Example-based learning: Integrating cognitive and social-cognitive research perspectives

NARCIS (Netherlands)

T.A.J.M. van Gog (Tamara); N. Rummel (Nikol)

2010-01-01

textabstractExample-based learning has been studied from different perspectives. Cognitive research has mainly focused on worked examples, which typically provide students with a written worked-out didactical solution to a problem to study. Social-cognitive research has mostly focused on modeling

On-line learning from clustered input examples

NARCIS (Netherlands)

Riegler, Peter; Biehl, Michael; Solla, Sara A.; Marangi, Carmela; Marinaro, Maria; Tagliaferri, Roberto

1996-01-01

We analyse on-line learning of a linearly separable rule with a simple perceptron. Example inputs are taken from two overlapping clusters of data and the rule is defined through a teacher vector which is in general not aligned with the connection line of the cluster centers. We find that the Hebb

Example-based learning: comparing the effects of additionally providing three different integrative learning activities on physiotherapy intervention knowledge

NARCIS (Netherlands)

J.-O. Dyer (Joseph-Omer); A. Hudon (Anne); K. Montpetit-Tourangeau (Katherine); B. Charlin (Bernard); S. Mamede (Silvia); T.A.J.M. van Gog (Tamara)

2015-01-01

textabstractBACKGROUND: Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of

Example-based learning: Comparing the effects of additionally providing three different integrative learning activities on physiotherapy intervention knowledge Approaches to teaching and learning

NARCIS (Netherlands)

J.-O. Dyer (Joseph-Omer); A. Hudon (Anne); K. Montpetit-Tourangeau (Katherine); B. Charlin (Bernard); S. Mamede (Silvia); T.A.J.M. van Gog (Tamara)

2015-01-01

textabstractBackground: Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of

Imitation and Education: A Philosophical Inquiry into Learning by Example

Science.gov (United States)

Warnick, Bryan R.

2008-01-01

"Imitation and Education" provides an in-depth reassessment of learning by example that places imitation in a larger social context. It is the first book to bring together ancient educational thought and startling breakthroughs in the fields of cognitive science, psychology, and philosophy to reconsider how we learn from the lives of…

Personalized Resource Recommendations using Learning from Positive and Unlabeled Examples

Directory of Open Access Journals (Sweden)

Priyank Thakkar

2016-08-01

Full Text Available This paper proposes a novel approach for recommending social resources using learning from positive and unlabeled examples. Bookmarks submitted on social bookmarking system delicious1 and artists on online music system last.fm2 are considered as social resources. The foremost feature of this problem is that there are no labeled negative resources/examples available for learning a recommender/classifier. The memory based collaborative filtering has served as the most widely used algorithm for social resource recommendation. However, its predictions are based on some ad hoc heuristic rules and its success depends on the availability of a critical mass of users. This paper proposes model based two-step techniques to learn a classifier using positive and unlabeled examples to address personalized resource recommendations. In the first step of these techniques, naïve Bayes classifier is employed to identify reliable negative resources. In the second step, to generate effective resource recommender, classification and regression tree and least square support vector machine (LS-SVM are exercised. A direct method based on LS-SVM is also put forward to realize the recommendation task. LS-SVM is customized for learning from positive and unlabeled data. Furthermore, the impact of feature selection on our proposed techniques is also studied. Memory based collaborative filtering as well as our proposed techniques exploit usage data to generate personalized recommendations. Experimental results show that the proposed techniques outperform existing method appreciably.

Statics learning from engineering examples

CERN Document Server

Emri, Igor

2016-01-01

This textbook introduces and explains the basic concepts on which statics is based utilizing real engineering examples. The authors emphasize the learning process by showing a real problem, analyzing it, simplifying it, and developing a way to solve it. This feature teaches students intuitive thinking in solving real engineering problems using the fundamentals of Newton’s laws. This book also: · Stresses representation of physical reality in ways that allow students to solve problems and obtain meaningful results · Emphasizes identification of important features of the structure that should be included in a model and which features may be omitted · Facilitates students' understanding and mastery of the "flow of thinking" practiced by professional engineers.

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

Science.gov (United States)

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and

Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account

Science.gov (United States)

Renkl, Alexander; Hilbert, Tatjana; Schworm, Silke

2009-01-01

One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies…

Adolescents with specific learning disabilities - perceptions of specific learning disabilities in the environment of secondary schools

OpenAIRE

Pospíšilová, Zuzana

2012-01-01

The thesis focuses on adolescents with specific learning disabilities in the milieu of secondary schools. It is divided into a theoretical part and an empirical part. The first part introduces a topic of specific learning disabilities in the developmental stage of adolescence. It first describes the most relevant aspects of adolescent development. The attention is then paid to typical manifestations of specific learning disabilities in adolescence, and also to secondary symptoms usually conne...

Design Guidelines for Collaboration and Participation with Examples from the LN4LD (Learning Network for Learning Design)

NARCIS (Netherlands)

Burgos, Daniel; Hummel, Hans; Tattersall, Colin; Brouns, Francis; Koper, Rob

2007-01-01

Burgos, D., Hummel, H. G. K., Tattersall, C., Brouns, F., & Koper, R. (2009). Design Guidelines for Collaboration and Participation with Examples from the LN4LD (Learning Network for Learning Design). In L. Lockyer, S. Bennett, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design

An introduction to Deep learning on biological sequence data - Examples and solutions

DEFF Research Database (Denmark)

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten

2017-01-01

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use....... Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively...

Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model

Science.gov (United States)

Panda, Priyadarshini; Srinivasa, Narayan

2018-01-01

A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccades influence visual perception, to extract spike information from raw video data while preserving the temporal correlation across different frames. Using this encoding, we show that the reservoir generalizes its rich dynamical activity toward signature action/movements enabling it to learn from few training examples. We evaluate our approach on the UCF-101 dataset. Our experiments demonstrate that our proposed reservoir achieves 81.3/87% Top-1/Top-5 accuracy, respectively, on the 101-class data while requiring just 8 video examples per class for training. Our results establish a new benchmark for action recognition from limited video examples for spiking neural models while yielding competitive accuracy with respect to state-of-the-art non-spiking neural models. PMID:29551962

Inductive learning of thyroid functional states using the ID3 algorithm. The effect of poor examples on the learning result.

Science.gov (United States)

Forsström, J

1992-01-01

The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.

34 CFR 300.307 - Specific learning disabilities.

Science.gov (United States)

2010-07-01

... 34 Education 2 2010-07-01 2010-07-01 false Specific learning disabilities. 300.307 Section 300.307... Educational Placements Additional Procedures for Identifying Children with Specific Learning Disabilities § 300.307 Specific learning disabilities. (a) General. A State must adopt, consistent with § 300.309...

Learning from video modeling examples : Effects of seeing the human model's face

NARCIS (Netherlands)

Van Gog, Tamara; Verveer, Ilse; Verveer, Lise

2014-01-01

Video modeling examples in which a human(-like) model shows learners how to perform a task are increasingly used in education, as they have become very easy to create and distribute in e-learning environments. However, little is known about design guidelines to optimize learning from video modeling

Learning Argumentation Skills through the Use of Prompts for Self-Explaining Examples

Science.gov (United States)

Schworm, Silke; Renkl, Alexander

2007-01-01

Learning with self-explaining examples is an effective method in well-structured domains. The authors analyzed this method in teaching the complex skill of argumentation, experimentally comparing 4 conditions (N = 71 student teachers) that differed with respect to whether and how the processing of the examples was supported by self-explanation…

Differential-associative processing or example elaboration: Which strategy is best for learning the definitions of related and unrelated concepts?

Science.gov (United States)

Hannon, Brenda

2012-10-01

Definitions of related concepts (e.g., genotype - phenotype ) are prevalent in introductory classes. Consequently, it is important that educators and students know which strategy(s) work best for learning them. This study showed that a new comparative elaboration strategy, called differential-associative processing, was better for learning definitions of related concepts than was an integrative elaborative strategy, called example elaboration. This outcome occurred even though example elaboration was administered in a naturalistic way (Experiment 1) and students spent more time in the example elaboration condition learning (Experiments 1, 2, 3), and generating pieces of information about the concepts (Experiments 2 and 3). Further, with unrelated concepts ( morpheme-fluid intelligence ), performance was similar regardless if students used differential-associative processing or example elaboration (Experiment 3). Taken as a whole, these results suggest that differential-associative processing is better than example elaboration for learning definitions of related concepts and is as good as example elaboration for learning definitions of unrelated concepts.

Learning and Understanding System Stability Using Illustrative Dynamic Texture Examples

Science.gov (United States)

Liu, Huaping; Xiao, Wei; Zhao, Hongyan; Sun, Fuchun

2014-01-01

System stability is a basic concept in courses on dynamic system analysis and control for undergraduate students with computer science backgrounds. Typically, this was taught using a simple simulation example of an inverted pendulum. Unfortunately, many difficult issues arise in the learning and understanding of the concepts of stability,…

STEM-related, Student-led Service Learning / Community Engagement Projects: Examples and Benefits

Science.gov (United States)

Swap, R. J.; Wayland, K.

2015-12-01

Field-based, STEM-related service learning / community engagement projects present an opportunity for undergraduate students to demonstrate proficiencies related to the process of inquiry. These proficiencies include: appreciation of the larger project context, articulation of an informed question/hypothesis, project proposal development, interdisciplinary collaboration, project management (including planning, implementation reconfiguration and synthesis) and lastly the generation and handing off of acquired knowledge. Calls for these types of proficiencies have been expressed by governmental, non-governmental as well as the private sector. Accordingly, institutions of higher learning have viewed such activities as opportunities for enriching the learning experience for undergraduate students and for making such students more marketable, especially those from STEM-related fields. This institutional interest has provided an opportunity to support and expand field-based learning. Here we present examples of student-led/faculty-mentored international service learning and community engagement projects along the arc of preparation, implementation and post-field process. Representative examples that draw upon environmental science and engineering knowledge have been selected from more than 20 international undergraduate student projects over past decade and include: slow-sand water filtration, rainwater harvesting, methane biodigesters, water reticulation schemes and development and implementation of rocket stoves for communal cooking. We discuss these efforts in terms of the development of the aforementioned proficiencies, the utility of such proficiencies to the larger enterprise of STEM and the potential for transformative student learning outcomes. We share these experiences and lessons learned with the hope that others may intelligently borrow from our approach in a manner appropriate for their particular context.

An introduction to deep learning on biological sequence data: examples and solutions.

Science.gov (United States)

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Zen of cloud learning cloud computing by examples on Microsoft Azure

CERN Document Server

Bai, Haishi

2014-01-01

Zen of Cloud: Learning Cloud Computing by Examples on Microsoft Azure provides comprehensive coverage of the essential theories behind cloud computing and the Windows Azure cloud platform. Sharing the author's insights gained while working at Microsoft's headquarters, it presents nearly 70 end-to-end examples with step-by-step guidance on implementing typical cloud-based scenarios.The book is organized into four sections: cloud service fundamentals, cloud solutions, devices and cloud, and system integration and project management. Each chapter contains detailed exercises that provide readers w

Sequence-specific procedural learning deficits in children with specific language impairment.

Science.gov (United States)

Hsu, Hsinjen Julie; Bishop, Dorothy V M

2014-05-01

This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children's performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7- to 11-year-old children with SLI (n = 48), typically developing age-matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar-matched children, but poorer than age-matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age-matched children and better than younger grammar-matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence-specific information, rather than generally weak procedural learning. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

Example and Non-Example Pada Pembelajaran Matematika

OpenAIRE

Yunarto, Wanda Nugroho

2016-01-01

Abstrak Example and Non-Example Learning Model merupakan model pembelajaran yang menggunakan gambar sebagai media pembelajaran yang bertujuan mendorong mahasiswa untuk belajar berfikir kritis dengan jalan memecahkan permasalahan-permasalahan yang terkandung dalam contoh-contoh permasalahan/ konsep yang disajikan. Tujuan dari penelitian ini adalah mendapatkan gambaran mengenai bagaimana penerapan model pembelajaran Example and non-Example pada mahasiswa program studi Pendidikan Matematika Univ...

Statistical physics of learning from examples: a brief introduction

International Nuclear Information System (INIS)

Broeck, C. van den

1994-01-01

The problem of how one can learn from examples is illustrated on the case of a student perception trained by the Hebb rule on examples generated by a teacher perception. Two basic quantities are calculated: the training error and the generalization error. The obtained results are found to be typical. Other training rules are discussed. For the case of an Ising student with an Ising teacher, the existence of a first order phase transition is shown. Special effects such as dilution, queries, rejection, etc. are discussed and some results for multilayer networks are reviewed. In particular, the properties of a self-similar committee machine are derived. Finally, we discuss the statistic of generalization, with a review of the Hoeffding inequality, the Dvoretzky Kiefer Wolfowitz theorem and the Vapnik Chervonenkis theorem. (author). 29 refs, 6 figs

Teaching Foreign Languages to Pupils with Specific Learning Disability

OpenAIRE

VOLDÁNOVÁ, Veronika

2015-01-01

This diploma thesis deals with the topic of specific learning disability. In the theoretical part I define the term specific learning disability and I mention the related terms. I deal with the history, types and causes of specific learning disability, further I describe the possibilities of diagnostics and re-education concerning specific learning disability. I also attend to the situation of a pupil in the family and school background. The main attention is especially paid to teaching forei...

Effects of creating video-based modeling examples on learning and transfer

NARCIS (Netherlands)

Hoogerheide, Vincent; Loyens, Sofie M M; van Gog, Tamara

2014-01-01

Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study

Operant Conditioning and Learning: Examples, Sources, Technology.

Science.gov (United States)

Pedrini, Bonnie C.; Pedrini, D. T.

The purpose of this paper is to relate psychology to teaching generally, and to relate behavior shaping to curriculum, specifically. Focusing on operant conditioning and learning, many studies are cited which illustrate some of the work being done toward effectively shaping or modifying student behavior whether in terms of subject matter or…

Issues in Institutional Benchmarking of Student Learning Outcomes Using Case Examples

Science.gov (United States)

Judd, Thomas P.; Pondish, Christopher; Secolsky, Charles

2013-01-01

Benchmarking is a process that can take place at both the inter-institutional and intra-institutional level. This paper focuses on benchmarking intra-institutional student learning outcomes using case examples. The findings of the study illustrate the point that when the outcomes statements associated with the mission of the institution are…

Effects of Worked Examples, Example-Problem Pairs, and Problem-Example Pairs Compared to Problem Solving

NARCIS (Netherlands)

Van Gog, Tamara; Kester, Liesbeth; Paas, Fred

2010-01-01

Van Gog, T., Kester, L., & Paas, F. (2010, August). Effects of worked examples, example-problem pairs, and problem-example pairs compared to problem solving. Paper presented at the Biannual EARLI SIG meeting of Instructional design and Learning and instruction with computers, Ulm, Germany.

Specificity, transfer, and the development of expertise

Directory of Open Access Journals (Sweden)

David T. Brookes

2011-04-01

Full Text Available In this paper we present the results of two experiments designed to understand how physics students’ learning of the concept of refraction is influenced by the cognitive phenomenon of “specificity.” In both experiments participants learned why light bends as it travels from one optical medium to another with an analogy made to a car driving from paved road into mud and vice versa. They then learned how to qualitatively draw the direction of refracted light rays with an example of a glass prism. One group learned with a rectangular prism example while a second group learned with a triangular prism example. In a transfer test, the participants revealed how, even when they seemed able to implement the refraction concept, their responses were biased by the example they had seen. Participants frequently violated the refraction principle they had just learned (reversing the bend direction in order to make sure their response matched the surface features of their learning example. This tended to happen when their test question looked superficially similar to their learning example. We discuss the implications of these results for physics instruction.

Specificity, transfer, and the development of expertise

Directory of Open Access Journals (Sweden)

David T. Brookes

2011-04-01

Full Text Available In this paper we present the results of two experiments designed to understand how physics students’ learning of the concept of refraction is influenced by the cognitive phenomenon of “specificity.” In both experiments participants learned why light bends as it travels from one optical medium to another with an analogy made to a car driving from paved road into mud and vice versa. They then learned how to qualitatively draw the direction of refracted light rays with an example of a glass prism. One group learned with a rectangular prism example while a second group learned with a triangular prism example. In a transfer test, the participants revealed how, even when they seemed able to implement the refraction concept, their responses were biased by the example they had seen. Participants frequently violated the refraction principle they had just learned (reversing the bend direction in order to make sure their response matched the surface features of their learning example. This tended to happen when their test question looked superficially similar to their learning example. We discuss the implications of these results for physics instruction.

Alpha particle effects in burning tokamak plasmas: overview and specific examples

International Nuclear Information System (INIS)

Sigmar, D.J.

1986-07-01

Using the total power balance of an ignited tokamak plasma as a guideline, a range of alpha driven effects is surveyed regarding their impact on achieving and maintaining fusion burn. Specific examples of MHD and kinetic modes and multi species transport dynamics are discussed, including the possible interaction of these categories of effects. This power balance approach rather than a straightforward enumeration of possible effects serves to reveal their non-linear dependence and the ensuing fragility of our understanding of the approach to and maintenance of ignition. Specific examples are given of the interaction between α-power driven sawtoothing and ideal MHD stability, and direct α-effects on MHD modes including kinetic corrections. Anomalous ion heat transport and central impurity peaking mechanisms and anomalous and collisional α-transport including the ambipolar electric field are discussed

Greek Young Adults with Specific Learning Disabilities Seeking Learning Assessments

Science.gov (United States)

Bonti, Eleni; Bampalou, Christina E.; Kouimtzi, Eleni M.; Kyritsis, Zacharias

2018-01-01

The purpose of this study is to investigate the reasons why Greek young adults with Specific Learning Disabilities (SLD) seek learning assessments. The study sample consisted of 106 adults meeting Diagnostic and Statistical Manual of Mental Disorders criteria for SLD. Data were collected through self-report records (clinical interview) of adults…

Workplace Learning by Action Learning: A Practical Example.

Science.gov (United States)

Miller, Peter

2003-01-01

An action learning approach to help managers enhance learning capacity involved a performance management seminar, work by action learning sets, implementation of a new performance management instrument with mentoring by action learning facilitators, and evaluation. Survey responses from 392 participants revealed satisfaction with managerial…

Learning with multiple representations: an example of a revision lesson in mechanics

Science.gov (United States)

Wong, Darren; Poo, Sng Peng; Eng Hock, Ng; Loo Kang, Wee

2011-03-01

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.

Worked Examples with Errors: When Self-Explanation Prompts Hinder Learning of Teachers Diagnostic Competences on Problem-Based Learning

Science.gov (United States)

Heitzmann, Nicole; Fischer, Frank; Fischer, Martin R.

2018-01-01

To diagnose classroom situations is crucial for teachers' everyday practice. The approach of worked examples with errors seems promising to support the diagnosis of classroom situations in student teachers (Stark et al. in "Learn Instr" 21(1):22-33, 2011). To enhance that approach, error-explanation prompts and an adaptable feedback…

Learning with Multiple Representations: An Example of a Revision Lesson in Mathematics

Science.gov (United States)

Wong, Darren; Poo, Sng Peng; Hock, Ng Eng; Kang, Wee Loo

2011-01-01

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion…

E-learning in an undergraduate radiography programme: Example of an interactive website

International Nuclear Information System (INIS)

White, Peter; Cheung, Alice K.Y.

2006-01-01

Purpose: To demonstrate how e-learning can be integrated into an undergraduate radiography programme, using an academic subject dealing with ethico-legal issues as an example. Information provided could be applied to any form of online learning. Methods: One academic subject from an undergraduate radiography programme, Case-Based Learning for Professional Studies, which had previously been taught using traditional face-to-face methods, was transformed into an e-learning format. Students who experienced the new e-learning format were evaluated by means of an online evaluation questionnaire. Results: Eighty-three percentage of respondents felt confident/semi-confident about participating in online Chat sessions. Around 34% of respondents thought that the Discussion Board was useful for communicating with fellow students. Nearly 70% of respondents believed that access to online materials enabled them to prepare for lectures and tutorials. However, 34% of students preferred more face-to-face lectures/tutorials. Overall, feedback was positive. Conclusion: Course providers and other relevant stakeholders need to be proactive in determining ways to facilitate undergraduate and post-registration development and learning. E-learning can be utilized to benefit learners who wish to work at their own pace and who cannot attend courses at remote sites. Individuals can reap the benefits of an online learning format and affording learners more flexibility and providing guidance for them, by means of a website, may help to promote a positive attitude to lifelong learning

E-learning in an undergraduate radiography programme: Example of an interactive website

Energy Technology Data Exchange (ETDEWEB)

White, Peter [Department of Optometry and Radiography, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)]. E-mail: orpwhite@polyu.edu.hk; Cheung, Alice K.Y. [Department of Optometry and Radiography, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)]. E-mail: alice.cheung@iee.org

2006-08-15

Purpose: To demonstrate how e-learning can be integrated into an undergraduate radiography programme, using an academic subject dealing with ethico-legal issues as an example. Information provided could be applied to any form of online learning. Methods: One academic subject from an undergraduate radiography programme, Case-Based Learning for Professional Studies, which had previously been taught using traditional face-to-face methods, was transformed into an e-learning format. Students who experienced the new e-learning format were evaluated by means of an online evaluation questionnaire. Results: Eighty-three percentage of respondents felt confident/semi-confident about participating in online Chat sessions. Around 34% of respondents thought that the Discussion Board was useful for communicating with fellow students. Nearly 70% of respondents believed that access to online materials enabled them to prepare for lectures and tutorials. However, 34% of students preferred more face-to-face lectures/tutorials. Overall, feedback was positive. Conclusion: Course providers and other relevant stakeholders need to be proactive in determining ways to facilitate undergraduate and post-registration development and learning. E-learning can be utilized to benefit learners who wish to work at their own pace and who cannot attend courses at remote sites. Individuals can reap the benefits of an online learning format and affording learners more flexibility and providing guidance for them, by means of a website, may help to promote a positive attitude to lifelong learning.

Pitch discrimination learning: specificity for pitch and harmonic resolvability, and electrophysiological correlates.

Science.gov (United States)

Carcagno, Samuele; Plack, Christopher J

2011-08-01

Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed in pitch and/or spectral resolvability of their components by the cochlea, but were filtered into the same spectral region. Cortical-evoked potentials and a behavioral measure of pitch discrimination were assessed before and after training for all the four complexes. The change in these measures was compared to that of two control groups: one trained on a level discrimination task and one without any training. The behavioral results showed that learning was partly specific to both pitch and resolvability. Training with a resolved-harmonic complex improved pitch discrimination for resolved complexes more than training with an unresolved complex. However, we did not find evidence that training with an unresolved complex leads to specific learning for unresolved complexes. Training affected the P2 component of the cortical-evoked potentials, as well as a later component (250-400 ms). No significant changes were found on the mismatch negativity (MMN) component, although a separate experiment showed that this measure was sensitive to pitch changes equivalent to the pitch discriminability changes induced by training. This result suggests that pitch discrimination training affects processes not measured by the MMN, for example, processes higher in level or parallel to those involved in MMN generation.

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

Science.gov (United States)

Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

One-trial overshadowing: Evidence for fast specific fear learning in humans.

Science.gov (United States)

Haesen, Kim; Beckers, Tom; Baeyens, Frank; Vervliet, Bram

2017-03-01

Adaptive defensive actions necessitate a fear learning system that is both fast and specific. Fast learning serves to minimize the number of threat confrontations, while specific learning ensures that the acquired fears are tied to threat-relevant cues only. In Pavlovian fear conditioning, fear acquisition is typically studied via repetitive pairings of a single cue with an aversive experience, which is not optimal for the examination of fast specific fear learning. In this study, we adopted the one-trial overshadowing procedure from basic learning research, in which a combination of two visual cues is presented once and paired with an aversive electrical stimulation. Using on-line shock expectancy ratings, skin conductance reactivity and startle reflex modulation as indices of fear learning, we found evidence of strong fear after a single conditioning trial (fast learning) as well as attenuated fear responding when only half of the trained stimulus combination was presented (specific learning). Moreover, specificity of fear responding tended to correlate with levels of state and trait anxiety. These results suggest that one-trial overshadowing can be used as a model to study fast specific fear learning in humans and individual differences therein. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Time to Define: Making the Specific Learning Disability Definition Prescribe Specific Learning Disability

Science.gov (United States)

Kavale, Kenneth A.; Spaulding, Lucinda S.; Beam, Andrea P.

2009-01-01

Unlike other special education categories defined in U.S. law (Individuals with Disabilities Education Act), the definition of specific learning disability (SLD) has not changed since first proposed in 1968. Thus, although the operational definition of SLD has responded to new knowledge and understanding about the construct, the formal definition…

Impact of Computer Aided Learning on Children with Specific Learning Disabilities

OpenAIRE

The Spastic Society Of Karnataka , Bangalore

2004-01-01

Study conducted by The Spastics Society of Karnataka on behalf of Azim Premji Foundation to assess the effectiveness of computers in enhancing learning for children with specific learning disabilities. Azim Premji Foundation is not liable for any direct or indirect loss or damage whatsoever arising from the use or access of any information, interpretation and conclusions that may be printed in this report.; Study to assess the effectiveness of computers in enhancing learning for children with...

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

Science.gov (United States)

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Cultivating Collaborations: Site Specific Design for Embodied Science Learning.

Science.gov (United States)

Gill, Katherine; Glazier, Jocelyn; Towns, Betsy

2018-05-21

Immersion in well-designed outdoor environments can foster the habits of mind that enable critical and authentic scientific questions to take root in students' minds. Here we share two design cases in which careful, collaborative, and intentional design of outdoor learning environments for informal inquiry provide people of all ages with embodied opportunities to learn about the natural world, developing the capacity for understanding ecology and the ability to empathize, problem-solve and reflect. Embodied learning, as facilitated by and in well-designed outdoor learning environments, leads students to develop new ways of seeing, new scientific questions, new ways to connect with ideas, with others and new ways of thinking about the natural world. Using examples from our collaborative practices as experiential learning designers, we illustrate how creating the habits of mind critical to creating scientists, science-interested, and science-aware individuals benefits from providing students spaces to engage in embodied learning in nature. We show how public landscapes designed in creative partnerships between educators, scientists, designers and the public have potential to amplify science learning for all.

Learning LM Specificity for Ganglion Cells

Science.gov (United States)

Ahumada, Albert J.

2015-01-01

Unsupervised learning models have been proposed based on experience (Ahumada and Mulligan, 1990;Wachtler, Doi, Lee and Sejnowski, 2007) that allow the cortex to develop units with LM specific color opponent receptive fields like the blob cells reported by Hubel and Wiesel on the basis of visual experience. These models used ganglion cells with LM indiscriminate wiring as inputs to the learning mechanism, which was presumed to occur at the cortical level.

Student Behavior and Epistemological Framing: Examples from Collaborative Active-Learning Activities in Physics

Science.gov (United States)

Scherr, Rachel E.; Hammer, David

2009-01-01

The concept of framing from anthropology and sociolinguistics is useful for understanding student reasoning. For example, a student may frame a learning activity as an opportunity for sensemaking or as an assignment to fill out a worksheet. The student's framing affects what she notices, what knowledge she accesses, and how she thinks to act. We…

Cognitive Clusters in Specific Learning Disorder.

Science.gov (United States)

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Adam John Rock

2016-03-01

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

Visual Perceptual Learning and its Specificity and Transfer: A New Perspective

Directory of Open Access Journals (Sweden)

Cong Yu

2011-05-01

Full Text Available Visual perceptual learning is known to be location and orientation specific, and is thus assumed to reflect the neuronal plasticity in the early visual cortex. However, in recent studies we created “Double training” and “TPE” procedures to demonstrate that these “fundamental” specificities of perceptual learning are in some sense artifacts and that learning can completely transfer to a new location or orientation. We proposed a rule-based learning theory to reinterpret perceptual learning and its specificity and transfer: A high-level decision unit learns the rules of performing a visual task through training. However, the learned rules cannot be applied to a new location or orientation automatically because the decision unit cannot functionally connect to new visual inputs with sufficient strength because these inputs are unattended or even suppressed during training. It is double training and TPE training that reactivate these new inputs, so that the functional connections can be strengthened to enable rule application and learning transfer. Currently we are investigating the properties of perceptual learning free from the bogus specificities, and the results provide some preliminary but very interesting insights into how training reshapes the functional connections between the high-level decision units and sensory inputs in the brain.

Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model.

Science.gov (United States)

De Leeuw, R A; Westerman, Michiel; Nelson, E; Ket, J C F; Scheele, F

2016-07-08

E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings.

Learning speaker-specific characteristics with a deep neural architecture.

Science.gov (United States)

Chen, Ke; Salman, Ahmad

2011-11-01

Speech signals convey various yet mixed information ranging from linguistic to speaker-specific information. However, most of acoustic representations characterize all different kinds of information as whole, which could hinder either a speech or a speaker recognition (SR) system from producing a better performance. In this paper, we propose a novel deep neural architecture (DNA) especially for learning speaker-specific characteristics from mel-frequency cepstral coefficients, an acoustic representation commonly used in both speech recognition and SR, which results in a speaker-specific overcomplete representation. In order to learn intrinsic speaker-specific characteristics, we come up with an objective function consisting of contrastive losses in terms of speaker similarity/dissimilarity and data reconstruction losses used as regularization to normalize the interference of non-speaker-related information. Moreover, we employ a hybrid learning strategy for learning parameters of the deep neural networks: i.e., local yet greedy layerwise unsupervised pretraining for initialization and global supervised learning for the ultimate discriminative goal. With four Linguistic Data Consortium (LDC) benchmarks and two non-English corpora, we demonstrate that our overcomplete representation is robust in characterizing various speakers, no matter whether their utterances have been used in training our DNA, and highly insensitive to text and languages spoken. Extensive comparative studies suggest that our approach yields favorite results in speaker verification and segmentation. Finally, we discuss several issues concerning our proposed approach.

Training Self-Regulated Learning Skills with Video Modeling Examples: Do Task-Selection Skills Transfer?

Science.gov (United States)

Raaijmakers, Steven F.; Baars, Martine; Schaap, Lydia; Paas, Fred; van Merriënboer, Jeroen; van Gog, Tamara

2018-01-01

Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and…

Learning the Brain in Introductory Psychology: Examining the Generation Effect for Mnemonics and Examples

Science.gov (United States)

McCabe, Jennifer A.

2015-01-01

The goal of this research was to determine whether there is a generation effect for learner-created keyword mnemonics and real-life examples, compared to instructor-provided materials, when learning neurophysiological terms and definitions in introductory psychology. Students participated in an individual (Study 1) or small-group (Study 2)…

Bayesian methods for the physical sciences learning from examples in astronomy and physics

CERN Document Server

Andreon, Stefano

2015-01-01

Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications.

Transforming Passive Receptivity of Knowledge into Deep Learning Experiences at the Undergraduate Level: An Example from Music Theory

Science.gov (United States)

Ferenc, Anna

2015-01-01

This article discusses transformation of passive knowledge receptivity into experiences of deep learning in a lecture-based music theory course at the second-year undergraduate level through implementation of collaborative projects that evoke natural critical learning environments. It presents an example of such a project, addresses key features…

It's All a Matter of Perspective: Viewing First-Person Video Modeling Examples Promotes Learning of an Assembly Task

Science.gov (United States)

Fiorella, Logan; van Gog, Tamara; Hoogerheide, Vincent; Mayer, Richard E.

2017-01-01

The present study tests whether presenting video modeling examples from the learner's (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed a video showing how to assemble an 8-component…

It’s all a matter of perspective : Viewing first-person video modeling examples promotes learning of an assembly task

NARCIS (Netherlands)

Fiorella, Logan; van Gog, T.; Hoogerheide, V.; Mayer, Richard

2017-01-01

The present study tests whether presenting video modeling examples from the learner’s (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed

Perceptual learning is specific to the trained structure of information.

Science.gov (United States)

Cohen, Yamit; Daikhin, Luba; Ahissar, Merav

2013-12-01

What do we learn when we practice a simple perceptual task? Many studies have suggested that we learn to refine or better select the sensory representations of the task-relevant dimension. Here we show that learning is specific to the trained structural regularities. Specifically, when this structure is modified after training with a fixed temporal structure, performance regresses to pretraining levels, even when the trained stimuli and task are retained. This specificity raises key questions as to the importance of low-level sensory modifications in the learning process. We trained two groups of participants on a two-tone frequency discrimination task for several days. In one group, a fixed reference tone was consistently presented in the first interval (the second tone was higher or lower), and in the other group the same reference tone was consistently presented in the second interval. When following training, these temporal protocols were switched between groups, performance of both groups regressed to pretraining levels, and further training was needed to attain postlearning performance. ERP measures, taken before and after training, indicated that participants implicitly learned the temporal regularity of the protocol and formed an attentional template that matched the trained structure of information. These results are consistent with Reverse Hierarchy Theory, which posits that even the learning of simple perceptual tasks progresses in a top-down manner, hence can benefit from temporal regularities at the trial level, albeit at the potential cost that learning may be specific to these regularities.

Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

Science.gov (United States)

Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

2009-10-28

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

A predictive validity study of the Learning Style Questionnaire (LSQ) using multiple, specific learning criteria

NARCIS (Netherlands)

Kappe, F.R.; Boekholt, L.; den Rooyen, C.; van der Flier, H.

2009-01-01

Multiple and specific learning criteria were used to examine the predictive validity of the Learning Style Questionnaire (LSQ). Ninety-nine students in a college of higher learning in The Netherlands participated in a naturally occurring field study. The students were categorized into one of four

Evaluating OO example programs for CS1

DEFF Research Database (Denmark)

Börstler, Jürgen; Christensen, Henrik Bærbak; Bennedsen, Jens

2008-01-01

Example programs play an important role in learning to program. They work as templates, guidelines, and inspiration for learners when developing their own programs. It is therefore important to provide learners with high quality examples. In this paper, we discuss properties of example programs...... that might affect the teaching and learning of object-oriented programming. Furthermore, we present an evaluation instrument for example programs and report on initial experiences of its application to a selection of examples from popular introductory programming textbooks....

Conduct disorders as a result of specific learning disorders

OpenAIRE

VOKROJOVÁ, Nela

2012-01-01

This thesis focuses on relationship between specific learning disorders and conduct disorders in puberty. The theoretical part explains the basic terms apearing in the thesis such as specific learning disorders, conduct disorders, puberty and prevention of conduct disorder formation. It presents Czech and foreign research which have already been done in this and related areas. The empirical part uses a quantitative method to measure anxiety and occurrence of conduct disorders in second grade ...

Multinational Companies as a Source of Entrepreneurial Learning Examples from the It Sector in Ireland

Science.gov (United States)

McKeon, Helen; Johnston, Kate; Henry, Colette

2004-01-01

Entrepreneurial learning has recently become a topic of significant interest, with academics and economists alike recognising that the success of any new business venture is closely linked to the learning and knowledge of the entrepreneur. To date, research into entrepreneurial learning and the specific ways in which entrepreneurs learn is…

Showing a model's eye movements in examples does not improve learning of problem-solving tasks

NARCIS (Netherlands)

van Marlen, Tim; van Wermeskerken, Margot; Jarodzka, Halszka; van Gog, Tamara

2016-01-01

Eye movement modeling examples (EMME) are demonstrations of a computer-based task by a human model (e.g., a teacher), with the model's eye movements superimposed on the task to guide learners' attention. EMME have been shown to enhance learning of perceptual classification tasks; however, it is an

HTML5 web application development by example

CERN Document Server

Gustafson, JM

2013-01-01

The best way to learn anything is by doing. The author uses a friendly tone and fun examples to ensure that you learn the basics of application development. Once you have read this book, you should have the necessary skills to build your own applications.If you have no experience but want to learn how to create applications in HTML5, this book is the only help you'll need. Using practical examples, HTML5 Web Application Development by Example will develop your knowledge and confidence in application development.

Computational learning on specificity-determining residue-nucleotide interactions

KAUST Repository

Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Moses, Alan M.; Zhang, Zhaolei

2015-01-01

The protein–DNA interactions between transcription factors and transcription factor binding sites are essential activities in gene regulation. To decipher the binding codes, it is a long-standing challenge to understand the binding mechanism across different transcription factor DNA binding families. Past computational learning studies usually focus on learning and predicting the DNA binding residues on protein side. Taking into account both sides (protein and DNA), we propose and describe a computational study for learning the specificity-determining residue-nucleotide interactions of different known DNA-binding domain families. The proposed learning models are compared to state-of-the-art models comprehensively, demonstrating its competitive learning performance. In addition, we describe and propose two applications which demonstrate how the learnt models can provide meaningful insights into protein–DNA interactions across different DNA binding families.

Computational learning on specificity-determining residue-nucleotide interactions

KAUST Repository

Wong, Ka-Chun

2015-11-02

The protein–DNA interactions between transcription factors and transcription factor binding sites are essential activities in gene regulation. To decipher the binding codes, it is a long-standing challenge to understand the binding mechanism across different transcription factor DNA binding families. Past computational learning studies usually focus on learning and predicting the DNA binding residues on protein side. Taking into account both sides (protein and DNA), we propose and describe a computational study for learning the specificity-determining residue-nucleotide interactions of different known DNA-binding domain families. The proposed learning models are compared to state-of-the-art models comprehensively, demonstrating its competitive learning performance. In addition, we describe and propose two applications which demonstrate how the learnt models can provide meaningful insights into protein–DNA interactions across different DNA binding families.

Stochastic collusion and the power law of learning: a general reinforcement learning model of cooperation

NARCIS (Netherlands)

Flache, A.

2002-01-01

Concerns about models of cultural adaptation as analogs of genetic selection have led cognitive game theorists to explore learning-theoretic specifications. Two prominent examples, the Bush-Mosteller stochastic learning model and the Roth-Erev payoff-matching model, are aligned and integrated as

Learning with hierarchical-deep models.

Science.gov (United States)

Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

2013-08-01

We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

The future of the IMS Learning Design specification: a critical look

NARCIS (Netherlands)

Sloep, Peter

2009-01-01

P. B. Sloep (2009). The future of the IMS Learning Design specification: a critical look. Presentation at the IMS Learning Design seminar 'The future of IMS Learning Design'. December, 10, 2009, Wollongong, Australia: University of Wollongong.

Specific Deficit in Implicit Motor Sequence Learning following Spinal Cord Injury.

Directory of Open Access Journals (Sweden)

Ayala Bloch

Full Text Available Physical and psychosocial rehabilitation following spinal cord injury (SCI leans heavily on learning and practicing new skills. However, despite research relating motor sequence learning to spinal cord activity and clinical observations of impeded skill-learning after SCI, implicit procedural learning following spinal cord damage has not been examined.To test the hypothesis that spinal cord injury (SCI in the absence of concomitant brain injury is associated with a specific implicit motor sequence learning deficit that cannot be explained by depression or impairments in other cognitive measures.Ten participants with SCI in T1-T11, unharmed upper limb motor and sensory functioning, and no concomitant brain injury were compared to ten matched control participants on measures derived from the serial reaction time (SRT task, which was used to assess implicit motor sequence learning. Explicit generation of the SRT sequence, depression, and additional measures of learning, memory, and intelligence were included to explore the source and specificity of potential learning deficits.There was no between-group difference in baseline reaction time, indicating that potential differences between the learning curves of the two groups could not be attributed to an overall reduction in response speed in the SCI group. Unlike controls, the SCI group showed no decline in reaction time over the first six blocks of the SRT task and no advantage for the initially presented sequence over the novel interference sequence. Meanwhile, no group differences were found in explicit learning, depression, or any additional cognitive measures.The dissociation between impaired implicit learning and intact declarative memory represents novel empirical evidence of a specific implicit procedural learning deficit following SCI, with broad implications for rehabilitation and adjustment.

Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases

NARCIS (Netherlands)

Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit

2010-01-01

Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2010, August). Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases. Poster presented at the 32nd Annual Conference of the Cognitive Science

The specificity of learned parallelism in dual-memory retrieval.

Science.gov (United States)

Strobach, Tilo; Schubert, Torsten; Pashler, Harold; Rickard, Timothy

2014-05-01

Retrieval of two responses from one visually presented cue occurs sequentially at the outset of dual-retrieval practice. Exclusively for subjects who adopt a mode of grouping (i.e., synchronizing) their response execution, however, reaction times after dual-retrieval practice indicate a shift to learned retrieval parallelism (e.g., Nino & Rickard, in Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 373-388, 2003). In the present study, we investigated how this learned parallelism is achieved and why it appears to occur only for subjects who group their responses. Two main accounts were considered: a task-level versus a cue-level account. The task-level account assumes that learned retrieval parallelism occurs at the level of the task as a whole and is not limited to practiced cues. Grouping response execution may thus promote a general shift to parallel retrieval following practice. The cue-level account states that learned retrieval parallelism is specific to practiced cues. This type of parallelism may result from cue-specific response chunking that occurs uniquely as a consequence of grouped response execution. The results of two experiments favored the second account and were best interpreted in terms of a structural bottleneck model.

Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases

NARCIS (Netherlands)

Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit

2010-01-01

Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2010). Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the

Polyunsaturated fatty acids (PUFAs) for children with specific learning disorders.

Science.gov (United States)

Tan, May Loong; Ho, Jacqueline J; Teh, Keng Hwang

2016-09-28

About 5% of school children have a specific learning disorder, defined as unexpected failure to acquire adequate abilities in reading, writing or mathematics that is not a result of reduced intellectual ability, inadequate teaching or social deprivation. Of these events, 80% are reading disorders. Polyunsaturated fatty acids (PUFAs), in particular, omega-3 and omega-6 fatty acids, which normally are abundant in the brain and in the retina, are important for learning. Some children with specific learning disorders have been found to be deficient in these PUFAs, and it is argued that supplementation of PUFAs may help these children improve their learning abilities. 1. To assess effects on learning outcomes of supplementation of polyunsaturated fatty acids (PUFAs) for children with specific learning disorders.2. To determine whether adverse effects of supplementation of PUFAs are reported in these children. In November 2015, we searched CENTRAL, Ovid MEDLINE, Embase, PsycINFO, 10 other databases and two trials registers. We also searched the reference lists of relevant articles. Randomised controlled trials (RCTs) or quasi-RCTs comparing PUFAs with placebo or no treatment in children younger than 18 years with specific learning disabilities, as diagnosed in accordance with the fifth (or earlier) edition of theDiagnostic and Statistical Manual of Mental Disorders (DSM-5), or the 10th (or earlier) revision of the International Classification of Diseases (ICD-10) or equivalent criteria. We included children with coexisting developmental disorders such as attention deficit hyperactivity disorder (ADHD) or autism. Two review authors (MLT and KHT) independently screened the titles and abstracts of articles identified by the search and eliminated all studies that did not meet the inclusion criteria. We contacted study authors to ask for missing information and clarification, when needed. We used the GRADE approach to assess the quality of evidence. Two small studies

Enhancing Learning in Statistics Classes Through The Use of Concrete Historical Examples: The Space Shuttle Challenger, Pearl Harbor, and the RMS Titanic.

Science.gov (United States)

Schumm, Walter R.; Webb, Farrell J.; Castelo, Carlos S.; Akagi, Cynthia G.; Jensen, Erick J.; Ditto, Rose M.; Spencer Carver, Elaine; Brown, Beverlyn F.

2002-01-01

Discusses the use of historical events as examples for teaching college level statistics courses. Focuses on examples of the space shuttle Challenger, Pearl Harbor (Hawaii), and the RMS Titanic. Finds real life examples can bridge a link to short term experiential learning and provide a means for long term understanding of statistics. (KDR)

[Specific learning disabilities - from DSM-IV to DSM-5].

Science.gov (United States)

Schulte-Körne, Gerd

2014-09-01

The publication of the DSM-5 means changes in the classification and recommendations for diagnosis of specific learning disabilities. Dyslexia and dyscalculia have been reintroduced into the DSM. Three specific learning disorders - impairment in reading, impairment in the written expression, and impairment in mathematics, described by subskills - are now part of the DSM-5. Three subcomponents of the reading disorder are expressly differentiated: word reading accuracy, reading rate, and fluency and reading comprehension. Impaired subskills of the specific learning disorder with impairment in written expression are spelling accuracy, grammar and punctuation accuracy, and clarity and organization of written expression. Four subskills are found in the mathematics disorder: number sense, memorization of arithmetic facts, accurate or fluent calculation, and accurate math reasoning. Each impaired academic domain and subskill should be recorded. A description of the severity degree was also included. The diagnosis is based on a variety of methods, including medical history, clinical interview, school report, teacher evaluation, rating scales, and psychometric tests. The IQ discrepancy criterion was abandoned, though that of age or class discrepancy criterion was retained. The application of a discrepancy is recommended by 1 to 2.5 SD. All three specific developmental disorders are common (prevalence 5 %-15 %), occur early during the first years of formal schooling, and persist into adulthood.

Alfanet Worked Example: What is Greatness?

NARCIS (Netherlands)

dr. Pierre Gorissen

2004-01-01

This document consists of an example of a Learning Design based on the What is Greatness example originally created by James Dalziel from WebMCQ using LAMS. Note: The example has been created in parallel with the actual development of the Alfanet system. So no claims can be made that the example

A Learning Model for L/M Specificity in Ganglion Cells

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Ahumada, Albert J.

2016-01-01

An unsupervised learning model for developing LM specific wiring at the ganglion cell level would support the research indicating LM specific wiring at the ganglion cell level (Reid and Shapley, 2002). Removing the contributions to the surround from cells of the same cone type improves the signal-to-noise ratio of the chromatic signals. The unsupervised learning model used is Hebbian associative learning, which strengthens the surround input connections according to the correlation of the output with the input. Since the surround units of the same cone type as the center are redundant with the center, their weights end up disappearing. This process can be thought of as a general mechanism for eliminating unnecessary cells in the nervous system.

Interference in Ballistic Motor Learning: Specificity and Role of Sensory Error Signals

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Lundbye-Jensen, Jesper; Petersen, Tue Hvass; Rothwell, John C.; Nielsen, Jens Bo

2011-01-01

Humans are capable of learning numerous motor skills, but newly acquired skills may be abolished by subsequent learning. Here we ask what factors determine whether interference occurs in motor learning. We speculated that interference requires competing processes of synaptic plasticity in overlapping circuits and predicted specificity. To test this, subjects learned a ballistic motor task. Interference was observed following subsequent learning of an accuracy-tracking task, but only if the competing task involved the same muscles and movement direction. Interference was not observed from a non-learning task suggesting that interference requires competing learning. Subsequent learning of the competing task 4 h after initial learning did not cause interference suggesting disruption of early motor memory consolidation as one possible mechanism underlying interference. Repeated transcranial magnetic stimulation (rTMS) of corticospinal motor output at intensities below movement threshold did not cause interference, whereas suprathreshold rTMS evoking motor responses and (re)afferent activation did. Finally, the experiments revealed that suprathreshold repetitive electrical stimulation of the agonist (but not antagonist) peripheral nerve caused interference. The present study is, to our knowledge, the first to demonstrate that peripheral nerve stimulation may cause interference. The finding underscores the importance of sensory feedback as error signals in motor learning. We conclude that interference requires competing plasticity in overlapping circuits. Interference is remarkably specific for circuits involved in a specific movement and it may relate to sensory error signals. PMID:21408054

Reduced autobiographical memory specificity is associated with impaired discrimination learning in anxiety disorder patients

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Lenaert, Bert; Boddez, Yannick; Vervliet, Bram; Schruers, Koen; Hermans, Dirk

2015-01-01

Associative learning plays an important role in the development of anxiety disorders, but a thorough understanding of the variables that impact such learning is still lacking. We investigated whether individual differences in autobiographical memory specificity are related to discrimination learning and generalization. In an associative learning task, participants learned the association between two pictures of female faces and a non-aversive outcome. Subsequently, six morphed pictures functioning as generalization stimuli (GSs) were introduced. In a sample of healthy participants (Study 1), we did not find evidence for differences in discrimination learning as a function of memory specificity. In a sample of anxiety disorder patients (Study 2), individuals who were characterized by low memory specificity showed deficient discrimination learning relative to high specific individuals. In contrast to previous findings, results revealed no effect of memory specificity on generalization. These results indicate that impaired discrimination learning, previously shown in patients suffering from an anxiety disorder, may be—in part—due to limited memory specificity. Together, these studies emphasize the importance of incorporating cognitive variables in associative learning theories and their implications for the development of anxiety disorders. In addition, re-analyses of the data (Study 3) showed that patients suffering from panic disorder showed higher outcome expectancies in the presence of the stimulus that was never followed by an outcome during discrimination training, relative to patients suffering from other anxiety disorders and healthy participants. Because we used a neutral, non-aversive outcome (i.e., drawing of a lightning bolt), these data suggest that learning abnormalities in panic disorder may not be restricted to fear learning, but rather reflect a more general associative learning deficit that also manifests in fear irrelevant contexts. PMID

Designing Learning Resources in Synchronous Learning Environments

DEFF Research Database (Denmark)

Christiansen, Rene B

2015-01-01

Computer-mediated Communication (CMC) and synchronous learning environments offer new solutions for teachers and students that transcend the singular one-way transmission of content knowledge from teacher to student. CMC makes it possible not only to teach computer mediated but also to design...... and create new learning resources targeted to a specific group of learners. This paper addresses the possibilities of designing learning resources within synchronous learning environments. The empirical basis is a cross-country study involving students and teachers in primary schools in three Nordic...... Countries (Denmark, Sweden and Norway). On the basis of these empirical studies a set of design examples is drawn with the purpose of showing how the design fulfills the dual purpose of functioning as a remote, synchronous learning environment and - using the learning materials used and recordings...

On the Quality of Examples in Introductory Java Textbooks

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Borstler, Jurgen; Nordstrom, Marie; Paterson, James H.

2011-01-01

Example programs play an important role in the teaching and learning of programming. Students as well as teachers rank examples as the most important resources for learning to program. Example programs work as role models and must therefore always be consistent with the principles and rules we are teaching. However, it is difficult to find or…

E-Learning Lifecycles:How Communities and Context can affect E-learning Specifications and Tool Design

Directory of Open Access Journals (Sweden)

Michael Magee

2004-10-01

Full Text Available The development of a large body of e-learning specifications, such as IMS and SCORM, has led to the proposal for a new way to facilitate content workflow. This involves the movement of educational digital content and the knowledge of pedagogical communities into an online space. Several projects have looked at the theoretical structure of these specifications. They implemented a series of tools in order to examine and research the issues around the actual usage of these specifications. The CAREO, ALOHA and ALOHA 2 projects were designed to expose both individual users and whole institutions to these ideas. Initial research into the result of those interactions indicates that there is some utility in the adoption of e-learning specifications. The future success of them will depend on their ability to adapt and meet the needs of the educational community as they begin to adopt, use and evolve the way they use the specifications and the tools created around them.

Achieving HBSE Competencies through Service-learning

Directory of Open Access Journals (Sweden)

Sarah E. Twill

2011-04-01

Full Text Available Service-learning pedagogy allows social work educators to create meaningful learning opportunities for students and better prepare them for practicum, while at the same time, meeting a community need. This paper outlines the relevance of incorporating service-learning into the social work curriculum, specifically the human behavior and the social environment (HBSE area. Using Bloom’s taxonomy as a guide, the authors propose how the CSWE competencies and practice behaviors specific to HBSE may be assessed using service-learning pedagogy. An example is reviewed to illustrate how service-learning can assist faculty and students achieve the HBSE competencies and practice behaviors. Finally, implications for service-learning as a pedagogical strategy for social work education are discussed.

Encouraging Example Generation: A Teaching Experiment in First-Semester Calculus

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Wagner, Elaine Rumsey; Orme, Susan Marla; Turner, Heidi Jean; Yopp, David

2017-01-01

Mathematicians use example generation to test and verify mathematical ideas; however, the processes through which undergraduates learn to productively generate examples are not well understood. We engaged calculus students in a teaching experiment designed to develop skills in productively generating examples to learn novel concepts. This article…

Teaching the science of learning.

Science.gov (United States)

Weinstein, Yana; Madan, Christopher R; Sumeracki, Megan A

2018-01-01

The science of learning has made a considerable contribution to our understanding of effective teaching and learning strategies. However, few instructors outside of the field are privy to this research. In this tutorial review, we focus on six specific cognitive strategies that have received robust support from decades of research: spaced practice, interleaving, retrieval practice, elaboration, concrete examples, and dual coding. We describe the basic research behind each strategy and relevant applied research, present examples of existing and suggested implementation, and make recommendations for further research that would broaden the reach of these strategies.

Agent-specific learning signals for self-other distinction during mentalising.

Directory of Open Access Journals (Sweden)

Sam Ereira

2018-04-01

Full Text Available Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self-other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG enabled us to track neural representations of prediction errors (PEs and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self-other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self-other distinction also had a reduced behavioural capacity for self-other distinction and displayed more marked subclinical psychopathological traits. The neural self-other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self-other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker.

Comparing Examples: WebAssign versus Textbook

Science.gov (United States)

Richards, Evan; Polak, Jeff; Hardin, Ashley; Risley, John, , Dr.

2005-11-01

Research shows students can learn from worked examples.^1 This pilot study compared two groups of students' performance (10 each) in solving physics problems. One group had access to interactive examples^2 released in WebAssign^3, while the other group had access to the counterpart textbook examples. Verbal data from students in problem solving sessions was collected using a think aloud protocol^4 and the data was analyzed using Chi's procedures.^5 An explanation of the methodology and results will be presented. Future phases of this pilot study based upon these results will also be discussed. ^1Atkinson, R.K., Derry, S.J., Renkl A., Wortham, D. (2000). ``Learning from Examples: Instructional Principles from the Worked Examples Research'', Review of Educational Research, vol. 70, n. 2, pp. 181-214. ^2Serway, R.A. & Faughn, J.S. (2006). College Physics (7^th ed.). Belmont, CA: Thomson Brooks/Cole. ^3 see www.webassign.net ^4 Ericsson, K.A. & Simon, H.A. (1984). Protocol Analysis: Verbal Reports as Data. Cambridge, Massachusetts: The MIT Press. ^5 Chi, Michelene T.H. (1997). ``Quantifying Qualitative Analyses of Verbal Data: A Practical Guide,'' The Journal of the Learning Sciences, vol. 6, n. 3, pp. 271-315.

Machine Learning examples on Invenio

CERN Document Server

CERN. Geneva

2017-01-01

This talk will present the different Machine Learning tools that the INSPIRE is developing and integrating in order to automatize as much as possible content selection and curation in a subject based repository.

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

Science.gov (United States)

Coya, Liliam de Barbosa; Perez-Coffie, Jorge

1982-01-01

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

Learning Disabilities.

Science.gov (United States)

Neuwirth, Sharyn

This booklet uses hypothetical case examples to illustrate the definition, causal theories, and specific types of learning disabilities (LD). The cognitive and language performance of students with LD is compared to standard developmental milestones, and common approaches to the identification and education of children with LD are outlined.…

Attention to the Model's Face When Learning from Video Modeling Examples in Adolescents with and without Autism Spectrum Disorder

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van Wermeskerken, Margot; Grimmius, Bianca; van Gog, Tamara

2018-01-01

We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate…

The Value of Identifying and Recovering Lost GN&C Lessons Learned: Aeronautical, Spacecraft, and Launch Vehicle Examples

Science.gov (United States)

Dennehy, Cornelius J.; Labbe, Steve; Lebsock, Kenneth L.

2010-01-01

Within the broad aerospace community the importance of identifying, documenting and widely sharing lessons learned during system development, flight test, operational or research programs/projects is broadly acknowledged. Documenting and sharing lessons learned helps managers and engineers to minimize project risk and improve performance of their systems. Often significant lessons learned on a project fail to get captured even though they are well known 'tribal knowledge' amongst the project team members. The physical act of actually writing down and documenting these lessons learned for the next generation of NASA GN&C engineers fails to happen on some projects for various reasons. In this paper we will first review the importance of capturing lessons learned and then will discuss reasons why some lessons are not documented. A simple proven approach called 'Pause and Learn' will be highlighted as a proven low-impact method of organizational learning that could foster the timely capture of critical lessons learned. Lastly some examples of 'lost' GN&C lessons learned from the aeronautics, spacecraft and launch vehicle domains are briefly highlighted. In the context of this paper 'lost' refers to lessons that have not achieved broad visibility within the NASA-wide GN&C CoP because they are either undocumented, masked or poorly documented in the NASA Lessons Learned Information System (LLIS).

Compositions of fuzzy relations applied to veryfication learning outcomes on the example of the major “Geodesy and Cartography”

Directory of Open Access Journals (Sweden)

A. Mreła

2015-05-01

    Abstract The paper presents discussion about using mathematical functions in order to help academic teachers to verify acquirement of learning outcomes by students on the example of the major “geodesy and cartography”. It is relatively easy to build fuzzy relation describing levels of realization and validation learning outcomes during subject examinations and the fuzzy relation with students’ grades is already built by teachers, the problem is to combine these two relations to get one which describes the level of acquiring learning outcomes by students. There are two main requirements facing this combinations and the paper shows that the best combination according to these requirements is algebraic composition.   Keywords: learning outcome, fuzzy relation, algebraic composition.

Vulnerability Assessment by Learning Attack Specifications in Graphs

NARCIS (Netherlands)

Nunes Leal Franqueira, V.; Lopes, Raul H.C.

This paper presents an evolutionary approach for learning attack specifications that describe attack scenarios. The objective is to find vulnerabilities in computer networks which minimise the cost of an attack with maximum impact. Although we focus on Insider Threat, the proposed approach applies

The lasting effects of process-specific versus stimulus-specific learning during infancy.

Science.gov (United States)

Hadley, Hillary; Pickron, Charisse B; Scott, Lisa S

2015-09-01

The capacity to tell the difference between two faces within an infrequently experienced face group (e.g. other species, other race) declines from 6 to 9 months of age unless infants learn to match these faces with individual-level names. Similarly, the use of individual-level labels can also facilitate differentiation of a group of non-face objects (strollers). This early learning leads to increased neural specialization for previously unfamiliar face or object groups. The current investigation aimed to determine whether early conceptual learning between 6 and 9 months leads to sustained behavioral advantages and neural changes in these same children at 4-6 years of age. Results suggest that relative to a control group of children with no previous training and to children with infant category-level naming experience, children with early individual-level training exhibited faster response times to human faces. Further, individual-level training with a face group - but not an object group - led to more adult-like neural responses for human faces. These results suggest that early individual-level learning results in long-lasting process-specific effects, which benefit categories that continue to be perceived and recognized at the individual level (e.g. human faces). © 2014 John Wiley & Sons Ltd.

Learning Algebra from Worked Examples

Science.gov (United States)

Lange, Karin E.; Booth, Julie L.; Newton, Kristie J.

2014-01-01

For students to be successful in algebra, they must have a truly conceptual understanding of key algebraic features as well as the procedural skills to complete a problem. One strategy to correct students' misconceptions combines the use of worked example problems in the classroom with student self-explanation. "Self-explanation" is the…

On-line Learning of Prototypes and Principal Components

NARCIS (Netherlands)

Biehl, M.; Freking, A.; Hölzer, M.; Reents, G.; Schlösser, E.; Saad, David

1998-01-01

We review our recent investigation of on-line unsupervised learning from high-dimensional structured data. First, on-line competitive learning is studied as a method for the identification of prototype vectors from overlapping clusters of examples. Specifically, we analyse the dynamics of the

Example-Based Learning: Effects of Different Types of Examples on Student Performance, Cognitive Load and Self-Efficacy in a Statistical Learning Task

Science.gov (United States)

Huang, Xiaoxia

2017-01-01

Previous research has indicated the disconnect between example-based research focusing on worked examples (WEs) and that focusing on modeling examples. The purpose of this study was to examine and compare the effect of four different types of examples from the two separate lines of research, including standard WEs, erroneous WEs, expert (masterly)…

Specific Learning Difficulties--What Teachers Need to Know

Science.gov (United States)

Hudson, Diana

2015-01-01

This book clearly explains what Specific Learning Difficulties (SpLD) are, and describes the symptoms of conditions most commonly encountered in the mainstream classroom: dyslexia, dyspraxia, dyscalculia, dysgraphia, Autism Spectrum Disorder, ADHD, and OCD. The author provides an overview of the strengths and weaknesses commonly associated with…

Effectiveness of Memantine in Improvement of Cognitive Deficits in Specific Learning Disorder

Directory of Open Access Journals (Sweden)

Elham Ahmadi Zahrani

2016-12-01

Full Text Available Abstract Background: Specific learning disorder is a neurodevelopmental disorder characterized by persistent difficulties in learning academic skills in reading, written expression, or mathematics. This study was performed to investigate the effectiveness of memantine in the relief of cognitive deficits (selective attention, sustained attention, and working memory in specific learning disorder. Materials and Methods: This study is a clinical trial. Of all children 8-12 years referred to Amir Kabir Hospital 94 patients diagnosed with specific learning disorder based on DSMV diagnostic interview referred by specialist and randomly divided by two groups, memantine and placebo. Cognitive deficits before and after treatment were measured with continuous performance test, Stroop test and Wechsler Digit Span forward and reverse and Corsi test. Results: Multivariate analysis of variance showed a significant difference in error when answering, omission answer and corrected answer in continuous performance test, but this difference is not significant in response time. Difference in forward, reverse and collected auditory was significant and not significant in the auditory span. In active visual working memory at corsi cube test, difference was significant (p <0.05. Conclusion: The results showed that memantine in improvement of sustained attention, auditory working memory and visual working memory, is effective, while in selective attention is not effective and according to similarities of learning disorder and Attention deficit / Hyperactivity disorder (ADHD and the effectiveness of memantine in improvement of symptoms of ADHD, we can also use this drug in improvement of cognitive deficits of specific learning disorder.

Managing specific learning disability in schools in India.

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Karande, Sunil; Sholapurwala, Rukhshana; Kulkarni, Madhuri

2011-07-01

Specific learning disability (dyslexia, dysgraphia, and dyscalculia) afflicts 5-15% of school-going children. Over the last decade; awareness about this invisible handicap has grown in India. However, much needs to be done to ensure that each afflicted child gets an opportunity to achieve his or her full academic potential in regular mainstream schools. In order to achieve this ideal scenario, all regular classroom teachers should be sensitized to suspect, and trained to screen for this disability when the child is in primary school. School managements should become proactive to set up resource rooms and employ special educators to ensure that these children receive regular and affordable remedial education; and be diligent in ensuring that these children get the mandatory provisions both during school and board examinations. Once specific learning disability is recognized as a disability by the Government of India, these children with the backing of the Right to Education Act, would be able to benefit significantly.

Qualitative and quantitative revaluation of specific learning disabilities: a multicentric study.

Science.gov (United States)

Operto, Francesca F; Mazza, Roberta; Buttiglione, Maura; Craig, Francesco; Frolli, Alessandro; Pisano, Simone; Margari, Lucia; Coppola, Giangennaro

2018-04-12

Specific learning disabilities are disorders that affect the instrumental skills of academic learning, leaving intact the general intellectual functioning. It is possible to distinguish: dyslexia, dysorthography, dysgraphia, and dyscalculia. The diagnosis is made according to DSMV. The aim of this study is to evaluate the implementation of Law N° 170 following a diagnosis of specific learning disabilities in children and their evolution over time. The sample under examination consists of 75 children, 56 males and 18 females aged 7,8 to 16 years, with a diagnosis of specific learning disabilities; a revaluation was carried outthrough the use of standardized instruments according to age and school attended. A twopart questionnaire was proposed: the first part turned to the parents/carers of the child and the second part turned to the boy himself. The improvement parameter has been linked, through a statistical analysis of univarianza with intelligence quotient, age, application of the law 10 October 2010 n 170, rehabilitative paths and attending afterschool program. Most of the guys are followed at school by the application of the law 170 and, outside school, by attending speech and neuropsychological therapy and after school. Going to investigate the actual use of the measures put in place by the school, it is evident a partial and incomplete application of Law 170. The most suitable measures for these children are pedagogical measures in order to make them integrate with the group class and strengthen their capacities through specific measures provided by a specific legislative decree.

The e-MapScholar project—an example of interoperability in GIScience education

Science.gov (United States)

Purves, R. S.; Medyckyj-Scott, D. J.; Mackaness, W. A.

2005-03-01

The proliferation of the use of digital spatial data in learning and teaching provides a set of opportunities and challenges for the development of e-learning materials suitable for use by a broad spectrum of disciplines in Higher Education. Effective e-learning materials must both provide engaging materials with which the learner can interact and be relevant to the learners' disciplinary and background knowledge. Interoperability aims to allow sharing of data and materials through the use of common agreements and specifications. Shared learning materials can take advantage of interoperable components to provide customisable components, and must consider issues in sharing data across institutional borders. The e-MapScholar project delivers teaching materials related to spatial data, which are customisable with respect to both context and location. Issues in the provision of such interoperable materials are discussed, including suitable levels of granularity of materials, the provision of tools to facilitate customisation and mechanisms to deliver multiple data sets and the metadata issues related to such materials. The examples shown make extensive use of the OpenGIS consortium specifications in the delivery of spatial data.

PAC-Learning from General Examples

DEFF Research Database (Denmark)

Fischer, Paul; Hoeffgen, K.- U.; Lefmann, H.

1997-01-01

dimension of a target class with respect to a sample class, which replaces the Vapnik-Chervonenkis dimension (V.N. Vapnik and A.Y. Chervonenkis, 1971). The investigation of structural aspects of the relative dimension is followed by its applications to learning environments. It turns out that computing...

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

Science.gov (United States)

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

2014-01-01

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

Active Learning by Querying Informative and Representative Examples.

Science.gov (United States)

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

2014-10-01

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

Academic Achievement and Memory Differences among Specific Learning Disabilities Subtypes

Science.gov (United States)

Carmichael, Jessica A.; Fraccaro, Rebecca L.; Miller, Daniel C.; Maricle, Denise E.

2014-01-01

Reading, writing, and math are academic skills involving a number of different executive functions, particularly working memory. Children with specific learning disabilities (SLD) may present myriad academic difficulties, depending on their specific area(s) of processing weakness. is study examined differences in academic achievement and working…

Killer "Killer Examples" for Design Patterns

DEFF Research Database (Denmark)

Caspersen, Michael Edelgaard; Alphonce, Carl; Decker, Adrienne

2007-01-01

Giving students an appreciation of the benefits of using design patterns and an ability to use them effectively in developing code presents several interesting pedagogical challenges. This paper discusses pedagogical lessons learned at the "Killer Examples" for Design Patterns and Objects First s...... series of workshops held at the Object Oriented Programming, Systems, Languages and Applications (OOPSLA) conference over the past four years. It also showcases three "killer examples" which can be used to support the teaching of design patterns.......Giving students an appreciation of the benefits of using design patterns and an ability to use them effectively in developing code presents several interesting pedagogical challenges. This paper discusses pedagogical lessons learned at the "Killer Examples" for Design Patterns and Objects First...

Off-line learning from clustered input examples

NARCIS (Netherlands)

Marangi, Carmela; Solla, Sara A.; Biehl, Michael; Riegler, Peter; Marinaro, Maria; Tagliaferri, Roberto

1996-01-01

We analyze the generalization ability of a simple perceptron acting on a structured input distribution for the simple case of two clusters of input data and a linearly separable rule. The generalization ability computed for three learning scenarios: maximal stability, Gibbs, and optimal learning, is

Indicators of ADHD symptoms in virtual learning context using machine learning technics

Directory of Open Access Journals (Sweden)

Laura Patricia Mancera Valetts

2015-12-01

Full Text Available Rev.esc.adm.neg This paper presents a user model for students performing virtual learning processes. This model is used to infer the presence of Attention Deficit Hyperactivity Disorder (ADHD indicators in a student. The user model is built considering three user characteristics, which can be also used as variables in different contexts. These variables are: behavioral conduct (BC, executive functions performance (EFP, and emotional state (ES. For inferring the ADHD symptomatic profile of a student and his/her emotional alterations, these features are used as input in a set of classification rules. Based on the testing of the proposed model, training examples are obtained. These examples are used to prepare a classification machine learning algorithm for performing, and improving, the task of profiling a student. The proposed user model can provide the first step to adapt learning resources in e-learning platforms to people with attention problems, specifically, young-adult students with ADHD.

Understanding Impulsivity among Children with Specific Learning Disabilities in Inclusion Schools

Science.gov (United States)

Al-Dababneh, Kholoud Adeeb; Al-Zboon, Eman K.

2018-01-01

Impulsive behavior is a characteristic of children with specific learning disabilities (SLD), and is related to learning ability. The present study aims to identify impulsivity behavior in children with SLD who attend inclusion schools, from their resource room teachers' perspectives. A 31-item questionnaire that addressed four subscales was…

Higher Education Outcomes at the National Level on the Example of the Project “Collegiate Learning Assessment”

Directory of Open Access Journals (Sweden)

Sabelnikova E. V.

2015-08-01

Full Text Available We discuss the interpretation of the concept of “learning outcomes”. Theoretical analysis widely represents the interpretations of the learning outcomes of a high school student: academic skills: understanding, application of knowledge to solve problems, synthesis, analysis and evaluation; basic skills and basic knowledge, and skills of a higher order and advanced knowledge; skills of a higher order represented as a system of critical thinking, analytic reasoning, problem solving and written communication; wide abilities interpreted as verbal, quantitative and spatial thinking, understanding, problem solving and decision making. We conclude that each considered approach distinguishes meta-subjective skills, i.e. skills to interact with the quality of information regardless of the context. The ability to measure the meta-skills is discussed on an example of the “Collegiate learning assessment”, realized in the United States

The Effect of Cooperative Learning: University Example

Science.gov (United States)

Tombak, Busra; Altun, Sertel

2016-01-01

Problem Statement: Motivation is a significant component of success in education, and it is best achieved by constructivist learning methods, especially cooperative Learning (CL). CL is a popular method among primary and secondary schools, but it is rarely used in higher education due to the large numbers of students and time restrictions. The…

Collaborative Learning in Practice : Examples from Natural ...

International Development Research Centre (IDRC) Digital Library (Canada)

1 déc. 2010 ... Parmi ses publications récentes, citons Learning from the Field: Innovating China's Higher Education System (Foundation Books et CRDI, 2008) et Social and Gender Analysis in Natural Resource Management: Learning Studies and Lessons from Asia (Sage India, CAP et CRDI, 2006). Edición español: ...

Identifying Learning Patterns of Children at Risk for Specific Reading Disability

Science.gov (United States)

Barbot, Baptiste; Krivulskaya, Suzanna; Hein, Sascha; Reich, Jodi; Thuma, Philip E.; Grigorenko, Elena L.

2016-01-01

Differences in learning patterns of vocabulary acquisition in children at risk (+SRD) and not at risk (-SRD) for Specific Reading Disability (SRD) were examined using a microdevelopmental paradigm applied to the multi-trial Foreign Language Learning Task (FLLT; Baddeley et al., 1995). The FLLT was administered to 905 children from rural…

Constraints on reusability of learning objects

DEFF Research Database (Denmark)

May, Michael; Hussmann, Peter Munkebo; Jensen, Anne Skov

2010-01-01

It is the aim of this paper to discuss some didactic constraints on the use and reuse of digital modular learning objects. Engineering education is used as the specific context of use with examples from courses in introductory electronics and mathematics. Digital multimedia and modular learning....... Constraints on reuse arise from the nature of conceptual understanding in higher education and the functionality of learning objects within present technologies. We will need didactic as well as technical perspectives on learning objects in designing for understanding....

Assessing the Learning Path Specification: a Pragmatic Quality Approach

NARCIS (Netherlands)

Janssen, José; Berlanga, Adriana; Heyenrath, Stef; Martens, Harrie; Vogten, Hubert; Finders, Anton; Herder, Eelco; Hermans, Henry; Melero, Javier; Schaeps, Leon; Koper, Rob

2010-01-01

Janssen, J., Berlanga, A. J., Heyenrath, S., Martens, H., Vogten, H., Finders, A., Herder, E., Hermans, H., Melero Gallardo, J., Schaeps, L., & Koper, R. (2010). Assessing the Learning Path Specification: a Pragmatic Quality Approach. Journal of Universal Computer Science, 16(21), 3191-3209.

Self-Esteem among Boys with and without Specific Learning Disabilities.

Science.gov (United States)

Bingham, Grace

1980-01-01

The self-esteem of 120 males with and without specific learning disabilities, at each of two levels of development (preadolescent and adolescent) was measured using Coopersmith Self-esteem Inventory. (MP)

Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

Science.gov (United States)

Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

2004-01-01

Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

Interference in ballistic motor learning: specificity and role of sensory error signals

DEFF Research Database (Denmark)

Lundbye-Jensen, Jesper; Petersen, Tue Hvass; Rothwell, John C

2011-01-01

Humans are capable of learning numerous motor skills, but newly acquired skills may be abolished by subsequent learning. Here we ask what factors determine whether interference occurs in motor learning. We speculated that interference requires competing processes of synaptic plasticity in overlap......Humans are capable of learning numerous motor skills, but newly acquired skills may be abolished by subsequent learning. Here we ask what factors determine whether interference occurs in motor learning. We speculated that interference requires competing processes of synaptic plasticity...... in overlapping circuits and predicted specificity. To test this, subjects learned a ballistic motor task. Interference was observed following subsequent learning of an accuracy-tracking task, but only if the competing task involved the same muscles and movement direction. Interference was not observed from a non......-learning task suggesting that interference requires competing learning. Subsequent learning of the competing task 4 h after initial learning did not cause interference suggesting disruption of early motor memory consolidation as one possible mechanism underlying interference. Repeated transcranial magnetic...

Scheduling projects with multiskill learning effect.

Science.gov (United States)

Zha, Hong; Zhang, Lianying

2014-01-01

We investigate the project scheduling problem with multiskill learning effect. A new model is proposed to deal with the problem, where both autonomous and induced learning are considered. In order to obtain the optimal solution, a genetic algorithm with specific encoding and decoding schemes is introduced. A numerical example is used to illustrate the proposed model. The computational results show that the learning effect cannot be neglected in project scheduling. By means of determining the level of induced learning, the project manager can balance the project makespan with total cost.

Satellite Remote Sensing and the Hydroclimate: Two Specific Examples of Improved Knowledge and Applications

Science.gov (United States)

Shepherd, M.; Santanello, J. A., Jr.

2017-12-01

When Explorer 1 launched nearly 60 years ago, it helped usher in a golden age of scientific understanding of arguably the most important planet in our solar system. From its inception NASA and its partners were charged with leveraging the vantagepoint of space to advance knowledge outside and within Earth's atmosphere. Earth is a particularly complex natural system that is increasingly modified by human activities. The hydrological or water cycle is a critical circuit in the Earth system. Its complexity requires novel observations and simulation capability to fully understand it and predict changes. This talk will introduce some of the unique satellite-based observations used for hydroclimate studies. Two specific examples will be presented. The first example explores a relatively new thread of research examining the impact of soil moisture on landfalling and other types of tropical systems. Recent literature suggests that tropical cyclones or large rain-producing systems like the one that caused catastrophic flooding in Louisiana (2016) derive moisture from a "brown ocean" of wet soils or wetlands. The second example summarizes a decade of research on how urbanization has altered the precipitation and land surface hydrology components of the water cycle. With both cases, a multitude of satellite or model-based datesets will be summarized (e.g., TRMM, GPM, SMAP, NLDAS).

Domain-specific and domain-general constraints on word and sequence learning.

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Archibald, Lisa M D; Joanisse, Marc F

2013-02-01

The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.

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

OpenAIRE

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

2014-01-01

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

Generalized query-based active learning to identify differentially methylated regions in DNA.

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

2013-01-01

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.

Using Active Learning in a Studio Classroom to Teach Molecular Biology

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Nogaj, Luiza A.

2013-01-01

This article describes the conversion of a lecture-based molecular biology course into an active learning environment in a studio classroom. Specific assignments and activities are provided as examples. The goal of these activities is to involve students in collaborative learning, teach them how to participate in the learning process, and give…

Learning strategies and general cognitive ability as predictors of gender- specific academic achievement.

Science.gov (United States)

Ruffing, Stephanie; Wach, F-Sophie; Spinath, Frank M; Brünken, Roland; Karbach, Julia

2015-01-01

Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability in the prediction of academic achievement. The relationship between these variables was examined by correlation analyses. A set of t-tests was used to test for gender differences in learning strategies, whereas structural equation modeling as well as multi-group analyses were applied to investigate the incremental contribution of learning strategies for male and female students' academic performance. The sample consisted of 461 students (mean age = 21.2 years, SD = 3.2). Correlation analyses revealed that general cognitive ability as well as the learning strategies effort, attention, and learning environment were positively correlated with academic achievement. Gender differences were found in the reported application of many learning strategies. Importantly, the prediction of achievement in structural equation modeling revealed that only effort explained incremental variance (10%) over general cognitive ability. Results of multi-group analyses showed no gender differences in this prediction model. This finding provides further knowledge regarding gender differences in learning research and the specific role of learning strategies for academic achievement. The incremental assessment of learning strategy use as well as gender-differences in their predictive value contributes to the understanding and improvement of successful academic development.

Organizational Learning Capability: An Example of University Hospital

Directory of Open Access Journals (Sweden)

Yasin UZUNTARLA

2015-06-01

Full Text Available In health care institutions aiming healthy society by the way protecting and promoting human health, reaching information has a vital importance. This descriptive research purposed an evaluation of organizational learning capability of 396 employees working in Gülhane Military Medical Academy Hospital. A questionnaire including socio-demographic characteristics was used along with Organizational Learning Capability scale designed by Ricardo CHIVA and His Friends. Data acquired was analyzed with SPSS 15.0 program. Participants’ Organizational Learning Capability and its subscales means were assessed in terms of their sociodemographic characteristics. Assessing participants’ answers in terms of 5 subscales which are experimentation, risk taking, interaction with the external environment, dialogue and participatory decision-making; for education level and professional groups, statistical significant differences was found between Organizational Learning Capability and its subscales means.

Working Memory Functioning in Children with Learning Disorders and Specific Language Impairment

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Schuchardt, Kirsten; Bockmann, Ann-Katrin; Bornemann, Galina; Maehler, Claudia

2013-01-01

Purpose: On the basis of Baddeley's working memory model (1986), we examined working memory functioning in children with learning disorders with and without specific language impairment (SLI). We pursued the question whether children with learning disorders exhibit similar working memory deficits as children with additional SLI. Method: In…

Placement and Achievement of Urban Hispanic Middle Schoolers with Specific Learning Disabilities

Science.gov (United States)

Barrocas, Lisa; Cramer, Elizabeth D.

2014-01-01

This study examined achievement gains in reading and math for Hispanic middle school students with specific learning disabilities in inclusive versus segregated settings in a large urban school district. The authors report learning gains for students with and without disabilities in inclusive versus segregated settings. Results indicate no…

Learning physical space

DEFF Research Database (Denmark)

Hasse, Cathrine

2002-01-01

The article argues that cultural learning is a useful concept in analysing how neophytes learn from reactions and other forms of social designation. Through the newcomers learning process a concrete physical place takes on new cultural meaning. The specific example deals with first year students...... who have to learn that certain physical places, acts and objects are imbued with a cultural significance as the act of sitting on a chair or wearing a short dress takes on a new symbolic meaning in a cultural context where inclusion and exclusion are a constant concern. By following and analysing what...... is involved in the process of becoming ? in this case the becoming of physicist students ? the moral cultural logic behind in- and exclusion from physical places are established....

Best practices in incident investigation in the chemical process industries with examples from the industry sector and specifically from Nova Chemicals

International Nuclear Information System (INIS)

Morrison, Lisa M.

2004-01-01

This paper will summarize best practices in incident investigation in the chemical process industries and will provide examples from both the industry sector and specifically from NOVA Chemicals. As a sponsor of the Center for Chemical Process Safety (CCPS), an industry technology alliance of the American Institute of Chemical Engineers, NOVA Chemicals participates in a number of working groups to help develop best practices and tools for the chemical process and associated industries in order to advance chemical process safety. A recent project was to develop an update on guidelines for investigating chemical process incidents. A successful incident investigation management system must ensure that all incidents and near misses are reported, that root causes are identified, that recommendations from incident investigations identify appropriate preventive measures, and that these recommendations are resolved in a timely manner. The key elements of an effective management system for incident investigation will be described. Accepted definitions of such terms as near miss, incident, and root cause will be reviewed. An explanation of the types of incident classification systems in use, along with expected levels of follow-up, will be provided. There are several incident investigation methodologies in use today by members of the CCPS; most of these methodologies incorporate the use of several tools. These tools include: timelines, sequence diagrams, causal factor identification, brainstorming, checklists, pre-defined trees, and team-defined logic trees. Developing appropriate recommendations and then ensuring their resolution is the key to prevention of similar events from recurring, along with the sharing of lessons learned from incidents. There are several sources of information on previous incidents and lessons learned available to companies. In addition, many companies in the chemical process industries use their own internal databases to track recommendations from

Challenges in the Verification of Reinforcement Learning Algorithms

Science.gov (United States)

Van Wesel, Perry; Goodloe, Alwyn E.

2017-01-01

Machine learning (ML) is increasingly being applied to a wide array of domains from search engines to autonomous vehicles. These algorithms, however, are notoriously complex and hard to verify. This work looks at the assumptions underlying machine learning algorithms as well as some of the challenges in trying to verify ML algorithms. Furthermore, we focus on the specific challenges of verifying reinforcement learning algorithms. These are highlighted using a specific example. Ultimately, we do not offer a solution to the complex problem of ML verification, but point out possible approaches for verification and interesting research opportunities.

Simulations with Elaborated Worked Example Modeling: Beneficial Effects on Schema Acquisition

Science.gov (United States)

Meier, Debra K.; Reinhard, Karl J.; Carter, David O.; Brooks, David W.

2008-01-01

Worked examples have been effective in enhancing learning outcomes, especially with novice learners. Most of this research has been conducted in laboratory settings. This study examined the impact of embedding elaborated worked example modeling in a computer simulation practice activity on learning achievement among 39 undergraduate students…

Video2vec Embeddings Recognize Events When Examples Are Scarce.

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Habibian, Amirhossein; Mensink, Thomas; Snoek, Cees G M

2017-10-01

This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire representation from freely available web videos and their descriptions using an embedding between video features and term vectors. In our proposed embedding, which we call Video2vec, the correlations between the words are utilized to learn a more effective representation by optimizing a joint objective balancing descriptiveness and predictability. We show how learning the Video2vec embedding using a multimodal predictability loss, including appearance, motion and audio features, results in a better predictable representation. We also propose an event specific variant of Video2vec to learn a more accurate representation for the words, which are indicative of the event, by introducing a term sensitive descriptiveness loss. Our experiments on three challenging collections of web videos from the NIST TRECVID Multimedia Event Detection and Columbia Consumer Videos datasets demonstrate: i) the advantages of Video2vec over representations using attributes or alternative embeddings, ii) the benefit of fusing video modalities by an embedding over common strategies, iii) the complementarity of term sensitive descriptiveness and multimodal predictability for event recognition. By its ability to improve predictability of present day audio-visual video features, while at the same time maximizing their semantic descriptiveness, Video2vec leads to state-of-the-art accuracy for both few- and zero-example recognition of events in video.

Comparing Three Patterns of Strengths and Weaknesses Models for the Identification of Specific Learning Disabilities

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Miller, Daniel C.; Maricle, Denise E.; Jones, Alicia M.

2016-01-01

Processing Strengths and Weaknesses (PSW) models have been proposed as a method for identifying specific learning disabilities. Three PSW models were examined for their ability to predict expert identified specific learning disabilities cases. The Dual Discrepancy/Consistency Model (DD/C; Flanagan, Ortiz, & Alfonso, 2013) as operationalized by…

Machine learning paradigms applications in recommender systems

CERN Document Server

Lampropoulos, Aristomenis S

2015-01-01

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and ...

Projection specificity in heterogeneous locus coeruleus cell populations: implications for learning and memory

Science.gov (United States)

Uematsu, Akira; Tan, Bao Zhen

2015-01-01

Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory. This relatively small population of cells sends widespread projections throughout the brain including to a number of regions such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is important for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical, behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons respond during associative learning and when previously learned task contingencies change. Together, these studies suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection specificity. PMID:26330494

Alignment-free genome tree inference by learning group-specific distance metrics.

Science.gov (United States)

Patil, Kaustubh R; McHardy, Alice C

2013-01-01

Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. One can now attempt to use genome-scale information, because of the ever increasing number of genomes available. This opportunity also presents a challenge in terms of computational efficiency. Two fundamentally different methods are often employed for sequence comparisons, namely alignment-based and alignment-free methods. Alignment-free methods rely on the genome signature concept and provide a computationally efficient way that is also applicable to nonhomologous sequences. The genome signature contains evolutionary signal as it is more similar for closely related organisms than for distantly related ones. We used genome-scale sequence information to infer taxonomic distances between organisms without additional information such as gene annotations. We propose a method to improve genome tree inference by learning specific distance metrics over the genome signature for groups of organisms with similar phylogenetic, genomic, or ecological properties. Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. By applying this method to more than a thousand prokaryotic genomes, we showed that, indeed, better distance metrics could be learned for most of the 18 groups of organisms tested here. Once a group-specific metric is available, it can be used to estimate the taxonomic distances for other sequenced organisms from the group. This study also presents a large scale comparison between 10 methods--9 alignment-free and 1 alignment-based.

With Educational Benefits for All: Campus Inclusion through Learning Communities Designed for Underserved Student Populations

Science.gov (United States)

Fink, John E.; Hummel, Mary L.

2015-01-01

This chapter explores the practices of learning communities designed for specific, underserved student populations, highlighting on-campus examples and culminating with a synthesized list of core practices from these "inclusive" learning communities.

To what degree does the missing-data technique influence the estimated growth in learning strategies over time? A tutorial example of sensitivity analysis for longitudinal data.

Science.gov (United States)

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2017-01-01

Longitudinal data is almost always burdened with missing data. However, in educational and psychological research, there is a large discrepancy between methodological suggestions and research practice. The former suggests applying sensitivity analysis in order to the robustness of the results in terms of varying assumptions regarding the mechanism generating the missing data. However, in research practice, participants with missing data are usually discarded by relying on listwise deletion. To help bridge the gap between methodological recommendations and applied research in the educational and psychological domain, this study provides a tutorial example of sensitivity analysis for latent growth analysis. The example data concern students' changes in learning strategies during higher education. One cohort of students in a Belgian university college was asked to complete the Inventory of Learning Styles-Short Version, in three measurement waves. A substantial number of students did not participate on each occasion. Change over time in student learning strategies was assessed using eight missing data techniques, which assume different mechanisms for missingness. The results indicated that, for some learning strategy subscales, growth estimates differed between the models. Guidelines in terms of reporting the results from sensitivity analysis are synthesised and applied to the results from the tutorial example.

Mobile Learning Based Worked Example in Electric Circuit (WEIEC) Application to Improve the High School Students' Electric Circuits Interpretation Ability

Science.gov (United States)

Yadiannur, Mitra; Supahar

2017-01-01

This research aims to determine the feasibility and effectivity of mobile learning based Worked Example in Electric Circuits (WEIEC) application in improving the high school students' electric circuits interpretation ability on Direct Current Circuits materials. The research method used was a combination of Four-D Models and ADDIE model. The…

Is there a need for a specific educational scholarship for using e-learning in medical education?

Science.gov (United States)

Sandars, John; Goh, Poh Sun

2016-10-01

We propose the need for a specific educational scholarship when using e-learning in medical education. Effective e-learning has additional factors that require specific critical attention, including the design and delivery of e-learning. An important aspect is the recognition that e-learning is a complex intervention, with several interconnecting components that have to be aligned. This alignment requires an essential iterative development process with usability testing. Effectiveness of e-learning in one context may not be fully realized in another context unless there is further consideration of applicability and scalability. We recommend a participatory approach for an educational scholarship for using e-learning in medical education, such as by action research or design-based research.

Learning by Example: Designing and Developing Linked Data Application

Science.gov (United States)

Tharani, Karim

2016-01-01

According to constructivist theory of learning, new knowledge is learned on the basis of what is already known by learners. Thus for an emerging and transformative technology such as Linked Data to be learned, the technology must be made relevant for learners and must be compatible with their skillset. Designing and developing Linked Data…

A new learning paradigm: learning using privileged information.

Science.gov (United States)

Vapnik, Vladimir; Vashist, Akshay

2009-01-01

In the Afterword to the second edition of the book "Estimation of Dependences Based on Empirical Data" by V. Vapnik, an advanced learning paradigm called Learning Using Hidden Information (LUHI) was introduced. This Afterword also suggested an extension of the SVM method (the so called SVM(gamma)+ method) to implement algorithms which address the LUHI paradigm (Vapnik, 1982-2006, Sections 2.4.2 and 2.5.3 of the Afterword). See also (Vapnik, Vashist, & Pavlovitch, 2008, 2009) for further development of the algorithms. In contrast to the existing machine learning paradigm where a teacher does not play an important role, the advanced learning paradigm considers some elements of human teaching. In the new paradigm along with examples, a teacher can provide students with hidden information that exists in explanations, comments, comparisons, and so on. This paper discusses details of the new paradigm and corresponding algorithms, introduces some new algorithms, considers several specific forms of privileged information, demonstrates superiority of the new learning paradigm over the classical learning paradigm when solving practical problems, and discusses general questions related to the new ideas.

Learning e-Learning

Directory of Open Access Journals (Sweden)

Gabriel ZAMFIR

2009-01-01

Full Text Available What You Understand Is What Your Cognitive Integrates. Scientific research develops, as a native environment, knowledge. This environment consists of two interdependent divisions: theory and technology. First division occurs as a recursive research, while the second one becomes an application of the research activity. Over time, theories integrate methodologies and technology extends as infrastructure. The engine of this environment is learning, as the human activity of knowledge work. The threshold term of this model is the concepts map; it is based on Bloom’ taxonomy for the cognitive domain and highlights the notion of software scaffolding which is grounded in Vygotsky’s Social Development Theory with its major theme, Zone of Proximal Development. This article is designed as a conceptual paper, which analyzes specific structures of this type of educational research: the model reflects a foundation for a theory and finally, the theory evolves as groundwork for a system. The outcomes of this kind of approach are the examples, which are, theoretically, learning outcomes, and practically exist as educational objects, so-called e-learning.

First-order and higher order sequence learning in specific language impairment.

Science.gov (United States)

Clark, Gillian M; Lum, Jarrad A G

2017-02-01

A core claim of the procedural deficit hypothesis of specific language impairment (SLI) is that the disorder is associated with poor implicit sequence learning. This study investigated whether implicit sequence learning problems in SLI are present for first-order conditional (FOC) and higher order conditional (HOC) sequences. Twenty-five children with SLI and 27 age-matched, nonlanguage-impaired children completed 2 serial reaction time tasks. On 1 version, the sequence to be implicitly learnt comprised a FOC sequence and on the other a HOC sequence. Results showed that the SLI group learned the HOC sequence (η p ² = .285, p = .005) but not the FOC sequence (η p ² = .099, p = .118). The control group learned both sequences (FOC η p ² = .497, HOC η p 2= .465, ps < .001). The SLI group's difficulty learning the FOC sequence is consistent with the procedural deficit hypothesis. However, the study provides new evidence that multiple mechanisms may underpin the learning of FOC and HOC sequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

Science.gov (United States)

Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

2014-02-01

This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

Examples of learning activities for Earth and Space Sciences in the new Italian National curriculum

Science.gov (United States)

Macario, Maddalena

2016-04-01

In the last few years, starting from 2010, science curricula were changed dramatically in the secondary Italian school as consequence of a radical law reform. In particular, Earth Science and Astronomy subjects have been shifted from the last to the previous school years; in addition, these subjects have been integrated with other natural sciences learning, such as biology and chemistry. As a consequence, Italian teachers felt forced to totally revise their teaching methods for all of these disciplines. The most demanding need was adapting content to younger learners, as those of the first years are, who usually do have neither pre-knowledge in physics nor high level maths skills. Secondly, content learning was progressively driven toward a greater attention to environmental issues in order to raise more awareness in learners about global changes as examples of fragile equilibrium of our planet. In this work some examples of activities are shown, to introduce students to some astronomical phenomena in a simpler way, which play a key role in influencing other Earth's events, in order to make pupils more conscious about how and to what extent our planet depends on space, at different time scales. The activities range from moon motions affecting tides, to secondary Earth motions, which are responsible for climate changes, to the possibility to find life forms in other parts of the Universe, to the possibility for humans to live in the space for future space missions. Students are involved in hands-on inquiry-based laboratories that scaffold both theoretic knowledge and practical skills for a deeper understanding of cause-effect relationships existing in the Earth.

A Collaborative Learning Network Approach to Improvement: The CUSP Learning Network.

Science.gov (United States)

Weaver, Sallie J; Lofthus, Jennifer; Sawyer, Melinda; Greer, Lee; Opett, Kristin; Reynolds, Catherine; Wyskiel, Rhonda; Peditto, Stephanie; Pronovost, Peter J

2015-04-01

Collaborative improvement networks draw on the science of collaborative organizational learning and communities of practice to facilitate peer-to-peer learning, coaching, and local adaption. Although significant improvements in patient safety and quality have been achieved through collaborative methods, insight regarding how collaborative networks are used by members is needed. Improvement Strategy: The Comprehensive Unit-based Safety Program (CUSP) Learning Network is a multi-institutional collaborative network that is designed to facilitate peer-to-peer learning and coaching specifically related to CUSP. Member organizations implement all or part of the CUSP methodology to improve organizational safety culture, patient safety, and care quality. Qualitative case studies developed by participating members examine the impact of network participation across three levels of analysis (unit, hospital, health system). In addition, results of a satisfaction survey designed to evaluate member experiences were collected to inform network development. Common themes across case studies suggest that members found value in collaborative learning and sharing strategies across organizational boundaries related to a specific improvement strategy. The CUSP Learning Network is an example of network-based collaborative learning in action. Although this learning network focuses on a particular improvement methodology-CUSP-there is clear potential for member-driven learning networks to grow around other methods or topic areas. Such collaborative learning networks may offer a way to develop an infrastructure for longer-term support of improvement efforts and to more quickly diffuse creative sustainment strategies.

School-wide PBIS: An Example of Applied Behavior Analysis Implemented at a Scale of Social Importance.

Science.gov (United States)

Horner, Robert H; Sugai, George

2015-05-01

School-wide Positive Behavioral Interventions and Supports (PBIS) is an example of applied behavior analysis implemented at a scale of social importance. In this paper, PBIS is defined and the contributions of behavior analysis in shaping both the content and implementation of PBIS are reviewed. Specific lessons learned from implementation of PBIS over the past 20 years are summarized.

Time-lapse videos for physics education: specific examples

Science.gov (United States)

Vollmer, Michael; Möllmann, Klaus-Peter

2018-05-01

There are many physics experiments with long time scales such that they are usually neither shown in the physics class room nor in student labs. However, they can be easily recorded with time-lapse cameras and the respective time-lapse videos allow qualitative and/or quantitative analysis of the underlying physics. Here, we present some examples from thermal physics (melting, evaporation, cooling) as well as diffusion processes

Code-specific learning rules improve action selection by populations of spiking neurons.

Science.gov (United States)

Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

2014-08-01

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

The Context-Specific Conceptions of Learning in Case-Based Accounting Assignments, Students' Characteristics and Performance

Science.gov (United States)

Moilanen, Sinikka

2017-01-01

The present study contributes to accounting education literature by describing context-specific conceptions of learning related to case assignments, and by exploring the associations between the conceptions of learning, students' characteristics and performance. The data analysed consist of 1320 learning diaries of 336 students, connected with…

Investigating learning strategies in a dispositional learning analytics context: the case of worked examples

NARCIS (Netherlands)

Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan

2018-01-01

This study aims to contribute to recent developments in empirical studies on students’ learning strategies, whereby the use of trace data is combined with self-report data to distinguish profiles of learning strategy use [3–5]. We do so in the context of an application of dispositional learning

d-Cycloserine reduces context specificity of sexual extinction learning.

Science.gov (United States)

Brom, Mirte; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip; Trimbos, Baptist; Both, Stephanie

2015-11-01

d-Cycloserine (DCS) enhances extinction processes in animals. Although classical conditioning is hypothesized to play a pivotal role in the aetiology of appetitive motivation problems, no research has been conducted on the effect of DCS on the reduction of context specificity of extinction in human appetitive learning, while facilitation hereof is relevant in the context of treatment of problematic reward-seeking behaviors. Female participants were presented with two conditioned stimuli (CSs) that either predicted (CS+) or did not predict (CS-) a potential sexual reward (unconditioned stimulus (US); genital vibrostimulation). Conditioning took place in context A and extinction in context B. Subjects received DCS (125mg) or placebo directly after the experiment on day 1 in a randomized, double-blind, between-subject fashion (Placebo n=31; DCS n=31). Subsequent testing for CS-evoked conditioned responses (CRs) in both the conditioning (A) and the extinction context (B) took place 24h later on day 2. Drug effects on consolidation were then assessed by comparing the recall of sexual extinction memories between the DCS and the placebo groups. Post learning administration of DCS facilitates sexual extinction memory consolidation and affects extinction's fundamental context specificity, evidenced by reduced conditioned genital and subjective sexual responses, relative to placebo, for presentations of the reward predicting cue 24h later outside the extinction context. DCS makes appetitive extinction memories context-independent and prevents the return of conditioned response. NMDA receptor glycine site agonists may be potential pharmacotherapies for the prevention of relapse of appetitive motivation disorders with a learned component. Copyright © 2015 Elsevier Inc. All rights reserved.

The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

Science.gov (United States)

Kunsting, Josef; Wirth, Joachim; Paas, Fred

2011-01-01

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

Learning trajectories for speech motor performance in children with specific language impairment.

Science.gov (United States)

Richtsmeier, Peter T; Goffman, Lisa

2015-01-01

Children with specific language impairment (SLI) often perform below expected levels, including on tests of motor skill and in learning tasks, particularly procedural learning. In this experiment we examined the possibility that children with SLI might also have a motor learning deficit. Twelve children with SLI and thirteen children with typical development (TD) produced complex nonwords in an imitation task. Productions were collected across three blocks, with the first and second blocks on the same day and the third block one week later. Children's lip movements while producing the nonwords were recorded using an Optotrak camera system. Movements were then analyzed for production duration and stability. Movement analyses indicated that both groups of children produced shorter productions in later blocks (corroborated by an acoustic analysis), and the rate of change was comparable for the TD and SLI groups. A nonsignificant trend for more stable productions was also observed in both groups. SLI is regularly accompanied by a motor deficit, and this study does not dispute that. However, children with SLI learned to make more efficient productions at a rate similar to their peers with TD, revealing some modification of the motor deficit associated with SLI. The reader will learn about deficits commonly associated with specific language impairment (SLI) that often occur alongside the hallmark language deficit. The authors present an experiment showing that children with SLI improved speech motor performance at a similar rate compared to typically developing children. The implication is that speech motor learning is not impaired in children with SLI. Copyright © 2015 Elsevier Inc. All rights reserved.

Benefits of augmentative signs in word learning: Evidence from children who are deaf/hard of hearing and children with specific language impairment.

Science.gov (United States)

van Berkel-van Hoof, Lian; Hermans, Daan; Knoors, Harry; Verhoeven, Ludo

2016-12-01

Augmentative signs may facilitate word learning in children with vocabulary difficulties, for example, children who are Deaf/Hard of Hearing (DHH) and children with Specific Language Impairment (SLI). Despite the fact that augmentative signs may aid second language learning in populations with a typical language development, empirical evidence in favor of this claim is lacking. We aim to investigate whether augmentative signs facilitate word learning for DHH children, children with SLI, and typically developing (TD) children. Whereas previous studies taught children new labels for familiar objects, the present study taught new labels for new objects. In our word learning experiment children were presented with pictures of imaginary creatures and pseudo words. Half of the words were accompanied by an augmentative pseudo sign. The children were tested for their receptive word knowledge. The DHH children benefitted significantly from augmentative signs, but the children with SLI and TD age-matched peers did not score significantly different on words from either the sign or no-sign condition. These results suggest that using Sign-Supported speech in classrooms of bimodal bilingual DHH children may support their spoken language development. The difference between earlier research findings and the present results may be caused by a difference in methodology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Semi-supervised eigenvectors for large-scale locally-biased learning

DEFF Research Database (Denmark)

Hansen, Toke Jansen; Mahoney, Michael W.

2014-01-01

improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph......In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks nearby that prespecified target region. For example, one might......-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing...

Context Fear Learning Specifically Activates Distinct Populations of Neurons in Amygdala and Hypothalamus

Science.gov (United States)

Trogrlic, Lidia; Wilson, Yvette M.; Newman, Andrew G.; Murphy, Mark

2011-01-01

The identity and distribution of neurons that are involved in any learning or memory event is not known. In previous studies, we identified a discrete population of neurons in the lateral amygdala that show learning-specific activation of a c-"fos"-regulated transgene following context fear conditioning. Here, we have extended these studies to…

Individualized Learning Through Non-Linear use of Learning Objects: With Examples From Math and Stat

DEFF Research Database (Denmark)

Rootzén, Helle

2015-01-01

Our aim is to ensure individualized learning that is fun, inspiring and innovative. We believe that when you enjoy, your brain will open up and learning will be easier and more effective. The methods use a non-linear learning environment based on self-contained learning objects which are pieced t...

Application of learning from examples methods for on-line dynamic security assessment of electric power systems - state of the art

Energy Technology Data Exchange (ETDEWEB)

Pecas Lopes, J.A. [Universidade do Porto, Porto (Portugal). Faculdade de Engenharia] Hatziargyriou, Nikos D. [National Technical University of Athens, Athens (Greece)

1994-12-31

This paper provides an overview of the application of `learning from examples` techniques like pattern recognition, artificial neural networks and decision trees, when used for fast dynamic security assessment. Problems concerning the system security evaluation relatively to transient stability and voltage stability are addressed with more details and references to research works in this field are briefly described. (author) 44 refs., 3 tabs.

Statistical word learning in children with autism spectrum disorder and specific language impairment.

Science.gov (United States)

Haebig, Eileen; Saffran, Jenny R; Ellis Weismer, Susan

2017-11-01

Word learning is an important component of language development that influences child outcomes across multiple domains. Despite the importance of word knowledge, word-learning mechanisms are poorly understood in children with specific language impairment (SLI) and children with autism spectrum disorder (ASD). This study examined underlying mechanisms of word learning, specifically, statistical learning and fast-mapping, in school-aged children with typical and atypical development. Statistical learning was assessed through a word segmentation task and fast-mapping was examined in an object-label association task. We also examined children's ability to map meaning onto newly segmented words in a third task that combined exposure to an artificial language and a fast-mapping task. Children with SLI had poorer performance on the word segmentation and fast-mapping tasks relative to the typically developing and ASD groups, who did not differ from one another. However, when children with SLI were exposed to an artificial language with phonemes used in the subsequent fast-mapping task, they successfully learned more words than in the isolated fast-mapping task. There was some evidence that word segmentation abilities are associated with word learning in school-aged children with typical development and ASD, but not SLI. Follow-up analyses also examined performance in children with ASD who did and did not have a language impairment. Children with ASD with language impairment evidenced intact statistical learning abilities, but subtle weaknesses in fast-mapping abilities. As the Procedural Deficit Hypothesis (PDH) predicts, children with SLI have impairments in statistical learning. However, children with SLI also have impairments in fast-mapping. Nonetheless, they are able to take advantage of additional phonological exposure to boost subsequent word-learning performance. In contrast to the PDH, children with ASD appear to have intact statistical learning, regardless of

Effects of practice schedule and task specificity on the adaptive process of motor learning.

Science.gov (United States)

Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

The Learning Leader: Reflecting, Modeling, and Sharing

Science.gov (United States)

Jacobs, Jacqueline E.; O'Gorman, Kevin L.

2012-01-01

With this book, principals, principals-in-training, and other school leaders get practical, easy-to-implement strategies for professional growth, strengthening relationships with faculty and staff, and making the necessary changes to improve K-12 learning environments. Grounded in specific, real-world examples and personal experiences, "The…

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

Science.gov (United States)

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

Talker-specific learning in amnesia: Insight into mechanisms of adaptive speech perception.

Science.gov (United States)

Trude, Alison M; Duff, Melissa C; Brown-Schmidt, Sarah

2014-05-01

A hallmark of human speech perception is the ability to comprehend speech quickly and effortlessly despite enormous variability across talkers. However, current theories of speech perception do not make specific claims about the memory mechanisms involved in this process. To examine whether declarative memory is necessary for talker-specific learning, we tested the ability of amnesic patients with severe declarative memory deficits to learn and distinguish the accents of two unfamiliar talkers by monitoring their eye-gaze as they followed spoken instructions. Analyses of the time-course of eye fixations showed that amnesic patients rapidly learned to distinguish these accents and tailored perceptual processes to the voice of each talker. These results demonstrate that declarative memory is not necessary for this ability and points to the involvement of non-declarative memory mechanisms. These results are consistent with findings that other social and accommodative behaviors are preserved in amnesia and contribute to our understanding of the interactions of multiple memory systems in the use and understanding of spoken language. Copyright © 2014 Elsevier Ltd. All rights reserved.

The geological model calibration - Learnings from integration of reservoir geology and field performance - Example from the upper carboniferous reservoirs of the Southern North Sea

NARCIS (Netherlands)

Moscariello, A.; Hoof, T.B. van; Kunakbayeva, G.; Veen, J.H. ten; Belt, F. van den; Twerda, A.; Peters, L.; Davis, P.; Williams, H.

2013-01-01

The Geological Model Calibration - Learnings from Integration of Reservoir Geology and Field Performance: example from the Upper Carboniferous Reservoirs of the Southern North Sea. Copyright © (2012) by the European Association of Geoscientists & Engineers All rights reserved.

Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption

OpenAIRE

Bao, Yukun; Xiong, Tao; Hu, Zhongyi; Kibelloh, Mboni

2014-01-01

Reasons for contradictory findings regarding the gender moderate effect on computer self-efficacy in the adoption of e-learning/mobile learning are limited. Recognizing the multilevel nature of the computer self-efficacy (CSE), this study attempts to explore gender differences in the adoption of mobile learning, by extending the Technology Acceptance Model (TAM) with general and specific CSE. Data collected from 137 university students were tested against the research model using the structur...

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

Science.gov (United States)

Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

2013-07-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

International Nuclear Information System (INIS)

Gueth, P; Freud, N; Létang, J M; Sarrut, D; Dauvergne, D; Ray, C; Testa, E

2013-01-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations. (paper)

Does Structured Quizzing with Process Specific Feedback Lead to Learning Gains in an Active Learning Geoscience Classroom?

Science.gov (United States)

Palsole, S.; Serpa, L. F.

2013-12-01

There is a great realization that efficient teaching in the geosciences has the potential to have far reaching effects in outreach to decision and policy makers (Herbert, 2006; Manduca & Mogk, 2006). This research in turn informs educators that the geosciences by the virtue of their highly integrative nature play an important role in serving as an entry point into STEM disciplines and helping developing a new cadre of geoscientists, scientists and a general population with an understanding of science. Keeping these goals in mind we set to design introductory geoscience courses for non-majors and majors that move away from the traditional lecture models which don't necessarily contribute well to knowledge building and retention ((Handelsman et al., 2007; Hake, 1997) to a blended active learning classroom where basic concepts and didactic information is acquired online via webquests, lecturettes and virtual field trips and the face to face portions of the class are focused on problem solving exercises. The traditional way to ensure that students are prepared for the in-class activity is to have the students take a quiz online to demonstrate basic competency. In the process of redesign, we decided to leverage the technology to build quizzes that are highly structured and map to a process (formation of divergent boundaries for example) or sets of earth processes that we needed the students to know before in-class activities. The quizzes can be taken multiple times and provide process specific feedback, thus serving as a heuristic to the students to ensure they have acquired the necessary competency. The heuristic quizzes were developed and deployed over a year with the student data driving the redesign process to ensure synchronicity. Preliminary data analysis indicates a positive correlation between higher student scores on in-class application exercises and time spent on the process quizzes. An assessment of learning gains also indicate a higher degree of self

Implementing US Department of Energy lessons learned programs. Volume 2

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-08-01

The DOE Lessons Learned Handbook is a two-volume publication developed to supplement the DOE Lessons Learned Standard (DOE-STD-7501-95) with information that will organizations in developing or improving their lessons learned programs. Volume 1 includes greater detail than the Standard in areas such as identification and documentation of lessons learned; it also contains sections on specific processes such as training and performance measurement. Volume 2 (this document) contains examples of program documents developed by existing lessons learned programs as well as communications material, functional categories, transmittal documents, sources of professional and industry lessons learned, and frequently asked questions about the Lessons Learned List Service.

Robust semi-supervised learning : projections, limits & constraints

NARCIS (Netherlands)

Krijthe, J.H.

2018-01-01

In many domains of science and society, the amount of data being gathered is increasing rapidly. To estimate input-output relationships that are often of interest, supervised learning techniques rely on a specific type of data: labeled examples for which we know both the input and an outcome. The

The learning continuum based on student's level of competence and specific pedagogical learning material on physiological aspects from teachers's opinions

Science.gov (United States)

Hadi, Ria Fitriyani; Subali, Bambang

2017-08-01

The scope of learning continuum at the conceptual knowledge is formulated based on the student's level of competence and specific pedagogical learning material. The purpose of this study is to develop a learning continuum of specific pedagogical material aspects of physiology targeted for students in primary and secondary education. This research was conducted in Province of Yogyakarta Special Region from October 2016 to January 2017. The method used in this study was survey method. The data were collected using questionnaire that had been validated from the aspects of construct validity and experts judgements. Respondents in this study consist of 281 Science/Biology teachers at Public Junior and Senior High Schools in the Province of Yogyakarta Special Region which spread in Yogyakarta city and 4 regencies namely Sleman, Bantul, Kulonprogo, and Gunungkidul. The data were taken using a census. Data were analyzed using a descriptive analysis technique. The results show the learning continuum of physiology based on teachers's opinion from grade VII, VIII, and IX are taught in grade VII, VIII, IX and X on level of C2 (understanding) and the learning continuum of physiology based on teachers's opinion from grade X, XI and XII are taught in grade X and XI on level of C2 (understanding), C3 (applying), and C4 (analyzing) based on teachers's opinions. The conclusion is that many teachers refer to the existing curriculum rather than their own original idea for developing learning continuum.

D.3.1 PLOT Persuasive Learning Design Framework

DEFF Research Database (Denmark)

Gram-Hansen, Sandra Burri; Schärfe, Henrik; Dinesen, Jens Vilhelm

2011-01-01

offer examples of central issues in learning theories can be aligned with persuasive efforts as seen from a rhetorical point of view. In section 3, we continue the work of defining intersections between persuasion and didactics, where more specifically oriented towards the notions of kairos...

SPECIFICITY OF ECOLOGICAL AUDIT OF BURIAL PLACES AND STORAGES OF RADIOACTIVE WASTES ON THE EXAMPLE OF CHNPP

Directory of Open Access Journals (Sweden)

George O. Biliavskiy

2008-02-01

Full Text Available  The specificity of ecological audit of burial places and storages of radioactive wastes on the example of CHNPP is considered; namely main principles, positions, requirements, tasks, objects, subjects of ecological audit, a team of specialists for its fulfillment, ecological problems, connected with storing of radioactive wastes and their influence on the human’s health. Main possibilities of improving radioactive wastes control system are also considered.

Are Students' Learning Styles Discipline Specific?

Science.gov (United States)

Jones, Cheryl; Reichard, Carla; Mokhtari, Kouider

2003-01-01

This study examines the extent to which community college students' learning style preferences vary as a function of discipline. Reports significant differences in students' learning style preferences across disciplines, but not by gender. Adds that student learning style preferences varied by academic performance as measured by gender. Discusses…

Training hydrologists to be ecohydrologists: A 'how-you-can-do-it' example leveraging an active learning environment

Science.gov (United States)

Lyon, Steve W.; Walter, M. Todd; Jantze, Elin J.; Archibald, Josephine A.

2015-04-01

Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a 'how-you-can-do-it' example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at Stockholm University's Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of 'activeness' across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more 'active' techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.

Training hydrologists to be ecohydrologists: A ';how-you-can-do-it' example leveraging an active learning environment

Science.gov (United States)

Lyon, S. W.; Walter, M. T.; Jantze, E. J.; Archibald, J. A.

2013-12-01

Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a ';how-you-can-do-it' example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at Stockholm University's Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of ';activeness' across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more ';active' techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.

Statistical Learning in Specific Language Impairment and Autism Spectrum Disorder: A Meta-Analysis

Directory of Open Access Journals (Sweden)

Rita Obeid

2016-08-01

Full Text Available Impairments in statistical learning might be a common deficit among individuals with Specific Language Impairment (SLI and Autism Spectrum Disorder (ASD. Using meta-analysis, we examined statistical learning in SLI (14 studies, 15 comparisons and ASD (13 studies, 20 comparisons to evaluate this hypothesis. Effect sizes were examined as a function of diagnosis across multiple statistical learning tasks (Serial Reaction Time, Contextual Cueing, Artificial Grammar Learning, Speech Stream, Observational Learning, Probabilistic Classification. Individuals with SLI showed deficits in statistical learning relative to age-matched controls g = .47, 95% CI [.28, .66], p < .001. In contrast, statistical learning was intact in individuals with ASD relative to controls, g = –.13, 95% CI [–.34, .08], p = .22. Effect sizes did not vary as a function of task modality or participant age. Our findings inform debates about overlapping social-communicative difficulties in children with SLI and ASD by suggesting distinct underlying mechanisms. In line with the procedural deficit hypothesis (Ullman & Pierpont, 2005, impaired statistical learning may account for phonological and syntactic difficulties associated with SLI. In contrast, impaired statistical learning fails to account for the social-pragmatic difficulties associated with ASD.

Using principles of learning to inform language therapy design for children with specific language impairment.

Science.gov (United States)

Alt, Mary; Meyers, Christina; Ancharski, Alexandra

2012-01-01

Language treatment for children with specific language impairment (SLI) often takes months to achieve moderate results. Interventions often do not incorporate the principles that are known to affect learning in unimpaired learners. To outline some key findings about learning in typical populations and to suggest a model of how they might be applied to language treatment design as a catalyst for further research and discussion. Three main principles of implicit learning are reviewed: variability, complexity and sleep-dependent consolidation. After explaining these principles, evidence is provided as to how they influence learning tasks in unimpaired learners. Information is reviewed on principles of learning as they apply to impaired populations, current treatment designs are also reviewed that conform to the principles, and ways in which principles of learning might be incorporated into language treatment design are demonstrated. This paper provides an outline for how theoretical knowledge might be applied to clinical practice in an effort to promote discussion. Although the authors look forward to more specific details on how the principles of learning relate to impaired populations, there is ample evidence to suggest that these principles should be considered during treatment design. © 2012 Royal College of Speech and Language Therapists.

Stochastic gradient learning and instability: an example

Czech Academy of Sciences Publication Activity Database

Slobodyan, Sergey; Bogomolova, A.; Kolyuzhnov, Dmitri

2016-01-01

Roč. 20, č. 3 (2016), s. 777-790 ISSN 1365-1005 R&D Projects: GA ČR(CZ) GCP402/11/J018 Institutional support: PRVOUK-P23 Keywords : constant gain * adaptive learning * e-stability Subject RIV: AH - Economics Impact factor: 0.718, year: 2016

An architecture for an autonomous learning robot

Science.gov (United States)

Tillotson, Brian

1988-01-01

An autonomous learning device must solve the example bounding problem, i.e., it must divide the continuous universe into discrete examples from which to learn. We describe an architecture which incorporates an example bounder for learning. The architecture is implemented in the GPAL program. An example run with a real mobile robot shows that the program learns and uses new causal, qualitative, and quantitative relationships.

Does Tracing Worked Examples Enhance Geometry Learning?

Science.gov (United States)

Hu, Fang-Tzu; Ginns, Paul; Bobis, Janette

2014-01-01

Cognitive load theory seeks to generate novel instructional designs through a focus on human cognitive architecture including a limited working memory; however, the potential for enhancing learning through non-visual or non-auditory working memory channels is yet to be evaluated. This exploratory experiment tested whether explicit instructions to…

Can Social Learning Increase Learning Speed, Performance or Both?

NARCIS (Netherlands)

Heinerman, J.V.; Stork, J.; Rebolledo Coy, M.A.; Hubert, J.G.; Eiben, A.E.; Bartz-Beielstein, Thomas; Haasdijk, Evert

2017-01-01

Social learning enables multiple robots to share learned experiences while completing a task. The literature offers contradicting examples of its benefits; robots trained with social learning reach a higher performance, an increased learning speed, or both, compared to their individual learning

Cognitive Load Theory and the Use of Worked Examples as an Instructional Strategy in Physics for Distance Learners: A Preliminary Study

Directory of Open Access Journals (Sweden)

Kim Guan SAW

2017-10-01

Full Text Available This article revisits the cognitive load theory to explore the use of worked examples to teach a selected topic in a higher level undergraduate physics course for distance learners at the School of Distance Education, Universiti Sains Malaysia. With a break of several years from receiving formal education and having only minimum science background, distance learners need an appropriate instructional strategy for courses that require complex conceptualization and mathematical manipulations. As the working memory is limited, distance learners need to acquire domain specific knowledge in stages to lessen cognitive load. This article charts a learning task with a lower cognitive load to teach Fermi-Dirac distribution and demonstrates the use of sequential worked examples. Content taught in stages using worked examples can be presented as a form of didactic conversation to reduce transactional distance. This instructional strategy can be applied to similar challenging topics in other well-structured domains in a distance learning environment.

Cognitive deficits are a matter of emotional context: inflexible strategy use mediates context-specific learning impairments in OCD.

Science.gov (United States)

Zetsche, Ulrike; Rief, Winfried; Westermann, Stefan; Exner, Cornelia

2015-01-01

The present study examines the interplay between cognitive deficits and emotional context in obsessive-compulsive disorder (OCD) and social phobia (SP). Specifically, this study examines whether the inflexible use of efficient learning strategies in an emotional context underlies impairments in probabilistic classification learning (PCL) in OCD, and whether PCL impairments are specific to OCD. Twenty-three participants with OCD, 30 participants with SP and 30 healthy controls completed a neutral and an OCD-specific PCL task. OCD participants failed to adopt efficient learning strategies and showed fewer beneficial strategy switches than controls only in an OCD-specific context, but not in a neutral context. Additionally, OCD participants did not show any explicit memory impairments. Number of beneficial strategy switches in the OCD-specific task mediated the difference in PCL performance between OCD and control participants. Individuals with SP were impaired in both PCL tasks. In contrast to neuropsychological models postulating general cognitive impairments in OCD, the present findings suggest that it is the interaction between cognition and emotion that is impaired in OCD. Specifically, activated disorder-specific fears may impair the flexible adoption of efficient learning strategies and compromise otherwise unimpaired PCL. Impairments in PCL are not specific to OCD.

Specific learning disability in mathematics: a comprehensive review.

Science.gov (United States)

Soares, Neelkamal; Evans, Teresa; Patel, Dilip R

2018-01-01

Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described.

Significant Learning and Civic Education: Shifting Frameworks for Teaching in Light of Learning about the Financial Crisis

Directory of Open Access Journals (Sweden)

KimMarie McGoldrick

2011-10-01

Full Text Available The recent financial crisis has motivated economic educators to rethink what economics should be taught, acknowledging disconnects between classroom content and real world events. We introduce a learning theory approach that is broader, one that goes beyond such context specific discussions of foundational knowledge and application (i.e., teaching about this specific crisis and provide a framework to address the broader issue of how teaching practices can, by their very nature, minimize such disconnects and provide more effective processes for teaching about current economic conditions. The theory of significant learning (Fink 2003 is presented as a model of how experiences can be used to develop a deep approach to learning, learning that lasts. Experiential learning pedagogies are timeless in that they can be readily modified to promote deeper understanding over a wide range of economic environments. Focusing on one category of significant learning, the human dimension, and one component of the financial crisis, unemployment, examples which modify existing experiential learning practices are described to demonstrate how such pedagogic practices can be readily adapted to teaching and learning about current economic conditions. In short, we demonstrate that incorporating student experiences into pedagogic practice provides a natural alignment of teaching content and real world events, regardless of how those change over time.

Principals' Perceptions of Instructional Leadership for Middle School Students of Color with Specific Learning Disabilities

Science.gov (United States)

Shannon-Luster, Beverly

2013-01-01

Instructional leadership is the most important responsibility for principals and the most vulnerable students in need of productive instructional leadership are students of color with specific learning disabilities. Instructional leaders are challenged with creating supportive learning environments and school cultures that promotes the education…

Motivating the interest in Danish literature with Mobile Persuasive Learning

DEFF Research Database (Denmark)

Gram-Hansen, Sandra Burri; Kristensen, Karina Dyrby; Gram-Hansen, Lasse Burri

2013-01-01

This paper analyses and discusses the potential of Mobile Persuasive Learning (MPL) in relation to learning scenarios that involve complex and interdisciplinary learning material. A specific example of MPL is presented, which has been developed with the intent to motivate the interest of the life...... and works of Danish author and playwright Kaj Munk. A Persuasive Learning Design (PLD) is tried in a specific learning scenario that aims to introduce the history of Kaj Munk to students in lower secondary education in Vester Hassing in Northern Jutland. The methodological background for the chosen scenario...... is described and evaluation activities are presented and discussed and it is argued that while the topic is possibly too complex for the particular age group of students chosen, evaluation feedback and researcher observations point towards a significant potential in further developing MPL-designs in a school...

Grammar predicts procedural learning and consolidation deficits in children with Specific Language Impairment.

Science.gov (United States)

Hedenius, Martina; Persson, Jonas; Tremblay, Antoine; Adi-Japha, Esther; Veríssimo, João; Dye, Cristina D; Alm, Per; Jennische, Margareta; Bruce Tomblin, J; Ullman, Michael T

2011-01-01

The Procedural Deficit Hypothesis (PDH) posits that Specific Language Impairment (SLI) can be largely explained by abnormalities of brain structures that subserve procedural memory. The PDH predicts impairments of procedural memory itself, and that such impairments underlie the grammatical deficits observed in the disorder. Previous studies have indeed reported procedural learning impairments in SLI, and have found that these are associated with grammatical difficulties. The present study extends this research by examining consolidation and longer-term procedural sequence learning in children with SLI. The Alternating Serial Reaction Time (ASRT) task was given to children with SLI and typically developing (TD) children in an initial learning session and an average of three days later to test for consolidation and longer-term learning. Although both groups showed evidence of initial sequence learning, only the TD children showed clear signs of consolidation, even though the two groups did not differ in longer-term learning. When the children were re-categorized on the basis of grammar deficits rather than broader language deficits, a clearer pattern emerged. Whereas both the grammar impaired and normal grammar groups showed evidence of initial sequence learning, only those with normal grammar showed consolidation and longer-term learning. Indeed, the grammar-impaired group appeared to lose any sequence knowledge gained during the initial testing session. These findings held even when controlling for vocabulary or a broad non-grammatical language measure, neither of which were associated with procedural memory. When grammar was examined as a continuous variable over all children, the same relationships between procedural memory and grammar, but not vocabulary or the broader language measure, were observed. Overall, the findings support and further specify the PDH. They suggest that consolidation and longer-term procedural learning are impaired in SLI, but that these

Grammar Predicts Procedural Learning and Consolidation Deficits in Children with Specific Language Impairment

Science.gov (United States)

Hedenius, Martina; Persson, Jonas; Tremblay, Antoine; Adi-Japha, Esther; Veríssimo, João; Dye, Cristina D.; Alm, Per; Jennische, Margareta; Tomblin, J. Bruce; Ullman, Michael T.

2011-01-01

The Procedural Deficit Hypothesis (PDH) posits that Specific Language Impairment (SLI) can be largely explained by abnormalities of brain structures that subserve procedural memory. The PDH predicts impairments of procedural memory itself, and that such impairments underlie the grammatical deficits observed in the disorder. Previous studies have indeed reported procedural learning impairments in SLI, and have found that these are associated with grammatical difficulties. The present study extends this research by examining the consolidation and longer-term procedural sequence learning in children with SLI. The Alternating Serial Reaction Time (ASRT) task was given to children with SLI and typically-developing (TD) children in an initial learning session and an average of three days later to test for consolidation and longer-term learning. Although both groups showed evidence of initial sequence learning, only the TD children showed clear signs of consolidation, even though the two groups did not differ in longer-term learning. When the children were re-categorized on the basis of grammar deficits rather than broader language deficits, a clearer pattern emerged. Whereas both the grammar impaired and normal grammar groups showed evidence of initial sequence learning, only those with normal grammar showed consolidation and longer-term learning. Indeed, the grammar-impaired group appeared to lose any sequence knowledge gained during the initial testing session. These findings held even when controlling for vocabulary or a broad non-grammatical language measure, neither of which were associated with procedural memory. When grammar was examined as a continuous variable over all children, the same relationships between procedural memory and grammar, but not vocabulary or the broader language measure, were observed. Overall, the findings support and further specify the PDH. They suggest that consolidation and longer-term procedural learning are impaired in SLI, but that

Suicide Attempts among Individuals with Specific Learning Disorders: An Underrecognized Issue

Science.gov (United States)

Fuller-Thomson, Esme; Carroll, Samara Z.; Yang, Wook

2018-01-01

Several studies have linked specific learning disorders (SLDs) with suicidal ideation, but less is known about the disorders' association with suicide attempts. This gap in the literature is addressed via the 2012 nationally representative Canadian Community Health Survey (n = 21,744). The prevalence of lifetime suicide attempts among those with…

Towards sophisticated learning from EHRs: increasing prediction specificity and accuracy using clinically meaningful risk criteria.

Science.gov (United States)

Vasiljeva, Ieva; Arandjelovic, Ognjen

2016-08-01

Computer based analysis of Electronic Health Records (EHRs) has the potential to provide major novel insights of benefit both to specific individuals in the context of personalized medicine, as well as on the level of population-wide health care and policy. The present paper introduces a novel algorithm that uses machine learning for the discovery of longitudinal patterns in the diagnoses of diseases. Two key technical novelties are introduced: one in the form of a novel learning paradigm which enables greater learning specificity, and another in the form of a risk driven identification of confounding diagnoses. We present a series of experiments which demonstrate the effectiveness of the proposed techniques, and which reveal novel insights regarding the most promising future research directions.

R statistical application development by example : beginner's guide

CERN Document Server

Tattar, Narayanachart Prabhanjan

2013-01-01

Full of screenshots and examples, this Beginner's Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.

Machine learning in Python essential techniques for predictive analysis

CERN Document Server

Bowles, Michael

2015-01-01

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

Fostering Self-Concept and Interest for Statistics through Specific Learning Environments

Science.gov (United States)

Sproesser, Ute; Engel, Joachim; Kuntze, Sebastian

2016-01-01

Supporting motivational variables such as self-concept or interest is an important goal of schooling as they relate to learning and achievement. In this study, we investigated whether specific interest and self-concept related to the domains of statistics and mathematics can be fostered through a four-lesson intervention focusing on statistics.…

[Acceptance of case-based, interactive e-learning in veterinary medicine on the example of the CASUS system].

Science.gov (United States)

Börchers, M; Tipold, A; Pfarrer, Ch; Fischer, M R; Ehlers, J P

2010-01-01

New teaching methods such as e-learning, are increasingly used to support common methods such as lectures, seminars and practical training in universities providing education in veterinary medicine. In the current study, the acceptance of e-learning in the example of the CASUS system by veterinarians as well as students of veterinary medicine of all German-speaking universities was analyzed. Material und methods: For this purpose an online evaluation questionnaire was developed. Members of the target groups were informed by e-mail and references in professional journals, as well as through veterinarian exchange platforms on the internet. Additionally, 224 students' final anatomy marks were compared and correlated to the utilization of CASUS to gain an important insight for the development of new teaching practices in the teaching of veterinary medicine. In total 1581 questionnaires were evaluated. A good acceptance regarding new teaching practices was found, although the classical textbook is still the most important instrument for imparting knowledge. The degree of utilization of e-learning strongly depends on its integration into the teaching content. CASUS is regarded as an efficient teaching method, with over 90% of the respondents indicating a strong desire to expand the number of case studies. Due to the present low degree of integration into the teaching content, no significant correlation could be found between the utilization of anatomy case studies and the final anatomy mark. However, based on their subjective perception, the students reported a high level of success in their study results with the likely effect of supporting increasing self-assurance in the situation of examinations. With the help of e-learning, educational objectives can be achieved that are not attainable by traditional teaching methods, e.g. the review of individual improvements by using the integrated feedback-function of e-learning programs. However, e-learning is not able to

Web-based experiments controlled by JavaScript: an example from probability learning.

Science.gov (United States)

Birnbaum, Michael H; Wakcher, Sandra V

2002-05-01

JavaScript programs can be used to control Web experiments. This technique is illustrated by an experiment that tested the effects of advice on performance in the classic probability-learning paradigm. Previous research reported that people tested via the Web or in the lab tended to match the probabilities of their responses to the probabilities that those responses would be reinforced. The optimal strategy, however, is to consistently choose the more frequent event; probability matching produces suboptimal performance. We investigated manipulations we reasoned should improve performance. A horse race scenario in which participants predicted the winner in each of a series of races between two horses was compared with an abstract scenario used previously. Ten groups of learners received different amounts of advice, including all combinations of (1) explicit instructions concerning the optimal strategy, (2) explicit instructions concerning a monetary sum to maximize, and (3) accurate information concerning the probabilities of events. The results showed minimal effects of horse race versus abstract scenario. Both advice concerning the optimal strategy and probability information contributed significantly to performance in the task. This paper includes a brief tutorial on JavaScript, explaining with simple examples how to assemble a browser-based experiment.

The Effect of Task-based Teaching on Incidental Vocabulary Learning in English for Specific Purposes

OpenAIRE

FALLAHRAFIE, Zahra; RAHMANY, Ramin; SADEGHI, Bahador

2015-01-01

Abstract. Learning vocabulary is an essential part of language learning linking the four skills of speaking, listening, reading and writing together. This paper considers the incidental vocabulary teaching and learning within the framework of task-based activities in the hope of improving learners’ vocabulary acquiring in English for Specific Purposes courses (ESP), concentrating on Mechanical Engineering students at Islamic Azad University of Hashtgerd, Iran. A total number of 55 male and fe...

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

Science.gov (United States)

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Post-Learning Sleep Transiently Boosts Context Specific Operant Extinction Memory

Directory of Open Access Journals (Sweden)

Marion Inostroza

2017-04-01

Full Text Available Operant extinction is learning to supress a previously rewarded behavior. It is known to be strongly associated with the specific context in which it was acquired, which limits the therapeutic use of operant extinction in behavioral treatments, e.g., of addiction. We examined whether sleep influences contextual memory of operant extinction over time, using two different recall tests (Recent and Remote. Rats were trained in an operant conditioning task (lever press in context A, then underwent extinction training in context B, followed by a 3-h retention period that contained either spontaneous morning sleep, morning sleep deprivation, or spontaneous evening wakefulness. A recall test was performed either immediately after the 3-h experimental retention period (Recent recall or after 48 h (Remote, in the extinction context B and in a novel context C. The two main findings were: (i at the Recent recall test, sleep in comparison with sleep deprivation and spontaneous wakefulness enhanced extinction memory but, only in the extinction context B; (ii at the Remote recall, extinction performance after sleep was enhanced in both contexts B and C to an extent comparable to levels at Recent recall in context B. Interestingly, extinction performance at Remote recall was also improved in the sleep deprivation groups in both contexts, with no difference to performance in the sleep group. Our results suggest that 3 h of post-learning sleep transiently facilitate the context specificity of operant extinction at a Recent recall. However, the improvement and contextual generalization of operant extinction memory observed in the long-term, i.e., after 48 h, does not require immediate post-learning sleep.

Construction of the Questionnaire on Foreign Language Learning Strategies in Specific Croatian Context.

Science.gov (United States)

Božinović, Nikolina; Sindik, Joško

2017-03-01

Learning strategies are special thoughts or behaviours that individuals use to understand, learn or retain new information, according to the point of view of O’Malley & Chamot. The other view, promoted by Oxford, believes learning strategies are specific actions taken by the learner to make learning easier, faster, more enjoyable, and more transferrable to new situations of language learning and use. The use of appropriate strategies ensures greater success in language learning. The aim of the research was to establish metric characteristics of the Questionnaire on learning strategies created by the author, in line with the template of the original SILL questionnaire (Strategy Inventory for Language Learning). The research was conducted at the Rochester Institute of Technology Croatia on a sample of 201 participants who learned German, Spanish, French and Italian as a foreign language. The results have shown that one-component latent dimensions which describe the space of foreign language learning strategies according to Oxford’s classification, have metric characteristics which are low, but still satisfactory (reliability and validity). All dimensions of learning strategies appeared not to be adequately defined. Therefore, we excluded compensation strategies and merged social and affective strategies into social-affective strategies into the unique dimension. Overall, this version of Oxford’s original questionnaire, based on Oxford’s theoretical construct, applied on Croatian students, clearly shows that current version of the questionnaire has poor metric characteristics. One of the explanations of the results obtained could be positioned in multicultural context and intercultural dialogue. Namely, particular social, political and economic context in Croatia could shape even foreign language learning strategies.

Working memory and novel word learning in children with hearing impairment and children with specific language impairment.

Science.gov (United States)

Hansson, K; Forsberg, J; Löfqvist, A; Mäki-Torkko, E; Sahlén, B

2004-01-01

Working memory is considered to influence a range of linguistic skills, i.e. vocabulary acquisition, sentence comprehension and reading. Several studies have pointed to limitations of working memory in children with specific language impairment. Few studies, however, have explored the role of working memory for language deficits in children with hearing impairment. The first aim was to compare children with mild-to-moderate bilateral sensorineural hearing impairment, children with a preschool diagnosis of specific language impairment and children with normal language development, aged 9-12 years, for language and working memory. The special focus was on the role of working memory in learning new words for primary school age children. The assessment of working memory included tests of phonological short-term memory and complex working memory. Novel word learning was assessed according to the methods of. In addition, a range of language tests was used to assess language comprehension, output phonology and reading. Children with hearing impairment performed significantly better than children with a preschool diagnosis of specific language impairment on tasks assessing novel word learning, complex working memory, sentence comprehension and reading accuracy. No significant correlation was found between phonological short-term memory and novel word learning in any group. The best predictor of novel word learning in children with specific language impairment and in children with hearing impairment was complex working memory. Furthermore, there was a close relationship between complex working memory and language in children with a preschool diagnosis of specific language impairment but not in children with hearing impairment. Complex working memory seems to play a significant role in vocabulary acquisition in primary school age children. The interpretation is that the results support theories suggesting a weakened influence of phonological short-term memory on novel word

Specific learning disorder: prevalence and gender differences.

Directory of Open Access Journals (Sweden)

Kristina Moll

Full Text Available Comprehensive models of learning disorders have to consider both isolated learning disorders that affect one learning domain only, as well as comorbidity between learning disorders. However, empirical evidence on comorbidity rates including all three learning disorders as defined by DSM-5 (deficits in reading, writing, and mathematics is scarce. The current study assessed prevalence rates and gender ratios for isolated as well as comorbid learning disorders in a representative sample of 1633 German speaking children in 3rd and 4th Grade. Prevalence rates were analysed for isolated as well as combined learning disorders and for different deficit criteria, including a criterion for normal performance. Comorbid learning disorders occurred as frequently as isolated learning disorders, even when stricter cutoff criteria were applied. The relative proportion of isolated and combined disorders did not change when including a criterion for normal performance. Reading and spelling deficits differed with respect to their association with arithmetic problems: Deficits in arithmetic co-occurred more often with deficits in spelling than with deficits in reading. In addition, comorbidity rates for arithmetic and reading decreased when applying stricter deficit criteria, but stayed high for arithmetic and spelling irrespective of the chosen deficit criterion. These findings suggest that the processes underlying the relationship between arithmetic and reading might differ from those underlying the relationship between arithmetic and spelling. With respect to gender ratios, more boys than girls showed spelling deficits, while more girls were impaired in arithmetic. No gender differences were observed for isolated reading problems and for the combination of all three learning disorders. Implications of these findings for assessment and intervention of learning disorders are discussed.

How Dispositional Learning Analytics helps understanding the worked-example principle

NARCIS (Netherlands)

Tempelaar, Dirk; Sampson, Demetrios G.; Spector, J. Michael; Ifenthaler, Dirk; Isaías, Pedro

2017-01-01

This empirical study aims to demonstrate how Dispositional Learning Analytics can contribute in the investigation of the effectiveness of didactical scenarios in authentic settings, where previous research has mostly been laboratory based. Using a showcase based on learning processes of 1080

Addiction memory as a specific, individually learned memory imprint.

Science.gov (United States)

Böning, J

2009-05-01

The construct of "addiction memory" (AM) and its importance for relapse occurrence has been the subject of discussion for the past 30 years. Neurobiological findings from "social neuroscience" and biopsychological learning theory, in conjunction with construct-valid behavioral pharmacological animal models, can now also provide general confirmation of addiction memory as a pathomorphological correlate of addiction disorders. Under multifactorial influences, experience-driven neuronal learning and memory processes of emotional and cognitive processing patterns in the specific individual "set" and "setting" play an especially pivotal role in this connection. From a neuropsychological perspective, the episodic (biographical) memory, located at the highest hierarchical level, is of central importance for the formation of the AM in certain structural and functional areas of the brain and neuronal networks. Within this context, neuronal learning and conditioning processes take place more or less unconsciously and automatically in the preceding long-term-memory systems (in particular priming and perceptual memory). They then regulate the individually programmed addiction behavior implicitly and thus subsequently stand for facilitated recollection of corresponding, previously stored cues or context situations. This explains why it is so difficult to treat an addiction memory, which is embedded above all in the episodic memory, from the molecular carrier level via the neuronal pattern level through to the psychological meaning level, and has thus meanwhile become a component of personality.

Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis.

Science.gov (United States)

Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

2016-05-15

Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require reverse inference, which presupposes specificity of brain activity for the hidden cognitive processes. We investigated whether multivariate pattern classification can provide this specificity. We used a word recall task to create single trial examples of immediate and long term retrieval and trained a learning algorithm to discriminate them. Next, participants performed a similar task involving monitoring instead of recall. The recall-trained classifier recognized the retrieval patterns underlying immediate and long term monitoring and classified delayed monitoring examples as long-term retrieval. This result demonstrates the feasibility of decoding cognitive processes, instead of their content. Copyright © 2016 Elsevier Inc. All rights reserved.

Collaborative Learning in Practice: Examples from Natural Resource ...

International Development Research Centre (IDRC) Digital Library (Canada)

2010-12-01

Dec 1, 2010 ... Case studies show how, through joint efforts with researchers and other actors, local ... address and learn from challenges in managing natural resources. ... health, and health systems research relevant to the emerging crisis.

Unsupervised behaviour-specific dictionary learning for abnormal event detection

DEFF Research Database (Denmark)

Ren, Huamin; Liu, Weifeng; Olsen, Søren Ingvor

2015-01-01

the training data is only a small proportion of the surveillance data. Therefore, we propose behavior-specific dictionaries (BSD) through unsupervised learning, pursuing atoms from the same type of behavior to represent one behavior dictionary. To further improve the dictionary by introducing information from...... potential infrequent normal patterns, we refine the dictionary by searching ‘missed atoms’ that have compact coefficients. Experimental results show that our BSD algorithm outperforms state-of-the-art dictionaries in abnormal event detection on the public UCSD dataset. Moreover, BSD has less false alarms...

Seamless Learning Environments in Higher Education with Mobile Devices and Examples

Science.gov (United States)

Marín, Victoria I.; Jääskelä, Päivikki; Häkkinen, Päivi; Juntunen, Merja; Rasku-Puttonen, Helena; Vesisenaho, Mikko

2016-01-01

The use of seamless learning environments that have the potential to support lifelong learning anytime and anywhere has become a reality. In this sense, many educational institutions have started to consider introducing seamless learning environments into their programs. The aim of this study is to analyze how various educational university…

Executive Functioning and Psychopathology in Psychotherapy for Adolescents with Specific Learning Disorders

Science.gov (United States)

Kopelman-Rubin, Daphne; Klomek, Anat Brunstein; Al-Yagon, Michal; Mufson, Laura; Apter, Alan; Mikulincer, Mario

2017-01-01

This study examined the contribution of executive functioning (EF) to improvements in psychiatric symptomatology following I Can Succeed (ICS; Kopelman-Rubin, 2012) psychotherapy, a skill-enhancement intervention designed to target EF and socio-emotional aspects of specific learning disabilities (SLD). Forty adolescents with SLD underwent ICS in…

SU-F-I-12: Region-Specific Dictionary Learning for Low-Dose X-Ray CT Reconstruction

International Nuclear Information System (INIS)

Xu, Q; Han, H; Xing, L

2016-01-01

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, a conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning

SU-F-I-12: Region-Specific Dictionary Learning for Low-Dose X-Ray CT Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Xu, Q; Han, H; Xing, L [Stanford University School of Medicine, Stanford, CA (United States)

2016-06-15

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, a conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning

Machine Learning Optimization of Evolvable Artificial Cells

DEFF Research Database (Denmark)

Caschera, F.; Rasmussen, S.; Hanczyc, M.

2011-01-01

can be explored. A machine learning approach (Evo-DoE) could be applied to explore this experimental space and define optimal interactions according to a specific fitness function. Herein an implementation of an evolutionary design of experiments to optimize chemical and biochemical systems based...... on a machine learning process is presented. The optimization proceeds over generations of experiments in iterative loop until optimal compositions are discovered. The fitness function is experimentally measured every time the loop is closed. Two examples of complex systems, namely a liposomal drug formulation...

Learning Object Repositories

Science.gov (United States)

Lehman, Rosemary

2007-01-01

This chapter looks at the development and nature of learning objects, meta-tagging standards and taxonomies, learning object repositories, learning object repository characteristics, and types of learning object repositories, with type examples. (Contains 1 table.)

Teaching with Games: Online Resources and Examples for Entry Level Courses

Science.gov (United States)

Teed, R.; Manduca, C.

2004-12-01

Using games to teach introductory geoscience can motivate students to enthusiastically learn material that they might otherwise condemn as "boring". A good educational game is one that immerses the players in the material and engages them for as long as it takes to master that material. There are some good geoscience games already available, but instructors can also create their own, suitable to their students and the content that they are teaching. Game-Based Learning is a module on the Starting Point website for faculty teaching entry level geosciences. It assists faculty in using games in their teaching by providing a description of the features of game-based learning, why you would use it, how to use games to teach geoscience, examples, and references. Other issues discussed include the development of video games for teaching, having your students create educational games, what makes a good game, handling competition in the classroom, and grading. The examples include descriptions of and rules for a GPS treasure hunt, a geology quiz show, and an earthquake game, as well as links to several online geological video games, and advice on how to design a paleontology board game. Starting Point is intended to help both experienced faculty and new instructors meet the challenge of teaching introductory geoscience classes, including environmental science and oceanography as well as more traditional geology classes. For many students, these classes are both the first and the last college-level science class that they will ever take. They need to learn enough about the Earth in that one class to sustain them for many decades as voters, consumers, and sometimes even as teachers. Starting Point is produced by a group of authors working with the Science Education Resource Center. It contains dozens of detailed examples categorized by geoscience topic with advice about using them and assessing learning. Each example is linked to one of many modules, such as Game

Specific learning disabilities in children: deficits and neuropsychological profile.

Science.gov (United States)

Kohli, Adarsh; Malhotra, Savita; Mohanty, Manju; Khehra, Nitasha; Kaur, Manreet

2005-06-01

The public is gradually becoming aware of specific learning disabilities (SLDs), which are very often the cause of academic difficulties. The aim of the study was to assess the SLDs in the clinic population at the Child and Adolescent Psychiatry Clinic at the Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh using the National Institute of Mental Health and Neurosciences SLD index and subsequently to assess the children's neuropsychological functions using a battery of tests. Thirty-five children in the age range of 7-14 years (both boys and girls) were recruited as the cohort, diagnosed clinically and assessed using the battery of tests for SLDs and neuropsychological tests consisting of the PGIMER memory scale for children, the Wisconsin card sorting test, the Bender visuo-motor gestalt test and Malin's intelligence scale for Indian children. The study revealed deficits in language and writing skills and impairments in specific areas of memory, executive functions and perceptuo-motor tasks. Identification of SLDs is useful in drawing up a treatment plan specific for a particular child.

Vicarious learning: a review of the literature.

Science.gov (United States)

Roberts, Debbie

2010-01-01

Experiential learning theory stresses the primacy of personal experience and the literature suggests that direct clinical experience is required in order for learning to take place. However, raw or first hand experience may not be the only mechanisms by which students engage in experiential learning. There is a growing body of literature within higher education which suggests that students are able to use another's experience to learn: vicarious learning. This literature review aims to outline vicarious learning within a nursing context. Many of the studies regarding vicarious learning are situated within Higher Education in general, however, within the United States these relate more specifically to nursing students. The literature indicates the increasing global interest in this area. This paper reveals that whilst the literature offers a number of examples illustrating how vicarious learning takes place, opinion on the role of the lecturer is divided and requires further exploration and clarification. The implications for nurse education are discussed.

Eclipse plugin development by example beginner's guide

CERN Document Server

Blewitt, Alex

2013-01-01

A Beginner's Guide following the ""by Example"" approach. There will be 5-8 major examples that will be used in the book to develop advanced plugins with the Eclipse IDE.This book is for Java developers who are familiar with Eclipse as a Java IDE and are interested in learning how to develop plug-ins for Eclipse. No prior knowledge of Eclipse plug-in development or OSGi is necessary, although you are expected to know how to create, run, and debug Java programs in Eclipse.

Bayesian Methods for the Physical Sciences. Learning from Examples in Astronomy and Physics.

Science.gov (United States)

Andreon, Stefano; Weaver, Brian

2015-05-01

-to-collect events or objects are over-represented in samples and difficult-to-collect are under-represented if not missing altogether. In this chapter we show how to account for non-random data collection to infer the properties of the population from the studied sample. Chapter 8: In this chapter we introduce regression models, i.e., how to fit (regress) one, or more quantities, against each other through a functional relationship and estimate any unknown parameters that dictate this relationship. Questions of interest include: how to deal with samples affected by selection effects? How does a rich data structure influence the fitted parameters? And what about non-linear multiple-predictor fits, upper/lower limits, measurements errors of different amplitudes and an intrinsic variety in the studied populations or an extra source of variability? A number of examples illustrate how to answer these questions and how to predict the value of an unavailable quantity by exploiting the existence of a trend with another, available, quantity. Chapter 9: This chapter provides some advice on how the careful scientist should perform model checking and sensitivity analysis, i.e., how to answer the following questions: is the considered model at odds with the current available data (the fitted data), for example because it is over-simplified compared to some specific complexity pointed out by the data? Furthermore, are the data informative about the quantity being measured or are results sensibly dependent on details of the fitted model? And, finally, what about if assumptions are uncertain? A number of examples illustrate how to answer these questions. Chapter 10: This chapter compares the performance of Bayesian methods against simple, non-Bayesian alternatives, such as maximum likelihood, minimal chi square, ordinary and weighted least square, bivariate correlated errors and intrinsic scatter, and robust estimates of location and scale. Performances are evaluated in terms of quality of the

Implicit sequence-specific motor learning after sub-cortical stroke is associated with increased prefrontal brain activations: An fMRI study

Science.gov (United States)

Meehan, Sean K.; Randhawa, Bubblepreet; Wessel, Brenda; Boyd, Lara A.

2010-01-01

Implicit motor learning is preserved after stroke, but how the brain compensates for damage to facilitate learning is unclear. We used a random effects analysis to determine how stroke alters patterns of brain activity during implicit sequence-specific motor learning as compared to general improvements in motor control. Nine healthy participants and 9 individuals with chronic, right focal sub-cortical stroke performed a continuous joystick-based tracking task during an initial fMRI session, over 5 days of practice, and a retention test during a separate fMRI session. Sequence-specific implicit motor learning was differentiated from general improvements in motor control by comparing tracking performance on a novel, repeated tracking sequences during early practice and again at the retention test. Both groups demonstrated implicit sequence-specific motor learning at the retention test, yet substantial differences were apparent. At retention, healthy control participants demonstrated increased BOLD response in left dorsal premotor cortex (BA 6) but decreased BOLD response left dorsolateral prefrontal cortex (DLPFC; BA 9) during repeated sequence tracking. In contrast, at retention individuals with stroke did not show this reduction in DLPFC during repeated tracking. Instead implicit sequence-specific motor learning and general improvements in motor control were associated with increased BOLD response in the left middle frontal gyrus BA 8, regardless of sequence type after stroke. These data emphasize the potential importance of a prefrontal-based attentional network for implicit motor learning after stroke. The present study is the first to highlight the importance of the prefrontal cortex for implicit sequence-specific motor learning after stroke. PMID:20725908

Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence.

Science.gov (United States)

Ahn, Woo-Young; Vassileva, Jasmin

2016-04-01

Recent animal and human studies reveal distinct cognitive and neurobiological differences between opiate and stimulant addictions; however, our understanding of the common and specific effects of these two classes of drugs remains limited due to the high rates of polysubstance-dependence among drug users. The goal of the current study was to identify multivariate substance-specific markers classifying heroin dependence (HD) and amphetamine dependence (AD), by using machine-learning approaches. Participants included 39 amphetamine mono-dependent, 44 heroin mono-dependent, 58 polysubstance dependent, and 81 non-substance dependent individuals. The majority of substance dependent participants were in protracted abstinence. We used demographic, personality (trait impulsivity, trait psychopathy, aggression, sensation seeking), psychiatric (attention deficit hyperactivity disorder, conduct disorder, antisocial personality disorder, psychopathy, anxiety, depression), and neurocognitive impulsivity measures (Delay Discounting, Go/No-Go, Stop Signal, Immediate Memory, Balloon Analogue Risk, Cambridge Gambling, and Iowa Gambling tasks) as predictors in a machine-learning algorithm. The machine-learning approach revealed substance-specific multivariate profiles that classified HD and AD in new samples with high degree of accuracy. Out of 54 predictors, psychopathy was the only classifier common to both types of addiction. Important dissociations emerged between factors classifying HD and AD, which often showed opposite patterns among individuals with HD and AD. These results suggest that different mechanisms may underlie HD and AD, challenging the unitary account of drug addiction. This line of work may shed light on the development of standardized and cost-efficient clinical diagnostic tests and facilitate the development of individualized prevention and intervention programs for HD and AD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Later learning stages in procedural memory are impaired in children with Specific Language Impairment.

Science.gov (United States)

Desmottes, Lise; Meulemans, Thierry; Maillart, Christelle

2016-01-01

According to the Procedural Deficit Hypothesis (PDH), difficulties in the procedural memory system may contribute to the language difficulties encountered by children with Specific Language Impairment (SLI). Most studies investigating the PDH have used the sequence learning paradigm; however these studies have principally focused on initial sequence learning in a single practice session. The present study sought to extend these investigations by assessing the consolidation stage and longer-term retention of implicit sequence-specific knowledge in 42 children with or without SLI. Both groups of children completed a serial reaction time task and were tested 24h and one week after practice. Results showed that children with SLI succeeded as well as children with typical development (TD) in the early acquisition stage of the sequence learning task. However, as training blocks progressed, only TD children improved their sequence knowledge while children with SLI did not appear to evolve any more. Moreover, children with SLI showed a lack of the consolidation gains in sequence knowledge displayed by the TD children. Overall, these results were in line with the predictions of the PDH and suggest that later learning stages in procedural memory are impaired in SLI. Copyright © 2015 Elsevier Ltd. All rights reserved.

FPGA prototyping by Verilog examples Xilinx Spartan-3 version

CERN Document Server

Chu, Pong P

2008-01-01

FPGA Prototyping Using Verilog Examples will provide you with a hands-on introduction to Verilog synthesis and FPGA programming through a "learn by doing" approach. By following the clear, easy-to-understand templates for code development and the numerous practical examples, you can quickly develop and simulate a sophisticated digital circuit, realize it on a prototyping device, and verify the operation of its physical implementation. This introductory text that will provide you with a solid foundation, instill confidence with rigorous examples for complex systems and prepare you for future development tasks.

The Ontogeny of Cultural Learning.

Science.gov (United States)

Legare, Cristine H; Harris, Paul L

2016-05-01

Developmental research has the potential to address some of the critical gaps in our scientific understanding of the role played by cultural learning in ontogenetic outcomes. The goal of this special section was to gather together leading examples of research on cultural learning across a variety of social contexts and caregiving settings. Although the field of developmental psychology continues to struggle with the persistent problem of oversampling U.S. and Western European populations, we argue that the articles in this special section add to the growing evidence that children everywhere draw on a repertoire of cultural learning strategies that optimize their acquisition of the specific practices, beliefs, and values of their communities. We also identify future directions and outline best practices for the conduct of research on cultural learning. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Nitric oxide regulates input specificity of long-term depression and context dependence of cerebellar learning.

Directory of Open Access Journals (Sweden)

Hideaki Ogasawara

2007-01-01

Full Text Available Recent studies have shown that multiple internal models are acquired in the cerebellum and that these can be switched under a given context of behavior. It has been proposed that long-term depression (LTD of parallel fiber (PF-Purkinje cell (PC synapses forms the cellular basis of cerebellar learning, and that the presynaptically synthesized messenger nitric oxide (NO is a crucial "gatekeeper" for LTD. Because NO diffuses freely to neighboring synapses, this volume learning is not input-specific and brings into question the biological significance of LTD as the basic mechanism for efficient supervised learning. To better characterize the role of NO in cerebellar learning, we simulated the sequence of electrophysiological and biochemical events in PF-PC LTD by combining established simulation models of the electrophysiology, calcium dynamics, and signaling pathways of the PC. The results demonstrate that the local NO concentration is critical for induction of LTD and for its input specificity. Pre- and postsynaptic coincident firing is not sufficient for a PF-PC synapse to undergo LTD, and LTD is induced only when a sufficient amount of NO is provided by activation of the surrounding PFs. On the other hand, above-adequate levels of activity in nearby PFs cause accumulation of NO, which also allows LTD in neighboring synapses that were not directly stimulated, ruining input specificity. These findings lead us to propose the hypothesis that NO represents the relevance of a given context and enables context-dependent selection of internal models to be updated. We also predict sparse PF activity in vivo because, otherwise, input specificity would be lost.

An example of active learning in Aerospace Engineering

NARCIS (Netherlands)

Brugemann, V.P.; Brummelen, van E.H.; Melkert, J.A.; Kamp, A.; Saunders-Smits, G.N.; Reith, B.A.; Zandbergen, B.T.C.; Graaf, de E.; Saunders-Smits, G.N.; Nieweg, M.R.

2005-01-01

This paper is a showcase for an on-going active learning capstone design project in the BSe. programme at the Faculty of Aerospace Engineering at Delft University of Technology. In multi-disciplinary teams supervised by tutors from different backgrounds students work towards an Aerospace (related)

Towards addressing transient learning challenges in undergraduate physics: an example from electrostatics

Science.gov (United States)

Fredlund, T.; Linder, C.; Airey, J.

2015-09-01

In this article we characterize transient learning challenges as learning challenges that arise out of teaching situations rather than conflicts with prior knowledge. We propose that these learning challenges can be identified by paying careful attention to the representations that students produce. Once a transient learning challenge has been identified, teachers can create interventions to address it. By illustration, we argue that an appropriate way to design such interventions is to create variation around the disciplinary-relevant aspects associated with the transient learning challenge.

Joint Feature Selection and Classification for Multilabel Learning.

Science.gov (United States)

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Perception and coping with the specific learning disabilities impacts on everyday life of children with this diagnosis

OpenAIRE

Vilímová, Zuzana

2015-01-01

TITLE: Perception and coping with the specific learning disabilities impacts on everyday life of children with this diagnosis. ABSTRACT This text is focused on recognition of impacts of the specific learning disabilities on everyday life as the children with this diagnosis themselves see it and the strategies used by these children in order to cope with these disabilities. The theoretical part summarizes the necessary knowledge of the early school age developmental stage, the interaction of a...

Developing a Learning Progression for Curriculum, Instruction, and Student Learning: An Example from Mathematics Education

Science.gov (United States)

Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Isler, Isil; Knuth, Eric; Gardiner, Angela Murphy

2018-01-01

Learning progressions have been demarcated by some for science education, or only concerned with levels of sophistication in student thinking as determined by logical analyses of the discipline. We take the stance that learning progressions can be leveraged in mathematics education as a form of curriculum research that advances a linked…

Workplaces as Transformative Learning Spaces

DEFF Research Database (Denmark)

Maslo, Elina

2010-01-01

some other examples on “successful learning” from the formal, informal and non-formal learning environments, trying to prove those criteria. This presentation provides a view on to new examples on transformative learning spaces we discovered doing research on Workplace Learning in Latvia as a part......Abstract to the Vietnam Forum on Lifelong Learning: Building a Learning Society Hanoi, 7-8 December 2010 Network 2: Competence development as Workplace Learning Title of proposal: Workplaces as Transformative Learning Spaces Author: Elina Maslo, dr. paed., University of Latvia, elina@latnet.lv Key...... words: learning, lifelong learning, adult learning, workplace learning, transformative learning spaces During many years of research on lifelong foreign language learning with very different groups of learners, we found some criteria, which make learning process successful. Since then we tried to find...

How do newcomers learn to use an object?

DEFF Research Database (Denmark)

Kjær, Malene

in the daily practice of assessing how a patient is doing. Learning how to operate it in situ is thus an important task.I will present an empirical example from clinical nursing education in a Danish hospital, where students learn to use specific medical objects (a sphygmomanometer) in the setting...... status and stance (Heritage, 2012) epistemic, cooperative and instrumental stance (Goodwin, 2007) is important, as is the understanding of situated embodied cognition in the workplace practice: the knowledge ‘understanding and use of objects’ that has been limited to the nurse, translates through...

Using Example Problems to Improve Student Learning in Algebra: Differentiating between Correct and Incorrect Examples

Science.gov (United States)

Booth, Julie L.; Lange, Karin E.; Koedinger, Kenneth R.; Newton, Kristie J.

2013-01-01

In a series of two "in vivo" experiments, we examine whether correct and incorrect examples with prompts for self-explanation can be effective for improving students' conceptual understanding and procedural skill in Algebra when combined with guided practice. In Experiment 1, students working with the Algebra I Cognitive Tutor were randomly…

M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

Science.gov (United States)

Squires, David R.

2014-01-01

The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

The examples of forest management in secondary forests of Western Siberia

Directory of Open Access Journals (Sweden)

N. M. Debkov

2017-04-01

Full Text Available Identifying the best practices of responsible and sustainable forest use is an important aspect for possible learning of experience and replication of the most interesting examples in forestry. Qualitative and timely reforestation of disturbed areas with economically valuable species is the key indicator for the performance of effective forest management. Conservation of rare species of plants and animals in the logged areas is not less important factor. Today the priority is given to natural forest regeneration because it provides the best opportunity to avoid unreasonable financial costs and, as a rule, is more resilient against various natural and anthropogenic factors. The article discusses various examples and logging types in secondary forests in the Tomsk and Omsk Oblast, which allow increasing the economic, environmental, and social importance of forests. On specific examples it is shown that the principle of non-interference in the green zones of settlements is erroneous and may lead to undesirable consequences. The rejection of logging in these stands, as a rule, leads to increases of the fire danger, growth of phyto- and entomological threats, the reduction of recreational appeal, etc. The use of partial logging methods suggested in the papers has allowed solving some of these problems.

Simplicity and Specificity in Language: Domain-General Biases Have Domain-Specific Effects

Science.gov (United States)

Culbertson, Jennifer; Kirby, Simon

2016-01-01

The extent to which the linguistic system—its architecture, the representations it operates on, the constraints it is subject to—is specific to language has broad implications for cognitive science and its relation to evolutionary biology. Importantly, a given property of the linguistic system can be “specific” to the domain of language in several ways. For example, if the property evolved by natural selection under the pressure of the linguistic function it serves then the property is domain-specific in the sense that its design is tailored for language. Equally though, if that property evolved to serve a different function or if that property is domain-general, it may nevertheless interact with the linguistic system in a way that is unique. This gives a second sense in which a property can be thought of as specific to language. An evolutionary approach to the language faculty might at first blush appear to favor domain-specificity in the first sense, with individual properties of the language faculty being specifically linguistic adaptations. However, we argue that interactions between learning, culture, and biological evolution mean any domain-specific adaptations that evolve will take the form of weak biases rather than hard constraints. Turning to the latter sense of domain-specificity, we highlight a very general bias, simplicity, which operates widely in cognition and yet interacts with linguistic representations in domain-specific ways. PMID:26793132

Affordances of Telecollaboration tools for English for Specific Purposes online learning

OpenAIRE

Sevilla Pavón, Ana

2016-01-01

This paper explores students’ perceptions of the affordances of different telecollaboration tools used in an innovation project for English for Specific Purposes online learning carried out between the University of Valencia (Spain) and Wofford College (South Carolina, United States) during the school year 2015-2016. Different tools for synchronous and asynchronous communication were used. The asynchronous tools included a discussion forum, a wiki, social networking websites and Google forms;...

Standardized quality in MOOC based learning

Directory of Open Access Journals (Sweden)

Maiorescu Irina

2015-04-01

Full Text Available Quality in the field of e-learning and, particularly, in the field of MOOC( Massive Open Online Courses, is a topic of growing importance in both academic institutions and in the private sector as it has generally been proved that quality management can contribute to improving the performance of organizations, regardless of their object of activity. Despite the fact that there are standards relating to quality management in a general manner, professionals, academic staff, specialists and bodies felt the need for having a standardized approach of the quality in the sector of e-learning. Therefore, in the last years, in different countries quality guidelines have been developed and used for e-Learning or distance education (for example the ASTD criteria for e- Learning, the BLA Quality Mark, Quality Platform Learning by D-ELAN etc.. The current paper aims to give insights to this new form of online education provided by MOOC platforms using the specific quality standard approach.

Personalization for Specific Users : Designing Decision Support Systems to Support Stimulating Learning Environments

NARCIS (Netherlands)

Maruster, Laura; Faber, Niels R.; van Haren, Rob J.; Salvendy, G; Smith, MJ

2009-01-01

Creating adaptive systems becomes increasingly attractive in the context of specific groups of users, such as agricultural users. This group of users seems to differ with respect to information processing, knowledge management and learning styles. In this work we aim to offer directions toward

Ants use partner specific odors to learn to recognize a mutualistic partner.

Directory of Open Access Journals (Sweden)

Masaru K Hojo

Full Text Available Regulation via interspecific communication is an important for the maintenance of many mutualisms. However, mechanisms underlying the evolution of partner communication are poorly understood for many mutualisms. Here we show, in an ant-lycaenid butterfly mutualism, that attendant ants selectively learn to recognize and interact cooperatively with a partner. Workers of the ant Pristomyrmex punctatus learn to associate cuticular hydrocarbons of mutualistic Narathura japonica caterpillars with food rewards and, as a result, are more likely to tend the caterpillars. However, the workers do not learn to associate the cuticular hydrocarbons of caterpillars of a non-ant-associated lycaenid, Lycaena phlaeas, with artificial food rewards. Chemical analysis revealed cuticular hydrocarbon profiles of the mutualistic caterpillars were complex compared with those of non-ant-associated caterpillars. Our results suggest that partner-recognition based on partner-specific chemical signals and cognitive abilities of workers are important mechanisms underlying the evolution and maintenance of mutualism with ants.

Prime Example Ingress Reframing the Pervasive Game Design Framework (PGDF

Directory of Open Access Journals (Sweden)

Heinrich Söbke

2017-06-01

Full Text Available The growing availability of mobile communication infrastructure over the last decade has contributed significantly to the maturity of Pervasive Gaming. The massive success of games such as Ingress and Pokémon Go made pervasive gaming a viable option for transforming learning. By its adaptability to location and context, pervasive technology is a valuable support for the design of engaging learning experiences. Despite profound examples of pervasive gaming as learning tool, there is still a lack of reliable methodologies to construct purposeful pervasive learning experiences. The Pervasive Game Design Framework (PGDF is intended to fill this gap. In this article, we present the PGDF using the example of Ingress. Ingress is a prominent pervasive game, as it has received huge attention since its appearance in 2012. A large community of players and third-party-tool suppliers has created a rich set of experiences since then. In this research, we examine Ingress according to PGDF’s categories based on a survey among long-term Ingress players (N=133. Founded on this analysis we identify three main benefits for Ingress players. Furthermore, we discuss the consequences of these findings on the PGDF. Summarizing, this work strengthens the applicability of the PGDF, in order to enable the construction of enriched pervasive learning experiences.

Emotional and Meta-Emotional Intelligence as Predictors of Adjustment Problems in Students with Specific Learning Disorders

Science.gov (United States)

D'Amico, Antonella; Guastaferro, Teresa

2017-01-01

The purpose of this study was to analyse adjustment problems in a group of adolescents with a Specific Learning Disorder (SLD), examining to what extent they depend on the severity level of the learning disorder and/or on the individual's level of emotional intelligence. Adjustment problems,, perceived severity levels of SLD, and emotional and…

Extracurricular activities and the development of social skills in children with intellectual and specific learning disabilities.

Science.gov (United States)

Brooks, B A; Floyd, F; Robins, D L; Chan, W Y

2015-07-01

Children with intellectual disability and specific learning disabilities often lack age-appropriate social skills, which disrupts their social functioning. Because of the limited effectiveness of classroom mainstreaming and social skills training for these children, it is important to explore alternative opportunities for social skill acquisition. Participation in social activities is positively related to children's social adjustment, but little is known about the benefits of activity participation for children with intellectual and specific learning disabilities. This study investigated the association between frequency and type of social activity participation and the social competence of 8-11-year-old children with intellectual disability (n = 40) and specific learning disabilities (n = 53), in comparison with typically developing peers (n = 24). More time involved in unstructured activities, but not structured activities, was associated with higher levels of social competence for all children. This association was strongest for children with intellectual disability, suggesting that participation in unstructured social activities was most beneficial for these children. Future research on the quality of involvement is necessary to further understand specific aspects of unstructured activities that might facilitate social development. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Task-specificity of unilateral anodal and dual-M1 tDCS effects on motor learning.

Science.gov (United States)

Karok, Sophia; Fletcher, David; Witney, Alice G

2017-01-08

Task-specific effects of transcranial direct current stimulation (tDCS) on motor learning were investigated in 30 healthy participants. In a sham-controlled, mixed design, participants trained on 3 different motor tasks (Purdue Pegboard Test, Visuomotor Grip Force Tracking Task and Visuomotor Wrist Rotation Speed Control Task) over 3 consecutive days while receiving either unilateral anodal over the right primary motor cortex (M1), dual-M1 or sham stimulation. Retention sessions were administered 7 and 28 days after the end of training. In the Purdue Pegboard Test, both anodal and dual-M1 stimulation reduced average completion time approximately equally, an improvement driven by online learning effects and maintained for about 1 week. The Visuomotor Grip Force Tracking Task and the Visuomotor Wrist Rotation Speed Control Task were associated with an advantage of dual-M1 tDCS in consolidation processes both between training sessions and when testing at long-term retention; both were maintained for at least 1 month. This study demonstrates that M1-tDCS enhances and sustains motor learning with different electrode montages. Stimulation-induced effects emerged at different learning phases across the tasks, which strongly suggests that the influence of tDCS on motor learning is dynamic with respect to the functional recruitment of the distributed motor system at the time of stimulation. Divergent findings regarding M1-tDCS effects on motor learning may partially be ascribed to task-specific consequences and the effects of offline consolidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mathematics as a constructive activity learners generating examples

CERN Document Server

Watson, Anne

2005-01-01

Explains and demonstrates the role of examples in the teaching and learning of mathematics, and their place in mathematics generally at all levels. Includes a combination of exercises for the reader, practical applications for teaching, and solid scholarly grounding.

Comparison of executive functions in students with and without specific learning disability with the characteristic reading and writing

Directory of Open Access Journals (Sweden)

Saba Hasanvandi

2017-03-01

Full Text Available Background: The aim of present study was to investigate executive functions included of working memory, organization-planning and reasoning in the children with and without specific learning disability with the characteristic reading and writing. Materials and methods: The design of this research was Ex-Post Facto design. Statistical population was all male students of third grade primary schools in Tehran which were referred to education institution with diagnosis special learning disorders in educational centers. The sample included of 90 students chosen and assigned into 3 groups of 30 students, included of: children who had specific learning disability with characteristic reading, children who had specific learning disability with characteristic writing, normal children were selected by systematic randomized sampling and 3 groups were compared. The data instruments were: Wechsler’ subtests of similarities and digit differences, Andre Ray test, in formal (unofficial reading and dictation test. The obtained data were analyzed with ANOVA. Results: The results showed that there was difference between the group of normal children and other group in executive functions including working memory, organization-planning and reasoning (P<0.05. Also there was difference between two children groups with specific learning disability with  characteristic reading and writing in working memory and reasoning, whereas for organization-planning parameter there were not seen any differences between these two groups (P<0.05. Conclusion: Regarding to obtained results, it is recommended to adoption some ways for improvements of working memory, organization-planning and reasoning

Learning with peers, active citizenship and student engagement in Enabling Education

Directory of Open Access Journals (Sweden)

Nick Zepke

2018-02-01

Full Text Available This paper examines one specific question:  What support do students in Enabling Education need to learn the behaviours, knowledge and attitudes required to succeed in tertiary education, employment and life? Success appears in many guises. It can mean achieving officially desired outcomes such as retention, completion and employment. It can also mean achieving less measurable outcomes such as deep learning, wellbeing and active citizenship. The paper first introduces an overarching success framework before exploring how the widely used student engagement pedagogy can support learners to achieve both official and personal success outcomes. It then develops two specific constructs applicable to Enabling Education as found in student engagement: facilitated peer learning and active citizenship. Peer learning is here connected to tutor supported but peer facilitated mentoring; active citizenship to educational experiences in classrooms, institutions and workplaces that support flexibility, resilience, openness to change and diversity. The paper includes examples of how facilitated peer learning and active citizenship can build success in practice.

Psychological co-morbidity in children with specific learning disorders

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Manoj K Sahoo

2015-01-01

Full Text Available Children under 19 years of age constitute over 40% of India′s population and information about their mental health needs is a national imperative. Children with specific learning disorders (SLDs exhibit academic difficulties disproportionate to their intellectual capacities. Prevalence of SLD ranges from 2% to 10%. Dyslexia (developmental reading disorder is the most common type, affecting 80% of all SLD. About 30% of learning disabled children have behavioral and emotional problems, which range from attention deficit hyperactivity disorder (most common to depression, anxiety, suicide etc., to substance abuse (least common. Co-occurrence of such problems with SLD further adds to the academic difficulty. In such instances, diagnosis is difficult and tricky; improvement in academics demands comprehensive holistic treatment approach. SLD remains a large public health problem because of under-recognition, inadequate treatment and therefore merits greater effort to understand the co-morbidities, especially in the Indian population. As the literature is scarce regarding co-morbid conditions in learning disability in Indian scenario, the present study has tried to focus on Indian population. The educational concessions (recent most given to such children by Central Board of Secondary Education, New Delhi are referred to. The issues to be addressed by the family physicians are: Low level of awareness among families and teachers, improper dissemination of accurate information about psychological problems, available help seeking avenues, need to develop service delivery models in rural and urban areas and focus on the integration of mental health and primary care keeping such co-morbidity in mind.

Psychological Co-morbidity in Children with Specific Learning Disorders.

Science.gov (United States)

Sahoo, Manoj K; Biswas, Haritha; Padhy, Susanta Kumar

2015-01-01

Children under 19 years of age constitute over 40% of India's population and information about their mental health needs is a national imperative. Children with specific learning disorders (SLDs) exhibit academic difficulties disproportionate to their intellectual capacities. Prevalence of SLD ranges from 2% to 10%. Dyslexia (developmental reading disorder) is the most common type, affecting 80% of all SLD. About 30% of learning disabled children have behavioral and emotional problems, which range from attention deficit hyperactivity disorder (most common) to depression, anxiety, suicide etc., to substance abuse (least common). Co-occurrence of such problems with SLD further adds to the academic difficulty. In such instances, diagnosis is difficult and tricky; improvement in academics demands comprehensive holistic treatment approach. SLD remains a large public health problem because of under-recognition, inadequate treatment and therefore merits greater effort to understand the co-morbidities, especially in the Indian population. As the literature is scarce regarding co-morbid conditions in learning disability in Indian scenario, the present study has tried to focus on Indian population. The educational concessions (recent most) given to such children by Central Board of Secondary Education, New Delhi are referred to. The issues to be addressed by the family physicians are: Low level of awareness among families and teachers, improper dissemination of accurate information about psychological problems, available help seeking avenues, need to develop service delivery models in rural and urban areas and focus on the integration of mental health and primary care keeping such co-morbidity in mind.

Training School Psychologists to Identify Specific Learning Disabilities: A Content Analysis of Syllabi

Science.gov (United States)

Barrett, Courtenay A.; Cottrell, Joseph M.; Newman, Daniel S.; Pierce, Benjamin G.; Anderson, Alisha

2015-01-01

Approximately 2.4 million children receive special education services for specific learning disabilities (SLDs), and school psychologists are key contributors to the SLD eligibility decision-making process. The Individuals with Disabilities Education Act (2004) enabled local education agencies to use response to intervention (RTI) instead of the…

SRS SLUDGE BATCH QUALIFICATION AND PROCESSING; HISTORICAL PERSPECTIVE AND LESSONS LEARNED

Energy Technology Data Exchange (ETDEWEB)

Cercy, M.; Peeler, D.; Stone, M.

2013-09-25

This report provides a historical overview and lessons learned associated with the SRS sludge batch (SB) qualification and processing programs. The report covers the framework of the requirements for waste form acceptance, the DWPF Glass Product Control Program (GPCP), waste feed acceptance, examples of how the program complies with the specifications, an overview of the Startup Program, and a summary of continuous improvements and lessons learned. The report includes a bibliography of previous reports and briefings on the topic.

Computer game-based mathematics education : Embedded faded worked examples facilitate knowledge acquisition

NARCIS (Netherlands)

ter Vrugte, Judith; de Jong, Anthonius J.M.; Vandercruysse, Sylke; Wouters, Pieter; van Oostendorp, Herre; Elen, Jan

This study addresses the added value of faded worked examples in a computer game-based learning environment. The faded worked examples were introduced to encourage active selection and processing of domain content in the game. The content of the game was proportional reasoning and participants were

Penetrating learning barriers and the art of suggestion

Directory of Open Access Journals (Sweden)

Lynn Dhority

2013-02-01

Full Text Available A crucial factor preventing students from tapping their full learning potential is their mind set, consisting of subconscious conditioned beliefs, attitudes and self-images. Teachers can learn to work consciously and purposefully to evoke positive responses at the subconscious level in their students, thereby allowing fuller learning potential to unfold. Several specific examples and strategies are discussed. 'n Beslissende faktor wat verhoed dat studente hulle volle leerpotensiaal benut, is gelee in 'n geestesgesteldheid wat bestaan uit gekondisioneerde gelowe, houdings en selfbeelde in die onderbewuste. Dosente kan leer om bewustelik en doelgerig positiewe reaksies in die onderbewuste van hulle studente op te roep om sodoende 'n groter leerpotensiaal te laat ontvou. Verskeie voorbeelde en strategiee word bespreek.

Landscapes of Musical Metaphor and Musical Learning: The Example of Jazz Education

Science.gov (United States)

Bjerstedt, Sven

2015-01-01

Theoretical approaches to learning in practice-based jazz improvisation contexts include situated learning and ecological perspectives. This article focuses on how interest-driven, self-sustaining jazz learning activities can be matched against the results of a recent Swedish investigation based on extensive qualitative interviews with jazz…

LEARNING MATERIALS SELECTION FOR DIFFERENTIATED INSTRUCTION OF ENGLISH FOR SPECIFIC PURPOSES OF FUTURE PROFESSIONALS IN THE FIELD OF INFORMATION TECHNOLOGY

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Oksana Synekop

2017-09-01

Full Text Available In conditions of differentiation the learning materials selection will optimize the training English for Specific Purposes of the future professionals in the field of information technology at university level. The purpose of the article is to define the basic unit of learning material, the factors of influence on the learning material selection, principles, criteria and the procedure of learning material selection in this paper. Reviewing the scientific achievements in the learning material selection in teaching English has become a basis for defining the factors of influence, principles and criteria in the research. The basic unit of learning material (learning English text for professional purposes is outlined. The factors of influence and principles (correspondence of learning materials to professional interests and needs of information technology students; necessary ability and accessibility; regarding the linguistic and stylistic necessity and sufficiency; availability of Internet sources information of the learning material selection are defined. Also, the qualitative criteria (authenticity; professional significance, relevance and informativeness; conformity of foreign language level and intellectual development of students; variety of genres and forms of speech, their sufficient filling by linguistic material; coherence, integrity, consistency, semantic completeness; topic conformity; situation conformity; unlimited access, reliability and exemplarity of Internet sources and the quantitative criteria (the amount of material of the learning material selection are highlighted. The process of English for Specific Purposes material selection (defining the disciplines of different cycles; defining spheres and related topics; outlining situations, communicative roles and intentions of professional communication; specifying the sources of selection; evaluating the texts; analysis of the knowledge, skills and sub-skills required for the

Enhancing Learning within the 3-D Virtual Learning Environment

OpenAIRE

Shirin Shafieiyoun; Akbar Moazen Safaei

2013-01-01

Today’s using of virtual learning environments becomes more remarkable in education. The potential of virtual learning environments has frequently been related to the expansion of sense of social presence which is obtained from students and educators. This study investigated the effectiveness of social presence within virtual learning environments and analysed the impact of social presence on increasing learning satisfaction within virtual learning environments. Second Life, as an example of ...

Parents' Perspectives on Coping with Duchenne Muscular Dystrophy and Concomitant Specific Learning Disabilities

Science.gov (United States)

Webb, Carol L.

2005-01-01

This study addresses parental perspectives and coping strategies related to Duchenne muscular dystrophy and specific learning disabilities. Data were collected through individual semi-structured in-depth interviews with fifteen sets of parents. Participants were selected based on variables such as age of children, number of children with both…

Internet-Specific Epistemic Beliefs and Self-Regulated Learning in Online Academic Information Searching

Science.gov (United States)

Chiu, Yen-Lin; Liang, Jyh-Chong; Tsai, Chin-Chung

2013-01-01

Epistemic beliefs have been considered as important components of the self-regulatory model; however, their relationships with self-regulated learning processes in the Internet context need further research. The main purpose of this study was to examine the relationships between Internet-specific epistemic belief dimensions and self-regulated…

Cultural Learning Redux

Science.gov (United States)

Tomasello, Michael

2016-01-01

M. Tomasello, A. Kruger, and H. Ratner (1993) proposed a theory of cultural learning comprising imitative learning, instructed learning, and collaborative learning. Empirical and theoretical advances in the past 20 years suggest modifications to the theory; for example, children do not just imitate but overimitate in order to identify and…

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

Science.gov (United States)

Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the

Vulnerability of classifiers to evolutionary generated adversarial examples

Czech Academy of Sciences Publication Activity Database

Vidnerová, Petra; Neruda, Roman

submitted 14.1. 2017 (2018) ISSN 0941-0643 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : supervised learning * neural networks * kernel methods * genetic algorithm s * adversarial examples Subject RIV: IN - Informatics, Computer Science Impact factor: 2.505, year: 2016

SOME EXAMPLES OF APPLIED SYSTEMS WITH SPEECH INTERFACE

Directory of Open Access Journals (Sweden)

V. A. Zhitko

2017-01-01

Full Text Available Three examples of applied systems with a speech interface are considered in the article. The first two of these provide the end user with the opportunity to ask verbally the question and to hear the response from the system, creating an addition to the traditional I / O via the keyboard and computer screen. The third example, the «IntonTrainer» system, provides the user with the possibility of voice interaction and is designed for in-depth self-learning of the intonation of oral speech.

Which Technique Is Most Effective for Learning Declarative Concepts--Provided Examples, Generated Examples, or Both?

Science.gov (United States)

Zamary, Amanda; Rawson, Katherine A.

2018-01-01

Students in many courses are commonly expected to learn declarative concepts, which are abstract concepts denoted by key terms with short definitions that can be applied to a variety of scenarios as reported by Rawson et al. ("Educational Psychology Review" 27:483-504, 2015). Given that declarative concepts are common and foundational in…

Specific Learning Disabilities in DSM-5: Are the Changes for Better or Worse?

Science.gov (United States)

Tannock, Rosemary

2013-01-01

DSM-5, the fifth edition of the American Psychiatric Association's "Diagnostic and Statistical Manual of Mental Disorders," was published in May 2013, amidst a storm of controversy. This article focuses on changes made to the diagnostic criteria for Specific Learning Disorders (SLD). Primary criticisms of the changes in the SLD concern…

Fostering clinical reasoning in physiotherapy: comparing the effects of concept map study and concept map completion after example study in novice and advanced learners.

Science.gov (United States)

Montpetit-Tourangeau, Katherine; Dyer, Joseph-Omer; Hudon, Anne; Windsor, Monica; Charlin, Bernard; Mamede, Sílvia; van Gog, Tamara

2017-12-01

Health profession learners can foster clinical reasoning by studying worked examples presenting fully worked out solutions to a clinical problem. It is possible to improve the learning effect of these worked examples by combining them with other learning activities based on concept maps. This study investigated which combinaison of activities, worked examples study with concept map completion or worked examples study with concept map study, fosters more meaningful learning of intervention knowledge in physiotherapy students. Moreover, this study compared the learning effects of these learning activity combinations between novice and advanced learners. Sixty-one second-year physiotherapy students participated in the study which included a pre-test phase, a 130-min guided-learning phase and a four-week self-study phase. During the guided and self-study learning sessions, participants had to study three written worked examples presenting the clinical reasoning for selecting electrotherapeutic currents to treat patients with motor deficits. After each example, participants engaged in either concept map completion or concept map study depending on which learning condition they were randomly allocated to. Students participated in an immediate post-test at the end of the guided-learning phase and a delayed post-test at the end of the self-study phase. Post-tests assessed the understanding of principles governing the domain of knowledge to be learned (conceptual knowledge) and the ability to solve new problems that have similar (i.e., near transfer) or different (i.e., far transfer) solution rationales as problems previously studied in the examples. Learners engaged in concept map completion outperformed those engaged in concept map study on near transfer (p = .010) and far transfer (p concept map completion led to greater transfer performance than worked examples study combined with concept map study for both novice and advanced learners. Concept map completion

Working Examples (WEx): A Vehicle for Building Radical Innovations to Change Education

Science.gov (United States)

Zywica, Jolene; Roberts, Anna; Davidson, Drew

2013-01-01

Working Examples (WEx) is described by the authors as a vehicle for ideating and building radical innovations to change education. It is a community of researchers, designers, and educators working at the intersection of education and technology. "Examples" (ideas, work, and projects) allow people to explore new ideas, learn from each…

A Case Study to Evaluate Balance Training with Movement Test Items and through Teaching Observation: Beyond Specificity and Transfer of Learning

Science.gov (United States)

Kluwe, Margret; Miyahara, Motohide; Heveldt, Kate

2012-01-01

Background: Specificity and transfer of learning have been examined in experimental studies. However, their findings may not be relevant to practitioners because of the difference between the experiment conditions and teaching situations. This case study investigates the theoretical issue of specificity vs. transfer of learning by conducting…

Rapid motor learning in the translational vestibulo-ocular reflex

Science.gov (United States)

Zhou, Wu; Weldon, Patrick; Tang, Bingfeng; King, W. M.; Shelhamer, M. J. (Principal Investigator)

2003-01-01

Motor learning was induced in the translational vestibulo-ocular reflex (TVOR) when monkeys were repeatedly subjected to a brief (0.5 sec) head translation while they tried to maintain binocular fixation on a visual target for juice rewards. If the target was world-fixed, the initial eye speed of the TVOR gradually increased; if the target was head-fixed, the initial eye speed of the TVOR gradually decreased. The rate of learning acquisition was very rapid, with a time constant of approximately 100 trials, which was equivalent to or=1 d without any reinforcement, indicating induction of long-term synaptic plasticity. Although the learning generalized to targets with different viewing distances and to head translations with different accelerations, it was highly specific for the particular combination of head motion and evoked eye movement associated with the training. For example, it was specific to the modality of the stimulus (translation vs rotation) and the direction of the evoked eye movement in the training. Furthermore, when one eye was aligned with the heading direction so that it remained motionless during training, learning was not expressed in this eye, but only in the other nonaligned eye. These specificities show that the learning sites are neither in the sensory nor the motor limb of the reflex but in the sensory-motor transformation stage of the reflex. The dependence of the learning on both head motion and evoked eye movement suggests that Hebbian learning may be one of the underlying cellular mechanisms.

The «PBL WORKING ENVIRONMENT» as interactive and expert system to learn the problem-based learning method

Directory of Open Access Journals (Sweden)

Susana Correnti

2016-01-01

Full Text Available The «PBL working environment» is a virtual environment developed in the framework of SCENE project (profeSsional development for an effeCtive PBL approach: a practical experiENce through ICT-enabled lEarning solution, co-funded by the European Lifelong Learning Program. The «PBL working environment» is devoted to prepare headmasters and teachers of secondary and vocational schools to use Problem-Based Learning (PBL pedagogy effectively. It is a student-centered pedagogy where learners are «actively» engaged in real world problems to solve or challenges to meet. Students develop problem-solving, self-directed learning and team skills. The «PBL working environment» is an virtual tool including three main elements: e-learning platform, virtual facilitator and PBL repository. Teachers, trainers and headmasters/school managers learn the PBL pedagogy by attending an on-line course (e-learning platform delivered through the «inductive method». It allows learners to experience PBL approach, by practicing it stage by stage, and then learn to turn practice into theory by abstracting their experience to build a theoretical understanding. Since generating the proper scenario is the most critical aspect of PBL, after benefiting from the on-line course, users can benefit from a further support: the Virtual Facilitator. It provides tips and hints on how correctly design a problem scenario and by asking questions to collect data on user's specific needs. The Virtual Facilitator is able to provide a/or more suitable example(s which match as closest as possible the teacher/trainer need. Finally, users can share problem scenarios and projects of different subjects of studies and with different characteristics uploaded and downloaded in the PBL repository.

Developmental song learning as a model to understand neural mechanisms that limit and promote the ability to learn.

Science.gov (United States)

London, Sarah E

2017-11-20

Songbirds famously learn their vocalizations. Some species can learn continuously, others seasonally, and still others just once. The zebra finch (Taeniopygia guttata) learns to sing during a single developmental "Critical Period," a restricted phase during which a specific experience has profound and permanent effects on brain function and behavioral patterns. The zebra finch can therefore provide fundamental insight into features that promote and limit the ability to acquire complex learned behaviors. For example, what properties permit the brain to come "on-line" for learning? How does experience become encoded to prevent future learning? What features define the brain in receptive compared to closed learning states? This piece will focus on epigenomic, genomic, and molecular levels of analysis that operate on the timescales of development and complex behavioral learning. Existing data will be discussed as they relate to Critical Period learning, and strategies for future studies to more directly address these questions will be considered. Birdsong learning is a powerful model for advancing knowledge of the biological intersections of maturation and experience. Lessons from its study not only have implications for understanding developmental song learning, but also broader questions of learning potential and the enduring effects of early life experience on neural systems and behavior. Copyright © 2017. Published by Elsevier B.V.

Learning Apache Solr high performance

CERN Document Server

Mohan, Surendra

2014-01-01

This book is an easy-to-follow guide, full of hands-on, real-world examples. Each topic is explained and demonstrated in a specific and user-friendly flow, from search optimization using Solr to Deployment of Zookeeper applications. This book is ideal for Apache Solr developers and want to learn different techniques to optimize Solr performance with utmost efficiency, along with effectively troubleshooting the problems that usually occur while trying to boost performance. Familiarity with search servers and database querying is expected.

Technology-supported environments for learning through cognitive conflict

Directory of Open Access Journals (Sweden)

Anne McDougall

2002-12-01

Full Text Available This paper examines ways in which the idea of cognitive conflict is used to facilitate learning, looking at the design and use of learning environments for this purpose. Drawing on previous work in science education and educational computing, three approaches to the design of learning environments utilizing cognitive conflict are introduced. These approaches are described as confrontational, guiding and explanatory, based on the level of the designer's concern with learners' pre-existing understanding, the extent of modification to the learner's conceptual structures intended by the designer, and the directness of steering the learner to the desired understanding. The examples used to illustrate the three approaches are taken from science education, specifically software for learning about Newtonian physics; it is contended however that the argument of the paper applies more broadly, to learning environments for many curriculum areas for school levels and in higher education.

An Integrated Mixed Methods Research Design: Example of the Project Foreign Language Learning Strategies and Achievement: Analysis of Strategy Clusters and Sequences

OpenAIRE

Vlčková Kateřina

2014-01-01

The presentation focused on an so called integrated mixed method research design example on a basis of a Czech Science Foundation Project Nr. GAP407/12/0432 "Foreign Language Learning Strategies and Achievement: Analysis of Strategy Clusters and Sequences". All main integrated parts of the mixed methods research design were discussed: the aim, theoretical framework, research question, methods and validity threats. Prezentace se zaměřovala na tzv. integrovaný vícemetodový výzkumný design na...

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees.

Science.gov (United States)

Biergans, Stephanie D; Claudianos, Charles; Reinhard, Judith; Galizia, C G

2016-01-01

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., 'correct' (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes.

Shape-specific perceptual learning in a figure-ground segregation task.

Science.gov (United States)

Yi, Do-Joon; Olson, Ingrid R; Chun, Marvin M

2006-03-01

What does perceptual experience contribute to figure-ground segregation? To study this question, we trained observers to search for symmetric dot patterns embedded in random dot backgrounds. Training improved shape segmentation, but learning did not completely transfer either to untrained locations or to untrained shapes. Such partial specificity persisted for a month after training. Interestingly, training on shapes in empty backgrounds did not help segmentation of the trained shapes in noisy backgrounds. Our results suggest that perceptual training increases the involvement of early sensory neurons in the segmentation of trained shapes, and that successful segmentation requires perceptual skills beyond shape recognition alone.

SATLC applications as examples for systemic chemistry education ...

African Journals Online (AJOL)

It is also used as a vehicle to engage the students in a deep learning that focuses on relating ideas and making connection between new and prior knowledge. As applications of SATLC I present here systemic chemistry related units experimented in Egyptian secondary schools and universities with examples on systemic ...

Lessons Learned from the Development of an Example Precision Information Environment for International Safeguards

Energy Technology Data Exchange (ETDEWEB)

Gastelum, Zoe N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Henry, Michael J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Burtner, IV, E. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Doehle, J. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hampton, S. D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); La Mothe, R. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Nordquist, P. L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zarzhitsky, D. V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2014-12-01

The International Atomic Energy Agency (IAEA) is interested in increasing capabilities of IAEA safeguards inspectors to access information that would improve their situational awareness on the job. A mobile information platform could potentially provide access to information, analytics, and technical and logistical support to inspectors in the field, as well as providing regular updates to analysts at IAEA Headquarters in Vienna or at satellite offices. To demonstrate the potential capability of such a system, Pacific Northwest National Laboratory (PNNL) implemented a number of example capabilities within a PNNL-developed precision information environment (PIE), and using a tablet as a mobile information platform. PNNL’s safeguards proof-of-concept PIE intends to; demonstrate novel applications of mobile information platforms to international safeguards use cases; demonstrate proof-of-principle capability implementation; and provide “vision” for capabilities that could be implemented. This report documents the lessons learned from this two-year development activity for the Precision Information Environment for International Safeguards (PIE-IS), describing the developed capabilities, technical challenges, and considerations for future development, so that developers working to develop a similar system for the IAEA or other safeguards agencies might benefit from our work.

Lessons Learned from the Development of an Example Precision Information Environment for International Safeguards

International Nuclear Information System (INIS)

Gastelum, Zoe N.; Henry, Michael J.; Burtner, IV E.R.; Doehle, J. R.; Hampton, S. D.; La Mothe, R. R.; Nordquist, P. L.; Zarzhitsky, D. V.

2014-01-01

The International Atomic Energy Agency (IAEA) is interested in increasing capabilities of IAEA safeguards inspectors to access information that would improve their situational awareness on the job. A mobile information platform could potentially provide access to information, analytics, and technical and logistical support to inspectors in the field, as well as providing regular updates to analysts at IAEA Headquarters in Vienna or at satellite offices. To demonstrate the potential capability of such a system, Pacific Northwest National Laboratory (PNNL) implemented a number of example capabilities within a PNNL-developed precision information environment (PIE), and using a tablet as a mobile information platform. PNNL's safeguards proof-of-concept PIE intends to; demonstrate novel applications of mobile information platforms to international safeguards use cases; demonstrate proof-of-principle capability implementation; and provide ''vision''@ for capabilities that could be implemented. This report documents the lessons learned from this two-year development activity for the Precision Information Environment for International Safeguards (PIE-IS), describing the developed capabilities, technical challenges, and considerations for future development, so that developers working to develop a similar system for the IAEA or other safeguards agencies might benefit from our work.

Example-based learning: Effects of model expertise in relation to student expertise

NARCIS (Netherlands)

T. Boekhout (Teun); T.A.J.M. van Gog (Tamara); M.W.J. van de Wiel (Margje); D. Gerards-Last (Dorien); F. Geraets (Frank)

2010-01-01

textabstractBackground. Worked examples are very effective for novice learners. They typically present a written-out ideal (didactical) solution for learners to study. nAims. This study used worked examples of patient history taking in physiotherapy that presented a non-didactical solution (i.e.,

FLIPPED LEARNING: PRACTICAL ASPECTS

Directory of Open Access Journals (Sweden)

Olena Kuzminska

2016-03-01

Full Text Available The article is devoted to issues of implementation of the flipped learning technology in the practice of higher education institutions. The article defines the principles of technology and a model of the educational process, it notes the need to establish an information support system. The article defines online platforms and resources; it describes recommendations for the design of electronic training courses and organization of the students in the process of implementing the proposed model, as well as tools for assessing its effectiveness. The article provides a description of flipped learning implementation scenario and formulates suggestions regarding the use of this model as a mechanism to improve the efficiency of the learning process in the ICT-rich environment of high school: use of learning management systems (LMS and personal learning environments (PLE of participants in a learning process. The article provides an example of implementation of the flipped learning model as a part of the Information Technologies course in the National University of Life and Environmental Sciences of Ukraine (NULES. The article gives examples of tasks, resources and services, results of students’ research activity, as well as an example of the personal learning network, established in the course of implementation of the flipped learning model and elements of digital student portfolios. It presents the results of the monitoring of learning activities and students’ feedback. The author describes cautions against the mass introduction of the flipped learning model without monitoring of readiness of the participants of the educational process for its implementation

LEARNING TOOLS INTEROPERABILITY – A NEW STANDARD FOR INTEGRATION OF DISTANCE LEARNING PLATFORMS

Directory of Open Access Journals (Sweden)

Oleksandr A. Shcherbyna

2015-06-01

Full Text Available For information technology in education there is always an issue of re-usage of electronic educational resources, their transferring possibility from one virtual learning environment to another. Previously, standardized sets of files were used to serve this purpose, for example, SCORM-packages. In this article the new standard Learning Tools Interoperability (LTI is reviewed, which allows users from one environment to access resources from another environment. This makes it possible to integrate them into a single distributed learning environment that is created and shared. The article gives examples of the practical use of standard LTI in Moodle learning management system using External tool and LTI provider plugins.

Splendidly blended: a machine learning set up for CDU control

Science.gov (United States)

Utzny, Clemens

2017-06-01

As the concepts of machine learning and artificial intelligence continue to grow in importance in the context of internet related applications it is still in its infancy when it comes to process control within the semiconductor industry. Especially the branch of mask manufacturing presents a challenge to the concepts of machine learning since the business process intrinsically induces pronounced product variability on the background of small plate numbers. In this paper we present the architectural set up of a machine learning algorithm which successfully deals with the demands and pitfalls of mask manufacturing. A detailed motivation of this basic set up followed by an analysis of its statistical properties is given. The machine learning set up for mask manufacturing involves two learning steps: an initial step which identifies and classifies the basic global CD patterns of a process. These results form the basis for the extraction of an optimized training set via balanced sampling. A second learning step uses this training set to obtain the local as well as global CD relationships induced by the manufacturing process. Using two production motivated examples we show how this approach is flexible and powerful enough to deal with the exacting demands of mask manufacturing. In one example we show how dedicated covariates can be used in conjunction with increased spatial resolution of the CD map model in order to deal with pathological CD effects at the mask boundary. The other example shows how the model set up enables strategies for dealing tool specific CD signature differences. In this case the balanced sampling enables a process control scheme which allows usage of the full tool park within the specified tight tolerance budget. Overall, this paper shows that the current rapid developments off the machine learning algorithms can be successfully used within the context of semiconductor manufacturing.

A possible approach from BCS through HTS to RTS with three examples

International Nuclear Information System (INIS)

Chu, C.W.

2012-01-01

This paper is based on my talk delivered at the superconductivity centennial conference in The Hague, the Netherlands, on September 23, 2011, to explore the possibility of room temperature superconductivity according to what we have learned from the past, especially in the last 25 years since the discovery of high temperature superconductivity. While the field of superconductivity is broad, I have chosen to focus on the advancement of T c , which has been a major driving force for sustaining research on superconductivity for the last 100 years, ever since its discovery by Heike Kamerlingh Onnes in Leiden. A holistic multidisciplinary enlightened empirical approach is proposed with some specific steps following a brief summary of the past history in the search for superconductors with higher T c . Before concluding, three specific examples of our effort toward superconductors of higher T c are given to demonstrate that the future in raising T c is vast and bright.

Integrating Worked Examples into Problem Posing in a Web-Based Learning Environment

Science.gov (United States)

Hsiao, Ju-Yuan; Hung, Chun-Ling; Lan, Yu-Feng; Jeng, Yoau-Chau

2013-01-01

Most students always lack of experience and perceive difficult regarding problem posing. The study hypothesized that worked examples may have benefits for supporting students' problem posing activities. A quasi-experiment was conducted in the context of a business mathematics course for examining the effects of integrating worked examples into…

Effects of WOE Presentation Types Used in Pre-Training on the Cognitive Load and Comprehension of Content in Animation-Based Learning Environments

Science.gov (United States)

Jung, Jung,; Kim, Dongsik; Na, Chungsoo

2016-01-01

This study investigated the effectiveness of various types of worked-out examples used in pre-training to optimize the cognitive load and enhance learners' comprehension of the content in an animation-based learning environment. An animation-based learning environment was developed specifically for this study. The participants were divided into…

Example-Based Learning: Effects of Model Expertise in Relation to Student Expertise

Science.gov (United States)

Boekhout, Paul; van Gog, Tamara; van de Wiel, Margje W. J.; Gerards-Last, Dorien; Geraets, Jacques

2010-01-01

Background: Worked examples are very effective for novice learners. They typically present a written-out ideal (didactical) solution for learners to study. Aims: This study used worked examples of patient history taking in physiotherapy that presented a "non"-didactical solution (i.e., based on actual performance). The effects of model expertise…

Learning to learn: self-managed learning

Directory of Open Access Journals (Sweden)

Jesús Miranda Izquierdo

2006-09-01

Full Text Available Thi is article analyzes the potentialities and weaknesses that non directive Pedagogy presents, an example of the so called self managed pedagogy, whose postulates are good to analyze for the contributions that this position can make to the search of new ways of learning.

Quantum learning algorithms for quantum measurements

Energy Technology Data Exchange (ETDEWEB)

Bisio, Alessandro, E-mail: alessandro.bisio@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); D' Ariano, Giacomo Mauro, E-mail: dariano@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); Perinotti, Paolo, E-mail: paolo.perinotti@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); Sedlak, Michal, E-mail: michal.sedlak@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)

2011-09-12

We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information. -- Highlights: → Optimal learning algorithm for von Neumann measurements. → From 2 copies to 1 copy: the optimal strategy is parallel. → From 3 copies to 1 copy: the optimal strategy must be non-parallel.

Quantum learning algorithms for quantum measurements

International Nuclear Information System (INIS)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Sedlak, Michal

2011-01-01

We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information. -- Highlights: → Optimal learning algorithm for von Neumann measurements. → From 2 copies to 1 copy: the optimal strategy is parallel. → From 3 copies to 1 copy: the optimal strategy must be non-parallel.

The effects of inspecting and constructing part-task-specific visualizations on team and individual learning

NARCIS (Netherlands)

Slof, Bert; Erkens, Gijsbert; Kirschner, Paul A.; Helms-Lorenz, Michelle

This study examined whether inspecting and constructing different part-task-specific visualizations differentially affects learning. To this end, a complex business-economics problem was structured into three phase-related part-tasks: (1) determining core concepts, (2) proposing multiple solutions,

Pitch Discrimination Learning: Specificity for Pitch and Harmonic Resolvability, and Electrophysiological Correlates

OpenAIRE

Carcagno, Samuele; Plack, Christopher J.

2011-01-01

Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed...

Progress of the Architectural Competition: Learning Center, the Lausanne Example

Directory of Open Access Journals (Sweden)

Mirjana Rittmeyer

2006-07-01

Full Text Available Point of entry to the Ecole Polytechnique Fédérale de Lausanne (EPFL, the Learning Center will be a place to learn, to obtain information, and to live. Replacing and improving the old main library, this new building will gradually assimilate all EPFL department libraries collections and services, as they are integrated into a global information system. Conceived as the place for those who are learning, mainly students, who have no personal working area on the campus, it is designed to adapt itself to the ‘seasons’ of academic life throughout the year (flexibility and modularity of rooms, extended opening hours during exam periods. It will take into account group working habits (silence vs. noise, changes in the rhythm of student life (meals, working alone, discussions, etc., and other environmental factors. Of course the needs of EPFL staff and alumni, local industry and citizens have also been carefully considered in the design. By offering a multitude of community functions, such as a bookshop, cafeteria and restaurant services, and rooms for relaxation and discussion, the Learning Center will link the campus to the city. Areas devoted to exhibition and debate will also be included, enforcing its role as an interactive science showcase, in particular for those technologies related to the research and teaching of the EPFL. The presentation described the process and steps towards the actual realisation of such a vital public space: from the programme definition to the collaboration with the bureau of architects (SAANA, Tokyo who won the project competition, the speakers showed what are the challenges and lessons already taken when working on this major piece of architecture, indeed the heart of the transformation of the technical school build in the 1970s into a real 2000s campus.

SemiBoost: boosting for semi-supervised learning.

Science.gov (United States)

Mallapragada, Pavan Kumar; Jin, Rong; Jain, Anil K; Liu, Yi

2009-11-01

Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We call this as the Semi-supervised improvement problem, to distinguish the proposed approach from the existing approaches. We design a metasemi-supervised learning algorithm that wraps around the underlying supervised algorithm and improves its performance using unlabeled data. This problem is particularly important when we need to train a supervised learning algorithm with a limited number of labeled examples and a multitude of unlabeled examples. We present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages of the proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with a multitude of unlabeled data, 2) efficient computation by the iterative boosting algorithm, and 3) exploiting both manifold and cluster assumption in training classification models. An empirical study on 16 different data sets and text categorization demonstrates that the proposed framework improves the performance of several commonly used supervised learning algorithms, given a large number of unlabeled examples. We also show that the performance of the proposed algorithm, SemiBoost, is comparable to the state-of-the-art semi-supervised learning algorithms.

The Legal Meaning of Specific Learning Disability for IDEA Eligibility: The Latest Case Law

Science.gov (United States)

Zirkel, Perry A.

2013-01-01

Specific learning disability (SLD), although moderately declining in recent years, continues to be the largest of the eligibility classifications under the Individuals with Disabilities Education Act (IDEA; NCES, 2012). The recognition of response to intervention (RTI) in the 2004 amendments of the IDEA as an approach for identifying students with…

Learning and coding in biological neural networks

Science.gov (United States)

Fiete, Ila Rani

How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and

E-Learning for Geography's Teaching and Learning Spaces

Science.gov (United States)

Lynch, Kenneth; Bednarz, Bob; Boxall, James; Chalmers, Lex; France, Derek; Kesby, Julie

2008-01-01

The authors embed their advocacy of educational technology in a consideration of contemporary pedagogy in geography. They provide examples of e-learning from a wide range of teaching and learning contexts. They promote the idea that considering best practice with reference to educational technology will increase the versatility of teaching…

Using c-Jun to identify fear extinction learning-specific patterns of neural activity that are affected by single prolonged stress.

Science.gov (United States)

Knox, Dayan; Stanfield, Briana R; Staib, Jennifer M; David, Nina P; DePietro, Thomas; Chamness, Marisa; Schneider, Elizabeth K; Keller, Samantha M; Lawless, Caroline

2018-04-02

Neural circuits via which stress leads to disruptions in fear extinction is often explored in animal stress models. Using the single prolonged stress (SPS) model of post traumatic stress disorder and the immediate early gene (IEG) c-Fos as a measure of neural activity, we previously identified patterns of neural activity through which SPS disrupts extinction retention. However, none of these stress effects were specific to fear or extinction learning and memory. C-Jun is another IEG that is sometimes regulated in a different manner to c-Fos and could be used to identify emotional learning/memory specific patterns of neural activity that are sensitive to SPS. Animals were either fear conditioned (CS-fear) or presented with CSs only (CS-only) then subjected to extinction training and testing. C-Jun was then assayed within neural substrates critical for extinction memory. Inhibited c-Jun levels in the hippocampus (Hipp) and enhanced functional connectivity between the ventromedial prefrontal cortex (vmPFC) and basolateral amygdala (BLA) during extinction training was disrupted by SPS in the CS-fear group only. As a result, these effects were specific to emotional learning/memory. SPS also disrupted inhibited Hipp c-Jun levels, enhanced BLA c-Jun levels, and altered functional connectivity among the vmPFC, BLA, and Hipp during extinction testing in SPS rats in the CS-fear and CS-only groups. As a result, these effects were not specific to emotional learning/memory. Our findings suggest that SPS disrupts neural activity specific to extinction memory, but may also disrupt the retention of fear extinction by mechanisms that do not involve emotional learning/memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning to spell from reading: general knowledge about spelling patterns influences memory for specific words.

Science.gov (United States)

Pacton, Sébastien; Borchardt, Gaëlle; Treiman, Rebecca; Lété, Bernard; Fayol, Michel

2014-05-01

Adults often learn to spell words during the course of reading for meaning, without intending to do so. We used an incidental learning task in order to study this process. Spellings that contained double n, r and t which are common doublets in French, were learned more readily by French university students than spellings that contained less common but still legal doublets. When recalling or recognizing the latter, the students sometimes made transposition errors, doubling a consonant that often doubles in French rather than the consonant that was originally doubled (e.g., tiddunar recalled as tidunnar). The results, found in three experiments using different nonwords and different types of instructions, show that people use general knowledge about the graphotactic patterns of their writing system together with word-specific knowledge to reconstruct spellings that they learn from reading. These processes contribute to failures and successes in memory for spellings, as in other domains.

Statistical learning methods: Basics, control and performance

Energy Technology Data Exchange (ETDEWEB)

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

2006-04-01

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

Statistical learning methods: Basics, control and performance

International Nuclear Information System (INIS)

Zimmermann, J.

2006-01-01

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

A review of machine learning in obesity.

Science.gov (United States)

DeGregory, K W; Kuiper, P; DeSilvio, T; Pleuss, J D; Miller, R; Roginski, J W; Fisher, C B; Harness, D; Viswanath, S; Heymsfield, S B; Dungan, I; Thomas, D M

2018-05-01

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning provides sophisticated and elegant tools to describe, classify and predict obesity-related risks and outcomes. Here, we review machine learning methods that predict and/or classify such as linear and logistic regression, artificial neural networks, deep learning and decision tree analysis. We also review methods that describe and characterize data such as cluster analysis, principal component analysis, network science and topological data analysis. We introduce each method with a high-level overview followed by examples of successful applications. The algorithms were then applied to National Health and Nutrition Examination Survey to demonstrate methodology, utility and outcomes. The strengths and limitations of each method were also evaluated. This summary of machine learning algorithms provides a unique overview of the state of data analysis applied specifically to obesity. © 2018 World Obesity Federation.

Learning molecular energies using localized graph kernels

Science.gov (United States)

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-01

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Improving e-learning by Emotive Feedback

DEFF Research Database (Denmark)

Sharp, Robin; Gjedde, Lisa

2011-01-01

This paper considers the use of feedback with emotive elements in order to improve the efficiency of e-learning for teaching complex technical subjects to the general public by stimulation of implicit learning. An example is presented, based on an effort to investigate the current level of IT sec......This paper considers the use of feedback with emotive elements in order to improve the efficiency of e-learning for teaching complex technical subjects to the general public by stimulation of implicit learning. An example is presented, based on an effort to investigate the current level...

Distance-Learning for Advanced Military Education: Using Wargame Simulation Course as an Example

Science.gov (United States)

Keh, Huan-Chao; Wang, Kuei-Min; Wai, Shu-Shen; Huang, Jiung-yao; Hui, Lin; Wu, Ji-Jen

2008-01-01

Distance learning in advanced military education can assist officers around the world to become more skilled and qualified for future challenges. Through well-chosen technology, the efficiency of distance-learning can be improved significantly. In this paper we present the architecture of Advanced Military Education-Distance Learning (AME-DL)…

Group-Based Active Learning of Classification Models.

Science.gov (United States)

Luo, Zhipeng; Hauskrecht, Milos

2017-05-01

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.

Enhanced Assessment Technology and Neurocognitive Aspects of Specific Learning Disorder with Impairment in Mathematics.

Directory of Open Access Journals (Sweden)

Marios A. Pappas

2018-02-01

Full Text Available Specific Learning Disorder with impairment in Mathematics (Developmental Dyscalculia is a complex learning disorder which affects arithmetic skills, symbolic magnitude processing, alertness, flexibility in problem solving and maintained attention. Neuro-cognitive studies revealed that such difficulties in children with DD could be related to poor Working Memory and attention deficits. Furthermore, neuroimaging studies indicate that brain structure differences in children with DD compared to typically developing children could affect mathematical performance. In this study we present the cognitive profile of Dyscalculia, as well as the neuropsychological aspects of the deficit, with special reference to the utilization of enhanced assessment technology such as computerized neuropsychological tools and neuroimaging techniques.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

Science.gov (United States)

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

Directory of Open Access Journals (Sweden)

Kabilar Gunalan

Full Text Available Deep brain stimulation (DBS is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports.Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM and predict the response of the hyperdirect pathway to clinical stimulation.Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD. This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution.Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings.Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

Specificity of high-rise construction and real estate markets in the regional economy: an analysis of Russian practice (example of St. Petersburg)

Science.gov (United States)

Vilken, Viktoriya; Kalinina, Olga; Dubgorn, Alissa

2018-03-01

In paper features of the regional markets of construction the commercial and residential real estate on the example of St. Petersburg are defined. The current situation is analysed, the specific features of branch are revealed. The major factors influencing investors making decisions on construction of various types of objects are defined. The main methods of advance of real estate objects are considered.

Learning With Mixed Hard/Soft Pointwise Constraints.

Science.gov (United States)

Gnecco, Giorgio; Gori, Marco; Melacci, Stefano; Sanguineti, Marcello

2015-09-01

A learning paradigm is proposed and investigated, in which the classical framework of learning from examples is enhanced by the introduction of hard pointwise constraints, i.e., constraints imposed on a finite set of examples that cannot be violated. Such constraints arise, e.g., when requiring coherent decisions of classifiers acting on different views of the same pattern. The classical examples of supervised learning, which can be violated at the cost of some penalization (quantified by the choice of a suitable loss function) play the role of soft pointwise constraints. Constrained variational calculus is exploited to derive a representer theorem that provides a description of the functional structure of the optimal solution to the proposed learning paradigm. It is shown that such an optimal solution can be represented in terms of a set of support constraints, which generalize the concept of support vectors and open the doors to a novel learning paradigm, called support constraint machines. The general theory is applied to derive the representation of the optimal solution to the problem of learning from hard linear pointwise constraints combined with soft pointwise constraints induced by supervised examples. In some cases, closed-form optimal solutions are obtained.

Defining the Undefinable: Operationalization of Methods to Identify Specific Learning Disabilities among Practicing School Psychologists

Science.gov (United States)

Cottrell, Joseph M.; Barrett, Courtenay A.

2016-01-01

Accurate and consistent identification of students with specific learning disabilities (SLDs) is crucial; however, state and district guidelines regarding identification methods lack operationalization and are inconsistent throughout the United States. In the current study, the authors surveyed 471 school psychologists about "school" SLD…

Putting Fun Back into Learning.

Science.gov (United States)

Rao, Srikumar S.

1995-01-01

People will learn better if they like what they are learning. Computers offer an extensive library of cases, examples, and stories that are easy to access, fun to work through, and tell students what they want to know. One example is the ASK system, a 15-module, self-study, multimedia program that is fun for trainees to use, which should enhance…

LEARNING GEOMETRY THROUGH MIMESIS AND DIGITAL CONSTRUCT

OpenAIRE

Maria Mion POP; Mihaela GIURGIULESCU

2015-01-01

The theme proposed by us is useful to teachers and students for mathematics in the compulsory school cycle. The issues faced by school teachers/parents are the difficulty with which students read and understand the lessons/examples/synthesis in order to assimilate technical terms. The echoic and iconic memory facilitates the learning of the specific curriculum of linear, spatial and analytical geometry by the students using digital platform designed by us; it facilitates the acquiring of the ...

Working Memory and Learning in Children with Developmental Coordination Disorder and Specific Language Impairment

Science.gov (United States)

Alloway, Tracy Packiam; Archibald, Lisa

2008-01-01

The authors compared 6- to 11-year-olds with developmental coordination disorder (DCD) and those with specific language impairment (SLI) on measures of memory (verbal and visuospatial short-term and working memory) and learning (reading and mathematics). Children with DCD with typical language skills were impaired in all four areas of memory…

A Survey on Domain-Specific Languages for Machine Learning in Big Data

OpenAIRE

Portugal, Ivens; Alencar, Paulo; Cowan, Donald

2016-01-01

The amount of data generated in the modern society is increasing rapidly. New problems and novel approaches of data capture, storage, analysis and visualization are responsible for the emergence of the Big Data research field. Machine Learning algorithms can be used in Big Data to make better and more accurate inferences. However, because of the challenges Big Data imposes, these algorithms need to be adapted and optimized to specific applications. One important decision made by software engi...

Impact of an education program on parental knowledge of specific learning disability

OpenAIRE

Karande Sunil; Mehta Vishal; Kulkarni Madhuri

2007-01-01

Background :A supportive home environment is one of the factors that can favorably determine the outcome of specific learning disability (SpLD) in a school-going child. However, there is no reliable information available on parental knowledge about SpLD. Aims :To investigate parental knowledge of SpLD and to evaluate the impact of an educational intervention on it. Settings and Design : Prospective questionnaire-based study conducted in our clinic. Materials and Methods : From April to Novemb...

Effects of Students' Characteristics on Online Learning Readiness: A Vocational College Example

Science.gov (United States)

Cigdam, Harun; Yildirim, Osman Gazi

2014-01-01

Educational institutions rapidly adopt concepts and practices of online learning systems for students. But many institutions' online learning programs face enormous difficulty in achieving successful strategies. It is essential to evaluate its different aspects and understand factors which influence its effectiveness. Readiness stands out among…

Assuring Student Learning Outcomes Achievement through Faculty Development: An Online University Example

Science.gov (United States)

Lewis, Shelia; Ewing, Christopher

2016-01-01

Asynchronous discussions in the online teaching and learning environment significantly contributes to the achievement of student learning outcomes, which is dependent upon qualified and engaged faculty members. The discourse within this article addresses how an online university conducted faculty development through its unique Robust Learning…

A Learning Algorithm based on High School Teaching Wisdom

OpenAIRE

Philip, Ninan Sajeeth

2010-01-01

A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate a student and to give them training on the examples for which they repeatedly fail, until, they can correctly answer all types of questions. This incremental learning procedure produces better learning curves by demanding the student to optimally dedicate their learning time on the failed examples. When used in machine learning, the algorithm is found to train a machine...

[Multilingualism and child psychiatry: on differential diagnoses of language disorder, specific learning disorder, and selective mutism].

Science.gov (United States)

Tamiya, Satoshi

2014-01-01

Multilingualism poses unique psychiatric problems, especially in the field of child psychiatry. The author discusses several linguistic and transcultural issues in relation to Language Disorder, Specific Learning Disorder and Selective Mutism. Linguistic characteristics of multiple language development, including so-called profile effects and code-switching, need to be understood for differential diagnosis. It is also emphasized that Language Disorder in a bilingual person is not different or worse than that in a monolingual person. Second language proficiency, cultural background and transfer from the first language all need to be considered in an evaluation for Specific Learning Disorder. Selective Mutism has to be differentiated from the silent period observed in the normal successive bilingual development. The author concludes the review by remarking on some caveats around methods of language evaluation in a multilingual person.

Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy.

Science.gov (United States)

Smith, Mary Lou; Bigel, Marla; Miller, Laurie A

2011-02-01

The mesial temporal lobes are important for learning arbitrary associations. It has previously been demonstrated that left mesial temporal structures are involved in learning word pairs, but it is not yet known whether comparable lesions in the right temporal lobe impair visually mediated associative learning. Patients who had undergone left (n=16) or right (n=18) temporal lobectomy for relief of intractable epilepsy and healthy controls (n=13) were administered two paired-associate learning tasks assessing their learning and memory of pairs of abstract designs or pairs of symbols in unique locations. Both patient groups had deficits in learning the designs, but only the right temporal group was impaired in recognition. For the symbol location task, differences were not found in learning, but again a recognition deficit was found for the right temporal group. The findings implicate the mesial temporal structures in relational learning. They support a material-specific effect for recognition but not for learning and recall of arbitrary visual and visual-spatial associative information. Copyright © 2010 Elsevier Inc. All rights reserved.

A Survey of Quantum Learning Theory

OpenAIRE

Arunachalam, Srinivasan; de Wolf, Ronald

2017-01-01

This paper surveys quantum learning theory: the theoretical aspects of machine learning using quantum computers. We describe the main results known for three models of learning: exact learning from membership queries, and Probably Approximately Correct (PAC) and agnostic learning from classical or quantum examples.

Deep learning with Python

CERN Document Server

Chollet, Francois

2018-01-01

DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES • Practical code examples • In-depth introduction to Keras • Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural ...

Large-Scale Urban Decontamination; Developments, Historical Examples and Lessons Learned

Energy Technology Data Exchange (ETDEWEB)

Rick Demmer

2007-02-01

Recent terrorist threats and actual events have lead to a renewed interest in the technical field of large scale, urban environment decontamination. One of the driving forces for this interest is the real potential for the cleanup and removal of radioactive dispersal device (RDD or “dirty bomb”) residues. In response the U. S. Government has spent many millions of dollars investigating RDD contamination and novel decontamination methodologies. Interest in chemical and biological (CB) cleanup has also peaked with the threat of terrorist action like the anthrax attack at the Hart Senate Office Building and with catastrophic natural events such as Hurricane Katrina. The efficiency of cleanup response will be improved with these new developments and a better understanding of the “old reliable” methodologies. Perhaps the most interesting area of investigation for large area decontamination is that of the RDD. While primarily an economic and psychological weapon, the need to cleanup and return valuable or culturally significant resources to the public is nonetheless valid. Several private companies, universities and National Laboratories are currently developing novel RDD cleanup technologies. Because of its longstanding association with radioactive facilities, the U. S. Department of Energy National Laboratories are at the forefront in developing and testing new RDD decontamination methods. However, such cleanup technologies are likely to be fairly task specific; while many different contamination mechanisms, substrate and environmental conditions will make actual application more complicated. Some major efforts have also been made to model potential contamination, to evaluate both old and new decontamination techniques and to assess their readiness for use. Non-radioactive, CB threats each have unique decontamination challenges and recent events have provided some examples. The U. S. Environmental Protection Agency (EPA), as lead agency for these emergency

Effects of arousal on cognitive control: empirical tests of the conflict-modulated Hebbian-learning hypothesis.

Science.gov (United States)

Brown, Stephen B R E; van Steenbergen, Henk; Kedar, Tomer; Nieuwenhuis, Sander

2014-01-01

An increasing number of empirical phenomena that were previously interpreted as a result of cognitive control, turn out to reflect (in part) simple associative-learning effects. A prime example is the proportion congruency effect, the finding that interference effects (such as the Stroop effect) decrease as the proportion of incongruent stimuli increases. While this was previously regarded as strong evidence for a global conflict monitoring-cognitive control loop, recent evidence has shown that the proportion congruency effect is largely item-specific and hence must be due to associative learning. The goal of our research was to test a recent hypothesis about the mechanism underlying such associative-learning effects, the conflict-modulated Hebbian-learning hypothesis, which proposes that the effect of conflict on associative learning is mediated by phasic arousal responses. In Experiment 1, we examined in detail the relationship between the item-specific proportion congruency effect and an autonomic measure of phasic arousal: task-evoked pupillary responses. In Experiment 2, we used a task-irrelevant phasic arousal manipulation and examined the effect on item-specific learning of incongruent stimulus-response associations. The results provide little evidence for the conflict-modulated Hebbian-learning hypothesis, which requires additional empirical support to remain tenable.

Effects of arousal on cognitive control: Empirical tests of the conflict-modulated Hebbian-learning hypothesis

Directory of Open Access Journals (Sweden)

Stephen B.R.E. Brown

2014-01-01

Full Text Available An increasing number of empirical phenomena that were previously interpreted as a result of cognitive control, turn out to reflect (in part simple associative-learning effects. A prime example is the proportion congruency effect, the finding that interference effects (such as the Stroop effect decrease as the proportion of incongruent stimuli increases. While this was previously regarded as strong evidence for a global conflict monitoring-cognitive control loop, recent evidence has shown that the proportion congruency effect is largely item-specific and hence must be due to associative learning. The goal of our research was to test a recent hypothesis about the mechanism underlying such associative-learning effects, the conflict-modulated Hebbian-learning hypothesis, which proposes that the effect of conflict on associative learning is mediated by phasic arousal responses. In Experiment 1, we examined in detail the relationship between the item-specific proportion congruency effect and an autonomic measure of phasic arousal: task-evoked pupillary responses. In Experiment 2, we used a task-irrelevant phasic arousal manipulation and examined the effect on item-specific learning of incongruent stimulus-response associations. The results provide little evidence for the conflict-modulated Hebbian-learning hypothesis, which requires additional empirical support to remain tenable.

Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions.

Science.gov (United States)

Tamosiunaite, Minija; Asfour, Tamim; Wörgötter, Florentin

2009-03-01

Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of this paper is, thus, to develop a novel, rather simple method which uses reinforcement learning with function approximation in conjunction with different reward-strategies for solving such problems. For the testing of our method, we use a four degree-of-freedom reaching problem in 3D-space simulated by a two-joint robot arm system with two DOF each. Function approximation is based on 4D, overlapping kernels (receptive fields) and the state-action space contains about 10,000 of these. Different types of reward structures are being compared, for example, reward-on- touching-only against reward-on-approach. Furthermore, forbidden joint configurations are punished. A continuous action space is used. In spite of a rather large number of states and the continuous action space these reward/punishment strategies allow the system to find a good solution usually within about 20 trials. The efficiency of our method demonstrated in this test scenario suggests that it might be possible to use it on a real robot for problems where mixed rewards can be defined in situations where other types of learning might be difficult.

An Example-Based Brain MRI Simulation Framework.

Science.gov (United States)

He, Qing; Roy, Snehashis; Jog, Amod; Pham, Dzung L

2015-02-21

The simulation of magnetic resonance (MR) images plays an important role in the validation of image analysis algorithms such as image segmentation, due to lack of sufficient ground truth in real MR images. Previous work on MRI simulation has focused on explicitly modeling the MR image formation process. However, because of the overwhelming complexity of MR acquisition these simulations must involve simplifications and approximations that can result in visually unrealistic simulated images. In this work, we describe an example-based simulation framework, which uses an "atlas" consisting of an MR image and its anatomical models derived from the hard segmentation. The relationships between the MR image intensities and its anatomical models are learned using a patch-based regression that implicitly models the physics of the MR image formation. Given the anatomical models of a new brain, a new MR image can be simulated using the learned regression. This approach has been extended to also simulate intensity inhomogeneity artifacts based on the statistical model of training data. Results show that the example based MRI simulation method is capable of simulating different image contrasts and is robust to different choices of atlas. The simulated images resemble real MR images more than simulations produced by a physics-based model.

Region and task-specific activation of Arc in primary motor cortex of rats following motor skill learning.

Science.gov (United States)

Hosp, J A; Mann, S; Wegenast-Braun, B M; Calhoun, M E; Luft, A R

2013-10-10

Motor learning requires protein synthesis within the primary motor cortex (M1). Here, we show that the immediate early gene Arc/Arg3.1 is specifically induced in M1 by learning a motor skill. Arc mRNA was quantified using a fluorescent in situ hybridization assay in adult Long-Evans rats learning a skilled reaching task (SRT), in rats performing reaching-like forelimb movement without learning (ACT) and in rats that were trained in the operant but not the motor elements of the task (controls). Apart from M1, Arc expression was assessed within the rostral motor area (RMA), primary somatosensory cortex (S1), striatum (ST) and cerebellum. In SRT animals, Arc mRNA levels in M1 contralateral to the trained limb were 31% higher than ipsilateral (pmotor skill learning in rats. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Training hydrologists to be ecohydrologists: a "how-you-can-do-it" example leveraging an active learning environment for studying plant-water interaction

Science.gov (United States)

Lyon, S. W.; Walter, M. T.; Jantze, E. J.; Archibald, J. A.

2012-08-01

Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a "how-you-can-do-it" example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at the Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of "activeness" across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more "active" techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.

Video2vec Embeddings Recognize Events when Examples are Scarce

NARCIS (Netherlands)

Habibian, A.; Mensink, T.; Snoek, C.G.M.

2017-01-01

This paper aims for event recognition when video examples are scarce or even completely absent. The key in such a challenging setting is a semantic video representation. Rather than building the representation from individual attribute detectors and their annotations, we propose to learn the entire

The role of context in preschool learning: a multilevel examination of the contribution of context-specific problem behaviors and classroom process quality to low-income children's approaches to learning.

Science.gov (United States)

Domínguez, Ximena; Vitiello, Virginia E; Fuccillo, Janna M; Greenfield, Daryl B; Bulotsky-Shearer, Rebecca J

2011-04-01

Research suggests that promoting adaptive approaches to learning early in childhood may help close the gap between advantaged and disadvantaged children. Recent research has identified specific child-level and classroom-level variables that are significantly associated with preschoolers' approaches to learning. However, further research is needed to understand the interactive effects of these variables and determine whether classroom-level variables buffer the detrimental effects of child-level risk variables. Using a largely urban and minority sample (N=275) of preschool children, the present study examined the additive and interactive effects of children's context-specific problem behaviors and classroom process quality dimensions on children's approaches to learning. Teachers rated children's problem behavior and approaches to learning and independent assessors conducted classroom observations to assess process quality. Problem behaviors in structured learning situations and in peer and teacher interactions were found to negatively predict variance in approaches to learning. Classroom process quality domains did not independently predict variance in approaches to learning. Nonetheless, classroom process quality played an important role in these associations; high emotional support buffered the detrimental effects of problem behavior, whereas high instructional support exacerbated them. The findings of this study have important implications for classroom practices aimed at helping children who exhibit problem behaviors. Copyright © 2010 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Bionics by examples 250 scenarios from classical to modern times

CERN Document Server

Nachtigall, Werner

2015-01-01

Bionics means learning from the nature for the development of technology. The science of "bionics" itself is classified into several sections, from materials and structures over procedures and processes until evolution and optimization. Not all these areas, or only a few, are really known in the public and also in scientific literature. This includes the Lotus-effect, converted to the contamination-reduction of fassades and the shark-shed-effect, converted to the  resistance-reduction of airplanes. However, there are hundreds of highly interesting examples that contain the transformation of principles of the nature into technology. From the large number of these examples, 250 were selected for the present book according to "prehistory", "early-history", "classic" and "modern time". Most examples are new. Every example includes a printed page in a homogeneous arrangement. The examples from the field "modern time" are joint in blocks corresponding to the sub-disciplines of bionics.

Nonadjacent Dependency Learning in Cantonese-Speaking Children With and Without a History of Specific Language Impairment.

Science.gov (United States)

Iao, Lai-Sang; Ng, Lai Yan; Wong, Anita Mei Yin; Lee, Oi Ting

2017-03-01

This study investigated nonadjacent dependency learning in Cantonese-speaking children with and without a history of specific language impairment (SLI) in an artificial linguistic context. Sixteen Cantonese-speaking children with a history of SLI and 16 Cantonese-speaking children with typical language development (TLD) were tested with a nonadjacent dependency learning task using artificial languages that mimic Cantonese. Children with TLD performed above chance and were able to discriminate between trained and untrained nonadjacent dependencies. However, children with a history of SLI performed at chance and were not able to differentiate trained versus untrained nonadjacent dependencies. These findings, together with previous findings from English-speaking adults and adolescents with language impairments, suggest that individuals with atypical language development, regardless of age, diagnostic status, language, and culture, show difficulties in learning nonadjacent dependencies. This study provides evidence for early impairments to statistical learning in individuals with atypical language development.

Procedural learning in Parkinson's disease, specific language impairment, dyslexia, schizophrenia, developmental coordination disorder, and autism spectrum disorders: A second-order meta-analysis.

Science.gov (United States)

Clark, Gillian M; Lum, Jarrad A G

2017-10-01

The serial reaction time task (SRTT) has been used to study procedural learning in clinical populations. In this report, second-order meta-analysis was used to investigate whether disorder type moderates performance on the SRTT. Using this approach to quantitatively summarise past research, it was tested whether autism spectrum disorder, developmental coordination disorder, dyslexia, Parkinson's disease, schizophrenia, and specific language impairment differentially affect procedural learning on the SRTT. The main analysis revealed disorder type moderated SRTT performance (p=0.010). This report demonstrates comparable levels of procedural learning impairment in developmental coordination disorder, dyslexia, Parkinson's disease, schizophrenia, and specific language impairment. However, in autism, procedural learning is spared. Copyright © 2017 Elsevier Inc. All rights reserved.

A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining

Directory of Open Access Journals (Sweden)

Yohei Koga

2018-01-01

Full Text Available Recently, deep learning techniques have had a practical role in vehicle detection. While much effort has been spent on applying deep learning to vehicle detection, the effective use of training data has not been thoroughly studied, although it has great potential for improving training results, especially in cases where the training data are sparse. In this paper, we proposed using hard example mining (HEM in the training process of a convolutional neural network (CNN for vehicle detection in aerial images. We applied HEM to stochastic gradient descent (SGD to choose the most informative training data by calculating the loss values in each batch and employing the examples with the largest losses. We picked 100 out of both 500 and 1000 examples for training in one iteration, and we tested different ratios of positive to negative examples in the training data to evaluate how the balance of positive and negative examples would affect the performance. In any case, our method always outperformed the plain SGD. The experimental results for images from New York showed improved performance over a CNN trained in plain SGD where the F1 score of our method was 0.02 higher.

Learning by experience on the example of mathematic pendulum

Science.gov (United States)

Horváth, Peter

2017-01-01

The very suitable topic for independent student activities is the investigation of factors influencing an oscillation period of the mathematic pendulum. The article describes the experience from particular lessons. Students themselves were discovering new facts. They learned about the physics practice of acquiring new knowledge. The knowledge quality and retention was compared between the experimental classes and classes with a traditional instruction one year after the experiment.

Prevalence of specific learning disabilities among primary school children in a South Indian city.

Science.gov (United States)

Mogasale, Vijayalaxmi V; Patil, Vishwanath D; Patil, Nanasaheb M; Mogasale, Vittal

2012-03-01

To measure the prevalence of specific learning disabilities (SpLDs) such as dyslexia, dysgraphia and dyscalculia among primary school children in a South Indian city. A cross-sectional multi-staged stratified randomized cluster sampling study was conducted among children aged 8-11 years from third and fourth standard. A six level screening approach that commenced with identification of scholastic backwardness followed by stepwise exclusion of impaired vision and hearing, chronic medical conditions and subnormal intelligence was carried out among these children. In the final step, the remaining children were subjected to specific tests for reading, comprehension, writing and mathematical calculation. The prevalence of specific learning disabilities was 15.17% in sampled children, whereas 12.5%, 11.2% and 10.5% had dysgraphia, dyslexia and dyscalculia respectively. This study suggests that the prevalence of SpLDs is at the higher side of previous estimations in India. The study is unique due to its large geographically representative design and identification of the problem using simplified screening approach and tools, which minimizes the number and time of specialist requirement and spares the expensive investigation. This approach and tools are suitable for field situations and resource scarce settings. Based on the authors' experience, they express the need for more prevalence studies, remedial education and policy interventions to manage SpLDs at main stream educational system to improve the school performance in Indian children.

The Impact of an Assurance System on the Quality of Teaching and Learning--Using the Example of a University in Russia and One of the Universities in Germany

Science.gov (United States)

Szymenderski, Peggy; Yagudina, Liliya; Burenkova, Olga

2015-01-01

In this paper we consider the question of how quality assurance can have a real, positive impact on the quality of teaching and learning at universities, considering the realities of different systems--the system of control and the system of quality culture--in using the example of two universities: the KNITU-KAI in Russia and the TU Dresden in…

Learning to see the difference specifically alters the most informative V4 neurons.

Science.gov (United States)

Raiguel, Steven; Vogels, Rufin; Mysore, Santosh G; Orban, Guy A

2006-06-14

Perceptual learning is an instance of adult plasticity whereby training in a sensory (e.g., a visual task) results in neuronal changes leading to an improved ability to perform the task. Yet studies in primary visual cortex have found that changes in neuronal response properties were relatively modest. The present study examines the effects of training in an orientation discrimination task on the response properties of V4 neurons in awake rhesus monkeys. Results indicate that the changes induced in V4 are indeed larger than those in V1. Nonspecific effects of training included a decrease in response variance, and an increase in overall orientation selectivity in V4. The orientation-specific changes involved a local steepening in the orientation tuning curve around the trained orientation that selectively improved orientation discriminability at the trained orientation. Moreover, these changes were largely confined to the population of neurons whose orientation tuning was optimal for signaling small differences in orientation at the trained orientation. Finally, the modifications were restricted to the part of the tuning curve close to the trained orientation. Thus, we conclude that it is the most informative V4 neurons, those most directly involved in the discrimination, that are specifically modified by perceptual learning.

Examples to Keep the Passion for the Geosciences

Science.gov (United States)

Fernández Raga, María; Palencia Coto, Covadonga; Cerdà, Artemi

2014-05-01

It is said that the beasts can smell fear. The translation to education is that students know when our vocation is really teaching or when you are teaching as a result of the sequence of events like a side effect of an investigating vocation path. But to become a good teacher, you need to love teaching!!! Education work requires a dynamic appeal by the students. It should be entertaining, motivating, interactive and dynamic. In this session I will present several tips and examples to get attention on your geology sessions: 1. The teacher should maintain a high interest in the subject of your work. Motivation is contagious!!!!If you show passion the other will feel it. 2. Change the attitude of students. Some activities can help you to do that like asking for the preparation of an experiment, and analyzing the results. Some examples will be shown. 3. Arouse the curiosity of the students. Some strategies could be asking questions in novel, controversial or inconsistent ways, asking conceptual conflicts and paradox that looks not expected from what is studied or 4. Use some tools to get the attention of the students. Examples of these tools can be Google Maps and Google Earth (teaching them to design routes and marking studies), Google drive (to create documents online in a team and file sharing), Google plus (to hang interesting news). 5. Examine students each week. Although it will be laborious, their work and learning will be more gradual. 6. Increase levels of competition among peers. 7. Relate what you know with what you learn. It is very important to be aware of the basis on which pupils, through prior knowledge test match. 8. Feel competent. Teacher's confidence is vital when teaching a class. You must be aware of our weaknesses and humble, but our nerves should help us to improve the quality of our classes. 9. Individualized teaching and learning. Numerous psychological and sociological studies suggest that the existence of social networks contribute to the

A European perspective on e-learning

DEFF Research Database (Denmark)

Dirckinck-Holmfeld, Lone

2004-01-01

E-learning at Work , edited by Anne Marie Kanstrup. Roskilde Universitetsforlag, pages Pp.15-29. 2004 Short description: Based on a survey of 149 European e-learning and adult vocational training projects, the author presents examples of how ICT facilitates a positive change and development...... of workplace-related learning. Abstract: Based on a survey of 149 European e-learning and adult vocational training projects, the author presents examples of how ICT facilitates a positive change and development of workplace-related learning.The chapter ends with a suggestion for a historical categorisation...... that focus is on designing the technical tools rather than on the use of tools for e-learning in general, where ICT is just one integrated element among many: objective, motivation, ways to learning, profession, workplace etc. The rojects also reveal that different European countries move at different paces...

Contingency learning is not affected by conflict experience: Evidence from a task conflict-free, item-specific Stroop paradigm.

Science.gov (United States)

Levin, Yulia; Tzelgov, Joseph

2016-02-01

A contingency learning account of the item-specific proportion congruent effect has been described as an associative stimulus-response learning process that has nothing to do with controlling the Stroop conflict. As supportive evidence, contingency learning has been demonstrated with response conflict-free stimuli, such as neutral words. However, what gives rise to response conflict and to Stroop interference in general is task conflict. The present study investigated whether task conflict can constitute a trigger or, alternatively, a booster to the contingency learning process. This was done by employing a "task conflict-free" condition (i.e., geometric shapes) and comparing it with a "task conflict" condition (i.e., neutral words). The results showed a significant contingency learning effect in both conditions, refuting the possibility that contingency learning is triggered by the presence of a task conflict. Contingency learning was also not enhanced by the task conflict experience, indicating its complete insensitivity to Stroop conflict(s). Thus, the results showed no evidence that performance optimization as a result of contingency learning is greater under conflict, implying that contingency learning is not recruited to assist the control system to overcome conflict. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving buried threat detection in ground-penetrating radar with transfer learning and metadata analysis

Science.gov (United States)

Colwell, Kenneth A.; Torrione, Peter A.; Morton, Kenneth D.; Collins, Leslie M.

2015-05-01

Ground-penetrating radar (GPR) technology has proven capable of detecting buried threats. The system relies on a binary classifier that is trained to distinguish between two classes: a target class, encompassing many types of buried threats and their components; and a nontarget class, which includes false alarms from the system prescreener. Typically, the training process involves a simple partition of the data into these two classes, which allows for straightforward application of standard classifiers. However, since training data is generally collected in fully controlled environments, it includes auxiliary information about each example, such as the specific type of threat, its purpose, its components, and its depth. Examples from the same specific or general type may be expected to exhibit similarities in their GPR data, whereas examples from different types may differ greatly. This research aims to leverage this additional information to improve overall classification performance by fusing classifier concepts for multiple groups, and to investigate whether structure in this information can be further utilized for transfer learning, such that the amount of expensive training data necessary to learn a new, previously-unseen target type may be reduced. Methods for accomplishing these goals are presented with results from a dataset containing a variety of target types.

Different levels of food restriction reveal genotype-specific differences in learning a visual discrimination task.

Directory of Open Access Journals (Sweden)

Kalina Makowiecki

Full Text Available In behavioural experiments, motivation to learn can be achieved using food rewards as positive reinforcement in food-restricted animals. Previous studies reduce animal weights to 80-90% of free-feeding body weight as the criterion for food restriction. However, effects of different degrees of food restriction on task performance have not been assessed. We compared learning task performance in mice food-restricted to 80 or 90% body weight (BW. We used adult wildtype (WT; C57Bl/6j and knockout (ephrin-A2⁻/⁻ mice, previously shown to have a reverse learning deficit. Mice were trained in a two-choice visual discrimination task with food reward as positive reinforcement. When mice reached criterion for one visual stimulus (80% correct in three consecutive 10 trial sets they began the reverse learning phase, where the rewarded stimulus was switched to the previously incorrect stimulus. For the initial learning and reverse phase of the task, mice at 90%BW took almost twice as many trials to reach criterion as mice at 80%BW. Furthermore, WT 80 and 90%BW groups significantly differed in percentage correct responses and learning strategy in the reverse learning phase, whereas no differences between weight restriction groups were observed in ephrin-A2⁻/⁻ mice. Most importantly, genotype-specific differences in reverse learning strategy were only detected in the 80%BW groups. Our results indicate that increased food restriction not only results in better performance and a shorter training period, but may also be necessary for revealing behavioural differences between experimental groups. This has important ethical and animal welfare implications when deciding extent of diet restriction in behavioural studies.

Label Information Guided Graph Construction for Semi-Supervised Learning.

Science.gov (United States)

Zhuang, Liansheng; Zhou, Zihan; Gao, Shenghua; Yin, Jingwen; Lin, Zhouchen; Ma, Yi

2017-09-01

In the literature, most existing graph-based semi-supervised learning methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph. In this paper, we argue that it is beneficial to consider the label information in the graph learning stage. Specifically, by enforcing the weight of edges between labeled samples of different classes to be zero, we explicitly incorporate the label information into the state-of-the-art graph learning methods, such as the low-rank representation (LRR), and propose a novel semi-supervised graph learning method called semi-supervised low-rank representation. This results in a convex optimization problem with linear constraints, which can be solved by the linearized alternating direction method. Though we take LRR as an example, our proposed method is in fact very general and can be applied to any self-representation graph learning methods. Experiment results on both synthetic and real data sets demonstrate that the proposed graph learning method can better capture the global geometric structure of the data, and therefore is more effective for semi-supervised learning tasks.

Computer-Assisted Mathematics Instruction for Students with Specific Learning Disability: A Review of the Literature

Science.gov (United States)

Stultz, Sherry L.

2017-01-01

This review was conducted to evaluate the current body of scholarly research regarding the use of computer-assisted instruction (CAI) to teach mathematics to students with specific learning disability (SLD). For many years, computers are utilized for educational purposes. However, the effectiveness of CAI for teaching mathematics to this specific…

How specific is specific self-efficacy?

DEFF Research Database (Denmark)

Nielsen, Tine; Makransky, Guido; Vang, Maria Louison

2017-01-01

academic learning self-efficacy (SAL-SE) and specific academic exam self-efficacy (SAE-SE), each scale being measurement invariant relative to age, Gender, admission method and specific course targeted. Furthermore, significant and relevant differences between the SAL-SE and SAE-SE scores dependent......Self-efficacy is an important and much used construct in psychology and social science studies. The validity of the measurements used is not always sufficiently evaluated. The aim was to evaluate the psychometric properties of the Danish translation of the self-efficacy subscale of The Motivated...... Strategies for Learning Questionnaire (MSLQ-SE) within a higher education context. Rasch measurement models were employed focusing on measurement invariance and dimensionality. Results with one students sample showed the MSLQ-SE to be not one, but two separate unidimensional subscales, measuring specific...

Effect of Non-specific HCN1 Blocker CsCl on Spatial Learning and Memory in Mouse

Institute of Scientific and Technical Information of China (English)

YU Xin; GUO Lianjun; YIN Guangfu; ZONG Xiangang; AI Yongxun

2006-01-01

It has been suggested that HCN1 is primarily expressed in hippocampus, however little is known about its effects on spatial learning and memory. In the present study, we investigated the effects of non-specific HCN1 blocker CsCl on spatial learning and memory by using Morris water maze and in situ hybridization in mice. The results showed CsCl 160 mg/kg ip for 4 days, and the mean escape latency was 34 s longer than that of normal control (P＜0.01). In hippocampal tissues, staining for the HCN1 mRNA was stronger in the DG and CA1 region of the hippocampus (P ＜0.05, P＜0.05, when CsCl-administration group was compared with normal group). Our results suggested that CsCl could significantly affect the spatial learning and memory in mice, and HCN channel is involved in the process of learning and memory.

Trans-algorithmic nature of learning in biological systems.

Science.gov (United States)

Shimansky, Yury P

2018-05-02

Learning ability is a vitally important, distinctive property of biological systems, which provides dynamic stability in non-stationary environments. Although several different types of learning have been successfully modeled using a universal computer, in general, learning cannot be described by an algorithm. In other words, algorithmic approach to describing the functioning of biological systems is not sufficient for adequate grasping of what is life. Since biosystems are parts of the physical world, one might hope that adding some physical mechanisms and principles to the concept of algorithm could provide extra possibilities for describing learning in its full generality. However, a straightforward approach to that through the so-called physical hypercomputation so far has not been successful. Here an alternative approach is proposed. Biosystems are described as achieving enumeration of possible physical compositions though random incremental modifications inflicted on them by active operating resources (AORs) in the environment. Biosystems learn through algorithmic regulation of the intensity of the above modifications according to a specific optimality criterion. From the perspective of external observers, biosystems move in the space of different algorithms driven by random modifications imposed by the environmental AORs. A particular algorithm is only a snapshot of that motion, while the motion itself is essentially trans-algorithmic. In this conceptual framework, death of unfit members of a population, for example, is viewed as a trans-algorithmic modification made in the population as a biosystem by environmental AORs. Numerous examples of AOR utilization in biosystems of different complexity, from viruses to multicellular organisms, are provided.

Adapting research-based curricula at Seattle Pacific University: Results on student learning

Science.gov (United States)

Close, Eleanor; Vokos, Stamatis; Lindberg, John; Seeley, Lane

2004-05-01

Seattle Pacific University is the recent recipient of a NSF CCLI grant to improve student learning in introductory physics and calculus courses. This talk will outline the goals of this collaborative project and present some initial results on student performance. Results from research-based assessments will be presented as well as specific examples of successes and challenges from mechanics and electricity and magnetism.

Creating an Innovative Learning Organization

Science.gov (United States)

Salisbury, Mark

2010-01-01

This article describes how to create an innovative learning (iLearning) organization. It begins by discussing the life cycle of knowledge in an organization, followed by a description of the theoretical foundation for iLearning. Next, the article presents an example of iLearning, followed by a description of the distributed nature of work, the…

Incremental concept learning with few training examples and hierarchical classification

NARCIS (Netherlands)

Bouma, H.; Eendebak, P.T.; Schutte, K.; Azzopardi, G.; Burghouts, G.J.

2015-01-01

Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible

Exploring Culture-Specific Learning Styles in Accounting Education

Science.gov (United States)

Sikkema, Seth E.; Sauerwein, Joshua A.

2015-01-01

Purpose: The purpose of this paper is to review whether culture affects accounting students' learning processes to identify practical guidance for accounting educators facing a culturally diverse classroom. In spite of a significant literature thread in accounting education on student learning, relatively, little emphasis has been placed on…

Teaching Sustainability Using an Active Learning Constructivist Approach: Discipline-Specific Case Studies in Higher Education

Directory of Open Access Journals (Sweden)

Maria Kalamas Hedden

2017-07-01

Full Text Available In this paper we present our rationale for using an active learning constructivist approach to teach sustainability-related topics in a higher education. To push the boundaries of ecological literacy, we also develop a theoretical model for sustainability knowledge co-creation. Drawing on the experiences of faculty at a major Southeastern University in the United States, we present case studies in architecture, engineering, geography, and marketing. Four Sustainability Faculty Fellows describe their discipline-specific case studies, all of which are project-based learning experiences, and include details regarding teaching and assessment. Easily replicated in other educational contexts, these case studies contribute to the advancement of sustainability education.

An Example of Using History of Mathematics in Classes

Science.gov (United States)

Goktepe, Sevda; Ozdemir, Ahmet Sukru

2013-01-01

In recent years, the topic of integrating history to mathematics lessons in teaching-learning processes has been frequently discussed among researchers. The main aim of this study is to present an example activity which enriched with history of mathematics and to take the views of students about teaching course in this way. In addition, to create…

The Effectiveness of Computer-Assisted Instruction for Teaching Mathematics to Students with Specific Learning Disability

Science.gov (United States)

Stultz, Sherry L.

2013-01-01

Using computers to teach students is not a new idea. Computers have been utilized for educational purposes for over 80 years. However, the effectiveness of these programs for teaching mathematics to students with specific learning disability is unclear. This study was undertaken to determine if computer-assisted instruction was as effective as…

Using Epistemic Network Analysis to understand core topics as planned learning objectives

DEFF Research Database (Denmark)

Allsopp, Benjamin Brink; Dreyøe, Jonas; Misfeldt, Morten

Epistemic Network Analysis is a tool developed by the epistemic games group at the University of Wisconsin Madison for tracking the relations between concepts in students discourse (Shaffer 2017). In our current work we are applying this tool to learning objectives in teachers digital preparation....... The danish mathematics curriculum is organised in six competencies and three topics. In the recently implemented learning platforms teacher choose which of the mathematical competencies that serves as objective for a specific lesson or teaching sequence. Hence learning objectives for lessons and teaching...... sequences are defining a network of competencies, where two competencies are closely related of they often are part of the same learning objective or teaching sequence. We are currently using Epistemic Network Analysis to study these networks. In the poster we will include examples of different networks...

Students' explanations in complex learning of disciplinary programming

Science.gov (United States)

Vieira, Camilo

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, engineers do not know how to exploit CSE affordances. This dissertation intends to introduce computational tools and methods contextualized within the Materials Science and Engineering curriculum. Considering that learning how to program is a complex task, the dissertation explores effective pedagogical practices that can support student disciplinary and computational learning. Two case studies will be evaluated to identify the characteristics of effective worked examples in the context of CSE. Specifically, this dissertation explores students explanations of these worked examples in two engineering courses with different levels of transparency: a programming course in materials science and engineering glass box and a thermodynamics course involving computational representations black box. Results from this study suggest that students benefit in different ways from writing in-code comments. These benefits include but are not limited to: connecting xv individual lines of code to the overall problem, getting familiar with the syntax, learning effective algorithm design strategies, and connecting computation with their discipline. Students in the glass box context generate higher quality explanations than students in the black box context. These explanations are related to students prior experiences. Specifically, students with

A Bayesian foundation for individual learning under uncertainty

Directory of Open Access Journals (Sweden)

Christoph eMathys

2011-05-01

Full Text Available Computational learning models are critical for understanding mechanisms of adaptive behavior. However, the two major current frameworks, reinforcement learning (RL and Bayesian learning, both have certain limitations. For example, many Bayesian models are agnostic of inter-individual variability and involve complicated integrals, making online learning difficult. Here, we introduce a generic hierarchical Bayesian framework for individual learning under multiple forms of uncertainty (e.g., environmental volatility and perceptual uncertainty. The model assumes Gaussian random walks of states at all but the first level, with the step size determined by the next higher level. The coupling between levels is controlled by parameters that shape the influence of uncertainty on learning in a subject-specific fashion. Using variational Bayes under a mean field approximation and a novel approximation to the posterior energy function, we derive trial-by-trial update equations which (i are analytical and extremely efficient, enabling real-time learning, (ii have a natural interpretation in terms of RL, and (iii contain parameters representing processes which play a key role in current theories of learning, e.g., precision-weighting of prediction error. These parameters allow for the expression of individual differences in learning and may relate to specific neuromodulatory mechanisms in the brain. Our model is very general: it can deal with both discrete and continuous states and equally accounts for deterministic and probabilistic relations between environmental events and perceptual states (i.e., situations with and without perceptual uncertainty. These properties are illustrated by simulations and analyses of empirical time series. Overall, our framework provides a novel foundation for understanding normal and pathological learning that contextualizes RL within a generic Bayesian scheme and thus connects it to principles of optimality from probability

A bayesian foundation for individual learning under uncertainty.

Science.gov (United States)

Mathys, Christoph; Daunizeau, Jean; Friston, Karl J; Stephan, Klaas E

2011-01-01

Computational learning models are critical for understanding mechanisms of adaptive behavior. However, the two major current frameworks, reinforcement learning (RL) and Bayesian learning, both have certain limitations. For example, many Bayesian models are agnostic of inter-individual variability and involve complicated integrals, making online learning difficult. Here, we introduce a generic hierarchical Bayesian framework for individual learning under multiple forms of uncertainty (e.g., environmental volatility and perceptual uncertainty). The model assumes Gaussian random walks of states at all but the first level, with the step size determined by the next highest level. The coupling between levels is controlled by parameters that shape the influence of uncertainty on learning in a subject-specific fashion. Using variational Bayes under a mean-field approximation and a novel approximation to the posterior energy function, we derive trial-by-trial update equations which (i) are analytical and extremely efficient, enabling real-time learning, (ii) have a natural interpretation in terms of RL, and (iii) contain parameters representing processes which play a key role in current theories of learning, e.g., precision-weighting of prediction error. These parameters allow for the expression of individual differences in learning and may relate to specific neuromodulatory mechanisms in the brain. Our model is very general: it can deal with both discrete and continuous states and equally accounts for deterministic and probabilistic relations between environmental events and perceptual states (i.e., situations with and without perceptual uncertainty). These properties are illustrated by simulations and analyses of empirical time series. Overall, our framework provides a novel foundation for understanding normal and pathological learning that contextualizes RL within a generic Bayesian scheme and thus connects it to principles of optimality from probability theory.

Machine learning in geosciences and remote sensing

Directory of Open Access Journals (Sweden)

David J. Lary

2016-01-01

Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

Cultural Conceptualisations in Learning English as an L2: Examples from Persian-Speaking Learners

Science.gov (United States)

Sharifian, Farzad

2013-01-01

Traditionally, many studies of second language acquisition (SLA) were based on the assumption that learning a new language mainly involves learning a set of grammatical rules, lexical items, and certain new sounds and sound combinations. However, for many second language learners, learning a second language may involve contact and interactions…

Extracurricular Activities and the Development of Social Skills in Children with Intellectual and Specific Learning Disabilities

Science.gov (United States)

Brooks, B. A.; Floyd, F.; Robins, D. L.; Chan, W. Y.

2015-01-01

Background: Children with intellectual disability and specific learning disabilities often lack age-appropriate social skills, which disrupts their social functioning. Because of the limited effectiveness of classroom mainstreaming and social skills training for these children, it is important to explore alternative opportunities for social skill…

Human reinforcement learning subdivides structured action spaces by learning effector-specific values

OpenAIRE

Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.

2009-01-01

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality...

Examples of safety culture practices

International Nuclear Information System (INIS)

1997-01-01

This report has been prepared to illustrate the concepts and principles of safety culture produced in 1991 by the International Safety Advisory Group as 75-INSAG-4. It provides a small selection of examples taken from a worldwide collection of safety performance evaluations (e.g. IAEA safety series, national regulatory inspections, utility audits and a plant assessments). These documented evaluations collectively provide a database of safety performance strengths and weakness, and related safety culture observations. The examples which have been selected for inclusion in this report are those which are considered worthy of special mention and which illustrate a specific attribute of safety culture given in 75-INSAG-4

Evaluating the Impact of Dyslexia Laws on the Identification of Specific Learning Disability and Dyslexia

Science.gov (United States)

Phillips, B. Anne Barber; Odegard, Timothy N.

2017-01-01

Dyslexia is a specific learning disability that impacts word reading accuracy and/or reading fluency. Over half of the states in the USA have passed legislation intended to promote better identification of individuals with dyslexia. To date, no study has been conducted to investigate the potential impact of state laws on the identification of…

Learning Perforce SCM

CERN Document Server

Cowham, Robert

2013-01-01

Learning Perforce SCM is written in a friendly and practical style with a focus on getting you started with Perforce efficiently and effectively. The book provides plenty of examples and screenshots to guide you through the process of learning.""Learning Perforce SCM"" is for anyone who wants to know how to adeptly manage software development activities using Perforce. Experience with other version control tools is a plus but is not required.

Parts of the Whole: Learn More, Learn Better

Directory of Open Access Journals (Sweden)

Dorothy Wallace

2012-01-01

Full Text Available Building on previous columns in Numeracy, this column analyzes various teaching techniques in terms of their ability to build cognitive schema, extend existing schema, reinforce learning, move mean understanding of a group of students, and reduce variance in understanding of a group. We offer a pedagogical cycle as an example of how to address multiple learning goals using common teaching methods.

Creating a blended learning module in an online master study programme in oncology.

Science.gov (United States)

Mayer, Benjamin; Ring, Christina; Muche, Rainer; Rothenbacher, Dietrich; Schmidt-Strassburger, Uta

2015-01-01

The medical faculty of Ulm University has launched the postgraduate master online study programme Advanced Oncology (AO) in 2010. We describe the challenges in developing an e-learning module using the example of a medical biometry course, focusing the implementation of the course material and our single-loop learning experience after the first students have finished and evaluated the lecture. Programme participants are qualified medical doctors and researchers in biomedical areas related to the field of oncology. The study programme provides the majority of lectures online via didactic videos accompanied by one-week attendance seminars. Supplementary learning materials include review articles, supportive reading material, multiple choice questions, and exercises for each unit. Lecture evaluations based on specific questions concerning learning environment and information learned, each measured on a five-point Likert scale. Lecture videos were implemented following the classical triad of the didactic process, using oncological examples from practice to teach. The online tutorial support offered to students was hardly used, thus we enhanced faculty presence during the face-to-face seminars. Lecture evaluations improved after revising the learning material on the basis of the first AO student cohort's comments. Developing and implementing an online study programme is challenging with respect of maximizing the information students learn due to limited opportunities for personal contact between lecturers and students. A more direct interaction of lecturers and students in a blended learning setting outperforms a mere web-based contact in terms of learning advantage and students' satisfaction, especially for complex methodological content.

Using developmental evaluation as a system of organizational learning: An example from San Francisco.

Science.gov (United States)

Shea, Jennifer; Taylor, Tory

2017-12-01

In the last 20 years, developmental evaluation has emerged as a promising approach to support organizational learning in emergent social programs. Through a continuous system of inquiry, reflection, and application of knowledge, developmental evaluation serves as a system of tools, methods, and guiding principles intended to support constructive organizational learning. However, missing from the developmental evaluation literature is a nuanced framework to guide evaluators in how to elevate the organizational practices and concepts most relevant for emergent programs. In this article, we describe and reflect on work we did to develop, pilot, and refine an integrated pilot framework. Drawing on established developmental evaluation inquiry frameworks and incorporating lessons learned from applying the pilot framework, we put forward the Evaluation-led Learning framework to help fill that gap and encourage others to implement and refine it. We posit that without explicitly incorporating the assessments at the foundation of the Evaluation-led Learning framework, developmental evaluation's ability to affect organizational learning in productive ways will likely be haphazard and limited. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fostering clinical reasoning in physiotherapy: Comparing the effects of concept map study and concept map completion after example study in novice and advanced learners

NARCIS (Netherlands)

K. Montpetit-Tourangeau (Katherine); J.-O. Dyer (Joseph-Omer); A. Hudon (Anne); Windsor, M. (Monica); B. Charlin (Bernard); S. Mamede (Silvia); T. van Gog (Tamara)

2017-01-01

textabstractBackground: Health profession learners can foster clinical reasoning by studying worked examples presenting fully worked out solutions to a clinical problem. It is possible to improve the learning effect of these worked examples by combining them with other learning activities based on

Inquiry-Based Learning in Teacher Education: A Primary Humanities Example

Science.gov (United States)

Preston, Lou; Harvie, Kate; Wallace, Heather

2015-01-01

Inquiry-based learning features strongly in the new Australian Humanities and Social Sciences curriculum and increasingly in primary school practice. Yet, there is little research into, and few exemplars of, inquiry approaches in the primary humanities context. In this article, we outline and explain the implementation of a place-based simulation…

Psycho-Educational Assessment of Specific Learning Disabilities: Views and Practices of Australian Psychologists and Guidance Counsellors

Science.gov (United States)

Meteyard, John D.; Gilmore, Linda

2015-01-01

This article reports an investigation of the views and practices of 203 Australian psychologists and guidance counsellors with respect to psycho-educational assessment of students with specific learning disabilities (SLDs). Results from an online survey indicated that practitioners draw upon a wide range of theoretical perspectives when…

Fostering Information Problem Solving Skills: Effects of Worked Examples and Learner Support

NARCIS (Netherlands)

Frerejean, Jimmy; Brand-Gruwel, Saskia; Kirschner, Paul A.

2013-01-01

Frerejean, J., Brand-Gruwel, S., & Kirschner, P. A. (2013, August). Fostering Information Problem Solving Skills: Effects of Worked Examples and Learner Support. Paper presented at the biennial EARLI Conference for Research in Learning and Instruction, Münich, Germany.

Transfer Learning for Class Imbalance Problems with Inadequate Data.

Science.gov (United States)

Al-Stouhi, Samir; Reddy, Chandan K

2016-07-01

A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

Teaching and learning community work online: can e-learning promote competences for future practice?

OpenAIRE

Larsen, Anne Karin; Visser-Rotgans, Rina; Hole, Grete Oline

2011-01-01

This article presents a case study of an online course in Community Work and the learning outcomes for an international group of students participating in the course. Examples from the process of, and results from the development of virtual-learning material are presented. Finally, the students' learning experience and competences achieved by the use of innovative learning material and ICT communication tools are presented.

Sleep spindle-related reactivation of category-specific cortical regions after learning face-scene associations

DEFF Research Database (Denmark)

Bergmann, Til O; Mölle, Matthias; Diedrichs, Jens

2012-01-01

Newly acquired declarative memory traces are believed to be reactivated during NonREM sleep to promote their hippocampo-neocortical transfer for long-term storage. Yet it remains a major challenge to unravel the underlying neuronal mechanisms. Using simultaneous electroencephalography (EEG......-coupled reactivation of brain regions representing the specific task stimuli was traced during subsequent NonREM sleep with EEG-informed fMRI. Relative to the control task, learning face-scene associations triggered a stronger combined activation of neocortical and hippocampal regions during subsequent sleep. Notably......) and functional magnetic resonance imaging (fMRI) recordings in humans, we show that sleep spindles play a key role in the reactivation of memory-related neocortical representations. On separate days, participants either learned face-scene associations or performed a visuomotor control task. Spindle...

Optimal medication dosing from suboptimal clinical examples: a deep reinforcement learning approach.

Science.gov (United States)

Nemati, Shamim; Ghassemi, Mohammad M; Clifford, Gari D

2016-08-01

Misdosing medications with sensitive therapeutic windows, such as heparin, can place patients at unnecessary risk, increase length of hospital stay, and lead to wasted hospital resources. In this work, we present a clinician-in-the-loop sequential decision making framework, which provides an individualized dosing policy adapted to each patient's evolving clinical phenotype. We employed retrospective data from the publicly available MIMIC II intensive care unit database, and developed a deep reinforcement learning algorithm that learns an optimal heparin dosing policy from sample dosing trails and their associated outcomes in large electronic medical records. Using separate training and testing datasets, our model was observed to be effective in proposing heparin doses that resulted in better expected outcomes than the clinical guidelines. Our results demonstrate that a sequential modeling approach, learned from retrospective data, could potentially be used at the bedside to derive individualized patient dosing policies.

[E-learning with journal articles].

Science.gov (United States)

Adriaanse, Marcel T; van Eijsden, Pieter; de Leeuw, Peter W

2014-01-01

E-learning is a popular method of continuous medical education (CME) which is becoming increasingly available to doctors. A specific form of E-learning is an online knowledge test accompanying a journal article. CME accreditation points can be obtained by reading an article and then answering test questions on it. This is a user-friendly form of CME which an increasing number of journals are offering as a service to their readers. The Dutch Journal of Medicine (NTvG) has been offering accredited tests to its readers since 2011. On comparison with international journals, a high standard has been set by the development of a test concept in which interpretation and reflection play integral roles. In the Dutch setting, the concept of the test was developed by professional bodies working closely together and it is a concept that is used as an example to other journals.

Interactive Multimedia Instruction for Training Self-Directed Learning Techniques

Science.gov (United States)

2016-06-01

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

Fostering clinical reasoning in physiotherapy : Comparing the effects of concept map study and concept map completion after example study in novice and advanced learners

NARCIS (Netherlands)

Montpetit-tourangeau, Katherine; Dyer, Joseph-omer; Hudon, Anne; Windsor, Monica; Charlin, Bernard; Mamede, Sílvia; Van Gog, Tamara

2017-01-01

Background: Health profession learners can foster clinical reasoning by studying worked examples presenting fully worked out solutions to a clinical problem. It is possible to improve the learning effect of these worked examples by combining them with other learning activities based on concept maps.

Intersections of Critical Systems Thinking and Community Based Participatory Research: A Learning Organization Example with the Autistic Community.

Science.gov (United States)

Raymaker, Dora M

2016-10-01

Critical systems thinking (CST) and community based participatory research (CBPR) are distinct approaches to inquiry which share a primary commitment to holism and human emancipation, as well as common grounding in critical theory and emancipatory and pragmatic philosophy. This paper explores their intersections and complements on a historical, philosophical, and theoretical level, and then proposes a hybrid approach achieved by applying CBPR's principles and considerations for operationalizing emancipatory practice to traditional systems thinking frameworks and practices. This hybrid approach is illustrated in practice with examples drawn from of the implementation of the learning organization model in an action research setting with the Autistic community. Our experience of being able to actively attend to, and continuously equalize, power relations within an organizational framework that otherwise has great potential for reinforcing power inequity suggests CBPR's principles and considerations for operationalizing emancipatory practice could be useful in CST settings, and CST's vocabulary, methods, and clarity around systems thinking concepts could be valuable to CBPR practioners.

Learning Spaces

CERN Document Server

Falmagne, Jean-Claude

2011-01-01

Learning spaces offer a rigorous mathematical foundation for practical systems of educational technology. Learning spaces generalize partially ordered sets and are special cases of knowledge spaces. The various structures are investigated from the standpoints of combinatorial properties and stochastic processes. Leaning spaces have become the essential structures to be used in assessing students' competence of various topics. A practical example is offered by ALEKS, a Web-based, artificially intelligent assessment and learning system in mathematics and other scholarly fields. At the heart of A

Do students with Down syndrome have a specific learning profile for reading?

Science.gov (United States)

Ratz, Christoph

2013-12-01

The present study assessed achieved reading stages of 190 school-aged children with Down syndrome (DS, age 6-20) in Bavaria, one of the most populated federal states in Germany. Teachers described the reading stages of their students in a questionnaire. The achieved stages of reading according to the developmental model of Frith are compared to a sample of 1419 students with intellectual disability (ID) regardless of etiology, but excluding DS; thereafter parallelized ID-groups were compared. Results of the questionnaire addressed to the students' teachers showed that 20.2% of the students with DS do not read at all, 7.6% read at a logographic stage, 49.4% at an alphabetic and 22.8% at an orthographic level. Alongside these findings among the whole sample, correlations are described concerning age, gender, IQ and sociocultural background. The students with DS are then compared to other students with ID with mixed etiologies. This comparison stresses the emphasis on the alphabetic level amongst students with DS. This emphasis also exists when DS and non-DS students are parallelized in groups of ID, thus showing that students with DS and severe ID are ahead in reading, but those with mild ID are behind. Knowledge about specific literacy attainment of students with DS is vital for planning instruction, for creating learning environments, and for formulating future fields of research. Especially students with DS need specific teaching which takes their impaired verbal short term memory into account, such as learning to read in syllables. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cognitive Clusters in Specific Learning Disorder

Science.gov (United States)

Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo

2018-01-01

The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the "Diagnostic and Statistical Manual of Mental Disorders." The…

The Power of Example

DEFF Research Database (Denmark)

Bülow, Anne Marie

2013-01-01

This paper suggests that for negotiation studies, the well-researched role of cognitive closure in decision-making should be supplemented with specific research on what sort of information is seized on as unambiguous, salient and easily processable by negotiators. A study of email negotiation...... is reported that suggests that negotiators seize on concrete examples as building blocks that produce immediate positive feedback and consequent utilization in establishing common ground....

Drugs + HIV, Learn the Link

Medline Plus

Full Text Available ... people on HAART (highly active antiretroviral therapy), for example, who continue to misuse drugs. The Learn the Link public service campaign is just one example of how NIDA continues to respond to the ...

How do Artists Learn and What Can Educators Learn from Them?

DEFF Research Database (Denmark)

Chemi, Tatiana; Jensen, Julie Borup

2014-01-01

Among scholars and practitioners interested in creative learning, many assumptions and even stereotypes are nurtured about artists’ creativity. The myth of the lone genius, for example, is neither close to artistic practices nor beneficial to education. We address the topic of artistic creativity......, looking at its relevance to educational settings. Through asking the question: how do artists create, learn and how can education learn from them, we have investigated and described professional artists’ creative and learning processes. In this article, we present findings from a qualitative research...

An Observation Tool for Comprehensive Pedagogy in Content and Language Integrated Learning (CLIL: Examples from Primary Education

Directory of Open Access Journals (Sweden)

Taina M Wewer

2017-08-01

Full Text Available This article on principles and practices in Content and Language Integrated Learning (CLIL is also applicable for general foreign and second language instruction. Since there is no ‘one size fits all’ CLIL pedagogy, the origin of the article lies in the need of educators to obtain and exchange ideas of and tools for actual classroom practices (Pérez Cañado, 2017, and ensure that all key features of CLIL are present in instruction. Although there are a few handbooks available for launching CLIL and adopting CLIL pedagogy (e.g., Coyle, Hood, & Marsh, 2010; Mehisto, Marsh, & Frigols, 2008, these provide principles and general examples of content-based instruction at higher levels of education rather than more detailed advice on how to operate in the beginning phases with young language learners, hence the focus on primary education. The Observation Tool for Effective CLIL Teaching created by de Graaff, Koopman, Anikina, and Gerrit (2007 was chosen as the starting point and was complemented with three additional fields that were not markedly included in the original model: cultural aspects, affects, and assessment.

Cognitive profiles in bilingual children born to immigrant parents and Italian monolingual native children with specific learning disorders

Directory of Open Access Journals (Sweden)

Riva A

2016-12-01

Full Text Available Anna Riva, Renata Nacinovich, Nadia Bertuletti, Valentina Montrasi, Sara Marchetti, Francesca Neri, Monica Bomba Child and Adolescent Mental Health Department, University of Milan Bicocca, San Gerardo Hospital, Monza, Italy Purpose: The aim of this study is to compare the Wechsler Intelligence Scale for Children® – fourth edition IV (WISC IV intellectual profile of two groups of children with specific learning disorder, a group of bilingual children and a group of monolingual Italian children, in order to identify possible significant differences between them. Patients and methods: A group of 48 bilingual children and a group of 48 Italian monolingual children were included in this study. A preliminary comparison showed the homogeneity of the two groups regarding learning disorder typology and sociodemographic characteristics (age at WISC IV assessment, sex and years of education in Italy with the exception of socioeconomic status. Socioeconomic status was then used as a covariate in the analysis. Results: Even if the two groups were comparable in specific learning disorder severity and, in particular, in the text comprehension performance, our findings showed that the WISC IV performances of the bilingual group were significantly worse than the Italian group in Full Scale Intelligence Quotient (P=0.03, in General Ability Index (P=0.03, in Working Memory Index (P=0.009 and in some subtests and clusters requiring advanced linguistic abilities. Conclusion: These results support the hypothesis of a weakness in metalinguistic abilities in bilingual children with specific learning disorders than monolinguals. If confirmed, this result must be considered in the rehabilitation treatment. Keywords: children, bilingualism, WISC IV, SLD

Statistical learning in high energy and astrophysics

International Nuclear Information System (INIS)

Zimmermann, J.

2005-01-01

This thesis studies the performance of statistical learning methods in high energy and astrophysics where they have become a standard tool in physics analysis. They are used to perform complex classification or regression by intelligent pattern recognition. This kind of artificial intelligence is achieved by the principle ''learning from examples'': The examples describe the relationship between detector events and their classification. The application of statistical learning methods is either motivated by the lack of knowledge about this relationship or by tight time restrictions. In the first case learning from examples is the only possibility since no theory is available which would allow to build an algorithm in the classical way. In the second case a classical algorithm exists but is too slow to cope with the time restrictions. It is therefore replaced by a pattern recognition machine which implements a fast statistical learning method. But even in applications where some kind of classical algorithm had done a good job, statistical learning methods convinced by their remarkable performance. This thesis gives an introduction to statistical learning methods and how they are applied correctly in physics analysis. Their flexibility and high performance will be discussed by showing intriguing results from high energy and astrophysics. These include the development of highly efficient triggers, powerful purification of event samples and exact reconstruction of hidden event parameters. The presented studies also show typical problems in the application of statistical learning methods. They should be only second choice in all cases where an algorithm based on prior knowledge exists. Some examples in physics analyses are found where these methods are not used in the right way leading either to wrong predictions or bad performance. Physicists also often hesitate to profit from these methods because they fear that statistical learning methods cannot be controlled in a

Statistical learning in high energy and astrophysics

Energy Technology Data Exchange (ETDEWEB)

Zimmermann, J.

2005-06-16

This thesis studies the performance of statistical learning methods in high energy and astrophysics where they have become a standard tool in physics analysis. They are used to perform complex classification or regression by intelligent pattern recognition. This kind of artificial intelligence is achieved by the principle ''learning from examples'': The examples describe the relationship between detector events and their classification. The application of statistical learning methods is either motivated by the lack of knowledge about this relationship or by tight time restrictions. In the first case learning from examples is the only possibility since no theory is available which would allow to build an algorithm in the classical way. In the second case a classical algorithm exists but is too slow to cope with the time restrictions. It is therefore replaced by a pattern recognition machine which implements a fast statistical learning method. But even in applications where some kind of classical algorithm had done a good job, statistical learning methods convinced by their remarkable performance. This thesis gives an introduction to statistical learning methods and how they are applied correctly in physics analysis. Their flexibility and high performance will be discussed by showing intriguing results from high energy and astrophysics. These include the development of highly efficient triggers, powerful purification of event samples and exact reconstruction of hidden event parameters. The presented studies also show typical problems in the application of statistical learning methods. They should be only second choice in all cases where an algorithm based on prior knowledge exists. Some examples in physics analyses are found where these methods are not used in the right way leading either to wrong predictions or bad performance. Physicists also often hesitate to profit from these methods because they fear that statistical learning methods cannot

A study of concept-based similarity approaches for recommending program examples

Science.gov (United States)

Hosseini, Roya; Brusilovsky, Peter

2017-07-01

This paper investigates a range of concept-based example recommendation approaches that we developed to provide example-based problem-solving support in the domain of programming. The goal of these approaches is to offer students a set of most relevant remedial examples when they have trouble solving a code comprehension problem where students examine a program code to determine its output or the final value of a variable. In this paper, we use the ideas of semantic-level similarity-based linking developed in the area of intelligent hypertext to generate examples for the given problem. To determine the best-performing approach, we explored two groups of similarity approaches for selecting examples: non-structural approaches focusing on examples that are similar to the problem in terms of concept coverage and structural approaches focusing on examples that are similar to the problem by the structure of the content. We also explored the value of personalized example recommendation based on student's knowledge levels and learning goal of the exercise. The paper presents concept-based similarity approaches that we developed, explains the data collection studies and reports the result of comparative analysis. The results of our analysis showed better ranking performance of the personalized structural variant of cosine similarity approach.

e-Learning for Lifelong Learning in Denmark

DEFF Research Database (Denmark)

Buhl, Mie; Andreasen, Lars Birch

2010-01-01

The chapter on 'e-Learning for Lifelong Learning in Denmark' is part of an international White Paper, focusing on educational systems, describing status and characteristics and highlighting specific cases of e-learning and of lifelong learning....

On Learning Ring-Sum-Expansions

DEFF Research Database (Denmark)

Fischer, Paul; Simon, H. -U.

1992-01-01

The problem of learning ring-sum-expansions from examples is studied. Ring-sum-expansions (RSE) are representations of Boolean functions over the base {#123;small infinum, (+), 1}#125;, which reflect arithmetic operations in GF(2). k-RSE is the class of ring-sum-expansions containing only monomials...... of length at most k:. term-RSE is the class of ring-sum-expansions having at most I: monomials. It is shown that k-RSE, k>or=1, is learnable while k-term-RSE, k>2, is not learnable if RPnot=NP. Without using a complexity-theoretical hypothesis, it is proven that k-RSE, k>or=1, and k-term-RSE, k>or=2 cannot...... be learned from positive (negative) examples alone. However, if the restriction that the hypothesis which is output by the learning algorithm is also a k-RSE is suspended, then k-RSE is learnable from positive (negative) examples only. Moreover, it is proved that 2-term-RSE is learnable by a conjunction...

Evaluation of Contribution of Local Newspapers to Lifelong Learning (Example of Bartin Province)

Science.gov (United States)

Çuhadar, Elif; Ünal, Fatma

2018-01-01

In this study, while the definition of informal education, which displays the main features of lifelong learning, is made, it is also attempted to identify the contributions of the local newspapers, through which the society can reach its own unique and necessary information, to the lifelong learning of their readers. In the research, within this…

Organisational learning is crystallised into artefacts

DEFF Research Database (Denmark)

Bertelsen, Olav Wedege

1996-01-01

In this note I understand organisational learning in terms of manifest crystallisation of collective experience into artefacts, and I attempt to integrate an engineering and an emancipatory perspective. A Danish music festival serves as an example.......In this note I understand organisational learning in terms of manifest crystallisation of collective experience into artefacts, and I attempt to integrate an engineering and an emancipatory perspective. A Danish music festival serves as an example....

Non-adjacent dependency learning in Cantonese-speaking\\ud children with and without a history of specific language\\ud impairment

OpenAIRE

Iao, L-S; Ng, LY; Wong, AMY; Lee, OT

2017-01-01

Purpose: This study investigated non-adjacent dependency learning in Cantonese-speaking children with and without a history of Specific Language Impairment (SLI) in an artificial linguistic context.\\ud \\ud Method: Sixteen Cantonese-speaking children with SLI history and 16 Cantonese-speaking children with typical language development (TLD) were tested with a non-adjacent dependency learning task using artificial languages that mimic Cantonese.\\ud \\ud Results: Children with TLD performed above...

Machine learning with quantum relative entropy

International Nuclear Information System (INIS)

Tsuda, Koji

2009-01-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Machine learning with quantum relative entropy

Energy Technology Data Exchange (ETDEWEB)

Tsuda, Koji [Max Planck Institute for Biological Cybernetics, Spemannstr. 38, Tuebingen, 72076 (Germany)], E-mail: koji.tsuda@tuebingen.mpg.de

2009-12-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Engaging Digital Natives through Social Learning

Directory of Open Access Journals (Sweden)

Nina Sarkar

2017-04-01

Full Text Available Digital natives account for a substantial portion of the total enrollment in higher education. This calls for significant educational reforms because traditional education systems do not cater to the needs and interests of digital natives. The most effective way that both students and instructors can benefit from this paradigm shift is to integrate technology that is appropriate to the cognitive learning patterns of the digital natives into the curriculum. This paper builds upon previous research in technology/personality theory and specifically attempts to provide examples of technology that will address the instructional needs of digital natives. Further this paper provides empirical evidence of the impact of technology integration on the learning outcomes of digital natives. In this study, the authors explored the impact of targeted technology on academic performance in three businesses courses. Three functional technologies were used by the authors to build engaging course content, efficiently manage course content, and to interact with digital native students. This study found that these technologies can assist digital natives in the learning process and lead to better academic performance.

A Smart Web-Based Geospatial Data Discovery System with Oceanographic Data as an Example

Directory of Open Access Journals (Sweden)

Yongyao Jiang

2018-02-01

Full Text Available Discovering and accessing geospatial data presents a significant challenge for the Earth sciences community as massive amounts of data are being produced on a daily basis. In this article, we report a smart web-based geospatial data discovery system that mines and utilizes data relevancy from metadata user behavior. Specifically, (1 the system enables semantic query expansion and suggestion to assist users in finding more relevant data; (2 machine-learned ranking is utilized to provide the optimal search ranking based on a number of identified ranking features that can reflect users’ search preferences; (3 a hybrid recommendation module is designed to allow users to discover related data considering metadata attributes and user behavior; (4 an integrated graphic user interface design is developed to quickly and intuitively guide data consumers to the appropriate data resources. As a proof of concept, we focus on a well-defined domain-oceanography and use oceanographic data discovery as an example. Experiments and a search example show that the proposed system can improve the scientific community’s data search experience by providing query expansion, suggestion, better search ranking, and data recommendation via a user-friendly interface.

Learning unlearnable problems with perceptrons

Science.gov (United States)

Watkin, Timothy L. H.; Rau, Albrecht

1992-03-01

We study how well perceptrons learn to solve problems for which there is no perfect answer (the usual case), taking as examples a rule with a threshold, a rule in which the answer is not a monotonic function of the overlap between question and teacher, and a rule with many teachers (a ``hard'' unlearnable problem). In general there is a tendency for first-order transitions, even using spherical perceptrons, as networks compromise between conflicting requirements. Some existing learning schemes fail completely-occasionally even finding the worst possible solution; others are more successful. High-temperature learning seems more satisfactory than zero-temperature algorithms and avoids ``overlearning'' and ``overfitting,'' but care must be taken to avoid ``trapping'' in spurious free-energy minima. For some rules examples alone are not enough to learn from, and some prior information is required.

An Example of Learning about Plastics and Their Evaluation as a Contribution to Education for Sustainable Development in Secondary School Chemistry Teaching