plateau was 1.2 ± 0.2 min. The estimated mean learning rate for process time was 25 ± 3 cases. Important aspects of learning curve can be estimated by fitting inverse curves for TS puncture. The study demonstrated that this technique was a simple, safe, economic, and effective approach for learning of TS puncture. Base on the statistical analysis, approximately 29 TS punctures will be needed for trainee to pass the steepest area of learning curve.

  11. Prediction of drug synergy in cancer using ensemble-based machine learning techniques (United States)

    Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder


    Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

  12. Integrating SQ4R Technique with Graphic Postorganizers in the Science Learning of Earth and Space


    Djudin, Tomo; Amir, R


    This study examined the effect of integrating SQ4R reading technique with graphic post organizers on the students' Earth and Space Science learning achievement and development of metacognitive knowledge. The pretest-posttest non-equivalent control group design was employed in this quasi-experimental method. The sample which consists of 103 seventh grade of secondary school students of SMPN 1 Pontianak was drawn by using intact group random sampling technique. An achievement test and a questio...

  13. The application of radiotracer technique for preconcentration neutron activation analysis

    International Nuclear Information System (INIS)

    Wang Xiaolin; Chen Yinliang; Sun Ying; Fu Yibei


    The application of radiotracer technique for preconcentration neutron activation analysis (Pre-NAA) are studied and the method for determination of chemical yield of Pre-NAA is developed. This method has been applied to determination of gold, iridium and rhenium in steel and rock samples and the contents of noble metal are in the range of 1-20 ng·g -1 (sample). In addition, the accuracy difference caused by determination of chemical yield between RNAA and Pre-NAA are also discussed

  14. Pulsed neutron generator for use with pulsed neutron activation techniques

    International Nuclear Information System (INIS)

    Rochau, G.E.


    A high-output, transportable, pulsed neutron generator has been developed by Sandia National Laboratories for use with Pulsed Neutron Activation (PNA) techniques. The PNA neutron generator generates > 10 10 14 MeV D-T neutrons in a 1.2 millisecond pulse. Each operation of the unit will produce a nominal total neutron output of 1.2 x 10 10 neutrons. The generator has been designed to be easily repaired and modified. The unit requires no additional equipment for operation or measurement of output

  15. Active Learning of Classification Models with Likert-Scale Feedback. (United States)

    Xue, Yanbing; Hauskrecht, Milos


    Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

  16. MLS student active learning within a "cloud" technology program. (United States)

    Tille, Patricia M; Hall, Heather


    In November 2009, the MLS program in a large public university serving a geographically large, sparsely populated state instituted an initiative for the integration of technology enhanced teaching and learning within the curriculum. This paper is intended to provide an introduction to the system requirements and sample instructional exercises used to create an active learning technology-based classroom. Discussion includes the following: 1.) define active learning and the essential components, 2.) summarize teaching methods, technology and exercises utilized within a "cloud" technology program, 3.) describe a "cloud" enhanced classroom and programming 4.) identify active learning tools and exercises that can be implemented into laboratory science programs, and 5.) describe the evaluation and assessment of curriculum changes and student outcomes. The integration of technology in the MLS program is a continual process and is intended to provide student-driven active learning experiences.

  17. Telling Active Learning Pedagogies Apart: from theory to practice

    Directory of Open Access Journals (Sweden)

    Kelsey Hood Cattaneo


    Full Text Available Designing learning environments to incorporate active learning pedagogies is difficult as definitions are often contested and intertwined. This article seeks to determine whether classification of active learning pedagogies (i.e., project-based, problem-based, inquiry-based, case-based, and discovery-based, through theoretical and practical lenses, could function as a useful tool for researchers and practitioners in comparing pedagogies. This article classified five active learning pedagogies based on six constructivist elements. The comparison was completed through a comparative analysis and a content analysis informed by a systematic literature review. The findings were that learner-centeredness is a primary goal of all pedagogies; however, there is a strong dissonance between each pedagogy’s theoretical underpinnings and implementation realities. This dissonance complicates differentiating active learning pedagogies and classification as a comparative tool has proved to have limited usefulness.

  18. A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Allah Bux Sargano


    Full Text Available Human activity recognition (HAR is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR.

  19. Characterizing root activity of guava trees by radiotracer technique

    International Nuclear Information System (INIS)

    Purohit, A.G.; Mukherjee, S.K.


    The distribution pattern of root activity of 12-year-old trees of guava (Psidium guajava L.) was determined by radiotracer technique. 32 P soloution was injected into the soil at lateral distances of 120, 240 and 360 cm from the tree trunk at depths of 15,30,60 and 90 cm. The 32 P uptake by the tree was determined by leaf analysis. In the rainy season the root activity or 32 P uptake was greater near the soil surface and midway between the trunk and the drip-line. The root activity decreased with an increase in the depth and distance from trunk. These results compared well with the actual distribution of feeder roots as determined by the soil-auger method. In summer the roots near the surface become less active in 32 P absorption with a drcrease in surface soil moisture. A decrease in the root activity in the surface soil was accompanied by an increase in 32 P uptake from lower depths. (author)

  20. Detection of uranium enrichment activities using environmental monitoring techniques

    International Nuclear Information System (INIS)

    Belew, W.L.; Carter, J.A.; Smith, D.H.; Walker, R.L.


    Uranium enrichment processes have the capability of producing weapons-grade material in the form of highly enriched uranium. Thus, detection of undeclared uranium enrichment activities is an international safeguards concern. The uranium separation technologies currently in use employ UF 6 gas as a separation medium, and trace quantities of enriched uranium are inevitably released to the environment from these facilities. The isotopic content of uranium in the vegetation, soil, and water near the plant site will be altered by these releases and can provide a signature for detecting the presence of enriched uranium activities. This paper discusses environmental sampling and analytical procedures that have been used for the detection of uranium enrichment facilities and possible safeguards applications of these techniques

  1. The search for active learning: Lessons from a happy accident


    Bashforth, Hedley; Parmar, Nitin R


    This article suggests that the concept of ‘active learning’ has different meanings. These meanings are created in the dynamic and variable relationships between the uses of learning technologies and approaches to pedagogy. Institutions play a key role in mediating these relationships, privileging some meanings of ‘active learning’ over others. More dialogical forms of active learning call for changes in the mediating role of the institution. This article draws on a case study of the use of El...

  2. Technology transfer and technological learning through CERN's procurement activity

    CERN Document Server

    Autio, Erkko; Hameri, Ari-Pekka; CERN. Geneva


    This report analyses the technological learning and innovation benefits derived from CERN's procurement activity during the period 1997-2001. The base population of our study, the technology-intensive suppliers to CERN, consisted of 629 companies out of 6806 companies during the same period, representing 1197 MCHF in procurement. The main findings from the study can be summarized as follows: the various learning and innovation benefits (e.g., technological learning, organizational capability development, market learning) tend to occur together. Learning and innovation benefits appear to be regulated by the quality of the supplier's relationship with CERN: the greater the amount of social capital built into the relationship, the greater the learning and innovation benefits. Regardless of relationship quality, virtually all suppliers derived significant marketing reference benefits from CERN. Many corollary benefits are associated with procurement activity. As an example, as many as 38% of the respondents devel...

  3. Applying active learning to supervised word sense disambiguation in MEDLINE (United States)

    Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua


    Objectives This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. Methods We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Results Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. Conclusions This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models. PMID:23364851

  4. Applying active learning to supervised word sense disambiguation in MEDLINE. (United States)

    Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua


    This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models.

  5. Site characterization techniques used in environmental remediation activities

    International Nuclear Information System (INIS)

    Kostelnik, K.M.


    As a result of decades of nuclear energy research, weapons production, as well as ongoing operations, a significant amount of radioactive contamination has occurred throughout the United States Department of Energy (DOE) complex. DOE facility are in the process of assessing and potentially remediating various sites according to the regulations imposed by a Federal Facility Agreement and Consent order (FFA/CO) between DOE, the state in which the facility is located, and the U.S. Environmental Protection Agency (EPA). In support of these active site remediation efforts, the DOE has devoted considerable resources towards the development of innovative site characterization techniques that support environmental restoration activities. These resources and efforts have focused on various aspects of this complex problem. Research and technology development conducted at the Idaho National Engineering and Environmental Laboratory (INEEL) has resulted in the ability and state-of-the-art equipment required to obtain real-time, densely spaced, in situ characterization data (i.e. detection, speciation, and location) of various radionuclides and contaminants. The Remedial Action Monitoring System (RAMS), developed by the INEEL, consists of enhanced sensor technology, measurement modeling and interpretation techniques, and a suite of deployment platforms which can be interchanged to directly support remedial cleanup and site verification operations. In situ characterization techniques have advanced to the point where they are being actively deployed in support of remedial operations. The INEEL has deployed its system at various DOE and international sites. The deployment of in situ characterization systems during environmental restoration operations has shown that this approach results in several significant benefits versus conventional sampling techniques. A flexible characterization system permits rapid modification to satisfy physical site conditions, available site resources

  6. 76 FR 45334 - Innovative Techniques for Delivering ITS Learning; Request for Information (United States)


    ... adult learners? 5. Are you aware of any ITS training applications that work on a mobile phone or smart... DEPARTMENT OF TRANSPORTATION Research and Innovative Technology Administration Innovative Techniques for Delivering ITS Learning; Request for Information AGENCY: Research and Innovative Technology...

  7. Learning L2 German vocabulary through reading: the effect of three enhancement techniques compared

    NARCIS (Netherlands)

    Peters, E.; Hulstijn, J.H.; Sercu, L.; Lutjeharms, M.


    This study investigated three techniques designed to increase the chances that second language (L2) readers look up and learn unfamiliar words during and after reading an L2 text. Participants in the study, 137 college students in Belgium (L1 = Dutch, L2 = German), were randomly assigned to one of

  8. Phishtest: Measuring the Impact of Email Headers on the Predictive Accuracy of Machine Learning Techniques (United States)

    Tout, Hicham


    The majority of documented phishing attacks have been carried by email, yet few studies have measured the impact of email headers on the predictive accuracy of machine learning techniques in detecting email phishing attacks. Research has shown that the inclusion of a limited subset of email headers as features in training machine learning…

  9. Critique: Can Children with AD/HD Learn Relaxation and Breathing Techniques through Biofeedback Video Games? (United States)

    Wright, Craig; Conlon, Elizabeth


    This article presents a critique on K. Amon and A. Campbell's "Can children with AD/HD learn relaxation and breathing techniques through biofeedback video games?". Amon and Campbell reported a successful trial of a commercially available biofeedback program, "The Wild Divine", in reducing symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD)…

  10. WHO activities in teaching radioimmunoassay and related techniques

    International Nuclear Information System (INIS)

    Goncharov, N.P.; Sufi, S.B.; Donaldson, A.; Jeffcoate, S.L.


    The Special Programme of Research, Development and Research Training in Human Reproduction of the World Health Organization has recognized from its beginning that training is a key component of its activities, including its immunoassay standardization programme. Since the start of the Special Programme more than 250 scientists have received training in RIA and related procedures and 27 training courses have been held in various countries. Many of the courses have been held in collaboration with the International Atomic Energy Agency, and these co-operative activities have established a core of scientific expertise worldwide which has contributed to the increased availability of modern diagnostic techniques in many countries. The increasing number of medical and non-medical applications of immunoassays and the special expertise required for some immunoassay methods create a continuing demand for training in RIA techniques. Both WHO and the IAEA have responded by organizing courses to 'train the trainers' and by supporting national and regional courses based on centrally provided material, as well as by commissioning the production of additional teaching documents and audio-visual aids in English and Spanish. It is envisaged that such materials, complete with centrally provided materials for practicals and other teaching aids, will be made available to national reagent programmes and will be used in the future as a well characterized, standardized core around which local organizers can construct training programmes geared to local needs and drawing upon local experience. (author)

  11. Using the IGCRA (individual, group, classroom reflective action technique to enhance teaching and learning in large accountancy classes

    Directory of Open Access Journals (Sweden)

    Cristina Poyatos


    Full Text Available First year accounting has generally been perceived as one of the more challenging first year business courses for university students. Various Classroom Assessment Techniques (CATs have been proposed to attempt to enrich and enhance student learning, with these studies generally positioning students as learners alone. This paper uses an educational case study approach and examines the implementation of the IGCRA (individual, group, classroom reflective action technique, a Classroom Assessment Technique, on first year accounting students’ learning performance. Building on theoretical frameworks in the areas of cognitive learning, social development, and dialogical learning, the technique uses reports to promote reflection on both learning and teaching. IGCRA was found to promote feedback on the effectiveness of student, as well as teacher satisfaction. Moreover, the results indicated formative feedback can assist to improve the learning and learning environment for a large group of first year accounting students. Clear guidelines for its implementation are provided in the paper.

  12. Moments of movement: active learning and practice development. (United States)

    Dewing, Jan


    As our understanding of practice development becomes more sophisticated, we enhance our understanding of how the facilitation of learning in and from practice, can be more effectively achieved. This paper outlines an approach for enabling and maximizing learning within practice development known as 'Active Learning'. It considers how, given establishing a learning culture is a prerequisite for the sustainability of PD within organisations, practice developers can do more to maximize learning for practitioners and other stakeholders. Active Learning requires that more attention be given by organisations committed to PD, at a corporate and strategic level for how learning strategies are developed in the workplace. Specifically, a move away from a heavy reliance on training may be required. Practice development facilitators also need to review: how they organise and offer learning, so that learning strategies are consistent with the vision, aims and processes of PD; have skills in the planning, delivery and evaluation of learning as part of their role and influence others who provide more traditional methods of training and education.

  13. Active controllers and the time duration to learn a task (United States)

    Repperger, D. W.; Goodyear, C.


    An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.

  14. A comparison of professional-level faculty and student perceptions of active learning: its current use, effectiveness, and barriers (United States)

    Metz, Michael J.


    Active learning is an instructional method in which students become engaged participants in the classroom through the use of in-class written exercises, games, problem sets, audience-response systems, debates, class discussions, etc. Despite evidence supporting the effectiveness of active learning strategies, minimal adoption of the technique has occurred in many professional programs. The goal of this study was to compare the perceptions of active learning between students who were exposed to active learning in the classroom (n = 116) and professional-level physiology faculty members (n = 9). Faculty members reported a heavy reliance on lectures and minimal use of educational games and activities, whereas students indicated that they learned best via the activities. A majority of faculty members (89%) had observed active learning in the classroom and predicted favorable effects of the method on student performance and motivation. The main reported barriers by faculty members to the adoption of active learning were a lack of necessary class time, a high comfort level with traditional lectures, and insufficient time to develop materials. Students hypothesized similar obstacles for faculty members but also associated many negative qualities with the traditional lecturers. Despite these barriers, a majority of faculty members (78%) were interested in learning more about the alternative teaching strategy. Both faculty members and students indicated that active learning should occupy portions (29% vs. 40%) of face-to-face class time. PMID:25179615

  15. A comparison of professional-level faculty and student perceptions of active learning: its current use, effectiveness, and barriers. (United States)

    Miller, Cynthia J; Metz, Michael J


    Active learning is an instructional method in which students become engaged participants in the classroom through the use of in-class written exercises, games, problem sets, audience-response systems, debates, class discussions, etc. Despite evidence supporting the effectiveness of active learning strategies, minimal adoption of the technique has occurred in many professional programs. The goal of this study was to compare the perceptions of active learning between students who were exposed to active learning in the classroom (n = 116) and professional-level physiology faculty members (n = 9). Faculty members reported a heavy reliance on lectures and minimal use of educational games and activities, whereas students indicated that they learned best via the activities. A majority of faculty members (89%) had observed active learning in the classroom and predicted favorable effects of the method on student performance and motivation. The main reported barriers by faculty members to the adoption of active learning were a lack of necessary class time, a high comfort level with traditional lectures, and insufficient time to develop materials. Students hypothesized similar obstacles for faculty members but also associated many negative qualities with the traditional lecturers. Despite these barriers, a majority of faculty members (78%) were interested in learning more about the alternative teaching strategy. Both faculty members and students indicated that active learning should occupy portions (29% vs. 40%) of face-to-face class time. Copyright © 2014 The American Physiological Society.

  16. Active Learning by Querying Informative and Representative Examples. (United States)

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


    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.

  17. Medical Student Perspectives of Active Learning: A Focus Group Study. (United States)

    Walling, Anne; Istas, Kathryn; Bonaminio, Giulia A; Paolo, Anthony M; Fontes, Joseph D; Davis, Nancy; Berardo, Benito A


    Phenomenon: Medical student perspectives were sought about active learning, including concerns, challenges, perceived advantages and disadvantages, and appropriate role in the educational process. Focus groups were conducted with students from all years and campuses of a large U.S. state medical school. Students had considerable experience with active learning prior to medical school and conveyed accurate understanding of the concept and its major strategies. They appreciated the potential of active learning to deepen and broaden learning and its value for long-term professional development but had significant concerns about the efficiency of the process, the clarity of expectations provided, and the importance of receiving preparatory materials. Most significantly, active learning experiences were perceived as disconnected from grading and even as impeding preparation for school and national examinations. Insights: Medical students understand the concepts of active learning and have considerable experience in several formats prior to medical school. They are generally supportive of active learning concepts but frustrated by perceived inefficiencies and lack of contribution to the urgencies of achieving optimal grades and passing United States Medical Licensing Examinations, especially Step 1.

  18. An Effective Performance Analysis of Machine Learning Techniques for Cardiovascular Disease

    Directory of Open Access Journals (Sweden)

    Vinitha DOMINIC


    Full Text Available Machine learning techniques will help in deriving hidden knowledge from clinical data which can be of great benefit for society, such as reduce the number of clinical trials required for precise diagnosis of a disease of a person etc. Various areas of study are available in healthcare domain like cancer, diabetes, drugs etc. This paper focuses on heart disease dataset and how machine learning techniques can help in understanding the level of risk associated with heart diseases. Initially, data is preprocessed then analysis is done in two stages, in first stage feature selection techniques are applied on 13 commonly used attributes and in second stage feature selection techniques are applied on 75 attributes which are related to anatomic structure of the heart like blood vessels of the heart, arteries etc. Finally, validation of the reduced set of features using an exhaustive list of classifiers is done.In parallel study of the anatomy of the heart is done using the identified features and the characteristics of each class is understood. It is observed that these reduced set of features are anatomically relevant. Thus, it can be concluded that, applying machine learning techniques on clinical data is beneficial and necessary.

  19. Analysis and design of machine learning techniques evolutionary solutions for regression, prediction, and control problems

    CERN Document Server

    Stalph, Patrick


    Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain – at least to some extent. Therefore three suitable machine learning algorithms are selected – algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the...

  20. Employability and work-related learning activities in higher education

    DEFF Research Database (Denmark)

    Magnell, Marie; Kolmos, Anette


    The focus of this paper is on how academic staff perceive their roles and responsibilities regarding work-related learning, and how they approach and implement work-related learning activities in curricula across academic environments in higher education. The study is based on case studies...

  1. Resource Letter ALIP-1: Active-Learning Instruction in Physics (United States)

    Meltzer, David E.; Thornton, Ronald K.


    This Resource Letter provides a guide to the literature on research-based active-learning instruction in physics. These are instructional methods that are based on, assessed by, and validated through research on the teaching and learning of physics. They involve students in their own learning more deeply and more intensely than does traditional instruction, particularly during class time. The instructional methods and supporting body of research reviewed here offer potential for significantly improved learning in comparison to traditional lecture-based methods of college and university physics instruction. We begin with an introduction to the history of active learning in physics in the United States, and then discuss some methods for and outcomes of assessing pedagogical effectiveness. We enumerate and describe common characteristics of successful active-learning instructional strategies in physics. We then discuss a range of methods for introducing active-learning instruction in physics and provide references to those methods for which there is published documentation of student learning gains.

  2. Presence in a Collaborative Science Learning Activity in Second Life

    DEFF Research Database (Denmark)

    Vrellis, Ioannis; Papachristos, Nikiforos; Natsis, Antonios


    interacting with and via virtual environments and seems to play an important role in learning. This chapter presents empirical data gathered from an exploratory study regarding a problem-based physics learning activity in Second Life (SL). Our aim is to gain knowledge and experience about the sense...

  3. An active role for machine learning in drug development (United States)

    Murphy, Robert F.


    Due to the complexity of biological systems, cutting-edge machine-learning methods will be critical for future drug development. In particular, machine-vision methods to extract detailed information from imaging assays and active-learning methods to guide experimentation will be required to overcome the dimensionality problem in drug development. PMID:21587249

  4. Creating Activating Events for Transformative Learning in a Prison Classroom (United States)

    Keen, Cheryl H.; Woods, Robert


    In this article, we interpreted, in light of Mezirow's theory of transformative learning, interviews with 13 educators regarding their work with marginalized adult learners in prisons in the northeastern United States. Transformative learning may have been aided by the educators' response to unplanned activating events, humor, and respect, and…

  5. Cognitive and Social Aspects of Engagement in Active Learning (United States)

    Koretsky, Milo


    This article reports analysis of students' written reflections as to what helps them learn in an active learning environment. Eight hundred and twenty seven responses from 403 students in four different studio courses over two years were analyzed. An emergent coding scheme identified 55% of the responses as associated with cognitive processes…

  6. An active learning organisation: teaching projects in electrical engineering education

    NARCIS (Netherlands)

    Christensen, H.-P.; Vos, Henk; de Graaff, E.; Lemoult, B.


    The introduction of active learning in engineering education is often started by enthusiastic teachers or change agents. They usually encounter resistance from stakeholders such as colleagues, department boards or students. For a successful introduction these stakeholders all have to learn what

  7. How an Active Learning Classroom Transformed IT Executive Management (United States)

    Connolly, Amy; Lampe, Michael


    This article describes how our university built a unique classroom environment specifically for active learning. This classroom changed students' experience in the undergraduate executive information technology (IT) management class. Every college graduate should learn to think critically, solve problems, and communicate solutions, but 90% of…

  8. Enhanced Memory as a Common Effect of Active Learning (United States)

    Markant, Douglas B.; Ruggeri, Azzurra; Gureckis, Todd M.; Xu, Fei


    Despite widespread consensus among educators that "active learning" leads to better outcomes than comparatively passive forms of instruction, it is often unclear why these benefits arise. In this article, we review research showing that the opportunity to control the information experienced while learning leads to improved memory…

  9. Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities. (United States)

    Bryant, D P; Bryant, B R


    Cooperative learning (CL) is a common instructional arrangement that is used by classroom teachers to foster academic achievement and social acceptance of students with and without learning disabilities. Cooperative learning is appealing to classroom teachers because it can provide an opportunity for more instruction and feedback by peers than can be provided by teachers to individual students who require extra assistance. Recent studies suggest that students with LD may need adaptations during cooperative learning activities. The use of assistive technology adaptations may be necessary to help some students with LD compensate for their specific learning difficulties so that they can engage more readily in cooperative learning activities. A process for integrating technology adaptations into cooperative learning activities is discussed in terms of three components: selecting adaptations, monitoring the use of the adaptations during cooperative learning activities, and evaluating the adaptations' effectiveness. The article concludes with comments regarding barriers to and support systems for technology integration, technology and effective instructional practices, and the need to consider technology adaptations for students who have learning disabilities.

  10. Use of Active Learning to Design Wind Tunnel Runs for Unsteady Cavity Pressure Measurements

    Directory of Open Access Journals (Sweden)

    Ankur Srivastava


    Full Text Available Wind tunnel tests to measure unsteady cavity flow pressure measurements can be expensive, lengthy, and tedious. In this work, the feasibility of an active machine learning technique to design wind tunnel runs using proxy data is tested. The proposed active learning scheme used scattered data approximation in conjunction with uncertainty sampling (US. We applied the proposed intelligent sampling strategy in characterizing cavity flow classes at subsonic and transonic speeds and demonstrated that the scheme has better classification accuracies, using fewer training points, than a passive Latin Hypercube Sampling (LHS strategy.

  11. Promoting Active Learning in Calculus and General Physics through Interactive and Media-Enhanced Lectures

    Directory of Open Access Journals (Sweden)

    Guoqing Tang


    Full Text Available In this paper we present an approach of incorporating interactive and media-enhanced lectures to promote active learning in Calculus and General Physics courses. The pedagogical practice of using interactive techniques in lectures to require "heads-on" and "hands-on" learning, and involve students more as active participants than passive receivers is a part of academic curricular reform efforts undertaken currently by the mathematics, physics and chemistry departments at North Carolina A&T State University under the NSF funded project "Talent-21: Gateway for Advancing Science and Mathematics Talents."

  12. Identifying Key Features of Effective Active Learning: The Effects of Writing and Peer Discussion (United States)

    Pangle, Wiline M.; Wyatt, Kevin H.; Powell, Karli N.; Sherwood, Rachel E.


    We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. PMID:25185230

  13. Changing University Students’ Alternative Conceptions of Optics by Active Learning

    Directory of Open Access Journals (Sweden)

    Zalkida Hadžibegović


    Full Text Available Active learning is individual and group participation in effective activities such as in-class observing, writing, experimenting, discussion, solving problems, and talking about to-be-learned topics. Some instructors believe that active learning is impossible, or at least extremely difficult to achieve in large lecture sessions. Nevertheless, the truly impressive implementation results of theSCALE-UP learning environment suggest that such beliefs are false (Beichner et al., 2000. In this study, we present a design of an active learning environment with positive effect on students. The design is based on the following elements: (1 helping students to learn from interactive lecture experiment; (2 guiding students to use justified explanation and prediction after observing and exploring a phenomenon; (3 developing a conceptual question sequencedesigned for use in an interactive lecture with students answering questions in worksheets by writing and drawing; (4 evaluating students’ conceptual change and gains by questions related to light reflection, refraction, and image formation in an exam held a week after the active learning session. Data were collected from 95 science freshmen with different secondary school backgrounds. They participated in geometrical optics classes organized for collecting research results during and after only one active learning session.The results have showed that around 60% of the students changed their initial alternative conceptions of vision and of image formation. It was also found that a large group of university students is likely to be engaged in active learning, shifting from a passive role they usually play during teacher’s lectures.

  14. A comparison of machine learning techniques for detection of drug target articles. (United States)

    Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo


    Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

  15. Developing capability through peer-assisted learning activities ...

    African Journals Online (AJOL)

    L-CAS) is an activity by means of which each student is exposed to primary healthcare learning and practice in communities. Capability has been described as 'an integration of knowledge, skills, personal qualities and understanding used ...

  16. Physical Activity and Wellness: Applied Learning through Collaboration (United States)

    Long, Lynn Hunt; Franzidis, Alexia


    This article describes how two university professors teamed up to initiate a university-sponsored physical activity and wellness expo in an effort to promote an authentic and transformative learning experience for preservice students.

  17. Teachers' Perceptions and Practices of Active Learning in ...

    African Journals Online (AJOL)

    Teachers' Perceptions and Practices of Active Learning in Haramaya ... Science, Technology and Arts Research Journal ... traditional/lecture method, lack of students' interest, shortage of time, lack of instructional material and large class size.

  18. Revitalizing pathology laboratories in a gastrointestinal pathophysiology course using multimedia and team-based learning techniques. (United States)

    Carbo, Alexander R; Blanco, Paola G; Graeme-Cooke, Fiona; Misdraji, Joseph; Kappler, Steven; Shaffer, Kitt; Goldsmith, Jeffrey D; Berzin, Tyler; Leffler, Daniel; Najarian, Robert; Sepe, Paul; Kaplan, Jennifer; Pitman, Martha; Goldman, Harvey; Pelletier, Stephen; Hayward, Jane N; Shields, Helen M


    In 2008, we changed the gastrointestinal pathology laboratories in a gastrointestinal pathophysiology course to a more interactive format using modified team-based learning techniques and multimedia presentations. The results were remarkably positive and can be used as a model for pathology laboratory improvement in any organ system. Over a two-year period, engaging and interactive pathology laboratories were designed. The initial restructuring of the laboratories included new case material, Digital Atlas of Video Education Project videos, animations and overlays. Subsequent changes included USMLE board-style quizzes at the beginning of each laboratory, with individual readiness assessment testing and group readiness assessment testing, incorporation of a clinician as a co-teacher and role playing for the student groups. Student responses for pathology laboratory contribution to learning improved significantly compared to baseline. Increased voluntary attendance at pathology laboratories was observed. Spontaneous student comments noted the positive impact of the laboratories on their learning. Pathology laboratory innovations, including modified team-based learning techniques with individual and group self-assessment quizzes, multimedia presentations, and paired teaching by a pathologist and clinical gastroenterologist led to improvement in student perceptions of pathology laboratory contributions to their learning and better pathology faculty evaluations. These changes can be universally applied to other pathology laboratories to improve student satisfaction. Copyright © 2012 Elsevier GmbH. All rights reserved.

  19. Prediction of mortality after radical cystectomy for bladder cancer by machine learning techniques. (United States)

    Wang, Guanjin; Lam, Kin-Man; Deng, Zhaohong; Choi, Kup-Sze


    Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Proton-activation technique for the determination of antimony

    International Nuclear Information System (INIS)

    Krivan, V.; Barth, P.


    Photon-activation analysis has been applied to the determination of antimony. Thick-target yields and analytical sensitivities are given for the indicator-radionuclides sup(119m)Te, sup(119g)Te, sup(121m)Te, sup(121g)Te, sup(123m)Te, sup(120m)Sb and sup(122g)Sb for proton energies between 9 and 25 MeV. In irradiations with a 5-μA beam for 5 hr, followed by a specific separation of the indicator-radionuclides, limits of detection at the ppm level can be achieved. Data are given for the most significant interfering reactions. Antimony was determined instrumentally in bismuth of very pure grade and the results are compared with those obtained from two independent techniques. (author)

  1. Prototype-based active learning for lemmatization

    CSIR Research Space (South Africa)

    Daelemans, W


    Full Text Available ] and Word Length [Long to Short] with the prototypical curves (e.g. Word Frequency [High to Low] and [Word Length Short to Long]). (With regard to the learning curves representing word frequency, refer to 4.1 for an explanation of why [High to Low... of language usage [15]. Secondly, in memory-based language processing [16] it has been argued, on the basis of com- parative machine learning experiments on natural lan- guage processing data, that exceptions are crucial for obtaining high generalization...

  2. A preclustering-based ensemble learning technique for acute appendicitis diagnoses. (United States)

    Lee, Yen-Hsien; Hu, Paul Jen-Hwa; Cheng, Tsang-Hsiang; Huang, Te-Chia; Chuang, Wei-Yao


    Acute appendicitis is a common medical condition, whose effective, timely diagnosis can be difficult. A missed diagnosis not only puts the patient in danger but also requires additional resources for corrective treatments. An acute appendicitis diagnosis constitutes a classification problem, for which a further fundamental challenge pertains to the skewed outcome class distribution of instances in the training sample. A preclustering-based ensemble learning (PEL) technique aims to address the associated imbalanced sample learning problems and thereby support the timely, accurate diagnosis of acute appendicitis. The proposed PEL technique employs undersampling to reduce the number of majority-class instances in a training sample, uses preclustering to group similar majority-class instances into multiple groups, and selects from each group representative instances to create more balanced samples. The PEL technique thereby reduces potential information loss from random undersampling. It also takes advantage of ensemble learning to improve performance. We empirically evaluate this proposed technique with 574 clinical cases obtained from a comprehensive tertiary hospital in southern Taiwan, using several prevalent techniques and a salient scoring system as benchmarks. The comparative results show that PEL is more effective and less biased than any benchmarks. The proposed PEL technique seems more sensitive to identifying positive acute appendicitis than the commonly used Alvarado scoring system and exhibits higher specificity in identifying negative acute appendicitis. In addition, the sensitivity and specificity values of PEL appear higher than those of the investigated benchmarks that follow the resampling approach. Our analysis suggests PEL benefits from the more representative majority-class instances in the training sample. According to our overall evaluation results, PEL records the best overall performance, and its area under the curve measure reaches 0.619. The

  3. Localization-Aware Active Learning for Object Detection


    Kao, Chieh-Chi; Lee, Teng-Yok; Sen, Pradeep; Liu, Ming-Yu


    Active learning - a class of algorithms that iteratively searches for the most informative samples to include in a training dataset - has been shown to be effective at annotating data for image classification. However, the use of active learning for object detection is still largely unexplored as determining informativeness of an object-location hypothesis is more difficult. In this paper, we address this issue and present two metrics for measuring the informativeness of an object hypothesis,...

  4. Learning Microbiology Through Cooperation: Designing Cooperative Learning Activities that Promote Interdependence, Interaction, and Accountability

    Directory of Open Access Journals (Sweden)

    Janine E. Trempy


    Full Text Available A microbiology course and its corresponding learning activities have been structured according to the Cooperative Learning Model. This course, The World According to Microbes, integrates science, math, engineering, and technology (SMET majors and non-SMET majors into teams of students charged with problem solving activities that are microbial in origin. In this study we describe development of learning activities that utilize key components of Cooperative Learning—positive interdependence, promotive interaction, individual accountability, teamwork skills, and group processing. Assessments and evaluations over an 8-year period demonstrate high retention of key concepts in microbiology and high student satisfaction with the course.

  5. Active Reading Behaviors in Tablet-Based Learning (United States)

    Palilonis, Jennifer; Bolchini, Davide


    Active reading is fundamental to learning. However, there is little understanding about whether traditional active reading frameworks sufficiently characterize how learners study multimedia tablet textbooks. This paper explores the nature of active reading in the tablet environment through a qualitative study that engaged 30 students in an active…

  6. Active Learning: 101 Strategies To Teach Any Subject. (United States)

    Silberman, Mel

    This book contains specific, practical strategies that can be used for almost any subject matters to promote active learning. It brings together in one source a comprehensive collection of instructional strategies, with ways to get students to be active from the beginning through activities that build teamwork and get students thinking about the…

  7. Active Learning of Markov Decision Processes for System Verification

    DEFF Research Database (Denmark)

    Chen, Yingke; Nielsen, Thomas Dyhre


    deterministic Markov decision processes from data by actively guiding the selection of input actions. The algorithm is empirically analyzed by learning system models of slot machines, and it is demonstrated that the proposed active learning procedure can significantly reduce the amount of data required...... demanding process, and this shortcoming has motivated the development of algorithms for automatically learning system models from observed system behaviors. Recently, algorithms have been proposed for learning Markov decision process representations of reactive systems based on alternating sequences...... of input/output observations. While alleviating the problem of manually constructing a system model, the collection/generation of observed system behaviors can also prove demanding. Consequently we seek to minimize the amount of data required. In this paper we propose an algorithm for learning...


    Directory of Open Access Journals (Sweden)



    Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.

  9. Big data - modelling of midges in Europa using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Cuellar, Ana Carolina; Kjær, Lene Jung; Skovgaard, Henrik


    coordinates of each trap, start and end dates of trapping. We used 120 environmental predictor variables together with Random Forest machine learning algorithms to predict the overall species distribution (probability of occurrence) and monthly abundance in Europe. We generated maps for every month...... and the Obsoletus group, although abundance was generally higher for a longer period of time for C. imicula than for the Obsoletus group. Using machine learning techniques, we were able to model the spatial distribution in Europe for C. imicola and the Obsoletus group in terms of abundance and suitability...

  10. [Supporting an Academic Society with the Active Learning Tool Clica]. (United States)

    Arai, Kensuke; Mitsubori, Masahiro


     Within school classrooms, Active Learning has been receiving unprecedented attention. Indeed, Active Learning's popularity does not stop in the classroom. As more and more people argue that the Japanese government needs to renew guidelines for education, Active Learning has surfaced as a method capable of providing the necessary knowledge and training for people in all areas of society, helping them reach their full potential. It has become accepted that Active Learning is more effective over the passive listening of lectures, where there is little to no interaction. Active Learning emphasizes that learners explain their thoughts, ask questions, and express their opinions, resulting in a better retention rate of the subject at hand. In this review, I introduce an Active Learning support tool developed at Digital Knowledge, "Clica". This tool is currently being used at many educational institutions. I will also introduce an online questionnaire that Digital Knowledge provided at the 10th Annual Meeting of the Japanese Society for Pharmaceutical Palliative Care and Sciences.

  11. Integrative Student Learning: An Effective Team Learning Activity in a Learner-Centered Paradigm

    Directory of Open Access Journals (Sweden)

    Reza Karimi, RPh, PhD


    Full Text Available Purpose: An Integrative Student Learning (ISL activity was developed with the intent to enhance the dynamic of student teamwork and enhance student learning by fostering critical-thinking skills, self-directed learning skills, and active learning. Case Study: The ISL activity consists of three portions: teambuilding, teamwork, and a facilitator driven “closing the loop” feedback discussion. For teambuilding, a set of clue sheets or manufacturer‘s drug containers were distributed among student pairs who applied their pharmaceutical knowledge to identify two more student pairs with similar clues or drugs, thus building a team of six. For teamwork, each team completed online exams, composed of integrated pharmaceutical science questions with clinical correlates, using only selected online library resources. For the feedback discussion, facilitators evaluated student impressions, opened a discussion about the ISL activity, and provided feedback to teams’ impressions and questions. This study describes three different ISL activities developed and implemented over three days with first year pharmacy students. Facilitators’ interactions with students and three surveys indicated a majority of students preferred ISL over traditional team activities and over 90% agreed ISL activities promoted active learning, critical-thinking, self-directed learning, teamwork, and student confidence in online library searches. Conclusions: The ISL activity has proven to be an effective learning activity that promotes teamwork and integration of didactic pharmaceutical sciences to enhance student learning of didactic materials and confidence in searching online library resources. It was found that all of this can be accomplished in a short amount of class time with a very reasonable amount of preparation.

  12. Integrative Student Learning: An Effective Team Learning Activity in a Learner-Centered Paradigm

    Directory of Open Access Journals (Sweden)

    Reza Karimi


    Full Text Available Purpose: An Integrative Student Learning (ISL activity was developed with the intent to enhance the dynamic of student teamwork and enhance student learning by fostering critical-thinking skills, self-directed learning skills, and active learning. Case Study: The ISL activity consists of three portions: teambuilding, teamwork, and a facilitator driven "closing the loop" feedback discussion. For teambuilding, a set of clue sheets or manufacturer's drug containers were distributed among student pairs who applied their pharmaceutical knowledge to identify two more student pairs with similar clues or drugs, thus building a team of six. For teamwork, each team completed online exams, composed of integrated pharmaceutical science questions with clinical correlates, using only selected online library resources. For the feedback discussion, facilitators evaluated student impressions, opened a discussion about the ISL activity, and provided feedback to teams' impressions and questions. This study describes three different ISL activities developed and implemented over three days with first year pharmacy students. Facilitators' interactions with students and three surveys indicated a majority of students preferred ISL over traditional team activities and over 90% agreed ISL activities promoted active learning, critical-thinking, self-directed learning, teamwork, and student confidence in online library searches. Conclusions: The ISL activity has proven to be an effective learning activity that promotes teamwork and integration of didactic pharmaceutical sciences to enhance student learning of didactic materials and confidence in searching online library resources. It was found that all of this can be accomplished in a short amount of class time with a very reasonable amount of preparation.   Type: Case Study

  13. Active Multi-Field Learning for Spam Filtering


    Wuying Liu; Lin Wang; Mianzhu Yi; Nan Xie


    Ubiquitous spam messages cause a serious waste of time and resources. This paper addresses the practical spam filtering problem, and proposes a universal approach to fight with various spam messages. The proposed active multi-field learning approach is based on: 1) It is cost-sensitive to obtain a label for a real-world spam filter, which suggests an active learning idea; and 2) Different messages often have a similar multi-field text structure, which suggests a multi-field learning idea. The...

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


    Ma'mun, Sholeh


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

  15. Collaborative learning in higher education : design, implementation and evaluation of group learning activities

    NARCIS (Netherlands)

    Hei, de M.S.A.


    In higher education, group learning activities (GLAs) are frequently implemented in online, blended or face-to-face educational contexts. A major problem for the design and implementation of good quality GLAs that lead to the desired learning outcomes is that many approaches to GLAs have been

  16. Learning Active Citizenship: Conflicts between Students' Conceptualisations of Citizenship and Classroom Learning Experiences in Lebanon (United States)

    Akar, Bassel


    Education for active citizenship continues to be a critical response for social cohesion and reconstruction in conflict-affected areas. Oftentimes, approaches to learning and teaching in such contexts can do as much harm as good. This study qualitatively examines 435 students' reflections of their civics classroom learning experiences and their…

  17. Student's Reflections on Their Learning and Note-Taking Activities in a Blended Learning Course (United States)

    Nakayama, Minoru; Mutsuura, Kouichi; Yamamoto, Hiroh


    Student's emotional aspects are often discussed in order to promote better learning activity in blended learning courses. To observe these factors, course participant's self-efficacy and reflections upon their studies were surveyed, in addition to the surveying of the metrics of student's characteristics during a Bachelor level credit course.…

  18. Learning by Doing: Twenty Successful Active Learning Exercises for Information Systems Courses (United States)

    Mitchell, Alanah; Petter, Stacie; Harris, Albert L.


    Aim/Purpose: This paper provides a review of previously published work related to active learning in information systems (IS) courses. Background: There are a rising number of strategies in higher education that offer promise in regards to getting students' attention and helping them learn, such as flipped classrooms and offering courses online.…

  19. Teach them to Fly: Strategies for Encouraging Active Online Learning

    Directory of Open Access Journals (Sweden)

    Karen HARDIN


    that represent intellectual activity on each level of Bloom’s Taxonomy are: ( Application Apply, choose, demonstrate, dramatize, employ, illustrate, interpret, operate, practice, schedule, sketch, solve, use, write. Analysis Analyze, appraise, calculate, categorize, compare, contrast, criticize, differentiate, discriminate, distinguish, examine, experiment, question, test. Synthesis Arrange, assemble, collect, compose, construct, create, design, develop, formulate, manage, organize, plan, prepare, propose, set up, write. Evaluation Appraise, argue, assess, attach, choose compare, defend estimate, judge, predict, rate, core, select, support, value, evaluate. Instead of multiple choice questions, ask multiple answer questions. Instead of “all of the above,” or “none of the above,” require the student to select all correct answers. I use this technique regularly. Though students complain that they cannot eliminate incorrect possibilities, it is a better evaluation of their learning because students must analyze all answers, because any or all of them may be correct. William Pierce suggest another method of quizzing, “Design self-testing quizzes and tutorials on basic chapter content. Instructors can use the quiz as a gateway to the online discussion, allowing only those students who pass the quiz into the discussion.” As you continue to evaluate learning, when assessing the understanding of a concept, instead of asking students to re-state facts, ask them to apply concepts. When I teach web design to my online class, they learn the difference between screen-based layout and paper-based layout. When evaluating their learning, I give them links to different popular web pages and ask them to evaluate whether the page implements advised layout and design techniques. My course is project-based. After three projects that develop a basic understanding in Web design, students are required to build web sites for subject matter

  20. Active-constructive-interactive: a conceptual framework for differentiating learning activities. (United States)

    Chi, Michelene T H


    Active, constructive, and interactive are terms that are commonly used in the cognitive and learning sciences. They describe activities that can be undertaken by learners. However, the literature is actually not explicit about how these terms can be defined; whether they are distinct; and whether they refer to overt manifestations, learning processes, or learning outcomes. Thus, a framework is provided here that offers a way to differentiate active, constructive, and interactive in terms of observable overt activities and underlying learning processes. The framework generates a testable hypothesis for learning: that interactive activities are most likely to be better than constructive activities, which in turn might be better than active activities, which are better than being passive. Studies from the literature are cited to provide evidence in support of this hypothesis. Moreover, postulating underlying learning processes allows us to interpret evidence in the literature more accurately. Specifying distinct overt activities for active, constructive, and interactive also offers suggestions for how learning activities can be coded and how each kind of activity might be elicited. Copyright © 2009 Cognitive Science Society, Inc.

  1. Active learning increases student performance in science, engineering, and mathematics. (United States)

    Freeman, Scott; Eddy, Sarah L; McDonough, Miles; Smith, Michelle K; Okoroafor, Nnadozie; Jordt, Hannah; Wenderoth, Mary Pat


    To test the hypothesis that lecturing maximizes learning and course performance, we metaanalyzed 225 studies that reported data on examination scores or failure rates when comparing student performance in undergraduate science, technology, engineering, and mathematics (STEM) courses under traditional lecturing versus active learning. The effect sizes indicate that on average, student performance on examinations and concept inventories increased by 0.47 SDs under active learning (n = 158 studies), and that the odds ratio for failing was 1.95 under traditional lecturing (n = 67 studies). These results indicate that average examination scores improved by about 6% in active learning sections, and that students in classes with traditional lecturing were 1.5 times more likely to fail than were students in classes with active learning. Heterogeneity analyses indicated that both results hold across the STEM disciplines, that active learning increases scores on concept inventories more than on course examinations, and that active learning appears effective across all class sizes--although the greatest effects are in small (n ≤ 50) classes. Trim and fill analyses and fail-safe n calculations suggest that the results are not due to publication bias. The results also appear robust to variation in the methodological rigor of the included studies, based on the quality of controls over student quality and instructor identity. This is the largest and most comprehensive metaanalysis of undergraduate STEM education published to date. The results raise questions about the continued use of traditional lecturing as a control in research studies, and support active learning as the preferred, empirically validated teaching practice in regular classrooms.

  2. Elemental analysis of brazing alloy samples by neutron activation technique

    International Nuclear Information System (INIS)

    Eissa, E.A.; Rofail, N.B.; Hassan, A.M.; El-Shershaby, A.; Walley El-Dine, N.


    Two brazing alloy samples (C P 2 and C P 3 ) have been investigated by Neutron activation analysis (NAA) technique in order to identify and estimate their constituent elements. The pneumatic irradiation rabbit system (PIRS), installed at the first egyptian research reactor (ETRR-1) was used for short-time irradiation (30 s) with a thermal neutron flux of 1.6 x 10 1 1 n/cm 2 /s in the reactor reflector, where the thermal to epithermal neutron flux ratio is 106. Long-time irradiation (48 hours) was performed at reactor core periphery with thermal neutron flux of 3.34 x 10 1 2 n/cm 2 /s, and thermal to epithermal neutron flux ratio of 79. Activation by epithermal neutrons was taken into account for the (1/v) and resonance neutron absorption in both methods. A hyper pure germanium detection system was used for gamma-ray acquisitions. The concentration values of Al, Cr, Fe, Co, Cu, Zn, Se, Ag and Sb were estimated as percentages of the sample weight and compared with reported values. 1 tab

  3. Elemental analysis of brazing alloy samples by neutron activation technique

    Energy Technology Data Exchange (ETDEWEB)

    Eissa, E A; Rofail, N B; Hassan, A M [Reactor and Neutron physics Department, Nuclear Research Centre, Atomic Energy Authority, Cairo (Egypt); El-Shershaby, A; Walley El-Dine, N [Physics Department, Faculty of Girls, Ain Shams Universty, Cairo (Egypt)


    Two brazing alloy samples (C P{sup 2} and C P{sup 3}) have been investigated by Neutron activation analysis (NAA) technique in order to identify and estimate their constituent elements. The pneumatic irradiation rabbit system (PIRS), installed at the first egyptian research reactor (ETRR-1) was used for short-time irradiation (30 s) with a thermal neutron flux of 1.6 x 10{sup 1}1 n/cm{sup 2}/s in the reactor reflector, where the thermal to epithermal neutron flux ratio is 106. Long-time irradiation (48 hours) was performed at reactor core periphery with thermal neutron flux of 3.34 x 10{sup 1}2 n/cm{sup 2}/s, and thermal to epithermal neutron flux ratio of 79. Activation by epithermal neutrons was taken into account for the (1/v) and resonance neutron absorption in both methods. A hyper pure germanium detection system was used for gamma-ray acquisitions. The concentration values of Al, Cr, Fe, Co, Cu, Zn, Se, Ag and Sb were estimated as percentages of the sample weight and compared with reported values. 1 tab.

  4. Tracing salmon to their birthplace by activable tracer technique

    International Nuclear Information System (INIS)

    Shibuya, Masao


    Activable tracer technique was applied to trace the recurrent migration of white salmons, as a typical example of employing radioactivation analysis to the study of agricultural and marinefields. Europium was adopted because it is easy to use technically with less influence on fish body and easy to detect, and its remaining time is very long. Artificially hatched young white salmons were stocked in the Saibetsu River after being raised for a month with europium-containing feed. These stocked fish were labeled by fin-cutting method. Recurrent salmons (fin cutting-labeled fish) were then collected and dissected. The fishes were divided into otoliths, scales, flesh, internal organs, gills, bones, etc., and irradiated for 5 min in JRR-2 reactor of Japan Atomic Energy Research Institute. Europium was detected from the scales and otoliths of 3 to 4 year stocked adult fishes by γ-spectrometry of Eu. This proved the availability of activable tracer method for tracing the recurrent migration of salmons. (Kobatake, H.)

  5. Competency and an active learning program in undergraduate nursing education. (United States)

    Shin, Hyunsook; Sok, Sohyune; Hyun, Kyung Sun; Kim, Mi Ja


    To evaluate the effect of an active learning program on competency of senior students. Active learning strategies have been used to help students achieve desired nursing competency, but their effectiveness has not been systematically examined. A descriptive, cross-sectional comparative design was used. Two cohort group comparisons using t-test were made: one in an active learning group and the other in a traditional learning group. A total of 147 senior nursing students near graduation participated in this study: 73 in 2010 and 74 in 2013. The active learning program incorporated high-fidelity simulation, situation-based case studies, standardized patients, audio-video playback, reflective activities and technology such as a SmartPad-based program. The overall scores of the nursing competency in the active group were significantly higher than those in the traditional group. Of five overall subdomains, the scores of the special and general clinical performance competency, critical thinking and human understanding were significantly higher in the active group than in the traditional group. Importance-performance analysis showed that all five subdomains of the active group clustered in the high importance and high performance quadrant, indicating significantly better achievements. In contrast, the students in the traditional group showed scattered patterns in three quadrants, excluding the low importance and low performance quadrants. This pattern indicates that the traditional learning method did not yield the high performance in most important areas. The findings of this study suggest that an active learning strategy is useful for helping undergraduate students to gain competency. © 2014 John Wiley & Sons Ltd.

  6. Improvements in Students' Understanding from Increased Implementation of Active Learning Strategies (United States)

    Hayes-Gehrke, Melissa N.; Prather, E. E.; Rudolph, A. L.; Collaboration of Astronomy Teaching Scholars CATS


    Many instructors are hesitant to implement active learning strategies in their introductory astronomy classrooms because they are not sure which techniques they should use, how to implement those techniques, and question whether the investment in changing their course will really bring the advertised learning gains. We present an example illustrating how thoughtful and systematic implementation of active learning strategies into a traditionally taught Astro 101 class can translate into significant increases in students' understanding. We detail the journey of one instructor, over several years, as she changes the instruction and design of her course from one that focuses almost exclusively on lecture to a course that provides an integrated use of several active learning techniques such as Lecture-Tutorials and Think-Pair-Share questions. The students in the initial lecture-only course achieved a low normalized gain score of only 0.2 on the Light and Spectroscopy Concept Inventory (LSCI), while the students in the re-designed learner-centered course achieved a significantly better normalized gain of 0.43. This material is based upon work supported by the National Science Foundation under Grant No. 0715517, a CCLI Phase III Grant for the Collaboration of Astronomy Teaching Scholars (CATS), and Grant No. 0847170, a PAARE Grant for the Calfornia-Arizona Minority Partnership for Astronomy Research and Education (CAMPARE). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

  7. Learning Is a Do-It-Yourself Activity (United States)

    Moore, John W.


    distractions now than then. And students' reasons for taking a chemistry course probably span a much greater range. How then do we get them engaged? Nash developed the idea that the most effective thing a teacher can do is to be an example of what it means to be a scientist. In the presence of students, teachers should demonstrate commitment and enthusiasm for their subject, ask questions of nature and obtain answers, think logically and with clarity, and respect and encourage their students' potential ability to engage in scientific inquiry. Though I am certain that he was an exemplar of Nash's approach, Ramette espoused a different one. To help students ask questions and find answers for themselves, he designed computer programs that can present a broad range of problems in a specific area, encourage students to think about how to address the problems, and then provide feedback on their approach. I have used two of these, KinWORKS and REACT, for the past half dozen years and find them quite effective. Both are available from JCE Software. There are many other approaches to engaging students actively in the learning process. The NSF has funded five systemic chemistry projects, and all of them have developed active-learning methods. New Traditions ( has an array of techniques ranging from ConcepTests in lectures and Challenge Problems for small-group work, through inquiry-based laboratories, to lecture-less courses in which students spend most of their class time working on problems that have been carefully designed to lead them to develop new insights. ChemLinks ( and Modular Chemistry Consortium ( are jointly developing thematic modules in which students learn chemical principles by studying a real-world problem such as how to make a blue LED, or what it takes to make an automobile air bag. The Workshop Chemistry project ( involves students

  8. Effectiveness of Student's Note-Taking Activities and Characteristics of Their Learning Performance in Two Types of Online Learning (United States)

    Nakayama, Minoru; Mutsuura, Kouichi; Yamamoto, Hiroh


    Aspects of learning behavior during two types of university courses, a blended learning course and a fully online course, were examined using note-taking activity. The contribution of students' characteristics and styles of learning to note-taking activity and learning performance were analyzed, and the relationships between the two types of…

  9. The planning illusion: Does active planning of a learning route support learning as well as learners think it does?

    NARCIS (Netherlands)

    Bonestroo, W.J.; de Jong, Anthonius J.M.


    Is actively planning one’s learning route through a learning domain beneficial for learning? Moreover, can learners accurately judge the extent to which planning has been beneficial for them? This study examined the effects of active planning on learning. Participants received a tool in which they

  10. Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

    CERN Document Server

    Ratner, Bruce


    The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

  11. Active Learning Classrooms and Educational Alliances: Changing Relationships to Improve Learning (United States)

    Baepler, Paul; Walker, J. D.


    This chapter explores the "educational alliance" among students and between students and instructors. We contend that this is a framework that can help us understand how active learning classrooms facilitate positive educational outcomes.

  12. Research and Teaching: Instructor Use of Group Active Learning in an Introductory Biology Sequence (United States)

    Auerbach, Anna Jo; Schussler, Elisabeth E.


    Active learning (or learner-centered) pedagogies have been shown to enhance student learning in introductory biology courses. Student collaboration has also been shown to enhance student learning and may be a critical part of effective active learning practices. This study focused on documenting the use of individual active learning and group…

  13. Active Learning: Qualitative Inquiries into Vocabulary Instruction in Chinese L2 Classrooms (United States)

    Shen, Helen H.; Xu, Wenjing


    Active learning emerged as a new approach to learning in the 1980s. The core concept of active learning involves engaging students not only in actively exploring knowledge but also in reflecting on their own learning process in order to become more effective learners. Because the nonalphabetic nature of the Chinese writing system makes learning to…

  14. A Cultural Psychological Approach to Analyze Intercultural Learning: Potential and Limits of the Structure Formation Technique

    Directory of Open Access Journals (Sweden)

    Doris Weidemann


    Full Text Available Despite the huge interest in sojourner adjustment, there is still a lack of qualitative as well as of longitudinal research that would offer more detailed insights into intercultural learning processes during overseas stays. The present study aims to partly fill that gap by documenting changes in knowledge structures and general living experiences of fifteen German sojourners in Taiwan in a longitudinal, cultural-psychological study. As part of a multimethod design a structure formation technique was used to document subjective theories on giving/losing face and their changes over time. In a second step results from this study are compared to knowledge-structures of seven long-term German residents in Taiwan, and implications for the conceptualization of intercultural learning will be proposed. Finally, results from both studies serve to discuss the potential and limits of structure formation techniques in the field of intercultural communication research. URN: urn:nbn:de:0114-fqs0901435

  15. A Bridge to Active Learning: A Summer Bridge Program Helps Students Maximize Their Active-Learning Experiences and the Active-Learning Experiences of Others (United States)

    Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.


    National calls to improve student academic success in college have sparked the development of bridge programs designed to help students transition from high school to college. We designed a 2-week Summer Bridge program that taught introductory biology content in an active-learning way. Through a set of exploratory interviews, we unexpectedly…

  16. A Nap But Not Rest or Activity Consolidates Language Learning

    Directory of Open Access Journals (Sweden)

    Stefan Heim


    Full Text Available Recent evidence suggests that a period of sleep after a motor learning task is a relevant factor for memory consolidation. However, it is yet open whether this also holds true for language-related learning. Therefore, the present study compared the short- and long-term effects of a daytime nap, rest, or an activity task after vocabulary learning on learning outcome. Thirty healthy subjects were divided into three treatment groups. Each group received a pseudo-word learning task in which pictures of monsters were associated with unique pseudo-word names. At the end of the learning block a first test was administered. Then, one group went for a 90-min nap, one for a waking rest period, and one for a resting session with interfering activity at the end during which a new set of monster names was to be learned. After this block, all groups performed a first re-test of the names that they initially learned. On the morning of the following day, a second re-test was administered to all groups. The nap group showed significant improvement from test to re-test and a stable performance onto the second re-test. In contrast, the rest and the interference groups showed decline in performance from test to re-test, with persistently low performance at re-test 2. The 3 (GROUP × 3 (TIME ANOVA revealed a significant interaction, indicating that the type of activity (nap/rest/interfering action after initial learning actually had an influence on the memory outcome. These data are discussed with respect to translation to clinical settings with suggestions for improvement of intervention outcome after speech-language therapy if it is followed by a nap rather than interfering activity.

  17. The Managers’ Experiential Learning of Program Planning in Active Ageing Learning Centers

    Directory of Open Access Journals (Sweden)

    Chun-Ting Yeh


    Full Text Available Planning older adult learning programs is really a complex work. Program planners go through different learning stages and accumulate experiences to be able to undertake the task alone. This study aimed to explore the experiential learning process of older adult learning program planners who work in the Active Ageing Learning Centers (AALCs. Semi-structure interviews were conducted with seven program planners. The findings of this study were identified as follows. 1 Before being a program planner, the participants’ knowledge results from grasping and transforming experience gained from their family, their daily lives and past learning experiences; 2 after being a program planner, the participants’ experiential learning focused on leadership, training in the institute, professional development, as well as involvement in organizations for elderly people; and 3 the participants’ experiential learning outcomes in the older adult learning program planning include: their ability to reflect on the appropriateness and fulfillment of program planning, to apply theoretical knowledge and professional background in the field, and to make plans for future learning and business strategies.

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

    Directory of Open Access Journals (Sweden)

    Arthur Shelley


    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.

  19. Approximate multi-state reliability expressions using a new machine learning technique

    International Nuclear Information System (INIS)

    Rocco S, Claudio M.; Muselli, Marco


    The machine-learning-based methodology, previously proposed by the authors for approximating binary reliability expressions, is now extended to develop a new algorithm, based on the procedure of Hamming Clustering, which is capable to deal with multi-state systems and any success criterion. The proposed technique is presented in details and verified on literature cases: experiment results show that the new algorithm yields excellent predictions

  20. Novel Machine Learning-Based Techniques for Efficient Resource Allocation in Next Generation Wireless Networks

    KAUST Repository

    AlQuerm, Ismail A.


    There is a large demand for applications of high data rates in wireless networks. These networks are becoming more complex and challenging to manage due to the heterogeneity of users and applications specifically in sophisticated networks such as the upcoming 5G. Energy efficiency in the future 5G network is one of the essential problems that needs consideration due to the interference and heterogeneity of the network topology. Smart resource allocation, environmental adaptivity, user-awareness and energy efficiency are essential features in the future networks. It is important to support these features at different networks topologies with various applications. Cognitive radio has been found to be the paradigm that is able to satisfy the above requirements. It is a very interdisciplinary topic that incorporates flexible system architectures, machine learning, context awareness and cooperative networking. Mitola’s vision about cognitive radio intended to build context-sensitive smart radios that are able to adapt to the wireless environment conditions while maintaining quality of service support for different applications. Artificial intelligence techniques including heuristics algorithms and machine learning are the shining tools that are employed to serve the new vision of cognitive radio. In addition, these techniques show a potential to be utilized in an efficient resource allocation for the upcoming 5G networks’ structures such as heterogeneous multi-tier 5G networks and heterogeneous cloud radio access networks due to their capability to allocate resources according to real-time data analytics. In this thesis, we study cognitive radio from a system point of view focusing closely on architectures, artificial intelligence techniques that can enable intelligent radio resource allocation and efficient radio parameters reconfiguration. We propose a modular cognitive resource management architecture, which facilitates a development of flexible control for