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Sample records for computational learning theory

  1. Computer-based teaching module design: principles derived from learning theories.

    Science.gov (United States)

    Lau, K H Vincent

    2014-03-01

    The computer-based teaching module (CBTM), which has recently gained prominence in medical education, is a teaching format in which a multimedia program serves as a single source for knowledge acquisition rather than playing an adjunctive role as it does in computer-assisted learning (CAL). Despite empirical validation in the past decade, there is limited research into the optimisation of CBTM design. This review aims to summarise research in classic and modern multimedia-specific learning theories applied to computer learning, and to collapse the findings into a set of design principles to guide the development of CBTMs. Scopus was searched for: (i) studies of classic cognitivism, constructivism and behaviourism theories (search terms: 'cognitive theory' OR 'constructivism theory' OR 'behaviourism theory' AND 'e-learning' OR 'web-based learning') and their sub-theories applied to computer learning, and (ii) recent studies of modern learning theories applied to computer learning (search terms: 'learning theory' AND 'e-learning' OR 'web-based learning') for articles published between 1990 and 2012. The first search identified 29 studies, dominated in topic by the cognitive load, elaboration and scaffolding theories. The second search identified 139 studies, with diverse topics in connectivism, discovery and technical scaffolding. Based on their relative representation in the literature, the applications of these theories were collapsed into a list of CBTM design principles. Ten principles were identified and categorised into three levels of design: the global level (managing objectives, framing, minimising technical load); the rhetoric level (optimising modality, making modality explicit, scaffolding, elaboration, spaced repeating), and the detail level (managing text, managing devices). This review examined the literature in the application of learning theories to CAL to develop a set of principles that guide CBTM design. Further research will enable educators to

  2. Learning theories in computer-assisted foreign language acquisition

    OpenAIRE

    Baeva, D.

    2013-01-01

    This paper reviews the learning theories, focusing to the strong interest in technology use for language learning. It is important to look at how technology has been used in the field thus far. The goals of this review are to understand how computers have been used in the past years to support foreign language learning, and to explore any research evidence with regards to how computer technology can enhance language skills acquisition

  3. Optimizing Computer Assisted Instruction By Applying Principles of Learning Theory.

    Science.gov (United States)

    Edwards, Thomas O.

    The development of learning theory and its application to computer-assisted instruction (CAI) are described. Among the early theoretical constructs thought to be important are E. L. Thorndike's concept of learning connectisms, Neal Miller's theory of motivation, and B. F. Skinner's theory of operant conditioning. Early devices incorporating those…

  4. En retorisk forståelsesramme for Computer Supported Collaborative Learning (A Rhetorical Theory on Computer Supported Collaborative Learning)

    DEFF Research Database (Denmark)

    Harlung, Asger

    2003-01-01

    The dissertation explores the potential of rhetorical theories for understanding, analyzing, or planning communication and learning processes, and for integrating the digitized contexts and human interaction and communication proccesses in a single theoretical framework. Based on Cicero's rhetori...... applied to two empirical case studies of Master programs, the dissertation develops and presents a new theory on Computer Supported Collaborative Learning (CSCL).......The dissertation explores the potential of rhetorical theories for understanding, analyzing, or planning communication and learning processes, and for integrating the digitized contexts and human interaction and communication proccesses in a single theoretical framework. Based on Cicero's rhetoric...

  5. Theory of computation

    CERN Document Server

    Tourlakis, George

    2012-01-01

    Learn the skills and acquire the intuition to assess the theoretical limitations of computer programming Offering an accessible approach to the topic, Theory of Computation focuses on the metatheory of computing and the theoretical boundaries between what various computational models can do and not do—from the most general model, the URM (Unbounded Register Machines), to the finite automaton. A wealth of programming-like examples and easy-to-follow explanations build the general theory gradually, which guides readers through the modeling and mathematical analysis of computational pheno

  6. Bridging Theory and Practice: Developing Guidelines to Facilitate the Design of Computer-based Learning Environments

    Directory of Open Access Journals (Sweden)

    Lisa D. Young

    2003-10-01

    Full Text Available Abstract. The design of computer-based learning environments has undergone a paradigm shift; moving students away from instruction that was considered to promote technical rationality grounded in objectivism, to the application of computers to create cognitive tools utilized in constructivist environments. The goal of the resulting computer-based learning environment design principles is to have students learn with technology, rather than from technology. This paper reviews the general constructivist theory that has guided the development of these environments, and offers suggestions for the adaptation of modest, generic guidelines, not mandated principles, that can be flexibly applied and allow for the expression of true constructivist ideals in online learning environments.

  7. Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

    Science.gov (United States)

    Gopnik, Alison; Wellman, Henry M

    2012-11-01

    We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

  8. Reconstructing constructivism: Causal models, Bayesian learning mechanisms and the theory theory

    OpenAIRE

    Gopnik, Alison; Wellman, Henry M.

    2012-01-01

    We propose a new version of the “theory theory” grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and non-technical way, and review an extensive but ...

  9. 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.

  10. Reconstructing Constructivism: Causal Models, Bayesian Learning Mechanisms, and the Theory Theory

    Science.gov (United States)

    Gopnik, Alison; Wellman, Henry M.

    2012-01-01

    We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework…

  11. Game Engagement Theory and Adult Learning

    Science.gov (United States)

    Whitton, Nicola

    2011-01-01

    One of the benefits of computer game-based learning is the ability of certain types of game to engage and motivate learners. However, theories of learning and engagement, particularly in the sphere of higher education, typically fail to consider gaming engagement theory. In this article, the author examines the principles of engagement from games…

  12. Computer-based theory of strategies

    Energy Technology Data Exchange (ETDEWEB)

    Findler, N V

    1983-01-01

    Some of the objectives and working tools of a new area of study, tentatively called theory of strategies, are described. It is based on the methodology of artificial intelligence, decision theory, operations research and digital gaming. The latter refers to computing activity that incorporates model building, simulation and learning programs in conflict situations. Three long-term projects which aim at automatically analyzing and synthesizing strategies are discussed. 27 references.

  13. Assessment of (Computer-Supported) Collaborative Learning

    Science.gov (United States)

    Strijbos, J. -W.

    2011-01-01

    Within the (Computer-Supported) Collaborative Learning (CS)CL research community, there has been an extensive dialogue on theories and perspectives on learning from collaboration, approaches to scaffold (script) the collaborative process, and most recently research methodology. In contrast, the issue of assessment of collaborative learning has…

  14. Computer-Supported Collaborative Learning in Higher Education

    Science.gov (United States)

    Roberts, Tim, Ed.

    2005-01-01

    "Computer-Supported Collaborative Learning in Higher Education" provides a resource for researchers and practitioners in the area of computer-supported collaborative learning (also known as CSCL); particularly those working within a tertiary education environment. It includes articles of relevance to those interested in both theory and practice in…

  15. Introducing Computers to Kindergarten Children Based on Vygotsky's Theory about Socio-Cultural Learning: The Greek Perspective.

    Science.gov (United States)

    Pange, Jenny; Kontozisis, Dimitrios

    2001-01-01

    Greek preschoolers' level of knowledge about computers was examined as they participated in a classroom project to introduce them to new technologies. The project was based on Vygotsky's theory of socio-cultural learning. Findings suggest that this approach is a successful way to introduce new technologies to young children. (JPB)

  16. Learning Theories Applied to Teaching Technology: Constructivism versus Behavioral Theory for Instructing Multimedia Software Programs

    Science.gov (United States)

    Reed, Cajah S.

    2012-01-01

    This study sought to find evidence for a beneficial learning theory to teach computer software programs. Additionally, software was analyzed for each learning theory's applicability to resolve whether certain software requires a specific method of education. The results are meant to give educators more effective teaching tools, so students…

  17. Too good to be true? Ideomotor Theory from a computational perspective

    Directory of Open Access Journals (Sweden)

    Oliver eHerbort

    2012-11-01

    Full Text Available In recent years, Ideomotor Theory has regained widespread attention and sparked the development of a number of theories on goal-directed behavior and learning. However, there are two issues with previous studies’ use of Ideomotor Theory. Although Ideomotor Theory is seen as very general, it is often studied in settings that are considerably more simplistic than most natural situations. Moreover, Ideomotor Theory’s claim that effect anticipations directly trigger actions and that action-effect learning is based on the formation of direct action-effect associations is hard to address empirically. We address these points from a computational perspective. A simple computational model of Ideomotor Theory was tested in tasks with different degrees of complexity. The model evaluation showed that Ideomotor Theory is a computationally feasible approach for understanding efficient action-effect learning for goal-directed behavior if the following preconditions are met: 1 The range of potential actions and effects has to be restricted. 2 Effects have to follow actions within a short time window. 3 Actions have to be simple and may not require sequencing. The first two preconditions also limit human performance and thus support Ideomotor Theory. The last precondition can be circumvented by extending the model with more complex, indirect action generation processes. In conclusion, we suggest that Ideomotor Theory offers a comprehensive framework to understand action-effect learning. However, we also suggest that additional processes may mediate the conversion of effect anticipations into actions in many situations.

  18. TEACHING AND LEARNING METHODOLOGIES SUPPORTED BY ICT APPLIED IN COMPUTER SCIENCE

    Directory of Open Access Journals (Sweden)

    Jose CAPACHO

    2016-04-01

    Full Text Available The main objective of this paper is to show a set of new methodologies applied in the teaching of Computer Science using ICT. The methodologies are framed in the conceptual basis of the following sciences: Psychology, Education and Computer Science. The theoretical framework of the research is supported by Behavioral Theory, Gestalt Theory. Genetic-Cognitive Psychology Theory and Dialectics Psychology. Based on the theoretical framework the following methodologies were developed: Game Theory, Constructivist Approach, Personalized Teaching, Problem Solving, Cooperative Collaborative learning, Learning projects using ICT. These methodologies were applied to the teaching learning process during the Algorithms and Complexity – A&C course, which belongs to the area of ​​Computer Science. The course develops the concepts of Computers, Complexity and Intractability, Recurrence Equations, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Shortest Path Problem and Graph Theory. The main value of the research is the theoretical support of the methodologies and their application supported by ICT using learning objects. The course aforementioned was built on the Blackboard platform evaluating the operation of methodologies. The results of the evaluation are presented for each of them, showing the learning outcomes achieved by students, which verifies that methodologies are functional.

  19. From the social learning theory to a social learning algorithm for global optimization

    OpenAIRE

    Gong, Yue-Jiao; Zhang, Jun; Li, Yun

    2014-01-01

    Traditionally, the Evolutionary Computation (EC) paradigm is inspired by Darwinian evolution or the swarm intelligence of animals. Bandura's Social Learning Theory pointed out that the social learning behavior of humans indicates a high level of intelligence in nature. We found that such intelligence of human society can be implemented by numerical computing and be utilized in computational algorithms for solving optimization problems. In this paper, we design a novel and generic optimization...

  20. The Effect of Computer Game-Based Learning on FL Vocabulary Transferability

    Science.gov (United States)

    Franciosi, Stephan J.

    2017-01-01

    In theory, computer game-based learning can support several vocabulary learning affordances that have been identified in the foreign language learning research. In the observable evidence, learning with computer games has been shown to improve performance on vocabulary recall tests. However, while simple recall can be a sign of learning,…

  1. Practice of Connectivism As Learning Theory: Enhancing Learning Process Through Social Networking Site (Facebook

    Directory of Open Access Journals (Sweden)

    Fahriye Altınay Aksal

    2013-12-01

    Full Text Available The impact of the digital age within learning and social interaction has been growing rapidly. The realm of digital age and computer mediated communication requires reconsidering instruction based on collaborative interactive learning process and socio-contextual experience for learning. Social networking sites such as facebook can help create group space for digital dialogue to inform, question and challenge within a frame of connectivism as learning theory within the digital age. The aim of this study is to elaborate the practice of connectivism as learning theory in terms of internship course. Facebook group space provided social learning platform for dialogue and negotiation beside the classroom learning and teaching process in this study. The 35 internship students provided self-reports within a frame of this qualitative research. This showed how principles of theory practiced and how this theory and facebook group space contribute learning, selfleadership, decision making and reflection skills. As the research reflects a practice of new theory based on action research, learning is not individualistic attempt in the digital age as regards the debate on learning in digital age within a frame of connectivism

  2. Why formal learning theory matters for cognitive science.

    Science.gov (United States)

    Fulop, Sean; Chater, Nick

    2013-01-01

    This article reviews a number of different areas in the foundations of formal learning theory. After outlining the general framework for formal models of learning, the Bayesian approach to learning is summarized. This leads to a discussion of Solomonoff's Universal Prior Distribution for Bayesian learning. Gold's model of identification in the limit is also outlined. We next discuss a number of aspects of learning theory raised in contributed papers, related to both computational and representational complexity. The article concludes with a description of how semi-supervised learning can be applied to the study of cognitive learning models. Throughout this overview, the specific points raised by our contributing authors are connected to the models and methods under review. Copyright © 2013 Cognitive Science Society, Inc.

  3. An E-learning System based on Affective Computing

    Science.gov (United States)

    Duo, Sun; Song, Lu Xue

    In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

  4. Cognitive Theory of Multimedia Learning, Instructional Design Principles, and Students with Learning Disabilities in Computer-Based and Online Learning Environments

    Science.gov (United States)

    Greer, Diana L.; Crutchfield, Stephen A.; Woods, Kari L.

    2013-01-01

    Struggling learners and students with Learning Disabilities often exhibit unique cognitive processing and working memory characteristics that may not align with instructional design principles developed with typically developing learners. This paper explains the Cognitive Theory of Multimedia Learning and underlying Cognitive Load Theory, and…

  5. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  6. Computational invariant theory

    CERN Document Server

    Derksen, Harm

    2015-01-01

    This book is about the computational aspects of invariant theory. Of central interest is the question how the invariant ring of a given group action can be calculated. Algorithms for this purpose form the main pillars around which the book is built. There are two introductory chapters, one on Gröbner basis methods and one on the basic concepts of invariant theory, which prepare the ground for the algorithms. Then algorithms for computing invariants of finite and reductive groups are discussed. Particular emphasis lies on interrelations between structural properties of invariant rings and computational methods. Finally, the book contains a chapter on applications of invariant theory, covering fields as disparate as graph theory, coding theory, dynamical systems, and computer vision. The book is intended for postgraduate students as well as researchers in geometry, computer algebra, and, of course, invariant theory. The text is enriched with numerous explicit examples which illustrate the theory and should be ...

  7. Deep learning for computational chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Garrett B. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Hodas, Nathan O. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Vishnu, Abhinav [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354

    2017-03-08

    The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.

  8. Deep learning for computational chemistry.

    Science.gov (United States)

    Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

    2017-06-15

    The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  9. Machine learning in radiation oncology theory and applications

    CERN Document Server

    El Naqa, Issam; Murphy, Martin J

    2015-01-01

    ​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided rad

  10. Metacognitive Load--Useful, or Extraneous Concept? Metacognitive and Self-Regulatory Demands in Computer-Based Learning

    Science.gov (United States)

    Schwonke, Rolf

    2015-01-01

    Instructional design theories such as the "cognitive load theory" (CLT) or the "cognitive theory of multimedia learning" (CTML) explain learning difficulties in (computer-based) learning usually as a result of design deficiencies that hinder effective schema construction. However, learners often struggle even in well-designed…

  11. An affective computing algorithm based on temperament type in E-Learning

    Directory of Open Access Journals (Sweden)

    WANG Biyun

    2013-02-01

    Full Text Available This paper extracts five emotional features according to the emotions that may affect in learning,and introduces psychological theory to generate emotional susceptibility matrix and to draw personalized emotion vector by different learners' temperament type vectors,which all reflect the emotional state of the learners more realistically.This paper also recommends learners of different emotions and emotional intensity to learn the knowledge of different levels of difficulty,making learning more humane.Temperament type is a temperament doctrine evolved based on the Hippocratic humoral theory and can be a good expression of human personality foundation.Temperament type has been introduced into affective computing in the E-Learning in this paper so that computer can be better on the classification of the learner's personality and learning state and realistically be individualized.

  12. Seven Affordances of Computer-Supported Collaborative Learning: How to Support Collaborative Learning? How Can Technologies Help?

    Science.gov (United States)

    Jeong, Heisawn; Hmelo-Silver, Cindy E.

    2016-01-01

    This article proposes 7 core affordances of technology for collaborative learning based on theories of collaborative learning and CSCL (Computer-Supported Collaborative Learning) practices. Technology affords learner opportunities to (1) engage in a joint task, (2) communicate, (3) share resources, (4) engage in productive collaborative learning…

  13. Learning Theory Foundations of Simulation-Based Mastery Learning.

    Science.gov (United States)

    McGaghie, William C; Harris, Ilene B

    2018-06-01

    Simulation-based mastery learning (SBML), like all education interventions, has learning theory foundations. Recognition and comprehension of SBML learning theory foundations are essential for thoughtful education program development, research, and scholarship. We begin with a description of SBML followed by a section on the importance of learning theory foundations to shape and direct SBML education and research. We then discuss three principal learning theory conceptual frameworks that are associated with SBML-behavioral, constructivist, social cognitive-and their contributions to SBML thought and practice. We then discuss how the three learning theory frameworks converge in the course of planning, conducting, and evaluating SBML education programs in the health professions. Convergence of these learning theory frameworks is illustrated by a description of an SBML education and research program in advanced cardiac life support. We conclude with a brief coda.

  14. 3rd International Conference on Frontiers of Intelligent Computing : Theory and Applications

    CERN Document Server

    Biswal, Bhabendra; Udgata, Siba; Mandal, JK

    2015-01-01

    Volume 1 contains 95 papers presented at FICTA 2014: Third International Conference on Frontiers in Intelligent Computing: Theory and Applications. The conference was held during 14-15, November, 2014 at Bhubaneswar, Odisha, India.  This volume contains papers mainly focused on Data Warehousing and Mining, Machine Learning, Mobile and Ubiquitous Computing, AI, E-commerce & Distributed Computing and Soft Computing, Evolutionary Computing, Bio-inspired Computing and its Applications.

  15. Errors and Intelligence in Computer-Assisted Language Learning: Parsers and Pedagogues. Routledge Studies in Computer Assisted Language Learning

    Science.gov (United States)

    Heift, Trude; Schulze, Mathias

    2012-01-01

    This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate…

  16. Neural computation and the computational theory of cognition.

    Science.gov (United States)

    Piccinini, Gualtiero; Bahar, Sonya

    2013-04-01

    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism-neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. Copyright © 2012 Cognitive Science Society, Inc.

  17. Complexity Theory and CALL Curriculum in Foreign Language Learning

    Directory of Open Access Journals (Sweden)

    Hassan Soleimani

    2014-05-01

    Full Text Available Complexity theory literally indicates the complexity of a system, behavior, or a process. Its connotative meaning, while, implies dynamism, openness, sensitivity to initial conditions and feedback, and adaptation properties of a system. Regarding English as a Foreign/ Second Language (EFL/ESL this theory emphasizes on the complexity of the process of teaching and learning, including all the properties of a complex system. The purpose of the current study is to discuss the role of CALL as a modern technology in simplifying the process of teaching and learning a new language while integrating into the complexity theory. Nonetheless, the findings obtained from reviewing previously conducted studies in this field confirmed the usefulness of CALL curriculum in EFL/ESL contexts. These findings can also provide pedagogical implications for employing computer as an effective teaching and learning tool.

  18. Dynasting Theory: Lessons in learning grounded theory

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    Johnben Teik-Cheok Loy, MBA, MTS, Ph.D.

    2011-06-01

    Full Text Available This article captures the key learning lessons gleaned from the author’s experience learning and developing a grounded theory for his doctoral dissertation using the classic methodology as conceived by Barney Glaser. The theory was developed through data gathered on founders and successors of Malaysian Chinese family-own businesses. The main concern for Malaysian Chinese family businesses emerged as dynasting . the building, maintaining, and growing the power and resources of the business within the family lineage. The core category emerged as dynasting across cultures, where founders and successors struggle to transition from traditional Chinese to hybrid cultural and modernized forms of family business from one generation to the next. The key learning lessons were categorized under five headings: (a sorting through different versions of grounded theory, (b educating and managing research stakeholders, (c embracing experiential learning, (d discovering the core category: grounded intuition, and (e recognizing limitations and possibilities.Keywords: grounded theory, learning, dynasting, family business, Chinese

  19. Constructivism, the so-called semantic learning theories, and situated cognition versus the psychological learning theories.

    Science.gov (United States)

    Aparicio, Juan José; Rodríguez Moneo, María

    2005-11-01

    In this paper, the perspective of situated cognition, which gave rise both to the pragmatic theories and the so-called semantic theories of learning and has probably become the most representative standpoint of constructivism, is examined. We consider the claim of situated cognition to provide alternative explanations of the learning phenomenon to those of psychology and, especially, to those of the symbolic perspective, currently predominant in cognitive psychology. The level of analysis of situated cognition (i.e., global interactive systems) is considered an inappropriate approach to the problem of learning. From our analysis, it is concluded that the pragmatic theories and the so-called semantic theories of learning which originated in situated cognition can hardly be considered alternatives to the psychological learning theories, and they are unlikely to add anything of interest to the learning theory or to contribute to the improvement of our knowledge about the learning phenomenon.

  20. Learning Theories In Instructional Multimedia For English Learning

    OpenAIRE

    Farani, Rizki

    2016-01-01

    Learning theory is the concept of human learning. This concept is one of the important components in instructional for learning, especially English learning. English subject becomes one of important subjects for students but learning English needs specific strategy since it is not our vernacular. Considering human learning process in English learning is expected to increase students' motivation to understand English better. Nowadays, the application of learning theories in English learning ha...

  1. When Do Computer Graphics Contribute to Early Literacy Learning?

    Science.gov (United States)

    Wepner, Shelley B.; Cotter, Michelle

    2002-01-01

    Notes that new literacies use computer graphics to tell a story, demonstrate a theory, or support a definition. Offers a functionality framework for assessing the value of computer graphics for early literacy learning. Provides ideas for determining the value of CD-ROM software and websites. Concludes that graphics that give text meaning or…

  2. Learning Vocabulary in a Foreign Language: A Computer Software Based Model Attempt

    Science.gov (United States)

    Yelbay Yilmaz, Yasemin

    2015-01-01

    This study aimed at devising a vocabulary learning software that would help learners learn and retain vocabulary items effectively. Foundation linguistics and learning theories have been adapted to the foreign language vocabulary learning context using a computer software named Parole that was designed exclusively for this study. Experimental…

  3. Situated learning theory: adding rate and complexity effects via Kauffman's NK model.

    Science.gov (United States)

    Yuan, Yu; McKelvey, Bill

    2004-01-01

    For many firms, producing information, knowledge, and enhancing learning capability have become the primary basis of competitive advantage. A review of organizational learning theory identifies two approaches: (1) those that treat symbolic information processing as fundamental to learning, and (2) those that view the situated nature of cognition as fundamental. After noting that the former is inadequate because it focuses primarily on behavioral and cognitive aspects of individual learning, this paper argues the importance of studying learning as interactions among people in the context of their environment. It contributes to organizational learning in three ways. First, it argues that situated learning theory is to be preferred over traditional behavioral and cognitive learning theories, because it treats organizations as complex adaptive systems rather than mere information processors. Second, it adds rate and nonlinear learning effects. Third, following model-centered epistemology, it uses an agent-based computational model, in particular a "humanized" version of Kauffman's NK model, to study the situated nature of learning. Using simulation results, we test eight hypotheses extending situated learning theory in new directions. The paper ends with a discussion of possible extensions of the current study to better address key issues in situated learning.

  4. Computability theory

    CERN Document Server

    Weber, Rebecca

    2012-01-01

    What can we compute--even with unlimited resources? Is everything within reach? Or are computations necessarily drastically limited, not just in practice, but theoretically? These questions are at the heart of computability theory. The goal of this book is to give the reader a firm grounding in the fundamentals of computability theory and an overview of currently active areas of research, such as reverse mathematics and algorithmic randomness. Turing machines and partial recursive functions are explored in detail, and vital tools and concepts including coding, uniformity, and diagonalization are described explicitly. From there the material continues with universal machines, the halting problem, parametrization and the recursion theorem, and thence to computability for sets, enumerability, and Turing reduction and degrees. A few more advanced topics round out the book before the chapter on areas of research. The text is designed to be self-contained, with an entire chapter of preliminary material including re...

  5. Learning and geometry computational approaches

    CERN Document Server

    Smith, Carl

    1996-01-01

    The field of computational learning theory arose out of the desire to for­ mally understand the process of learning. As potential applications to artificial intelligence became apparent, the new field grew rapidly. The learning of geo­ metric objects became a natural area of study. The possibility of using learning techniques to compensate for unsolvability provided an attraction for individ­ uals with an immediate need to solve such difficult problems. Researchers at the Center for Night Vision were interested in solving the problem of interpreting data produced by a variety of sensors. Current vision techniques, which have a strong geometric component, can be used to extract features. However, these techniques fall short of useful recognition of the sensed objects. One potential solution is to incorporate learning techniques into the geometric manipulation of sensor data. As a first step toward realizing such a solution, the Systems Research Center at the University of Maryland, in conjunction with the C...

  6. Developmental Changes in Learning: Computational Mechanisms and Social Influences

    Directory of Open Access Journals (Sweden)

    Florian Bolenz

    2017-11-01

    Full Text Available Our ability to learn from the outcomes of our actions and to adapt our decisions accordingly changes over the course of the human lifespan. In recent years, there has been an increasing interest in using computational models to understand developmental changes in learning and decision-making. Moreover, extensions of these models are currently applied to study socio-emotional influences on learning in different age groups, a topic that is of great relevance for applications in education and health psychology. In this article, we aim to provide an introduction to basic ideas underlying computational models of reinforcement learning and focus on parameters and model variants that might be of interest to developmental scientists. We then highlight recent attempts to use reinforcement learning models to study the influence of social information on learning across development. The aim of this review is to illustrate how computational models can be applied in developmental science, what they can add to our understanding of developmental mechanisms and how they can be used to bridge the gap between psychological and neurobiological theories of development.

  7. Health education and multimedia learning: educational psychology and health behavior theory (Part 1).

    Science.gov (United States)

    Mas, Francisco G Soto; Plass, Jan; Kane, William M; Papenfuss, Richard L

    2003-07-01

    When health education researchers began to investigate how individuals make decisions related to health and the factors that influence health behaviors, they referred to frameworks shared by educational and learning research. Health education adopted the basic principles of the cognitive revolution, which were instrumental in advancing the field. There is currently a new challenge to confront: the widespread use of new technologies for health education. To better overcome this challenge, educational psychology and instructional technology theory should be considered. Unfortunately, the passion to incorporate new technologies too often overshadows how people learn or, in particular, how people learn through computer technologies. This two-part article explains how educational theory contributed to the early development of health behavior theory, describes the most relevant multimedia learning theories and constructs, and provides recommendations for developing multimedia health education programs and connecting theory and practice.

  8. International Conference on Frontiers of Intelligent Computing : Theory and Applications

    CERN Document Server

    Udgata, Siba; Biswal, Bhabendra

    2013-01-01

    The volume contains the papers presented at FICTA 2012: International Conference on Frontiers in Intelligent Computing: Theory and Applications held on December 22-23, 2012 in Bhubaneswar engineering College, Bhubaneswar, Odissa, India. It contains 86 papers contributed by authors from the globe. These research papers mainly focused on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc  for various engineering applications such as data mining, image processing, cloud computing, networking etc.

  9. Chinese Learning Through Internet Inspired by Contructivist Learning Theory

    OpenAIRE

    Yan, Huang

    2011-01-01

    With the changing concept of education, there is growing emphasis on “student-centered”principle. This is one of the characteristics of Constructivist learning theory. On network teachingChinese, Constructivist learning theory is indispensable. This article is the design of online Chineseteaching which is basic on the Constructivist learning theory.

  10. Theories of Learning and Their Implications for On-Line Assesment

    Directory of Open Access Journals (Sweden)

    Anthony Francis UNDERHILL,

    2006-01-01

    Full Text Available The pedagogy underlying online learning and teaching is being reconceptualised to incorporate the opportunities being offered by the development of online educational settings. The pedagogy of constructivism and in particular socio-constructivism is underpinning much of the online learning and teaching developments currently being developed. The developments in online learning and teaching however are not being matched by developments in computer based assessment. The scope of computers to offer varied, adaptive and unique assessment is still underdeveloped according to Brown, Race and Bull (1999. This paper briefly reviews the theories of learning and their relationship with traditional forms of assessment and seeks to argue for the need to further develop online assessment tools to further facilitate the growth in process based learning activities such as collaborative and cooperative group work consistent with a socio-constructivist pedagogy.

  11. International Conference on Frontiers of Intelligent Computing : Theory and Applications

    CERN Document Server

    Udgata, Siba; Biswal, Bhabendra

    2014-01-01

    This volume contains the papers presented at the Second International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA-2013) held during 14-16 November 2013 organized by Bhubaneswar Engineering College (BEC), Bhubaneswar, Odisha, India. It contains 63 papers focusing on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc  for various engineering applications such as data mining, Fuzzy systems, Machine Intelligence and ANN, Web technologies and Multimedia applications and Intelligent computing and Networking etc.

  12. Simulating Serious Games: A Discrete-Time Computational Model Based on Cognitive Flow Theory

    Science.gov (United States)

    Westera, Wim

    2018-01-01

    This paper presents a computational model for simulating how people learn from serious games. While avoiding the combinatorial explosion of a games micro-states, the model offers a meso-level pathfinding approach, which is guided by cognitive flow theory and various concepts from learning sciences. It extends a basic, existing model by exposing…

  13. Computer Assisted Language Learning. Routledge Studies in Computer Assisted Language Learning

    Science.gov (United States)

    Pennington, Martha

    2011-01-01

    Computer-assisted language learning (CALL) is an approach to language teaching and learning in which computer technology is used as an aid to the presentation, reinforcement and assessment of material to be learned, usually including a substantial interactive element. This books provides an up-to date and comprehensive overview of…

  14. Computational Methods and Function Theory

    CERN Document Server

    Saff, Edward; Salinas, Luis; Varga, Richard

    1990-01-01

    The volume is devoted to the interaction of modern scientific computation and classical function theory. Many problems in pure and more applied function theory can be tackled using modern computing facilities: numerically as well as in the sense of computer algebra. On the other hand, computer algorithms are often based on complex function theory, and dedicated research on their theoretical foundations can lead to great enhancements in performance. The contributions - original research articles, a survey and a collection of problems - cover a broad range of such problems.

  15. A BCM theory of meta-plasticity for online self-reorganizing fuzzy-associative learning.

    Science.gov (United States)

    Tan, Javan; Quek, Chai

    2010-06-01

    Self-organizing neurofuzzy approaches have matured in their online learning of fuzzy-associative structures under time-invariant conditions. To maximize their operative value for online reasoning, these self-sustaining mechanisms must also be able to reorganize fuzzy-associative knowledge in real-time dynamic environments. Hence, it is critical to recognize that they would require self-reorganizational skills to rebuild fluid associative structures when their existing organizations fail to respond well to changing circumstances. In this light, while Hebbian theory (Hebb, 1949) is the basic computational framework for associative learning, it is less attractive for time-variant online learning because it suffers from stability limitations that impedes unlearning. Instead, this paper adopts the Bienenstock-Cooper-Munro (BCM) theory of neurological learning via meta-plasticity principles (Bienenstock et al., 1982) that provides for both online associative and dissociative learning. For almost three decades, BCM theory has been shown to effectively brace physiological evidence of synaptic potentiation (association) and depression (dissociation) into a sound mathematical framework for computational learning. This paper proposes an interpretation of the BCM theory of meta-plasticity for an online self-reorganizing fuzzy-associative learning system to realize online-reasoning capabilities. Experimental findings are twofold: 1) the analysis using S&P-500 stock index illustrated that the self-reorganizing approach could follow the trajectory shifts in the time-variant S&P-500 index for about 60 years, and 2) the benchmark profiles showed that the fuzzy-associative approach yielded comparable results with other fuzzy-precision models with similar online objectives.

  16. Some ideas for learning CP-theories

    OpenAIRE

    Fierens, Daan

    2008-01-01

    Causal Probabilistic logic (CP-logic) is a language for describing complex probabilistic processes. In this talk we consider the problem of learning CP-theories from data. We briefly discuss three possible approaches. First, we review the existing algorithm by Meert et al. Second, we show how simple CP-theories can be learned by using the learning algorithm for Logical Bayesian Networks and converting the result into a CP-theory. Third, we argue that for learning more complex CP-theories, an ...

  17. Aids to Computer-Based Multimedia Learning.

    Science.gov (United States)

    Mayer, Richard E.; Moreno, Roxana

    2002-01-01

    Presents a cognitive theory of multimedia learning that draws on dual coding theory, cognitive load theory, and constructivist learning theory and derives some principles of instructional design for fostering multimedia learning. These include principles of multiple representation, contiguity, coherence, modality, and redundancy. (SLD)

  18. Investigating the Learning-Theory Foundations of Game-Based Learning: A Meta-Analysis

    Science.gov (United States)

    Wu, W-H.; Hsiao, H-C.; Wu, P-L.; Lin, C-H.; Huang, S-H.

    2012-01-01

    Past studies on the issue of learning-theory foundations in game-based learning stressed the importance of establishing learning-theory foundation and provided an exploratory examination of established learning theories. However, we found research seldom addressed the development of the use or failure to use learning-theory foundations and…

  19. Learning theory and gestalt therapy.

    Science.gov (United States)

    Harper, R; Bauer, R; Kannarkat, J

    1976-01-01

    This article discusses the theory and operations of Gestalt Therapy from the viewpoint of learning theory. General comparative issues are elaborated as well as the concepts of introjection, retroflextion, confluence, and projection. Principles and techniques of Gestalt Therapy are discussed in terms of learning theory paradigm. Practical implications of the various Gestalt techniques are presented.

  20. The Effect of Animation in Multimedia Computer-Based Learning and Learning Style to the Learning Results

    Directory of Open Access Journals (Sweden)

    Muhammad RUSLI

    2017-10-01

    Full Text Available The effectiveness of a learning depends on four main elements, they are content, desired learning outcome, instructional method and the delivery media. The integration of those four elements can be manifested into a learning modul which is called multimedia learning or learning by using multimedia. In learning context by using computer-based multimedia, there are two main things that need to be noticed so that the learning process can run effectively: how the content is presented, and what the learner’s chosen way in accepting and processing the information into a meaningful knowledge. First it is related with the way to visualize the content and how people learn. The second one is related with the learning style of the learner. This research aims to investigate the effect of the type of visualization—static vs animated—on a multimedia computer-based learning, and learning styles—visual vs verbal, towards the students’ capability in applying the concepts, procedures, principles of Java programming. Visualization type act as independent variables, and learning styles of the students act as a moderator variable. Moreover, the instructional strategies followed the Component Display Theory of Merril, and the format of presentation of multimedia followed the Seven Principles of Multimedia Learning of Mayer and Moreno. Learning with the multimedia computer-based learning has been done in the classroom. The subject of this research was the student of STMIK-STIKOM Bali in odd semester 2016-2017 which followed the course of Java programming. The Design experiments used multivariate analysis of variance, MANOVA 2 x 2, with a large sample of 138 students in 4 classes. Based on the results of the analysis, it can be concluded that the animation in multimedia interactive learning gave a positive effect in improving students’ learning outcomes, particularly in the applying the concepts, procedures, and principles of Java programming. The

  1. Differential theory of learning for efficient neural network pattern recognition

    Science.gov (United States)

    Hampshire, John B., II; Vijaya Kumar, Bhagavatula

    1993-09-01

    We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

  2. An Elementary Introduction to Statistical Learning Theory

    CERN Document Server

    Kulkarni, Sanjeev

    2011-01-01

    A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these areas at a level and in a way that is not often found in other books on the topic, the authors present the basic theory behind contemporary machine learning and

  3. Interferometric Computation Beyond Quantum Theory

    Science.gov (United States)

    Garner, Andrew J. P.

    2018-03-01

    There are quantum solutions for computational problems that make use of interference at some stage in the algorithm. These stages can be mapped into the physical setting of a single particle travelling through a many-armed interferometer. There has been recent foundational interest in theories beyond quantum theory. Here, we present a generalized formulation of computation in the context of a many-armed interferometer, and explore how theories can differ from quantum theory and still perform distributed calculations in this set-up. We shall see that quaternionic quantum theory proves a suitable candidate, whereas box-world does not. We also find that a classical hidden variable model first presented by Spekkens (Phys Rev A 75(3): 32100, 2007) can also be used for this type of computation due to the epistemic restriction placed on the hidden variable.

  4. Experiential learning: transforming theory into practice.

    Science.gov (United States)

    Yardley, Sarah; Teunissen, Pim W; Dornan, Tim

    2012-01-01

    Whilst much is debated about the importance of experiential learning in curriculum development, the concept only becomes effective if it is applied in an appropriate way. We believe that this effectiveness is directly related to a sound understanding of the theory, supporting the learning. The purpose of this article is to introduce readers to the theories underpinning experiential learning, which are then expanded further in an AMEE Guide, which considers the theoretical basis of experiential learning from a social learning, constructionist perspective and applies it to three stages of medical education: early workplace experience, clerkships and residency. This article argues for the importance and relevance of experiential learning and addresses questions that are commonly asked about it. First, we answer the questions 'what is experiential learning?' and 'how does it relate to social learning theory?' to orientate readers to the principles on which our arguments are based. Then, we consider why those ideas (theories) are relevant to educators--ranging from those with responsibilities for curriculum design to 'hands-on' teachers and workplace supervisors. The remainder of this article discusses how experiential learning theories and a socio-cultural perspective can be applied in practice. We hope that this will give readers a taste for our more detailed AMEE Guide and the further reading recommended at the end of it.

  5. Learning theories application in nursing education

    Science.gov (United States)

    Aliakbari, Fatemeh; Parvin, Neda; Heidari, Mohammad; Haghani, Fariba

    2015-01-01

    Learning theories are the main guide for educational systems planning in the classroom and clinical training included in nursing. The teachers by knowing the general principles of these theories can use their knowledge more effectively according to various learning situations. In this study, Eric, Medline, and Cochrane databases were used for articles in English and for the Persian literature, Magiran, Iran doc, Iran medex, and Sid databases were used with the help of keywords including social cognitive learning, learning theory, behavioral theory, cognitive theory, constructive theory, and nursing education. The search period was considered from 1990 to 2012. Some related books were also studied about each method, its original vision, the founders, practical application of the training theory, especially training of nursing and its strengths and weaknesses. Behaviorists believe that learning is a change in an observable behavior and it happens when the communication occurs between the two events, a stimulus and a response. Among the applications of this approach is the influence on the learner's emotional reactions. Among the theories of this approach, Thorndike and Skinner works are subject to review and critique. Cognitive psychologists unlike the behaviorists believe that learning is an internal process objective and they focus on thinking, understanding, organizing, and consciousness. Fundamentalists believe that learners should be equipped with the skills of inquiry and problem solving in order to learn by the discovery and process of information. Among this group, we will pay attention to analyze Wertheimer, Brunner, Ausubel theories, Ganyeh information processing model, in addition to its applications in nursing education. Humanists in learning pay attention to the feelings and experiences. Carl Rogers support the retention of learning-centered approach and he is believed to a semantic continuum. At the other end of the continuum, experiential learning is

  6. Learning theories application in nursing education.

    Science.gov (United States)

    Aliakbari, Fatemeh; Parvin, Neda; Heidari, Mohammad; Haghani, Fariba

    2015-01-01

    Learning theories are the main guide for educational systems planning in the classroom and clinical training included in nursing. The teachers by knowing the general principles of these theories can use their knowledge more effectively according to various learning situations. In this study, Eric, Medline, and Cochrane databases were used for articles in English and for the Persian literature, Magiran, Iran doc, Iran medex, and Sid databases were used with the help of keywords including social cognitive learning, learning theory, behavioral theory, cognitive theory, constructive theory, and nursing education. The search period was considered from 1990 to 2012. Some related books were also studied about each method, its original vision, the founders, practical application of the training theory, especially training of nursing and its strengths and weaknesses. Behaviorists believe that learning is a change in an observable behavior and it happens when the communication occurs between the two events, a stimulus and a response. Among the applications of this approach is the influence on the learner's emotional reactions. Among the theories of this approach, Thorndike and Skinner works are subject to review and critique. Cognitive psychologists unlike the behaviorists believe that learning is an internal process objective and they focus on thinking, understanding, organizing, and consciousness. Fundamentalists believe that learners should be equipped with the skills of inquiry and problem solving in order to learn by the discovery and process of information. Among this group, we will pay attention to analyze Wertheimer, Brunner, Ausubel theories, Ganyeh information processing model, in addition to its applications in nursing education. Humanists in learning pay attention to the feelings and experiences. Carl Rogers support the retention of learning-centered approach and he is believed to a semantic continuum. At the other end of the continuum, experiential learning is

  7. Towards a general theory of neural computation based on prediction by single neurons.

    Directory of Open Access Journals (Sweden)

    Christopher D Fiorillo

    Full Text Available Although there has been tremendous progress in understanding the mechanics of the nervous system, there has not been a general theory of its computational function. Here I present a theory that relates the established biophysical properties of single generic neurons to principles of Bayesian probability theory, reinforcement learning and efficient coding. I suggest that this theory addresses the general computational problem facing the nervous system. Each neuron is proposed to mirror the function of the whole system in learning to predict aspects of the world related to future reward. According to the model, a typical neuron receives current information about the state of the world from a subset of its excitatory synaptic inputs, and prior information from its other inputs. Prior information would be contributed by synaptic inputs representing distinct regions of space, and by different types of non-synaptic, voltage-regulated channels representing distinct periods of the past. The neuron's membrane voltage is proposed to signal the difference between current and prior information ("prediction error" or "surprise". A neuron would apply a Hebbian plasticity rule to select those excitatory inputs that are the most closely correlated with reward but are the least predictable, since unpredictable inputs provide the neuron with the most "new" information about future reward. To minimize the error in its predictions and to respond only when excitation is "new and surprising," the neuron selects amongst its prior information sources through an anti-Hebbian rule. The unique inputs of a mature neuron would therefore result from learning about spatial and temporal patterns in its local environment, and by extension, the external world. Thus the theory describes how the structure of the mature nervous system could reflect the structure of the external world, and how the complexity and intelligence of the system might develop from a population of

  8. Advances in computational complexity theory

    CERN Document Server

    Cai, Jin-Yi

    1993-01-01

    This collection of recent papers on computational complexity theory grew out of activities during a special year at DIMACS. With contributions by some of the leading experts in the field, this book is of lasting value in this fast-moving field, providing expositions not found elsewhere. Although aimed primarily at researchers in complexity theory and graduate students in mathematics or computer science, the book is accessible to anyone with an undergraduate education in mathematics or computer science. By touching on some of the major topics in complexity theory, this book sheds light on this burgeoning area of research.

  9. Learning a commonsense moral theory.

    Science.gov (United States)

    Kleiman-Weiner, Max; Saxe, Rebecca; Tenenbaum, Joshua B

    2017-10-01

    We introduce a computational framework for understanding the structure and dynamics of moral learning, with a focus on how people learn to trade off the interests and welfare of different individuals in their social groups and the larger society. We posit a minimal set of cognitive capacities that together can solve this learning problem: (1) an abstract and recursive utility calculus to quantitatively represent welfare trade-offs; (2) hierarchical Bayesian inference to understand the actions and judgments of others; and (3) meta-values for learning by value alignment both externally to the values of others and internally to make moral theories consistent with one's own attachments and feelings. Our model explains how children can build from sparse noisy observations of how a small set of individuals make moral decisions to a broad moral competence, able to support an infinite range of judgments and decisions that generalizes even to people they have never met and situations they have not been in or observed. It also provides insight into the causes and dynamics of moral change across time, including cases when moral change can be rapidly progressive, changing values significantly in just a few generations, and cases when it is likely to move more slowly. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Consideration on Singularities in Learning Theory and the Learning Coefficient

    Directory of Open Access Journals (Sweden)

    Miki Aoyagi

    2013-09-01

    Full Text Available We consider the learning coefficients in learning theory and give two new methods for obtaining these coefficients in a homogeneous case: a method for finding a deepest singular point and a method to add variables. In application to Vandermonde matrix-type singularities, we show that these methods are effective. The learning coefficient of the generalization error in Bayesian estimation serves to measure the learning efficiency in singular learning models. Mathematically, the learning coefficient corresponds to a real log canonical threshold of singularities for the Kullback functions (relative entropy in learning theory.

  11. A Drawing and Multi-Representational Computer Environment for Beginners' Learning of Programming Using C: Design and Pilot Formative Evaluation

    Science.gov (United States)

    Kordaki, Maria

    2010-01-01

    This paper presents both the design and the pilot formative evaluation study of a computer-based problem-solving environment (named LECGO: Learning Environment for programming using C using Geometrical Objects) for the learning of computer programming using C by beginners. In its design, constructivist and social learning theories were taken into…

  12. Computer algebra in quantum field theory integration, summation and special functions

    CERN Document Server

    Schneider, Carsten

    2013-01-01

    The book focuses on advanced computer algebra methods and special functions that have striking applications in the context of quantum field theory. It presents the state of the art and new methods for (infinite) multiple sums, multiple integrals, in particular Feynman integrals, difference and differential equations in the format of survey articles. The presented techniques emerge from interdisciplinary fields: mathematics, computer science and theoretical physics; the articles are written by mathematicians and physicists with the goal that both groups can learn from the other field, including

  13. Assessing Cognitive Load Theory to Improve Student Learning for Mechanical Engineers

    Science.gov (United States)

    Impelluso, Thomas J.

    2009-01-01

    A computer programming class for students of mechanical engineering was redesigned and assessed: Cognitive Load Theory was used to redesign the content; online technologies were used to redesign the delivery. Student learning improved and the dropout rate was reduced. This article reports on both attitudinal and objective assessment: comparing…

  14. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

    Science.gov (United States)

    Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

    2016-03-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015

  15. Reinforcement learning in computer vision

    Science.gov (United States)

    Bernstein, A. V.; Burnaev, E. V.

    2018-04-01

    Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.

  16. Music Learning Based on Computer Software

    Directory of Open Access Journals (Sweden)

    Baihui Yan

    2017-12-01

    Full Text Available In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teachers have not found a reasonable countermeasure to them. Against this background, the introduction of computer music software to music learning is a new trial that can not only cultivate the students’ initiatives of music learning, but also enhance their abilities to learn music. Therefore, it is concluded that the computer software based music learning is of great significance to improving the current music learning modes and means.

  17. The sign learning theory

    African Journals Online (AJOL)

    KING OF DAWN

    The sign learning theory also holds secrets that could be exploited in accomplishing motor tasks. ... Introduction ... In his classic work: Cognitive Map in Rats and Men (1948),Tolman talked about five groups of experiments viz: latent learning ...

  18. A Dynamic Logic for Learning Theory

    DEFF Research Database (Denmark)

    Baltag, Alexandru; Gierasimczuk, Nina; Özgün, Aybüke

    2017-01-01

    Building on previous work that bridged Formal Learning Theory and Dynamic Epistemic Logic in a topological setting, we introduce a Dynamic Logic for Learning Theory (DLLT), extending Subset Space Logics with dynamic observation modalities, as well as with a learning operator, which encodes the le...... the learner’s conjecture after observing a finite sequence of data. We completely axiomatise DLLT, study its expressivity and use it to characterise various notions of knowledge, belief, and learning. ...

  19. Constructivist learning theories and complex learning environments

    NARCIS (Netherlands)

    R-J. Simons; Dr. S. Bolhuis

    2004-01-01

    Learning theories broadly characterised as constructivist, agree on the importance to learning of the environment, but differ on what exactly it is that constitutes this importance. Accordingly, they also differ on the educational consequences to be drawn from the theoretical perspective. Cognitive

  20. Effective Learning Environments in Relation to Different Learning Theories

    NARCIS (Netherlands)

    Guney, A.; Al, S.

    2012-01-01

    There are diverse learning theories which explain learning processes which are discussed within this paper, through cognitive structure of learning process. Learning environments are usually described in terms of pedagogical philosophy, curriculum design and social climate. There have been only just

  1. Advanced Learning Theories Applied to Leadership Development

    Science.gov (United States)

    2006-11-01

    Center for Army Leadership Technical Report 2006-2 Advanced Learning Theories Applied to Leadership Development Christina Curnow...2006 5a. CONTRACT NUMBER W91QF4-05-F-0026 5b. GRANT NUMBER 4. TITLE AND SUBTITLE Advanced Learning Theories Applied to Leadership Development 5c...ABSTRACT This report describes the development and implementation of an application of advanced learning theories to leadership development. A

  2. Moral learning as intuitive theory revision.

    Science.gov (United States)

    Rhodes, Marjorie; Wellman, Henry

    2017-10-01

    We argue that moral learning, like much of conceptual development more generally, involves development and change in children's intuitive theories of the world. Children's intuitive theories involve coherent and abstract representations of the world, which point to domain-specific, unobservable causal-explanatory entities. From this perspective, children rely on intuitive sociological theories (in particular, an abstract expectation that group memberships constrain people's obligations), and their intuitive psychological theories (including expectations that mental states motivate individual behavior) to predict, explain, and evaluate morally-relevant action. Thus, moral learning involves development and change in each of these theories of the world across childhood, as well as developmental change in how children integrate information from these two intuitive theories. This perspective is supported by a series of research studies on young children's moral reasoning and learning, and compared to other developmental approaches, including more traditional forms of constructivism and more recent nativist perspectives. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. A learning theory account of depression.

    Science.gov (United States)

    Ramnerö, Jonas; Folke, Fredrik; Kanter, Jonathan W

    2015-06-11

    Learning theory provides a foundation for understanding and deriving treatment principles for impacting a spectrum of functional processes relevant to the construct of depression. While behavioral interventions have been commonplace in the cognitive behavioral tradition, most often conceptualized within a cognitive theoretical framework, recent years have seen renewed interest in more purely behavioral models. These modern learning theory accounts of depression focus on the interchange between behavior and the environment, mainly in terms of lack of reinforcement, extinction of instrumental behavior, and excesses of aversive control, and include a conceptualization of relevant cognitive and emotional variables. These positions, drawn from extensive basic and applied research, cohere with biological theories on reduced reward learning and reward responsiveness and views of depression as a heterogeneous, complex set of disorders. Treatment techniques based on learning theory, often labeled Behavioral Activation (BA) focus on activating the individual in directions that increase contact with potential reinforcers, as defined ideographically with the client. BA is considered an empirically well-established treatment that generalizes well across diverse contexts and populations. The learning theory account is discussed in terms of being a parsimonious model and ground for treatments highly suitable for large scale dissemination. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  4. Introductory Tiling Theory for Computer Graphics

    CERN Document Server

    Kaplan, Craig

    2009-01-01

    Tiling theory is an elegant branch of mathematics that has applications in several areas of computer science. The most immediate application area is graphics, where tiling theory has been used in the contexts of texture generation, sampling theory, remeshing, and of course the generation of decorative patterns. The combination of a solid theoretical base (complete with tantalizing open problems), practical algorithmic techniques, and exciting applications make tiling theory a worthwhile area of study for practitioners and students in computer science. This synthesis lecture introduces the math

  5. Computational Aspects of Nuclear Coupled-Cluster Theory

    International Nuclear Information System (INIS)

    Dean, David Jarvis; Hagen, Gaute; Hjorth-Jensen, M.; Papenbrock, T.F.

    2008-01-01

    Coupled-cluster theory represents an important theoretical tool that we use to solve the quantum many-body problem. Coupled-cluster theory also lends itself to computation in a parallel computing environment. In this article, we present selected results from ab initio studies of stable and weakly bound nuclei utilizing computational techniques that we employ to solve coupled-cluster theory. We also outline several perspectives for future research directions in this area.

  6. The Scientific Status of Learning Styles Theories

    Science.gov (United States)

    Willingham, Daniel T.; Hughes, Elizabeth M.; Dobolyi, David G.

    2015-01-01

    Theories of learning styles suggest that individuals think and learn best in different ways. These are not differences of ability but rather preferences for processing certain types of information or for processing information in certain types of way. If accurate, learning styles theories could have important implications for instruction because…

  7. The Activity Theory Approach to Learning

    Directory of Open Access Journals (Sweden)

    Ritva Engeström

    2014-12-01

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

  8. Effects of Learning Style and Training Method on Computer Attitude and Performance in World Wide Web Page Design Training.

    Science.gov (United States)

    Chou, Huey-Wen; Wang, Yu-Fang

    1999-01-01

    Compares the effects of two training methods on computer attitude and performance in a World Wide Web page design program in a field experiment with high school students in Taiwan. Discusses individual differences, Kolb's Experiential Learning Theory and Learning Style Inventory, Computer Attitude Scale, and results of statistical analyses.…

  9. Learning network theory : its contribution to our understanding of work-based learning projects and learning climate

    NARCIS (Netherlands)

    Poell, R.F.; Moorsel, M.A.A.H. van

    1996-01-01

    This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of

  10. Pragmatically Framed Cross-Situational Noun Learning Using Computational Reinforcement Models.

    Science.gov (United States)

    Najnin, Shamima; Banerjee, Bonny

    2018-01-01

    Cross-situational learning and social pragmatic theories are prominent mechanisms for learning word meanings (i.e., word-object pairs). In this paper, the role of reinforcement is investigated for early word-learning by an artificial agent. When exposed to a group of speakers, the agent comes to understand an initial set of vocabulary items belonging to the language used by the group. Both cross-situational learning and social pragmatic theory are taken into account. As social cues, joint attention and prosodic cues in caregiver's speech are considered. During agent-caregiver interaction, the agent selects a word from the caregiver's utterance and learns the relations between that word and the objects in its visual environment. The "novel words to novel objects" language-specific constraint is assumed for computing rewards. The models are learned by maximizing the expected reward using reinforcement learning algorithms [i.e., table-based algorithms: Q-learning, SARSA, SARSA-λ, and neural network-based algorithms: Q-learning for neural network (Q-NN), neural-fitted Q-network (NFQ), and deep Q-network (DQN)]. Neural network-based reinforcement learning models are chosen over table-based models for better generalization and quicker convergence. Simulations are carried out using mother-infant interaction CHILDES dataset for learning word-object pairings. Reinforcement is modeled in two cross-situational learning cases: (1) with joint attention (Attentional models), and (2) with joint attention and prosodic cues (Attentional-prosodic models). Attentional-prosodic models manifest superior performance to Attentional ones for the task of word-learning. The Attentional-prosodic DQN outperforms existing word-learning models for the same task.

  11. Learned-Helplessness Theory: Implications for Research in Learning Disabilities.

    Science.gov (United States)

    Canino, Frank J.

    1981-01-01

    The application of learned helplessness theory to achievement is discussed within the context of implications for research in learning disabilities. Finally, the similarities between helpless children and learning disabled students in terms of problems solving and attention are discussed. (Author)

  12. What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

    Science.gov (United States)

    Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

    2016-07-01

    We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Artificial grammar learning meets formal language theory: an overview

    Science.gov (United States)

    Fitch, W. Tecumseh; Friederici, Angela D.

    2012-01-01

    Formal language theory (FLT), part of the broader mathematical theory of computation, provides a systematic terminology and set of conventions for describing rules and the structures they generate, along with a rich body of discoveries and theorems concerning generative rule systems. Despite its name, FLT is not limited to human language, but is equally applicable to computer programs, music, visual patterns, animal vocalizations, RNA structure and even dance. In the last decade, this theory has been profitably used to frame hypotheses and to design brain imaging and animal-learning experiments, mostly using the ‘artificial grammar-learning’ paradigm. We offer a brief, non-technical introduction to FLT and then a more detailed analysis of empirical research based on this theory. We suggest that progress has been hampered by a pervasive conflation of distinct issues, including hierarchy, dependency, complexity and recursion. We offer clarifications of several relevant hypotheses and the experimental designs necessary to test them. We finally review the recent brain imaging literature, using formal languages, identifying areas of convergence and outstanding debates. We conclude that FLT has much to offer scientists who are interested in rigorous empirical investigations of human cognition from a neuroscientific and comparative perspective. PMID:22688631

  14. Deep learning

    CERN Document Server

    Goodfellow, Ian; Courville, Aaron

    2016-01-01

    Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

  15. Statistical Learning Theory: Models, Concepts, and Results

    OpenAIRE

    von Luxburg, Ulrike; Schoelkopf, Bernhard

    2008-01-01

    Statistical learning theory provides the theoretical basis for many of today's machine learning algorithms. In this article we attempt to give a gentle, non-technical overview over the key ideas and insights of statistical learning theory. We target at a broad audience, not necessarily machine learning researchers. This paper can serve as a starting point for people who want to get an overview on the field before diving into technical details.

  16. Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

    Science.gov (United States)

    Fiorini, Rodolfo A.; Dacquino, Gianfranco

    2005-03-01

    GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

  17. Effective Learning Environments in Relation to Different Learning Theories

    OpenAIRE

    Guney, Ali; Al, Selda

    2012-01-01

    There are diverse learning theories which explain learning processes which are discussed within this paper, through cognitive structure of learning process. Learning environments are usually described in terms of pedagogical philosophy, curriculum design and social climate. There have been only just a few studies about how physical environment is related to learning process. Many researchers generally consider teaching and learning issues as if independent from physical environment, whereas p...

  18. Learning network theory : its contribution to our understanding of work-based learning projects and learning climate

    OpenAIRE

    Poell, R.F.; Moorsel, M.A.A.H. van

    1996-01-01

    This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of learning groups in organisations. Four theoretical types of learning projects are distinguished. Four different approaches to the learning climate of work groups are compared to the approach offered by t...

  19. Theory and computational science

    International Nuclear Information System (INIS)

    Durham, P.

    1985-01-01

    The theoretical and computational science carried out at the Daresbury Laboratory in 1984/5 is detailed in the Appendix to the Daresbury Annual Report. The Theory, Computational Science and Applications Groups, provide support work for the experimental projects conducted at Daresbury. Use of the FPS-164 processor is also described. (U.K.)

  20. Music Learning Based on Computer Software

    OpenAIRE

    Baihui Yan; Qiao Zhou

    2017-01-01

    In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teach...

  1. ANALYSIS OF EFFECTIVENESS OF METHODOLOGICAL SYSTEM FOR PROBABILITY AND STOCHASTIC PROCESSES COMPUTER-BASED LEARNING FOR PRE-SERVICE ENGINEERS

    Directory of Open Access Journals (Sweden)

    E. Chumak

    2015-04-01

    Full Text Available The author substantiates that only methodological training systems of mathematical disciplines with implementation of information and communication technologies (ICT can meet the requirements of modern educational paradigm and make possible to increase the educational efficiency. Due to this fact, the necessity of developing the methodology of theory of probability and stochastic processes computer-based learning for pre-service engineers is underlined in the paper. The results of the experimental study for analysis of the efficiency of methodological system of theory of probability and stochastic processes computer-based learning for pre-service engineers are shown. The analysis includes three main stages: ascertaining, searching and forming. The key criteria of the efficiency of designed methodological system are the level of probabilistic and stochastic skills of students and their learning motivation. The effect of implementing the methodological system of probability theory and stochastic processes computer-based learning on the level of students’ IT literacy is shown in the paper. The expanding of the range of objectives of ICT applying by students is described by author. The level of formation of students’ learning motivation on the ascertaining and forming stages of the experiment is analyzed. The level of intrinsic learning motivation for pre-service engineers is defined on these stages of the experiment. For this purpose, the methodology of testing the students’ learning motivation in the chosen specialty is presented in the paper. The increasing of intrinsic learning motivation of the experimental group students (E group against the control group students (C group is demonstrated.

  2. It Takes a Village: Supporting Inquiry- and Equity-Oriented Computer Science Pedagogy through a Professional Learning Community

    Science.gov (United States)

    Ryoo, Jean; Goode, Joanna; Margolis, Jane

    2015-01-01

    This article describes the importance that high school computer science teachers place on a teachers' professional learning community designed around an inquiry- and equity-oriented approach for broadening participation in computing. Using grounded theory to analyze four years of teacher surveys and interviews from the Exploring Computer Science…

  3. Creating Effective Educational Computer Games for Undergraduate Classroom Learning: A Conceptual Model

    Science.gov (United States)

    Rapeepisarn, Kowit; Wong, Kok Wai; Fung, Chun Che; Khine, Myint Swe

    2008-01-01

    When designing Educational Computer Games, designers usually consider target age, interactivity, interface and other related issues. They rarely explore the genres which should employ into one type of educational game. Recently, some digital game-based researchers made attempt to combine game genre with learning theory. Different researchers use…

  4. It takes a village: supporting inquiry- and equity-oriented computer science pedagogy through a professional learning community

    Science.gov (United States)

    Ryoo, Jean; Goode, Joanna; Margolis, Jane

    2015-10-01

    This article describes the importance that high school computer science teachers place on a teachers' professional learning community designed around an inquiry- and equity-oriented approach for broadening participation in computing. Using grounded theory to analyze four years of teacher surveys and interviews from the Exploring Computer Science (ECS) program in the Los Angeles Unified School District, this article describes how participating in professional development activities purposefully aimed at fostering a teachers' professional learning community helps ECS teachers make the transition to an inquiry-based classroom culture and break professional isolation. This professional learning community also provides experiences that challenge prevalent deficit notions and stereotypes about which students can or cannot excel in computer science.

  5. Integer programming theory, applications, and computations

    CERN Document Server

    Taha, Hamdy A

    1975-01-01

    Integer Programming: Theory, Applications, and Computations provides information pertinent to the theory, applications, and computations of integer programming. This book presents the computational advantages of the various techniques of integer programming.Organized into eight chapters, this book begins with an overview of the general categorization of integer applications and explains the three fundamental techniques of integer programming. This text then explores the concept of implicit enumeration, which is general in a sense that it is applicable to any well-defined binary program. Other

  6. Critical evidence for the prediction error theory in associative learning.

    Science.gov (United States)

    Terao, Kanta; Matsumoto, Yukihisa; Mizunami, Makoto

    2015-03-10

    In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. Complete evidence for the prediction error theory, however, has not been obtained in any learning systems: Prediction error theory stems from the finding of a blocking phenomenon, but blocking can also be accounted for by other theories, such as the attentional theory. We demonstrated blocking in classical conditioning in crickets and obtained evidence to reject the attentional theory. To obtain further evidence supporting the prediction error theory and rejecting alternative theories, we constructed a neural model to match the prediction error theory, by modifying our previous model of learning in crickets, and we tested a prediction from the model: the model predicts that pharmacological intervention of octopaminergic transmission during appetitive conditioning impairs learning but not formation of reward prediction itself, and it thus predicts no learning in subsequent training. We observed such an "auto-blocking", which could be accounted for by the prediction error theory but not by other competitive theories to account for blocking. This study unambiguously demonstrates validity of the prediction error theory in associative learning.

  7. Development and Evaluation of a Computer-Based Learning Environment for Teachers: Assessment of Learning Strategies in Learning Journals

    Directory of Open Access Journals (Sweden)

    Inga Glogger

    2013-01-01

    Full Text Available Training teachers to assess important components of self-regulated learning such as learning strategies is an important, yet somewhat neglected, aspect of the integration of self-regulated learning at school. Learning journals can be used to assess learning strategies in line with cyclical process models of self-regulated learning, allowing for rich formative feedback. Against this background, we developed a computer-based learning environment (CBLE that trains teachers to assess learning strategies with learning journals. The contents of the CBLE and its instructional design were derived from theory. The CBLE was further shaped by research in a design-based manner. Finally, in two evaluation studies, student teachers (N1=44; N2=89 worked with the CBLE. We analyzed satisfaction, interest, usability, and assessment skills. Additionally, in evaluation study 2, effects of an experimental variation on motivation and assessment skills were tested. We found high satisfaction, interest, and good usability, as well as satisfying assessment skills, after working with the CBLE. Results show that teachers can be trained to assess learning strategies in learning journals. The developed CBLE offers new perspectives on how to support teachers in fostering learning strategies as central component of effective self-regulated learning at school.

  8. Linking theory to practice in learning technology research

    Directory of Open Access Journals (Sweden)

    Cathy Gunn

    2012-03-01

    Full Text Available We present a case to reposition theory so that it plays a pivotal role in learning technology research and helps to build an ecology of learning. To support the case, we present a critique of current practice based on a review of articles published in two leading international journals from 2005 to 2010. Our study reveals that theory features only incidentally or not at all in many cases. We propose theory development as a unifying theme for learning technology research study design and reporting. The use of learning design as a strategy to develop and test theories in practice is integral to our argument. We conclude by supporting other researchers who recommend educational design research as a theory focused methodology to move the field forward in productive and consistent ways. The challenge of changing common practice will be involved. However, the potential to raise the profile of learning technology research and improve educational outcomes justifies the effort required.

  9. The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

    OpenAIRE

    Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

    2013-01-01

    The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constrain...

  10. 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

  11. Planning Computer-Aided Distance Learning

    Directory of Open Access Journals (Sweden)

    Nadja Dobnik

    1996-12-01

    Full Text Available Didactics of autonomous learning changes under the influence of new technologies. Computer technology can cover all the functions that a teacher develops in personal contact with the learner. People organizing distance learning must realize all the possibilities offered by computers. Computers can take over and also combine the functions of many tools and systems, e. g. type­ writer, video, telephone. This the contents can be offered in form of classic media by means of text, speech, picture, etc. Computers take over data pro­cessing and function as study materials. Computer included in a computer network can also function as a medium for interactive communication.

  12. Geometrical methods in learning theory

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  13. Learning Theory and Prosocial Behavior

    Science.gov (United States)

    Rosenhan, D. L.

    1972-01-01

    Although theories of learning which stress the role of reinforcement can help us understand altruistic behaviors, it seems clear that a more complete comprehension calls for an expansion of our notions of learning, such that they incorporate affect and cognition. (Author/JM)

  14. A Comparative Analysis of Three Unique Theories of Organizational Learning

    Science.gov (United States)

    Leavitt, Carol C.

    2011-01-01

    The purpose of this paper is to present three classical theories on organizational learning and conduct a comparative analysis that highlights their strengths, similarities, and differences. Two of the theories -- experiential learning theory and adaptive -- generative learning theory -- represent the thinking of the cognitive perspective, while…

  15. The use of games and computer simulation as a learning tool: paper airplanes championship and Hydrodynamic teaching

    Directory of Open Access Journals (Sweden)

    Ericarla de Jesus Souza

    2017-08-01

    Full Text Available This article presents a Physics teaching research using as teaching-learning technique a didactic sequence constructed from educational games, experimental activities and computational simulations. The content covered in this work is hydrodynamics and its application in the physical concepts involved in airplane flight. Learning content is reinforced through the use of computer simulation using the software Modellus. The students' evaluation was made with the use of educational games: crosswords, word searches and games of the seven errors. The assessment was carried out through the application of questions that evaluated the students' alternative conceptions. The theoretical framework is based on the theory of mental models of John-Laird and in the theory of meaningful learning of Ausubel. So, the evaluations of previous knowledge of the students were made through evaluation of test type questionnaire.

  16. Mobile Affordances and Learning Theories in Supporting and Enhancing Learning

    Science.gov (United States)

    MacCallum, Kathryn; Day, Stephanie; Skelton, David; Verhaart, Michael

    2017-01-01

    Mobile technology promises to enhance and better support students' learning. The exploration and adoption of appropriate pedagogies that enhance learning is crucial for the wider adoption of mobile learning. An increasing number of studies have started to address how existing learning theory can be used to underpin and better frame mobile learning…

  17. Computers for lattice field theories

    International Nuclear Information System (INIS)

    Iwasaki, Y.

    1994-01-01

    Parallel computers dedicated to lattice field theories are reviewed with emphasis on the three recent projects, the Teraflops project in the US, the CP-PACS project in Japan and the 0.5-Teraflops project in the US. Some new commercial parallel computers are also discussed. Recent development of semiconductor technologies is briefly surveyed in relation to possible approaches toward Teraflops computers. (orig.)

  18. The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

    Directory of Open Access Journals (Sweden)

    Mark G Orr

    Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

  19. The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

    Science.gov (United States)

    Orr, Mark G; Thrush, Roxanne; Plaut, David C

    2013-01-01

    The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

  20. A computable type theory for control systems

    NARCIS (Netherlands)

    P.J. Collins (Pieter); L. Guo; J. Baillieul

    2009-01-01

    htmlabstractIn this paper, we develop a theory of computable types suitable for the study of control systems. The theory uses type-two effectivity as the underlying computational model, but we quickly develop a type system which can be manipulated abstractly, but for which all allowable operations

  1. Learning Words through Computer-Adaptive Tool

    DEFF Research Database (Denmark)

    Zhang, Chun

    2005-01-01

    construction, I stress the design of a test theory, namely, a learning algorithm. The learning algorithm is designed under such principles that users experience both 'elaborative rehearsal’ (aspects in receptive and productive learning) and 'expanding rehearsal, (memory-based learning and repetitive act...

  2. Inference algorithms and learning theory for Bayesian sparse factor analysis

    International Nuclear Information System (INIS)

    Rattray, Magnus; Sharp, Kevin; Stegle, Oliver; Winn, John

    2009-01-01

    Bayesian sparse factor analysis has many applications; for example, it has been applied to the problem of inferring a sparse regulatory network from gene expression data. We describe a number of inference algorithms for Bayesian sparse factor analysis using a slab and spike mixture prior. These include well-established Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms as well as a novel hybrid of VB and Expectation Propagation (EP). For the case of a single latent factor we derive a theory for learning performance using the replica method. We compare the MCMC and VB/EP algorithm results with simulated data to the theoretical prediction. The results for MCMC agree closely with the theory as expected. Results for VB/EP are slightly sub-optimal but show that the new algorithm is effective for sparse inference. In large-scale problems MCMC is infeasible due to computational limitations and the VB/EP algorithm then provides a very useful computationally efficient alternative.

  3. Inference algorithms and learning theory for Bayesian sparse factor analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rattray, Magnus; Sharp, Kevin [School of Computer Science, University of Manchester, Manchester M13 9PL (United Kingdom); Stegle, Oliver [Max-Planck-Institute for Biological Cybernetics, Tuebingen (Germany); Winn, John, E-mail: magnus.rattray@manchester.ac.u [Microsoft Research Cambridge, Roger Needham Building, Cambridge, CB3 0FB (United Kingdom)

    2009-12-01

    Bayesian sparse factor analysis has many applications; for example, it has been applied to the problem of inferring a sparse regulatory network from gene expression data. We describe a number of inference algorithms for Bayesian sparse factor analysis using a slab and spike mixture prior. These include well-established Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms as well as a novel hybrid of VB and Expectation Propagation (EP). For the case of a single latent factor we derive a theory for learning performance using the replica method. We compare the MCMC and VB/EP algorithm results with simulated data to the theoretical prediction. The results for MCMC agree closely with the theory as expected. Results for VB/EP are slightly sub-optimal but show that the new algorithm is effective for sparse inference. In large-scale problems MCMC is infeasible due to computational limitations and the VB/EP algorithm then provides a very useful computationally efficient alternative.

  4. Development of a Computer-Based Visualised Quantitative Learning System for Playing Violin Vibrato

    Science.gov (United States)

    Ho, Tracy Kwei-Liang; Lin, Huann-shyang; Chen, Ching-Kong; Tsai, Jih-Long

    2015-01-01

    Traditional methods of teaching music are largely subjective, with the lack of objectivity being particularly challenging for violin students learning vibrato because of the existence of conflicting theories. By using a computer-based analysis method, this study found that maintaining temporal coincidence between the intensity peak and the target…

  5. Linking theory to practice in learning technology research

    OpenAIRE

    Cathy Gunn; Caroline Steel

    2012-01-01

    We present a case to reposition theory so that it plays a pivotal role in learning technology research and helps to build an ecology of learning. To support the case, we present a critique of current practice based on a review of articles published in two leading international journals from 2005 to 2010. Our study reveals that theory features only incidentally or not at all in many cases. We propose theory development as a unifying theme for learning technology research study design and repor...

  6. The Attribution Theory of Learning and Advising Students on Academic Probation

    Science.gov (United States)

    Demetriou, Cynthia

    2011-01-01

    Academic advisors need to be knowledgeable of the ways students learn. To aid advisors in their exploration of learning theories, I provide an overview of the attribution theory of learning, including recent applications of the theory to research in college student learning. An understanding of this theory may help advisors understand student…

  7. Learning theories application in nursing education

    OpenAIRE

    Aliakbari, Fatemeh; Parvin, Neda; Heidari, Mohammad; Haghani, Fariba

    2015-01-01

    Learning theories are the main guide for educational systems planning in the classroom and clinical training included in nursing. The teachers by knowing the general principles of these theories can use their knowledge more effectively according to various learning situations. In this study, Eric, Medline, and Cochrane databases were used for articles in English and for the Persian literature, Magiran, Iran doc, Iran medex, and Sid databases were used with the help of keywords including socia...

  8. Learning theory of distributed spectral algorithms

    International Nuclear Information System (INIS)

    Guo, Zheng-Chu; Lin, Shao-Bo; Zhou, Ding-Xuan

    2017-01-01

    Spectral algorithms have been widely used and studied in learning theory and inverse problems. This paper is concerned with distributed spectral algorithms, for handling big data, based on a divide-and-conquer approach. We present a learning theory for these distributed kernel-based learning algorithms in a regression framework including nice error bounds and optimal minimax learning rates achieved by means of a novel integral operator approach and a second order decomposition of inverse operators. Our quantitative estimates are given in terms of regularity of the regression function, effective dimension of the reproducing kernel Hilbert space, and qualification of the filter function of the spectral algorithm. They do not need any eigenfunction or noise conditions and are better than the existing results even for the classical family of spectral algorithms. (paper)

  9. Students' Perceptions of Computer-Based Learning Environments, Their Attitude towards Business Statistics, and Their Academic Achievement: Implications from a UK University

    Science.gov (United States)

    Nguyen, ThuyUyen H.; Charity, Ian; Robson, Andrew

    2016-01-01

    This study investigates students' perceptions of computer-based learning environments, their attitude towards business statistics, and their academic achievement in higher education. Guided by learning environments concepts and attitudinal theory, a theoretical model was proposed with two instruments, one for measuring the learning environment and…

  10. Learning by statistical cooperation of self-interested neuron-like computing elements.

    Science.gov (United States)

    Barto, A G

    1985-01-01

    Since the usual approaches to cooperative computation in networks of neuron-like computating elements do not assume that network components have any "preferences", they do not make substantive contact with game theoretic concepts, despite their use of some of the same terminology. In the approach presented here, however, each network component, or adaptive element, is a self-interested agent that prefers some inputs over others and "works" toward obtaining the most highly preferred inputs. Here we describe an adaptive element that is robust enough to learn to cooperate with other elements like itself in order to further its self-interests. It is argued that some of the longstanding problems concerning adaptation and learning by networks might be solvable by this form of cooperativity, and computer simulation experiments are described that show how networks of self-interested components that are sufficiently robust can solve rather difficult learning problems. We then place the approach in its proper historical and theoretical perspective through comparison with a number of related algorithms. A secondary aim of this article is to suggest that beyond what is explicitly illustrated here, there is a wealth of ideas from game theory and allied disciplines such as mathematical economics that can be of use in thinking about cooperative computation in both nervous systems and man-made systems.

  11. Learning Universal Computations with Spikes

    Science.gov (United States)

    Thalmeier, Dominik; Uhlmann, Marvin; Kappen, Hilbert J.; Memmesheimer, Raoul-Martin

    2016-01-01

    Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them. PMID:27309381

  12. Developing Scale for Assimilate the Integration between Learning Theories and E-learning.

    Directory of Open Access Journals (Sweden)

    George Maher Iskander

    2014-03-01

    Full Text Available As e-learning tend to get more and more significant for all kind of universities, researchers and consultants are becoming aware of the fact that a high technology approach and Blackboard do not guarantee successful teaching and learning. Thus, a move to pedagogy-based theories can be observed within the field of e-learning. This study describes the procedure of the development of an empirically-based psychometrically-sound instrument to measure instructional model for e-learning system at Middle East universities. In order to accelerate the acceptance of e-learning and implementation of institution-wide adoption of e-learning, it is important to understand students' perceptions with instructional model for e- learning. The 19-item scale developed shows a high probability of differentiating between positive and negative perceptions and the methods which can be used for embedding the traditional learning theories into e-learning.

  13. Hamiltonian lattice field theory: Computer calculations using variational methods

    International Nuclear Information System (INIS)

    Zako, R.L.

    1991-01-01

    I develop a variational method for systematic numerical computation of physical quantities -- bound state energies and scattering amplitudes -- in quantum field theory. An infinite-volume, continuum theory is approximated by a theory on a finite spatial lattice, which is amenable to numerical computation. I present an algorithm for computing approximate energy eigenvalues and eigenstates in the lattice theory and for bounding the resulting errors. I also show how to select basis states and choose variational parameters in order to minimize errors. The algorithm is based on the Rayleigh-Ritz principle and Kato's generalizations of Temple's formula. The algorithm could be adapted to systems such as atoms and molecules. I show how to compute Green's functions from energy eigenvalues and eigenstates in the lattice theory, and relate these to physical (renormalized) coupling constants, bound state energies and Green's functions. Thus one can compute approximate physical quantities in a lattice theory that approximates a quantum field theory with specified physical coupling constants. I discuss the errors in both approximations. In principle, the errors can be made arbitrarily small by increasing the size of the lattice, decreasing the lattice spacing and computing sufficiently long. Unfortunately, I do not understand the infinite-volume and continuum limits well enough to quantify errors due to the lattice approximation. Thus the method is currently incomplete. I apply the method to real scalar field theories using a Fock basis of free particle states. All needed quantities can be calculated efficiently with this basis. The generalization to more complicated theories is straightforward. I describe a computer implementation of the method and present numerical results for simple quantum mechanical systems

  14. Hamiltonian lattice field theory: Computer calculations using variational methods

    International Nuclear Information System (INIS)

    Zako, R.L.

    1991-01-01

    A variational method is developed for systematic numerical computation of physical quantities-bound state energies and scattering amplitudes-in quantum field theory. An infinite-volume, continuum theory is approximated by a theory on a finite spatial lattice, which is amenable to numerical computation. An algorithm is presented for computing approximate energy eigenvalues and eigenstates in the lattice theory and for bounding the resulting errors. It is shown how to select basis states and choose variational parameters in order to minimize errors. The algorithm is based on the Rayleigh-Ritz principle and Kato's generalizations of Temple's formula. The algorithm could be adapted to systems such as atoms and molecules. It is shown how to compute Green's functions from energy eigenvalues and eigenstates in the lattice theory, and relate these to physical (renormalized) coupling constants, bound state energies and Green's functions. Thus one can compute approximate physical quantities in a lattice theory that approximates a quantum field theory with specified physical coupling constants. The author discusses the errors in both approximations. In principle, the errors can be made arbitrarily small by increasing the size of the lattice, decreasing the lattice spacing and computing sufficiently long. Unfortunately, the author does not understand the infinite-volume and continuum limits well enough to quantify errors due to the lattice approximation. Thus the method is currently incomplete. The method is applied to real scalar field theories using a Fock basis of free particle states. All needed quantities can be calculated efficiently with this basis. The generalization to more complicated theories is straightforward. The author describes a computer implementation of the method and present numerical results for simple quantum mechanical systems

  15. Applying activity theory to computer-supported collaborative learning and work-based activities in corporate settings

    NARCIS (Netherlands)

    Collis, Betty; Margaryan, A.

    2004-01-01

    Business needs in many corporations call for learning outcomes that involve problem solutions, and creating and sharing new knowledge within worksplace situation that may involve collaboration among members of a team. We argue that work-based activities (WBA) and computer-supported collaborative

  16. Smart learning objects for smart education in computer science theory, methodology and robot-based implementation

    CERN Document Server

    Stuikys, Vytautas

    2015-01-01

    This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist a

  17. Computer and machine vision theory, algorithms, practicalities

    CERN Document Server

    Davies, E R

    2012-01-01

    Computer and Machine Vision: Theory, Algorithms, Practicalities (previously entitled Machine Vision) clearly and systematically presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fourth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date tutorial text suitable for graduate students, researchers and R&D engineers working in this vibrant subject. Key features include: Practical examples and case studies give the 'ins and outs' of developing real-world vision systems, giving engineers the realities of implementing the principles in practice New chapters containing case studies on surveillance and driver assistance systems give practical methods on these cutting-edge applications in computer vision Necessary mathematics and essential theory are made approachable by careful explanations and well-il...

  18. Fluid Dynamics Theory, Computation, and Numerical Simulation

    CERN Document Server

    Pozrikidis, Constantine

    2009-01-01

    Fluid Dynamics: Theory, Computation, and Numerical Simulation is the only available book that extends the classical field of fluid dynamics into the realm of scientific computing in a way that is both comprehensive and accessible to the beginner. The theory of fluid dynamics, and the implementation of solution procedures into numerical algorithms, are discussed hand-in-hand and with reference to computer programming. This book is an accessible introduction to theoretical and computational fluid dynamics (CFD), written from a modern perspective that unifies theory and numerical practice. There are several additions and subject expansions in the Second Edition of Fluid Dynamics, including new Matlab and FORTRAN codes. Two distinguishing features of the discourse are: solution procedures and algorithms are developed immediately after problem formulations are presented, and numerical methods are introduced on a need-to-know basis and in increasing order of difficulty. Matlab codes are presented and discussed for ...

  19. Learning "in" or "with" Games? Quality Criteria for Digital Learning Games from the Perspectives of Learning, Emotion, and Motivation Theory

    Science.gov (United States)

    Hense, Jan; Mandl, Heinz

    2012-01-01

    This conceptual paper aims to clarify the theoretical underpinnings of game based learning (GBL) and learning with digital learning games (DLGs). To do so, it analyses learning of game related skills and contents, which occurs constantly during playing conventional entertainment games, from three perspectives: learning theory, emotion theory, and…

  20. Learning Theory Bases of Communicative Methodology and the Notional/Functional Syllabus

    OpenAIRE

    Jacqueline D., Beebe

    1992-01-01

    This paper examines the learning theories that underlie the philosophy and practices known as communicative language teaching methodology. These theories are identified first as a reaction against the behavioristic learning theory of audiolingualism. Approaches to syllabus design based on both the "weak" version of communicative language teaching-learning to use the second language-and the "strong" version-using the second language to learn it-are examined. The application of cognitive theory...

  1. Connecting Expectations and Values: Students' Perceptions of Developmental Mathematics in a Computer-Based Learning Environment

    Science.gov (United States)

    Jackson, Karen Latrice Terrell

    2014-01-01

    Students' perceptions influence their expectations and values. According to Expectations and Values Theory of Achievement Motivation (EVT-AM), students' expectations and values impact their behaviors (Eccles & Wigfield, 2002). This study seeks to find students' perceptions of developmental mathematics in a mastery learning computer-based…

  2. Introduction to Views of Connectivism Theory of Learning

    Directory of Open Access Journals (Sweden)

    Sa’adi Sa’adi

    2016-07-01

    Full Text Available ‘Traditional’ theories of learning as pratical dimensions of psychology majorly tend to focus their interest on humans’ inner factors that influence the process of learning such as intelligences, motivation, interest, attitude, concentration and aptitude. They never connect it with instruments and technological inventions such as multimedia, cyber celluler, internet, even social organization, cultural values, traditions etc., while these are very influential nowdays towards the progress and behaviors of human life. As such the application of connectivism theory of learning which connect those dimensions of life with learning activities, is now and then insparable from any effort to promote the quality of humans’ learning itself, including in teaching and learning languages.

  3. Fluid dynamics theory, computation, and numerical simulation

    CERN Document Server

    Pozrikidis, C

    2001-01-01

    Fluid Dynamics Theory, Computation, and Numerical Simulation is the only available book that extends the classical field of fluid dynamics into the realm of scientific computing in a way that is both comprehensive and accessible to the beginner The theory of fluid dynamics, and the implementation of solution procedures into numerical algorithms, are discussed hand-in-hand and with reference to computer programming This book is an accessible introduction to theoretical and computational fluid dynamics (CFD), written from a modern perspective that unifies theory and numerical practice There are several additions and subject expansions in the Second Edition of Fluid Dynamics, including new Matlab and FORTRAN codes Two distinguishing features of the discourse are solution procedures and algorithms are developed immediately after problem formulations are presented, and numerical methods are introduced on a need-to-know basis and in increasing order of difficulty Matlab codes are presented and discussed for a broad...

  4. Simulation Methodology in Nursing Education and Adult Learning Theory

    Science.gov (United States)

    Rutherford-Hemming, Tonya

    2012-01-01

    Simulation is often used in nursing education as a teaching methodology. Simulation is rooted in adult learning theory. Three learning theories, cognitive, social, and constructivist, explain how learners gain knowledge with simulation experiences. This article takes an in-depth look at each of these three theories as each relates to simulation.…

  5. Computational Aspects of Cooperative Game Theory

    CERN Document Server

    Chalkiadakis, Georgios; Wooldridge, Michael

    2011-01-01

    Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representation

  6. Reflection of Learning Theories in Iranian ELT Textbooks

    Science.gov (United States)

    Neghad, Hossein Hashem

    2014-01-01

    This study was undertaken to evaluate Iranian ELT English textbooks (Senior High school and Pre-University) in the light of three learning theories i.e., behaviourism, cognitivism, and constructivism. Each of these learning theories embedding an array of instructional strategies and techniques acted as evaluation checklist. That is, Iranian ELT…

  7. Jigsaw Cooperative Learning: Acid-Base Theories

    Science.gov (United States)

    Tarhan, Leman; Sesen, Burcin Acar

    2012-01-01

    This study focused on investigating the effectiveness of jigsaw cooperative learning instruction on first-year undergraduates' understanding of acid-base theories. Undergraduates' opinions about jigsaw cooperative learning instruction were also investigated. The participants of this study were 38 first-year undergraduates in chemistry education…

  8. National Computational Infrastructure for Lattice Gauge Theory

    Energy Technology Data Exchange (ETDEWEB)

    Brower, Richard C.

    2014-04-15

    SciDAC-2 Project The Secret Life of Quarks: National Computational Infrastructure for Lattice Gauge Theory, from March 15, 2011 through March 14, 2012. The objective of this project is to construct the software needed to study quantum chromodynamics (QCD), the theory of the strong interactions of sub-atomic physics, and other strongly coupled gauge field theories anticipated to be of importance in the energy regime made accessible by the Large Hadron Collider (LHC). It builds upon the successful efforts of the SciDAC-1 project National Computational Infrastructure for Lattice Gauge Theory, in which a QCD Applications Programming Interface (QCD API) was developed that enables lattice gauge theorists to make effective use of a wide variety of massively parallel computers. This project serves the entire USQCD Collaboration, which consists of nearly all the high energy and nuclear physicists in the United States engaged in the numerical study of QCD and related strongly interacting quantum field theories. All software developed in it is publicly available, and can be downloaded from a link on the USQCD Collaboration web site, or directly from the github repositories with entrance linke http://usqcd-software.github.io

  9. Individual Differences and Learning Performance in Computer-based Training

    Science.gov (United States)

    2011-02-01

    learning style theories (e.g., Kolb , 1984) are often enthusiastic devotees. There is a thriving industry publishing learning -styles instruments and...and understanding (pp. 31–64). Hillsdale, N.J.: Erlbaum. Kolb , D. A. (1984). Experiential learning : experience as the source of learning and...opportunities to have control over their learning experience than traditional classroom instruction (Sitzmann et al., 2006), using self-regulation theories

  10. Task-Based Language Teaching and Expansive Learning Theory

    Science.gov (United States)

    Robertson, Margaret

    2014-01-01

    Task-Based Language Teaching (TBLT) has become increasingly recognized as an effective pedagogy, but its location in generalized sociocultural theories of learning has led to misunderstandings and criticism. The purpose of this article is to explain the congruence between TBLT and Expansive Learning Theory and the benefits of doing so. The merit…

  11. Learning Style and Attitude toward Computer among Iranian Medical Students

    Directory of Open Access Journals (Sweden)

    Seyedeh Shohreh Alavi

    2016-02-01

    Full Text Available Background and purpose: Presently, the method of medical teaching has shifted from lecture-based to computer-based. The learning style may play a key role in the attitude toward learning computer. The goal of this study was to study the relationship between the learning style and attitude toward computer among Iranian medical students.Methods: This cross-sectional study included 400 medical students. Barsch learning style inventory and a questionnaire on the attitude toward computer was sent to each student. The enthusiasm, anxiety, and overall attitude toward computer were compared among the different learning styles.Results: The response rate to the questionnaire was 91.8%. The distribution of learning styles in the students was 181 (49.3% visual, 106 (28.9% auditory, 27 (7.4% tactual, and 53 (14.4% overall. Visual learners were less anxious for computer use and showed more positive attitude toward computer. Sex, age, and academic grade were not associated with students’ attitude toward computer.Conclusions: The learning style is an important factor in the students’ attitude toward computer among medical students, which should be considered in planning computer-based learning programs.Keywords: LEARNING STYLE, ATTITUDE, COMPUTER, MEDICAL STUDENT, ANXIETY, ENTHUSIASM

  12. Computer use changes generalization of movement learning.

    Science.gov (United States)

    Wei, Kunlin; Yan, Xiang; Kong, Gaiqing; Yin, Cong; Zhang, Fan; Wang, Qining; Kording, Konrad Paul

    2014-01-06

    Over the past few decades, one of the most salient lifestyle changes for us has been the use of computers. For many of us, manual interaction with a computer occupies a large portion of our working time. Through neural plasticity, this extensive movement training should change our representation of movements (e.g., [1-3]), just like search engines affect memory [4]. However, how computer use affects motor learning is largely understudied. Additionally, as virtually all participants in studies of perception and actions are computer users, a legitimate question is whether insights from these studies bear the signature of computer-use experience. We compared non-computer users with age- and education-matched computer users in standard motor learning experiments. We found that people learned equally fast but that non-computer users generalized significantly less across space, a difference negated by two weeks of intensive computer training. Our findings suggest that computer-use experience shaped our basic sensorimotor behaviors, and this influence should be considered whenever computer users are recruited as study participants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Abstraction/Representation Theory for heterotic physical computing.

    Science.gov (United States)

    Horsman, D C

    2015-07-28

    We give a rigorous framework for the interaction of physical computing devices with abstract computation. Device and program are mediated by the non-logical representation relation; we give the conditions under which representation and device theory give rise to commuting diagrams between logical and physical domains, and the conditions for computation to occur. We give the interface of this new framework with currently existing formal methods, showing in particular its close relationship to refinement theory, and the implications for questions of meaning and reference in theoretical computer science. The case of hybrid computing is considered in detail, addressing in particular the example of an Internet-mediated social machine, and the abstraction/representation framework used to provide a formal distinction between heterotic and hybrid computing. This forms the basis for future use of the framework in formal treatments of non-standard physical computers. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  14. A learning-style theory for understanding autistic behaviors

    Directory of Open Access Journals (Sweden)

    Ning eQian

    2011-08-01

    Full Text Available Understanding autism’s ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically-developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup-table (LUT learning, which aims to store experiences precisely, to interpolation (INT learning, which focuses on extracting underlying statistical structure (regularities from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low and high dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name-number association in a phonebook. However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response. The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm, restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity, impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn

  15. A Learning-Style Theory for Understanding Autistic Behaviors

    Science.gov (United States)

    Qian, Ning; Lipkin, Richard M.

    2011-01-01

    Understanding autism's ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup table (LUT) learning, which aims to store experiences precisely, to interpolation (INT) learning, which focuses on extracting underlying statistical structure (regularities) from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low- and high-dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name–number association in a phonebook). However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response). The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm), restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity), impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn regularities

  16. Students experiences with collaborative learning in asynchronous computer-supported collaborative learning environments.

    NARCIS (Netherlands)

    Dewiyanti, Silvia; Brand-Gruwel, Saskia; Jochems, Wim; Broers, Nick

    2008-01-01

    Dewiyanti, S., Brand-Gruwel, S., Jochems, W., & Broers, N. (2007). Students experiences with collaborative learning in asynchronous computer-supported collaborative learning environments. Computers in Human Behavior, 23, 496-514.

  17. Motivation to learn: an overview of contemporary theories.

    Science.gov (United States)

    Cook, David A; Artino, Anthony R

    2016-10-01

    To succinctly summarise five contemporary theories about motivation to learn, articulate key intersections and distinctions among these theories, and identify important considerations for future research. Motivation has been defined as the process whereby goal-directed activities are initiated and sustained. In expectancy-value theory, motivation is a function of the expectation of success and perceived value. Attribution theory focuses on the causal attributions learners create to explain the results of an activity, and classifies these in terms of their locus, stability and controllability. Social- cognitive theory emphasises self-efficacy as the primary driver of motivated action, and also identifies cues that influence future self-efficacy and support self-regulated learning. Goal orientation theory suggests that learners tend to engage in tasks with concerns about mastering the content (mastery goal, arising from a 'growth' mindset regarding intelligence and learning) or about doing better than others or avoiding failure (performance goals, arising from a 'fixed' mindset). Finally, self-determination theory proposes that optimal performance results from actions motivated by intrinsic interests or by extrinsic values that have become integrated and internalised. Satisfying basic psychosocial needs of autonomy, competence and relatedness promotes such motivation. Looking across all five theories, we note recurrent themes of competence, value, attributions, and interactions between individuals and the learning context. To avoid conceptual confusion, and perhaps more importantly to maximise the theory-building potential of their work, researchers must be careful (and precise) in how they define, operationalise and measure different motivational constructs. We suggest that motivation research continue to build theory and extend it to health professions domains, identify key outcomes and outcome measures, and test practical educational applications of the principles

  18. New supervised learning theory applied to cerebellar modeling for suppression of variability of saccade end points.

    Science.gov (United States)

    Fujita, Masahiko

    2013-06-01

    A new supervised learning theory is proposed for a hierarchical neural network with a single hidden layer of threshold units, which can approximate any continuous transformation, and applied to a cerebellar function to suppress the end-point variability of saccades. In motor systems, feedback control can reduce noise effects if the noise is added in a pathway from a motor center to a peripheral effector; however, it cannot reduce noise effects if the noise is generated in the motor center itself: a new control scheme is necessary for such noise. The cerebellar cortex is well known as a supervised learning system, and a novel theory of cerebellar cortical function developed in this study can explain the capability of the cerebellum to feedforwardly reduce noise effects, such as end-point variability of saccades. This theory assumes that a Golgi-granule cell system can encode the strength of a mossy fiber input as the state of neuronal activity of parallel fibers. By combining these parallel fiber signals with appropriate connection weights to produce a Purkinje cell output, an arbitrary continuous input-output relationship can be obtained. By incorporating such flexible computation and learning ability in a process of saccadic gain adaptation, a new control scheme in which the cerebellar cortex feedforwardly suppresses the end-point variability when it detects a variation in saccadic commands can be devised. Computer simulation confirmed the efficiency of such learning and showed a reduction in the variability of saccadic end points, similar to results obtained from experimental data.

  19. Kolb's Experiential Learning Theory in Athletic Training Education: A Literature Review

    Science.gov (United States)

    Schellhase, Kristen C.

    2008-01-01

    Objective: Kolb's Experiential Learning Theory offers insight into the development of learning styles, classification of learning styles, and how students learn through experience. Discussion is presented on the value of Kolb's Experiential Learning Theory for Athletic Training Education. Data Sources: This article reviews research related to…

  20. Constructing a Grounded Theory of E-Learning Assessment

    Science.gov (United States)

    Alonso-Díaz, Laura; Yuste-Tosina, Rocío

    2015-01-01

    This study traces the development of a grounded theory of assessment in e-learning environments, a field in need of research to establish the parameters of an assessment that is both reliable and worthy of higher learning accreditation. Using grounded theory as a research method, we studied an e-assessment model that does not require physical…

  1. Developing a Domain Theory Defining and Exemplifying a Learning Theory of Progressive Attainments

    Science.gov (United States)

    Bunderson, C. Victor

    2011-01-01

    This article defines the concept of Domain Theory, or, when educational measurement is the goal, one might call it a "Learning Theory of Progressive Attainments in X Domain". The concept of Domain Theory is first shown to be rooted in validity theory, then the concept of domain theory is expanded to amplify its necessary but long neglected…

  2. Mobile Learning in Secondary Education: Teachers' and Students' Perceptions and Acceptance of Tablet Computers

    Science.gov (United States)

    Montrieux, Hannelore; Courtois, Cédric; De Grove, Frederik; Raes, Annelies; Schellens, Tammy; De Marez, Lieven

    2014-01-01

    This paper examines the school-wide introduction of the tablet computer as a mobile learning tool in a secondary school in Belgium. Drawing upon the Decomposed Theory of Planned Behavior, we question during three waves of data collection which factors influence teachers' and students' acceptance and use of these devices for educational purposes.…

  3. Theories of computational complexity

    CERN Document Server

    Calude, C

    1988-01-01

    This volume presents four machine-independent theories of computational complexity, which have been chosen for their intrinsic importance and practical relevance. The book includes a wealth of results - classical, recent, and others which have not been published before.In developing the mathematics underlying the size, dynamic and structural complexity measures, various connections with mathematical logic, constructive topology, probability and programming theories are established. The facts are presented in detail. Extensive examples are provided, to help clarify notions and constructions. The lists of exercises and problems include routine exercises, interesting results, as well as some open problems.

  4. Social Play at the Computer: Preschoolers Scaffold and Support Peers' Computer Competence.

    Science.gov (United States)

    Freeman, Nancy K.; Somerindyke, Jennifer

    2001-01-01

    Describes preschoolers' collaboration during free play in a computer lab, focusing on the computer's contribution to active, peer-mediated learning. Discusses these observations in terms of Parten's insights on children's social play and Vygotsky's socio-cultural learning theory, noting that the children scaffolded each other's growing computer…

  5. Developing the master learner: applying learning theory to the learner, the teacher, and the learning environment.

    Science.gov (United States)

    Schumacher, Daniel J; Englander, Robert; Carraccio, Carol

    2013-11-01

    As a result of the paradigm shift to a competency-based framework, both self-directed lifelong learning and learner-centeredness have become essential tenets of medical education. In the competency-based framework, learners drive their own educational process, and both learners and teachers share the responsibility for the path and content of learning. This learner-centered emphasis requires each physician to develop and maintain lifelong learning skills, which the authors propose culminate in becoming a "master leaner." To better understand the development of these skills and the attainment of that goal, the authors explore how learning theories inform the development of master learners and how to translate these theories into practical strategies for the learner, the teacher, and the learning environment so as to optimize this development.The authors begin by exploring self-determination theory, which lays the groundwork for understanding the motivation to learn. They next consider the theories of cognitive load and situated cognition, which inform the optimal context and environment for learning. Building from this foundation, the authors consider key educational theories that affect learners' abilities to serve as primary drivers of their learning, including self-directed learning (SDL); the self-assessment skills necessary for SDL; factors affecting self-assessment (self-concept, self-efficacy, illusory superiority, gap filling); and ways to mitigate the inaccuracies of self-assessment (reflection, self-monitoring, external information seeking, and self-directed assessment seeking).For each theory, they suggest practical action steps for the learner, the teacher, and the learning environment in an effort to provide a road map for developing master learners.

  6. Gender, general theory of crime and computer crime: an empirical test.

    Science.gov (United States)

    Moon, Byongook; McCluskey, John D; McCluskey, Cynthia P; Lee, Sangwon

    2013-04-01

    Regarding the gender gap in computer crime, studies consistently indicate that boys are more likely than girls to engage in various types of computer crime; however, few studies have examined the extent to which traditional criminology theories account for gender differences in computer crime and the applicability of these theories in explaining computer crime across gender. Using a panel of 2,751 Korean youths, the current study tests the applicability of the general theory of crime in explaining the gender gap in computer crime and assesses the theory's utility in explaining computer crime across gender. Analyses show that self-control theory performs well in predicting illegal use of others' resident registration number (RRN) online for both boys and girls, as predicted by the theory. However, low self-control, a dominant criminogenic factor in the theory, fails to mediate the relationship between gender and computer crime and is inadequate in explaining illegal downloading of software in both boy and girl models. Theoretical implication of the findings and the directions for future research are discussed.

  7. Repositioning Ideology Critique in a Critical Theory of Adult Learning.

    Science.gov (United States)

    Brookfield, Stephen

    2001-01-01

    Reexamines critical theory as a response to Marxism and repositions ideology critique as a crucial adult learning process. Argues that a critical theory of adult learning should focus on how adults learn to recognize and challenge ideological domination and manipulation. (Contains 31 references.) (SK)

  8. Learning Theory Applied to the Biology Classroom.

    Science.gov (United States)

    Novak, Joseph D.

    1980-01-01

    The material presented in this article is intended to help students learn how to learn. The seven key concepts of David Ausubel's assimilation theory for cognitive learning are discussed with reference to the classroom. Concept mapping is suggested as a tool for demonstrating how the seven key concepts function. (SA)

  9. Multimedia for occupational safety and health training: a pilot study examining a multimedia learning theory.

    Science.gov (United States)

    Wallen, Erik S; Mulloy, Karen B

    2006-10-01

    Occupational diseases are a significant problem affecting public health. Safety training is an important method of preventing occupational illness. Training is increasingly being delivered by computer although theories of learning from computer-based multimedia have been tested almost entirely on college students. This study was designed to determine whether these theories might also be applied to safety training applications for working adults. Participants viewed either computer-based multimedia respirator use training with concurrent narration, narration prior to the animation, or unrelated safety training. Participants then took a five-item transfer test which measured their ability to use their knowledge in new and creative ways. Participants who viewed the computer-based multimedia trainings both did significantly better than the control group on the transfer test. The results of this pilot study suggest that design guidelines developed for younger learners may be effective for training workers in occupational safety and health although more investigation is needed.

  10. Cloud Computing Benefits for E-learning Solutions

    OpenAIRE

    Paul POCATILU

    2010-01-01

    E-learning systems usually require many hardware and software resources. There are many educational institutions that cannot afford such investments, and cloud computing is the best solution. This paper presents the impact on using cloud computing for e-learning solutions.

  11. On-the-Job Training and Social Learning Theory. A Literature Review

    Science.gov (United States)

    1980-05-01

    and discussed by Albert Bandura (47). The principles of social learning theory and learning from models are first described. Then a series of rules...developed by Bandura and his students (47, 48, 49) to be the most useful theory to account for observational learning and to provide a basis for...Learning Theory and Its Application 47. Bandura , A. Principles of Behavior Modification, New York: Holt, Rinehart & Winston, 1969. 48. Bandura , A

  12. Elements of quantum computing history, theories and engineering applications

    CERN Document Server

    Akama, Seiki

    2015-01-01

    A quantum computer is a computer based on a computational model which uses quantum mechanics, which is a subfield of physics to study phenomena at the micro level. There has been a growing interest on quantum computing in the 1990's, and some quantum computers at the experimental level were recently implemented. Quantum computers enable super-speed computation, and can solve some important problems whose solutions were regarded impossible or intractable with traditional computers. This book provides a quick introduction to quantum computing for readers who have no backgrounds of both theory of computation and quantum mechanics. “Elements of Quantum Computing” presents the history, theories, and engineering applications of quantum computing. The book is suitable to computer scientists, physicist, and software engineers.

  13. Designs 2002 further computational and constructive design theory

    CERN Document Server

    2003-01-01

    This volume is a sequel to the 1996 compilation, Computational and Constructive Design Theory. It contains research papers and surveys of recent research work on two closely related aspects of the study of combinatorial designs: design construction and computer-aided study of designs. Audience: This volume is suitable for researchers in the theory of combinatorial designs

  14. Linking Theory to Practice in Learning Technology Research

    Science.gov (United States)

    Gunn, Cathy; Steel, Caroline

    2012-01-01

    We present a case to reposition theory so that it plays a pivotal role in learning technology research and helps to build an ecology of learning. To support the case, we present a critique of current practice based on a review of articles published in two leading international journals from 2005 to 2010. Our study reveals that theory features only…

  15. Fluid dynamics theory, computation, and numerical simulation

    CERN Document Server

    Pozrikidis, C

    2017-01-01

    This book provides an accessible introduction to the basic theory of fluid mechanics and computational fluid dynamics (CFD) from a modern perspective that unifies theory and numerical computation. Methods of scientific computing are introduced alongside with theoretical analysis and MATLAB® codes are presented and discussed for a broad range of topics: from interfacial shapes in hydrostatics, to vortex dynamics, to viscous flow, to turbulent flow, to panel methods for flow past airfoils. The third edition includes new topics, additional examples, solved and unsolved problems, and revised images. It adds more computational algorithms and MATLAB programs. It also incorporates discussion of the latest version of the fluid dynamics software library FDLIB, which is freely available online. FDLIB offers an extensive range of computer codes that demonstrate the implementation of elementary and advanced algorithms and provide an invaluable resource for research, teaching, classroom instruction, and self-study. This ...

  16. The application of learning theory in horse training

    DEFF Research Database (Denmark)

    McLean, Andrew N.; Christensen, Janne Winther

    2017-01-01

    The millennia-old practices of horse training markedly predate and thus were isolated from the mid-twentieth century revelation of animal learning processes. From this standpoint, the progress made in the application and understanding of learning theory in horse training is reviewed including...... on the correct application of learning theory, and safety and welfare benefits for people and horses would follow. Finally it is also proposed that the term ‘conflict theory’ be taken up in equitation science to facilitate diagnosis of training-related behaviour disorders and thus enable the emergence...

  17. Theory of mind selectively predicts preschoolers' knowledge-based selective word learning.

    Science.gov (United States)

    Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

    2015-11-01

    Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory-of-mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children's preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children's developing social cognition and early learning. © 2015 The British Psychological Society.

  18. Theory of mind selectively predicts preschoolers’ knowledge-based selective word learning

    Science.gov (United States)

    Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

    2015-01-01

    Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory of mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children’s preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children’s developing social cognition and early learning. PMID:26211504

  19. Connectivism: Learning theory of the future or vestige of the past?

    Directory of Open Access Journals (Sweden)

    Rita Kop

    2008-10-01

    Full Text Available Siemens and Downes initially received increasing attention in the blogosphere in 2005 when they discussed their ideas concerning distributed knowledge. An extended discourse has ensued in and around the status of ‘connectivism’ as a learning theory for the digital age. This has led to a number of questions in relation to existing learning theories. Do they still meet the needs of today’s learners, and anticipate the needs of learners of the future? Would a new theory that encompasses new developments in digital technology be more appropriate, and would it be suitable for other aspects of learning, including in the traditional class room, in distance education and e-learning? This paper will highlight current theories of learning and critically analyse connectivism within the context of its predecessors, to establish if it has anything new to offer as a learning theory or as an approach to teaching for the 21st Century.

  20. Computational constraints in cognitive theories of forgetting.

    Science.gov (United States)

    Ecker, Ullrich K H; Lewandowsky, Stephan

    2012-01-01

    This article highlights some of the benefits of computational modeling for theorizing in cognition. We demonstrate how computational models have been used recently to argue that (1) forgetting in short-term memory is based on interference not decay, (2) forgetting in list-learning paradigms is more parsimoniously explained by a temporal distinctiveness account than by various forms of consolidation, and (3) intrusion asymmetries that appear when information is learned in different contexts can be explained by temporal context reinstatement rather than labilization and reconsolidation processes.

  1. Interacting electrons theory and computational approaches

    CERN Document Server

    Martin, Richard M; Ceperley, David M

    2016-01-01

    Recent progress in the theory and computation of electronic structure is bringing an unprecedented level of capability for research. Many-body methods are becoming essential tools vital for quantitative calculations and understanding materials phenomena in physics, chemistry, materials science and other fields. This book provides a unified exposition of the most-used tools: many-body perturbation theory, dynamical mean field theory and quantum Monte Carlo simulations. Each topic is introduced with a less technical overview for a broad readership, followed by in-depth descriptions and mathematical formulation. Practical guidelines, illustrations and exercises are chosen to enable readers to appreciate the complementary approaches, their relationships, and the advantages and disadvantages of each method. This book is designed for graduate students and researchers who want to use and understand these advanced computational tools, get a broad overview, and acquire a basis for participating in new developments.

  2. 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...

  3. Three Theories of Learning and Their Implications for Teachers.

    Science.gov (United States)

    Ramirez, Aura I.

    Currently, three theories of learning dominate classroom practice. First, B.F. Skinner's Theory of Operant Conditioning states that if behavior, including learning behavior, is reinforced, the probability of its being repeated increases strongly. Different types and schedules of reinforcement have been studied, by Skinner and others, and the…

  4. Applying Distributed Learning Theory in Online Business Communication Courses.

    Science.gov (United States)

    Walker, Kristin

    2003-01-01

    Focuses on the critical use of technology in online formats that entail relatively new teaching media. Argues that distributed learning theory is valuable for teachers of online business communication courses for several reasons. Discusses the application of distributed learning theory to the teaching of business communication online. (SG)

  5. Developing a new experimental system for an undergraduate laboratory exercise to teach theories of visuomotor learning.

    Science.gov (United States)

    Kasuga, Shoko; Ushiba, Junichi

    2014-01-01

    Humans have a flexible motor ability to adapt their movements to changes in the internal/external environment. For example, using arm-reaching tasks, a number of studies experimentally showed that participants adapt to a novel visuomotor environment. These results helped develop computational models of motor learning implemented in the central nervous system. Despite the importance of such experimental paradigms for exploring the mechanisms of motor learning, because of the cost and preparation time, most students are unable to participate in such experiments. Therefore, in the current study, to help students better understand motor learning theories, we developed a simple finger-reaching experimental system using commonly used laptop PC components with an open-source programming language (Processing Motor Learning Toolkit: PMLT). We found that compared to a commercially available robotic arm-reaching device, our PMLT accomplished similar learning goals (difference in the error reduction between the devices, P = 0.10). In addition, consistent with previous reports from visuomotor learning studies, the participants showed after-effects indicating an adaptation of the motor learning system. The results suggest that PMLT can serve as a new experimental system for an undergraduate laboratory exercise of motor learning theories with minimal time and cost for instructors.

  6. [Linking learning theory with practice].

    Science.gov (United States)

    Ávalos-Carranza, María Teresa; Amador-Olvera, Eric; Zerón-Gutiérrez, Lydia

    2016-01-01

    It is often said that it is easier to learn what is observed and practiced on a daily basis; to the need to effectively link theory with practice considered in the process of teaching and learning, many strategies have been developed to allow this process to be carried out in a more efficiently maner. It is, therefore, very important to recognize that an appropriate teacher/student relationship is essential for students to acquire the skills and abilities required.

  7. The Computational Development of Reinforcement Learning during Adolescence.

    Directory of Open Access Journals (Sweden)

    Stefano Palminteri

    2016-06-01

    Full Text Available Adolescence is a period of life characterised by changes in learning and decision-making. Learning and decision-making do not rely on a unitary system, but instead require the coordination of different cognitive processes that can be mathematically formalised as dissociable computational modules. Here, we aimed to trace the developmental time-course of the computational modules responsible for learning from reward or punishment, and learning from counterfactual feedback. Adolescents and adults carried out a novel reinforcement learning paradigm in which participants learned the association between cues and probabilistic outcomes, where the outcomes differed in valence (reward versus punishment and feedback was either partial or complete (either the outcome of the chosen option only, or the outcomes of both the chosen and unchosen option, were displayed. Computational strategies changed during development: whereas adolescents' behaviour was better explained by a basic reinforcement learning algorithm, adults' behaviour integrated increasingly complex computational features, namely a counterfactual learning module (enabling enhanced performance in the presence of complete feedback and a value contextualisation module (enabling symmetrical reward and punishment learning. Unlike adults, adolescent performance did not benefit from counterfactual (complete feedback. In addition, while adults learned symmetrically from both reward and punishment, adolescents learned from reward but were less likely to learn from punishment. This tendency to rely on rewards and not to consider alternative consequences of actions might contribute to our understanding of decision-making in adolescence.

  8. Computational constraints in cognitive theories of forgetting

    Directory of Open Access Journals (Sweden)

    Ullrich eEcker

    2012-10-01

    Full Text Available This article highlights some of the benefits of computational modeling for theorizing in cognition. We demonstrate how computational models have been used recently to argue that (1 forgetting in short-term memory is based on interference not decay, (2 forgetting in list-learning paradigms is more parsimoniously explained by a temporal distinctiveness account than by various forms of consolidation, and (3 intrusion asymmetries that appear when information is learned in different contexts can be explained by temporal context reinstatement rather than labilization and reconsolidation processes.

  9. Intelligent Learning System using cognitive science theory and artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Cristensen, D.L.

    1986-01-01

    This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.

  10. Design of Intelligent Robot as A Tool for Teaching Media Based on Computer Interactive Learning and Computer Assisted Learning to Improve the Skill of University Student

    Science.gov (United States)

    Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.

    2018-01-01

    The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.

  11. Opportunities for discovery: Theory and computation in Basic Energy Sciences

    Energy Technology Data Exchange (ETDEWEB)

    Harmon, Bruce; Kirby, Kate; McCurdy, C. William

    2005-01-11

    New scientific frontiers, recent advances in theory, and rapid increases in computational capabilities have created compelling opportunities for theory and computation to advance the scientific mission of the Office of Basic Energy Sciences (BES). The prospects for success in the experimental programs of BES will be enhanced by pursuing these opportunities. This report makes the case for an expanded research program in theory and computation in BES. The Subcommittee on Theory and Computation of the Basic Energy Sciences Advisory Committee was charged with identifying current and emerging challenges and opportunities for theoretical research within the scientific mission of BES, paying particular attention to how computing will be employed to enable that research. A primary purpose of the Subcommittee was to identify those investments that are necessary to ensure that theoretical research will have maximum impact in the areas of importance to BES, and to assure that BES researchers will be able to exploit the entire spectrum of computational tools, including leadership class computing facilities. The Subcommittee s Findings and Recommendations are presented in Section VII of this report.

  12. Social cognitive theory, metacognition, and simulation learning in nursing education.

    Science.gov (United States)

    Burke, Helen; Mancuso, Lorraine

    2012-10-01

    Simulation learning encompasses simple, introductory scenarios requiring response to patients' needs during basic hygienic care and during situations demanding complex decision making. Simulation integrates principles of social cognitive theory (SCT) into an interactive approach to learning that encompasses the core principles of intentionality, forethought, self-reactiveness, and self-reflectiveness. Effective simulation requires an environment conducive to learning and introduces activities that foster symbolic coding operations and mastery of new skills; debriefing builds self-efficacy and supports self-regulation of behavior. Tailoring the level of difficulty to students' mastery level supports successful outcomes and motivation to set higher standards. Mindful selection of simulation complexity and structure matches course learning objectives and supports progressive development of metacognition. Theory-based facilitation of simulated learning optimizes efficacy of this learning method to foster maturation of cognitive processes of SCT, metacognition, and self-directedness. Examples of metacognition that are supported through mindful, theory-based implementation of simulation learning are provided. Copyright 2012, SLACK Incorporated.

  13. Computer Support for Vicarious Learning.

    Science.gov (United States)

    Monthienvichienchai, Rachada; Sasse, M. Angela

    This paper investigates how computer support for vicarious learning can be implemented by taking a principled approach to selecting and combining different media to capture educational dialogues. The main goal is to create vicarious learning materials of appropriate pedagogic content and production quality, and at the same time minimize the…

  14. Deep Learning for Computer Vision: A Brief Review

    Science.gov (United States)

    Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

    2018-01-01

    Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein. PMID:29487619

  15. Deep Learning for Computer Vision: A Brief Review

    Directory of Open Access Journals (Sweden)

    Athanasios Voulodimos

    2018-01-01

    Full Text Available Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

  16. Deep Learning for Computer Vision: A Brief Review.

    Science.gov (United States)

    Voulodimos, Athanasios; Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

    2018-01-01

    Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

  17. Local computations in Dempster-Shafer theory of evidence

    Czech Academy of Sciences Publication Activity Database

    Jiroušek, Radim

    2012-01-01

    Roč. 53, č. 8 (2012), s. 1155-1167 ISSN 0888-613X Grant - others:GA ČR(CZ) GAP403/12/2175 Program:GA Institutional support: RVO:67985556 Keywords : Discrete belief functions * Dempster-Shafer theory * conditional independence * decomposable model Subject RIV: IN - Informatics, Computer Science Impact factor: 1.729, year: 2012 http://library.utia.cas.cz/separaty/2012/MTR/jirousek-local computations in dempster–shafer theory of evidence. pdf

  18. Computer Assisted Language Learning (CALL): Using Internet for Effective Language Learning

    NARCIS (Netherlands)

    Kremenska, Anelly

    2006-01-01

    Please, cite this publication as: Kremenska, A. (2006). Computer Assisted Language Learning (CALL): Using Internet for Effective Language Learning. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia,

  19. The Impact of Cloud Computing Technologies in E-learning

    Directory of Open Access Journals (Sweden)

    Hosam Farouk El-Sofany

    2013-01-01

    Full Text Available Cloud computing is a new computing model which is based on the grid computing, distributed computing, parallel computing and virtualization technologies define the shape of a new technology. It is the core technology of the next generation of network computing platform, especially in the field of education, cloud computing is the basic environment and platform of the future E-learning. It provides secure data storage, convenient internet services and strong computing power. This article mainly focuses on the research of the application of cloud computing in E-learning environment. The research study shows that the cloud platform is valued for both students and instructors to achieve the course objective. The paper presents the nature, benefits and cloud computing services, as a platform for e-learning environment.

  20. An Interpretation of Dewey's Experiential Learning Theory.

    Science.gov (United States)

    Roberts, T. Grady

    "Experience and Education" (John Dewey, 1938) serves as a foundation piece of literature when discussing experiential learning. To facilitate a better understanding, a conceptual model was developed. In John Dewey's experiential learning theory, everything occurs within a social environment. Knowledge is socially constructed and based on…

  1. Utilizing Kolb’s Experiential Learning Theory to Implement a Golf Scramble

    OpenAIRE

    Glenna G. Bower

    2013-01-01

    This study introduced how Kolb’s Experiential Learning Theory was used across the four-mode learning cycle of abstract conceptualization, active experimentation, concrete experience and reflective observation as a pedagogical tool for implementing a golf scramble. The primary research question was to see whether Kolb’s Experiential Learning Theory four-mode learning cycle was an effective means for implementing a the golf scramble. The participants of the experiential learning experience wer...

  2. Exploring Cloud Computing for Distance Learning

    Science.gov (United States)

    He, Wu; Cernusca, Dan; Abdous, M'hammed

    2011-01-01

    The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

  3. Gallery Educators as Adult Learners: The Active Application of Adult Learning Theory

    Science.gov (United States)

    McCray, Kimberly H.

    2016-01-01

    In order to better understand the importance of adult learning theory to museum educators' work, and that of their profession at large, museum professionals must address the need for more adult learning research and practice in museums--particularly work informed by existing theory and work seeking to generate new theory. Adult learning theory…

  4. Virtual Learning Environments: A View from the Theory of Conceptual Fields

    Directory of Open Access Journals (Sweden)

    Iralí Araque

    2018-01-01

    Full Text Available The inclusion of communication and information technologies for formative purposes has given way to virtual learning environments, which, backed by constructivist theories, provide a theoretical and methodological framework, thus contributing to the cognitive development of students at university level, evidenced in the development of their learning schemes. The theory of conceptual fields offers an analysis of the elements of schemas and the process of knowledge construction. In this sense, the present work had as objective to raise some elements, such as teaching methodology, didactic strategies, materials and resources for learning, teacher and student roles, which should be considered in the design of virtual learning environments, in the light of the theory of conceptual fields, so as to enhance the construction of knowledge and where the emphasis of the educational process lies on learning rather than teaching. The methodology used is a documentary study, type descriptive, based on the review and bibliographical analysis of constructivist theories, as well as researchers related to the design and construction of virtual learning environments. The results show that conceptual fields theory is an excellent option to consider, as a constructivist theory, in order to consolidate the process of knowledge construction, from the individual to the collective.

  5. Filtration theory using computer simulations

    Energy Technology Data Exchange (ETDEWEB)

    Bergman, W.; Corey, I. [Lawrence Livermore National Lab., CA (United States)

    1997-08-01

    We have used commercially available fluid dynamics codes based on Navier-Stokes theory and the Langevin particle equation of motion to compute the particle capture efficiency and pressure drop through selected two- and three-dimensional fiber arrays. The approach we used was to first compute the air velocity vector field throughout a defined region containing the fiber matrix. The particle capture in the fiber matrix is then computed by superimposing the Langevin particle equation of motion over the flow velocity field. Using the Langevin equation combines the particle Brownian motion, inertia and interception mechanisms in a single equation. In contrast, most previous investigations treat the different capture mechanisms separately. We have computed the particle capture efficiency and the pressure drop through one, 2-D and two, 3-D fiber matrix elements. 5 refs., 11 figs.

  6. Introducing Scattering Theory with a Computer

    Science.gov (United States)

    Merrill, John R.

    1973-01-01

    Discusses a new method of presenting the scattering theory, including classical explanation of cross sections, quantum mechanical expressions for phase shifts, and use of a computer to solve problems. (CC)

  7. Cooperative Learning: Improving University Instruction by Basing Practice on Validated Theory

    Science.gov (United States)

    Johnson, David W.; Johnson, Roger T.; Smith, Karl A.

    2014-01-01

    Cooperative learning is an example of how theory validated by research may be applied to instructional practice. The major theoretical base for cooperative learning is social interdependence theory. It provides clear definitions of cooperative, competitive, and individualistic learning. Hundreds of research studies have validated its basic…

  8. Observational attachment theory-based parenting measures predict children's attachment narratives independently from social learning theory-based measures.

    Science.gov (United States)

    Matias, Carla; O'Connor, Thomas G; Futh, Annabel; Scott, Stephen

    2014-01-01

    Conceptually and methodologically distinct models exist for assessing quality of parent-child relationships, but few studies contrast competing models or assess their overlap in predicting developmental outcomes. Using observational methodology, the current study examined the distinctiveness of attachment theory-based and social learning theory-based measures of parenting in predicting two key measures of child adjustment: security of attachment narratives and social acceptance in peer nominations. A total of 113 5-6-year-old children from ethnically diverse families participated. Parent-child relationships were rated using standard paradigms. Measures derived from attachment theory included sensitive responding and mutuality; measures derived from social learning theory included positive attending, directives, and criticism. Child outcomes were independently-rated attachment narrative representations and peer nominations. Results indicated that Attachment theory-based and Social Learning theory-based measures were modestly correlated; nonetheless, parent-child mutuality predicted secure child attachment narratives independently of social learning theory-based measures; in contrast, criticism predicted peer-nominated fighting independently of attachment theory-based measures. In young children, there is some evidence that attachment theory-based measures may be particularly predictive of attachment narratives; however, no single model of measuring parent-child relationships is likely to best predict multiple developmental outcomes. Assessment in research and applied settings may benefit from integration of different theoretical and methodological paradigms.

  9. Sustainability of healthcare improvement: what can we learn from learning theory?

    Directory of Open Access Journals (Sweden)

    Hovlid Einar

    2012-08-01

    Full Text Available Abstract Background Changes that improve the quality of health care should be sustained. Falling back to old, unsatisfactory ways of working is a waste of resources and can in the worst case increase resistance to later initiatives to improve care. Quality improvement relies on changing the clinical system yet factors that influence the sustainability of quality improvements are poorly understood. Theoretical frameworks can guide further research on the sustainability of quality improvements. Theories of organizational learning have contributed to a better understanding of organizational change in other contexts. To identify factors contributing to sustainability of improvements, we use learning theory to explore a case that had displayed sustained improvement. Methods Førde Hospital redesigned the pathway for elective surgery and achieved sustained reduction of cancellation rates. We used a qualitative case study design informed by theory to explore factors that contributed to sustain the improvements at Førde Hospital. The model Evidence in the Learning Organization describes how organizational learning contributes to change in healthcare institutions. This model constituted the framework for data collection and analysis. We interviewed a strategic sample of 20 employees. The in-depth interviews covered themes identified through our theoretical framework. Through a process of coding and condensing, we identified common themes that were interpreted in relation to our theoretical framework. Results Clinicians and leaders shared information about their everyday work and related this knowledge to how the entire clinical pathway could be improved. In this way they developed a revised and deeper understanding of their clinical system and its interdependencies. They became increasingly aware of how different elements needed to interact to enhance the performance and how their own efforts could contribute. Conclusions The improved understanding of

  10. Sustainability of healthcare improvement: what can we learn from learning theory?

    Science.gov (United States)

    Hovlid, Einar; Bukve, Oddbjørn; Haug, Kjell; Aslaksen, Aslak Bjarne; von Plessen, Christian

    2012-08-03

    Changes that improve the quality of health care should be sustained. Falling back to old, unsatisfactory ways of working is a waste of resources and can in the worst case increase resistance to later initiatives to improve care. Quality improvement relies on changing the clinical system yet factors that influence the sustainability of quality improvements are poorly understood. Theoretical frameworks can guide further research on the sustainability of quality improvements. Theories of organizational learning have contributed to a better understanding of organizational change in other contexts. To identify factors contributing to sustainability of improvements, we use learning theory to explore a case that had displayed sustained improvement. Førde Hospital redesigned the pathway for elective surgery and achieved sustained reduction of cancellation rates. We used a qualitative case study design informed by theory to explore factors that contributed to sustain the improvements at Førde Hospital. The model Evidence in the Learning Organization describes how organizational learning contributes to change in healthcare institutions. This model constituted the framework for data collection and analysis. We interviewed a strategic sample of 20 employees. The in-depth interviews covered themes identified through our theoretical framework. Through a process of coding and condensing, we identified common themes that were interpreted in relation to our theoretical framework. Clinicians and leaders shared information about their everyday work and related this knowledge to how the entire clinical pathway could be improved. In this way they developed a revised and deeper understanding of their clinical system and its interdependencies. They became increasingly aware of how different elements needed to interact to enhance the performance and how their own efforts could contribute. The improved understanding of the clinical system represented a change in mental models of

  11. An instance theory of associative learning.

    Science.gov (United States)

    Jamieson, Randall K; Crump, Matthew J C; Hannah, Samuel D

    2012-03-01

    We present and test an instance model of associative learning. The model, Minerva-AL, treats associative learning as cued recall. Memory preserves the events of individual trials in separate traces. A probe presented to memory contacts all traces in parallel and retrieves a weighted sum of the traces, a structure called the echo. Learning of a cue-outcome relationship is measured by the cue's ability to retrieve a target outcome. The theory predicts a number of associative learning phenomena, including acquisition, extinction, reacquisition, conditioned inhibition, external inhibition, latent inhibition, discrimination, generalization, blocking, overshadowing, overexpectation, superconditioning, recovery from blocking, recovery from overshadowing, recovery from overexpectation, backward blocking, backward conditioned inhibition, and second-order retrospective revaluation. We argue that associative learning is consistent with an instance-based approach to learning and memory.

  12. The Impact of Computer Use on Learning of Quadratic Functions

    Science.gov (United States)

    Pihlap, Sirje

    2017-01-01

    Studies of the impact of various types of computer use on the results of learning and student motivation have indicated that the use of computers can increase learning motivation, and that computers can have a positive effect, a negative effect, or no effect at all on learning outcomes. Some results indicate that it is not computer use itself that…

  13. Deepening Learning through Learning-by-Inventing

    OpenAIRE

    Apiola, Mikko; Tedre, Matti

    2013-01-01

    It has been shown that deep approaches to learning, intrinsic motivation, and self-regulated learning have strong positive effects on learning. How those pedagogical theories can be integrated in computing curricula is, however, still lacking empirically grounded analyses. This study integrated, in a robotics-based programming class, a method of learning-by-inventing, and studied its qualitative effects on students’ learning through 144 interviews. Five findings were related with learning the...

  14. Obliczeniowe teorie świadomości (Computational theories of consciousness

    Directory of Open Access Journals (Sweden)

    Marcin Miłkowski

    2010-06-01

    Full Text Available In this paper, I review the motivations for having a computational theory of consciousness to see if they turn out to be no longer plausible in the light of recent criticisms. These criticisms focus on the alleged inability of computational theories to deal with qualia, or qualities of experience (or objects of experience in some accounts, and with so-called symbol grounding on the other hand. Yet it seems that computationalism remains the best game in town when one wants to explain and predict the dynamics of information processing of cognitive systems. Conscious information processing does not seem to be explainable better within any other framework; computationalism regarding consciousness can only be discarded by supposing that consciousness is epiphenomenal in information processing.I will argue that recent theories of consciousness that are to deal with the so-called hard problem of consciousness remain in their core computational if they do not subscribe to epiphenomenalism. For example, the quantum theory as proposed by Stuart Hameroff remains openly computational; the same goes for pan(protopsychist speculation of David Chalmers. The qualitative character of information processing that Chalmers takes to explain the existence of subjective experience piggy-backs, so to say, on the very fact that there is information processing that is best explained in a computationalist framework. I also briefly show that other alternative accounts of consciousness (such as direct theories of consciousness that were supposed to oppose computational and functionalist conceptions are not only compatible with them but require them to begin with.In short, to discard credentials of computationalism in consciousness research one would have to show that it`s possible to explain conscious information-processing mechanisms sufficiently in a non-computational way. And this has not been done by any of the critics of computational accounts. This all doesn`t suggest

  15. Learning With Computers; Today and Tomorrow.

    Science.gov (United States)

    Bork, Alfred

    This paper describes the present practical use of computers in two large beginning physics courses at the University of California, Irvine; discusses the versatility and desirability of computers in the field of education; and projects the possible future directions of computer-based learning. The advantages and disadvantages of educational…

  16. Concept-Based Learning in Clinical Experiences: Bringing Theory to Clinical Education for Deep Learning.

    Science.gov (United States)

    Nielsen, Ann

    2016-07-01

    Concept-based learning is used increasingly in nursing education to support the organization, transfer, and retention of knowledge. Concept-based learning activities (CBLAs) have been used in clinical education to explore key aspects of the patient situation and principles of nursing care, without responsibility for total patient care. The nature of best practices in teaching and the resultant learning are not well understood. The purpose of this multiple-case study research was to explore and describe concept-based learning in the context of clinical education in inpatient settings. Four clinical groups (each a case) were observed while they used CBLAs in the clinical setting. Major findings include that concept-based learning fosters deep learning, connection of theory with practice, and clinical judgment. Strategies used to support learning, major teaching-learning foci, and preconditions for concept-based teaching and learning will be described. Concept-based learning is promising to support integration of theory with practice and clinical judgment through application experiences with patients. [J Nurs Educ. 2016;55(7):365-371.]. Copyright 2016, SLACK Incorporated.

  17. Learning theories 101: application to everyday teaching and scholarship.

    Science.gov (United States)

    Kay, Denise; Kibble, Jonathan

    2016-03-01

    Shifts in educational research, in how scholarship in higher education is defined, and in how funding is appropriated suggest that educators within basic science fields can benefit from increased understanding of learning theory and how it applies to classroom practice. This article uses a mock curriculum design scenario as a framework for the introduction of five major learning theories. Foundational constructs and principles from each theory and how they apply to the proposed curriculum designs are described. A summative table that includes basic principles, constructs, and classroom applications as well as the role of the teacher and learner is also provided for each theory. Copyright © 2016 The American Physiological Society.

  18. International Conference on Frontiers of Intelligent Computing : Theory and Applications

    CERN Document Server

    Bhateja, Vikrant; Udgata, Siba; Pattnaik, Prasant

    2017-01-01

    The book is a collection of high-quality peer-reviewed research papers presented at International Conference on Frontiers of Intelligent Computing: Theory and applications (FICTA 2016) held at School of Computer Engineering, KIIT University, Bhubaneswar, India during 16 – 17 September 2016. The book presents theories, methodologies, new ideas, experiences and applications in all areas of intelligent computing and its applications to various engineering disciplines like computer science, electronics, electrical and mechanical engineering.

  19. The Impact of Cognitive Load Theory on Learning Astronomy

    Science.gov (United States)

    Foster, Thomas M.

    2010-01-01

    Every student is different, which is the challenge of astronomy education research (AER) and teaching astronomy. This difference also provides the greatest goal for education researchers - our GUT - we need to be able to quantify these differences and provide explanatory and predictive theories to curriculum developers and teachers. One educational theory that holds promise is Cognitive Load Theory. Cognitive Load Theory begins with the well-established fact that everyone's working memory can hold 7 ± 2 unique items. This quirk of the human brain is why phone numbers are 7 digits long. This quirk is also why we forget peoples’ names after just meeting them, leave the iron on when we leave the house, and become overwhelmed as students of new material. Once the intricacies of Cognitive Load are understood, it becomes possible to design learning environments to marshal the resources students have and guide them to success. Lessons learned from Cognitive Load Theory can and should be applied to learning astronomy. Classroom-ready ideas will be presented.

  20. Computer Augmented Learning; A Survey.

    Science.gov (United States)

    Kindred, J.

    The report contains a description and summary of computer augmented learning devices and systems. The devices are of two general types programed instruction systems based on the teaching machines pioneered by Pressey and developed by Skinner, and the so-called "docile" systems that permit greater user-direction with the computer under student…

  1. A Critical Comparison of Transformation and Deep Approach Theories of Learning

    Science.gov (United States)

    Howie, Peter; Bagnall, Richard

    2015-01-01

    This paper reports a critical comparative analysis of two popular and significant theories of adult learning: the transformation and the deep approach theories of learning. These theories are operative in different educational sectors, are significant, respectively, in each, and they may be seen as both touching on similar concerns with learning…

  2. Cloud computing theory and practice

    CERN Document Server

    Marinescu, Dan C

    2013-01-01

    Cloud Computing: Theory and Practice provides students and IT professionals with an in-depth analysis of the cloud from the ground up. Beginning with a discussion of parallel computing and architectures and distributed systems, the book turns to contemporary cloud infrastructures, how they are being deployed at leading companies such as Amazon, Google and Apple, and how they can be applied in fields such as healthcare, banking and science. The volume also examines how to successfully deploy a cloud application across the enterprise using virtualization, resource management and the ri

  3. High school students' implicit theories of what facilitates science learning

    Science.gov (United States)

    Carlton Parsons, Eileen; Miles, Rhea; Petersen, Michael

    2011-11-01

    Background: Research has primarily concentrated on adults' implicit theories about high quality science education for all students. Little work has considered the students' perspective. This study investigated high school students' implicit theories about what helped them learn science. Purpose: This study addressed (1) What characterizes high school students' implicit theories of what facilitates their learning of science?; (2) With respect to students' self-classifications as African American or European American and female or male, do differences exist in the students' implicit theories? Sample, design and methods: Students in an urban high school located in south-eastern United States were surveyed in 2006 about their thoughts on what helps them learn science. To confirm or disconfirm any differences, data from two different samples were analyzed. Responses of 112 African American and 118 European American students and responses from 297 European American students comprised the data for sample one and two, respectively. Results: Seven categories emerged from the deductive and inductive analyses of data: personal responsibility, learning arrangements, interest and knowledge, communication, student mastery, environmental responsiveness, and instructional strategies. Instructional strategies captured 82% and 80% of the data from sample one and two, respectively; consequently, this category was further subjected to Mann-Whitney statistical analysis at p ethnic differences. Significant differences did not exist for ethnicity but differences between females and males in sample one and sample two emerged. Conclusions: African American and European American students' implicit theories about instructional strategies that facilitated their science learning did not significantly differ but female and male students' implicit theories about instructional strategies that helped them learn science significantly differed. Because students attend and respond to what they think

  4. Improving self-regulated learning junior high school students through computer-based learning

    Science.gov (United States)

    Nurjanah; Dahlan, J. A.

    2018-05-01

    This study is back grounded by the importance of self-regulated learning as an affective aspect that determines the success of students in learning mathematics. The purpose of this research is to see how the improvement of junior high school students' self-regulated learning through computer based learning is reviewed in whole and school level. This research used a quasi-experimental research method. This is because individual sample subjects are not randomly selected. The research design used is Pretest-and-Posttest Control Group Design. Subjects in this study were students of grade VIII junior high school in Bandung taken from high school (A) and middle school (B). The results of this study showed that the increase of the students' self-regulated learning who obtain learning with computer-based learning is higher than students who obtain conventional learning. School-level factors have a significant effect on increasing of the students' self-regulated learning.

  5. Theory-based Bayesian models of inductive learning and reasoning.

    Science.gov (United States)

    Tenenbaum, Joshua B; Griffiths, Thomas L; Kemp, Charles

    2006-07-01

    Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction emphasize either the power of statistical learning, or the importance of strong constraints from structured domain knowledge, intuitive theories or schemas. We argue that both components are necessary to explain the nature, use and acquisition of human knowledge, and we introduce a theory-based Bayesian framework for modeling inductive learning and reasoning as statistical inferences over structured knowledge representations.

  6. Understanding Self-Controlled Motor Learning Protocols through the Self-Determination Theory.

    Science.gov (United States)

    Sanli, Elizabeth A; Patterson, Jae T; Bray, Steven R; Lee, Timothy D

    2012-01-01

    The purpose of the present review was to provide a theoretical understanding of the learning advantages underlying a self-controlled practice context through the tenets of the self-determination theory (SDT). Three micro-theories within the macro-theory of SDT (Basic psychological needs theory, Cognitive Evaluation Theory, and Organismic Integration Theory) are used as a framework for examining the current self-controlled motor learning literature. A review of 26 peer-reviewed, empirical studies from the motor learning and medical training literature revealed an important limitation of the self-controlled research in motor learning: that the effects of motivation have been assumed rather than quantified. The SDT offers a basis from which to include measurements of motivation into explanations of changes in behavior. This review suggests that a self-controlled practice context can facilitate such factors as feelings of autonomy and competence of the learner, thereby supporting the psychological needs of the learner, leading to long term changes to behavior. Possible tools for the measurement of motivation and regulation in future studies are discussed. The SDT not only allows for a theoretical reinterpretation of the extant motor learning research supporting self-control as a learning variable, but also can help to better understand and measure the changes occurring between the practice environment and the observed behavioral outcomes.

  7. Understanding self-controlled motor learning protocols through the self determination theory

    Directory of Open Access Journals (Sweden)

    Elizabeth Ann Sanli

    2013-01-01

    Full Text Available The purpose of the present review was to provide a theoretical understanding of the learning advantages underlying a self-controlled practice context through the tenets of the self-determination theory (SDT. Three micro theories within the macro theory of SDT (Basic psychological needs theory, Cognitive Evaluation Theory & Organismic Integration Theory are used as a framework for examining the current self-controlled motor learning literature. A review of 26 peer-reviewed, empirical studies from the motor learning and medical training literature revealed an important limitation of the self-controlled research in motor learning: that the effects of motivation have been assumed rather than quantified. The SDT offers a basis from which to include measurements of motivation into explanations of changes in behavior. This review suggests that a self-controlled practice context can facilitate such factors as feelings of autonomy and competence of the learner, thereby supporting the psychological needs of the learner, leading to long term changes to behavior. Possible tools for the measurement of motivation and regulation in future studies are discussed. The SDT not only allows for a theoretical reinterpretation of the extant motor learning research supporting self-control as a learning variable, but also can help to better understand and measure the changes occurring between the practice environment and the observed behavioral outcomes.

  8. Computer-Based Learning in Chemistry Classes

    Science.gov (United States)

    Pietzner, Verena

    2014-01-01

    Currently not many people would doubt that computers play an essential role in both public and private life in many countries. However, somewhat surprisingly, evidence of computer use is difficult to find in German state schools although other countries have managed to implement computer-based teaching and learning in their schools. This paper…

  9. Implications of learning theory for developing programs to decrease overeating.

    Science.gov (United States)

    Boutelle, Kerri N; Bouton, Mark E

    2015-10-01

    Childhood obesity is associated with medical and psychological comorbidities, and interventions targeting overeating could be pragmatic and have a significant impact on weight. Calorically dense foods are easily available, variable, and tasty which allows for effective opportunities to learn to associate behaviors and cues in the environment with food through fundamental conditioning processes, resulting in measurable psychological and physiological food cue reactivity in vulnerable children. Basic research suggests that initial learning is difficult to erase, and that it is vulnerable to a number of phenomena that will allow the original learning to re-emerge after it is suppressed or replaced. These processes may help explain why it may be difficult to change food cue reactivity and overeating over the long term. Extinction theory may be used to develop effective cue-exposure treatments to decrease food cue reactivity through inhibitory learning, although these processes are complex and require an integral understanding of the theory and individual differences. Additionally, learning theory can be used to develop other interventions that may prove to be useful. Through an integration of learning theory, basic and translational research, it may be possible to develop interventions that can decrease the urges to overeat, and improve the weight status of children. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Evaluating theories of bird song learning: implications for future directions.

    Science.gov (United States)

    Margoliash, D

    2002-12-01

    Studies of birdsong learning have stimulated extensive hypotheses at all levels of behavioral and physiological organization. This hypothesis building is valuable for the field and is consistent with the remarkable range of issues that can be rigorously addressed in this system. The traditional instructional (template) theory of song learning has been challenged on multiple fronts, especially at a behavioral level by evidence consistent with selectional hypotheses. In this review I highlight the caveats associated with these theories to better define the limits of our knowledge and identify important experiments for the future. The sites and representational forms of the various conceptual entities posited by the template theory are unknown. The distinction between instruction and selection in vocal learning is not well established at a mechanistic level. There is as yet insufficient neurophysiological data to choose between competing mechanisms of error-driven learning and reinforcement learning. Both may obtain for vocal learning. The possible role of sleep in acoustic or procedural memory consolidation, while supported by some physiological observations, does not yet have support in the behavioral literature. The remarkable expansion of knowledge in the past 20 years and the recent development of new technologies for physiological and behavioral experiments should permit direct tests of these theories in the coming decade.

  11. Group Theory, Computational Thinking, and Young Mathematicians

    Science.gov (United States)

    Gadanidis, George; Clements, Erin; Yiu, Chris

    2018-01-01

    In this article, we investigate the artistic puzzle of designing mathematics experiences (MEs) to engage young children with ideas of group theory, using a combination of hands-on and computational thinking (CT) tools. We elaborate on: (1) group theory and why we chose it as a context for young mathematicians' experiences with symmetry and…

  12. Toward an Instructionally Oriented Theory of Example-Based Learning

    Science.gov (United States)

    Renkl, Alexander

    2014-01-01

    Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from…

  13. Smart learning services based on smart cloud computing.

    Science.gov (United States)

    Kim, Svetlana; Song, Su-Mi; Yoon, Yong-Ik

    2011-01-01

    Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user's behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S)--smart pull, smart prospect, smart content, and smart push--concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users' needs by collecting and analyzing users' behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users' behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users.

  14. Smart Learning Services Based on Smart Cloud Computing

    Directory of Open Access Journals (Sweden)

    Yong-Ik Yoon

    2011-08-01

    Full Text Available Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user’s behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S—smart pull, smart prospect, smart content, and smart push—concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users’ needs by collecting and analyzing users’ behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users’ behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users.

  15. Theory and practice of Auto CAD, computer graphics

    International Nuclear Information System (INIS)

    Hwang, Si Won; Choe, Hong Yeong; Shin, Jae Yeon; Lee, Ryong Cheol

    1990-08-01

    This book describes theory and practice of Auto CAD, computer graphics, which deals with peripheral of computer, occurrence of digital line by DDA, BRM, theory of conversion, data base and display and shape modeling. This book gives descriptions of outline of CAD system, Auto CAD, basic function practice, simple figure practice, the third angle projection drawing a little complex single object, machine drawing I, function practice of improved Auto CAD, edit, set up layer, and 3D, and 3D display function.

  16. MLnet report: training in Europe on machine learning

    OpenAIRE

    Ellebrecht, Mario; Morik, Katharina

    1999-01-01

    Machine learning techniques offer opportunities for a variety of applications and the theory of machine learning investigates problems that are of interest for other fields of computer science (e.g., complexity theory, logic programming, pattern recognition). However, the impacts of machine learning can only be recognized by those who know the techniques and are able to apply them. Hence, teaching machine learning is necessary before this field can diversify computer science. In order ...

  17. Computational Psychiatry and the Challenge of Schizophrenia

    Science.gov (United States)

    Murray, John D.; Chekroud, Adam M.; Corlett, Philip R.; Yang, Genevieve; Wang, Xiao-Jing; Anticevic, Alan

    2017-01-01

    Abstract Schizophrenia research is plagued by enormous challenges in integrating and analyzing large datasets and difficulties developing formal theories related to the etiology, pathophysiology, and treatment of this disorder. Computational psychiatry provides a path to enhance analyses of these large and complex datasets and to promote the development and refinement of formal models for features of this disorder. This presentation introduces the reader to the notion of computational psychiatry and describes discovery-oriented and theory-driven applications to schizophrenia involving machine learning, reinforcement learning theory, and biophysically-informed neural circuit models. PMID:28338845

  18. Computer-Mediated Intersensory Learning Model for Students with Learning Disabilities

    Science.gov (United States)

    Seok, Soonhwa; DaCosta, Boaventura; Kinsell, Carolyn; Poggio, John C.; Meyen, Edward L.

    2010-01-01

    This article proposes a computer-mediated intersensory learning model as an alternative to traditional instructional approaches for students with learning disabilities (LDs) in the inclusive classroom. Predominant practices of classroom inclusion today reflect the six principles of zero reject, nondiscriminatory evaluation, appropriate education,…

  19. An introduction to quantum machine learning

    Science.gov (United States)

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2015-04-01

    Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT industry. In the last couple of years, researchers investigated if quantum computing can help to improve classical machine learning algorithms. Ideas range from running computationally costly algorithms or their subroutines efficiently on a quantum computer to the translation of stochastic methods into the language of quantum theory. This contribution gives a systematic overview of the emerging field of quantum machine learning. It presents the approaches as well as technical details in an accessible way, and discusses the potential of a future theory of quantum learning.

  20. Affect and Learning : a computational analysis

    NARCIS (Netherlands)

    Broekens, Douwe Joost

    2007-01-01

    In this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is modelled as artificial affect, a measure that denotes the positiveness versus negativeness of a situation

  1. The ‘taking place’ of learning in computer games

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel; Løfgreen, Lars Bo

    2008-01-01

    In the long-standing tradition for discounting digital technologies as a learning resource within the formal educational setting, computer games have often either been marked as distraction or totally ignored. However, as argued in the paradigmatic text by Shaffer, Squire, Halverson and Gee, Video...... Games and The Future of Learning, computer games do not only offer an interesting perspective on how “learners can understand complex concepts without losing the connection between abstract ideas and the real problems”, but can as well cast “a glimpse into how we might create new and more powerful ways...... to learn in schools, communities, and workplaces – new ways to learn for a new Information Age” [1].  In line with this general approach to seeing computer games as a reservoir of learning strategies and potentials, this paper aims to examine how a specific computer game teach us how to play the game. [1...

  2. Lattice guage theories on a hypercube computer

    International Nuclear Information System (INIS)

    Otto, S.W.

    1984-01-01

    A report on the parallel computer effort underway at Caltech and the use of these machines for lattice gauge theories is given. The computational requirements of the Monte Carlos are, of course, enormous, so high Mflops (Million floating point operations per second) and large memories are required. Various calculations on the machines in regards to their programmability (a non-trivial issue on a parallel computer) and their efficiency in usage of the machine are discussed

  3. SOFSEM 2009: Theory and Practice of Computer Science

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2009, held in Špindleruv Mlýn, Czech Republic, in January 2009. The 49 revised full papers, presented together with 9 invited contributions, were carefully...... reviewed and selected from 132 submissions. SOFSEM 2009 was organized around the following four tracks: Foundations of Computer Science; Theory and Practice of Software Services; Game Theoretic Aspects of E-commerce; and Techniques and Tools for Formal Verification....

  4. Theories and control models and motor learning: clinical applications in neuro-rehabilitation.

    Science.gov (United States)

    Cano-de-la-Cuerda, R; Molero-Sánchez, A; Carratalá-Tejada, M; Alguacil-Diego, I M; Molina-Rueda, F; Miangolarra-Page, J C; Torricelli, D

    2015-01-01

    In recent decades there has been a special interest in theories that could explain the regulation of motor control, and their applications. These theories are often based on models of brain function, philosophically reflecting different criteria on how movement is controlled by the brain, each being emphasised in different neural components of the movement. The concept of motor learning, regarded as the set of internal processes associated with practice and experience that produce relatively permanent changes in the ability to produce motor activities through a specific skill, is also relevant in the context of neuroscience. Thus, both motor control and learning are seen as key fields of study for health professionals in the field of neuro-rehabilitation. The major theories of motor control are described, which include, motor programming theory, systems theory, the theory of dynamic action, and the theory of parallel distributed processing, as well as the factors that influence motor learning and its applications in neuro-rehabilitation. At present there is no consensus on which theory or model defines the regulations to explain motor control. Theories of motor learning should be the basis for motor rehabilitation. The new research should apply the knowledge generated in the fields of control and motor learning in neuro-rehabilitation. Copyright © 2011 Sociedad Española de Neurología. Published by Elsevier Espana. All rights reserved.

  5. Early Learning Theories Made Visible

    Science.gov (United States)

    Beloglovsky, Miriam; Daly, Lisa

    2015-01-01

    Go beyond reading about early learning theories and see what they look like in action in modern programs and teacher practices. With classroom vignettes and colorful photographs, this book makes the works of Jean Piaget, Erik Erikson, Lev Vygotsky, Abraham Maslow, John Dewey, Howard Gardner, and Louise Derman-Sparks visible, accessible, and easier…

  6. An Overview of the History of Learning Theory

    Science.gov (United States)

    Illeris, Knud

    2018-01-01

    This article is an account of the history of learning theory as the author has come to know and interpret it by dealing with this subject for almost half a century during which he has also himself gradually developed the broad understanding of human learning which is presented in his well known books on "How We Learn" and a lot of other…

  7. Learning Styles of Baccalaureate Nursing Students and Attitudes toward Theory-Based Nursing.

    Science.gov (United States)

    Laschinger, Heather K.; Boss, Marvin K.

    1989-01-01

    The personal and environmental factors related to undergraduate and post-RN nursing students' attitudes toward theory-based nursing from Kolb's experiential learning theory perspective were investigated. Learning style and environmental press perceptions were found to be related to attitudes toward theory-based nursing. (Author/MLW)

  8. Computer-Assisted Language Learning: Diversity in Research and Practice

    Science.gov (United States)

    Stockwell, Glenn, Ed.

    2012-01-01

    Computer-assisted language learning (CALL) is an approach to teaching and learning languages that uses computers and other technologies to present, reinforce, and assess material to be learned, or to create environments where teachers and learners can interact with one another and the outside world. This book provides a much-needed overview of the…

  9. Learning and instruction with computer simulations

    NARCIS (Netherlands)

    de Jong, Anthonius J.M.

    1991-01-01

    The present volume presents the results of an inventory of elements of such a computer learning environment. This inventory was conducted within a DELTA project called SIMULATE. In the project a learning environment that provides intelligent support to learners and that has a simulation as its

  10. The Development of a Comprehensive and Coherent Theory of Learning

    Science.gov (United States)

    Illeris, Knud

    2015-01-01

    This article is an account of how the author developed a comprehensive understanding of human learning over a period of almost 50 years. The learning theory includes the structure of learning, different types of learning, barriers of learning as well as how individual dispositions, age, the learning environment and general social and societal…

  11. Strategies for application of learning theories in art studio practices ...

    African Journals Online (AJOL)

    This study highlights the link between learning theories and art studio practices. The paper is of the opinion that if these theories are critically understood and applied to the practical aspect of fine and applied arts then learning will be more functional. Nigerian Journal of Technology and Education in Nigeria Vol. 8(1) 2003: ...

  12. Computer-based learning in neuroanatomy: A longitudinal study of learning, transfer, and retention

    Science.gov (United States)

    Chariker, Julia H.

    A longitudinal experiment was conducted to explore computer-based learning of neuroanatomy. Using a realistic 3D graphical model of neuroanatomy, and sections derived from the model, exploratory graphical tools were integrated into interactive computer programs so as to allow adaptive exploration. 72 participants learned either sectional anatomy alone or learned whole anatomy followed by sectional anatomy. Sectional anatomy was explored either in perceptually continuous animation or discretely, as in the use of an anatomical atlas. Learning was measured longitudinally to a high performance criterion. After learning, transfer to biomedical images and long-term retention was tested. Learning whole anatomy prior to learning sectional anatomy led to a more efficient learning experience. Learners demonstrated high levels of transfer from whole anatomy to sectional anatomy and from sectional anatomy to complex biomedical images. All learning groups demonstrated high levels of retention at 2--3 weeks.

  13. KARATE WITH CONSTRUCTIVE LEARNING

    Directory of Open Access Journals (Sweden)

    Srikrishna Karanam

    2012-02-01

    Full Text Available Any conventional learning process involves the traditional hierarchy of garnering of information and then recall gathered information. Constructive learning is an important research area having wide impact on teaching methods in education, learning theories, and plays a major role in many education reform movements. It is observed that constructive learning advocates the interconnection between emotions and learning. Human teachers identify the emotions of students with varying degrees of accuracy and can improve the learning rate of the students by motivating them. In learning with computers, computers also should be given the capability to recognize emotions so as to optimize the learning process. Image Processing is a very popular tool used in the process of establishing the theory of Constructive Learning. In this paper we use the Optical Flow computation in image sequences to analyze the accuracy of the moves of a karate player. We have used the Lucas-Kanade method for computing the optical flow in image sequences. A database consisting of optical flow images by a group of persons learning karate is formed and the learning rates are analyzed in order to main constructive learning. The contours of flow images are compared with the standard images and the error graphs are plotted. Analysis of the emotion of the amateur karate player is made by observing the error plots.

  14. Algebraic computability and enumeration models recursion theory and descriptive complexity

    CERN Document Server

    Nourani, Cyrus F

    2016-01-01

    This book, Algebraic Computability and Enumeration Models: Recursion Theory and Descriptive Complexity, presents new techniques with functorial models to address important areas on pure mathematics and computability theory from the algebraic viewpoint. The reader is first introduced to categories and functorial models, with Kleene algebra examples for languages. Functorial models for Peano arithmetic are described toward important computational complexity areas on a Hilbert program, leading to computability with initial models. Infinite language categories are also introduced to explain descriptive complexity with recursive computability with admissible sets and urelements. Algebraic and categorical realizability is staged on several levels, addressing new computability questions with omitting types realizably. Further applications to computing with ultrafilters on sets and Turing degree computability are examined. Functorial models computability is presented with algebraic trees realizing intuitionistic type...

  15. From Theory Use to Theory Building in Learning Analytics: A Commentary on "Learning Analytics to Support Teachers during Synchronous CSCL"

    Science.gov (United States)

    Chen, Bodong

    2015-01-01

    In this commentary on Van Leeuwen (2015, this issue), I explore the relation between theory and practice in learning analytics. Specifically, I caution against adhering to one specific theoretical doctrine while ignoring others, suggest deeper applications of cognitive load theory to understanding teaching with analytics tools, and comment on…

  16. Playing styles based on experiential learning theory

    NARCIS (Netherlands)

    Bontchev, Boyan; Vassileva, Dessislava; Aleksieva-Petrova, Adelina; Petrov, Milen

    2018-01-01

    In recent years, many researchers have reported positive outcomes and effects from applying computer games to the educational process. The main preconditions for an effective game-based learning process include the presence of high learning interest and the desire to study hard. Therefore,

  17. Computer Assisted Language Learning (CALL) Software: Evaluation ...

    African Journals Online (AJOL)

    Evaluating the nature and extent of the influence of Computer Assisted Language Learning (CALL) on the quality of language learning is highly problematic. This is owing to the number and complexity of interacting variables involved in setting the items for teaching and learning languages. This paper identified and ...

  18. a Radical Collaborative Approach: Developing a Model for Learning Theory, Human-Based Computation and Participant Motivation in a Rock-Art Heritage Application

    Science.gov (United States)

    Haubt, R.

    2016-06-01

    This paper explores a Radical Collaborative Approach in the global and centralized Rock-Art Database project to find new ways to look at rock-art by making information more accessible and more visible through public contributions. It looks at rock-art through the Key Performance Indicator (KPI), identified with the latest Australian State of the Environment Reports to help develop a better understanding of rock-art within a broader Cultural and Indigenous Heritage context. Using a practice-led approach the project develops a conceptual collaborative model that is deployed within the RADB Management System. Exploring learning theory, human-based computation and participant motivation the paper develops a procedure for deploying collaborative functions within the interface design of the RADB Management System. The paper presents the results of the collaborative model implementation and discusses considerations for the next iteration of the RADB Universe within an Agile Development Approach.

  19. Conformal prediction for reliable machine learning theory, adaptations and applications

    CERN Document Server

    Balasubramanian, Vineeth; Vovk, Vladimir

    2014-01-01

    The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detecti

  20. Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

    Science.gov (United States)

    Ball, John E.; Anderson, Derek T.; Chan, Chee Seng

    2017-10-01

    In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, and natural language processing. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV, e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should not only be aware of advancements such as DL, but also be leading researchers in this area. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools, and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as they relate to (i) inadequate data sets, (ii) human-understandable solutions for modeling physical phenomena, (iii) big data, (iv) nontraditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial, and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.

  1. Shaping a valued learning journey: Student satisfaction with learning in undergraduate nursing programs, a grounded theory study.

    Science.gov (United States)

    Smith, Morgan R; Grealish, Laurie; Henderson, Saras

    2018-05-01

    Student satisfaction is a quality measure of increasing importance in undergraduate programs, including nursing programs. To date theories of student satisfaction have focused primarily on students' perceptions of the educational environment rather than their perceptions of learning. Understanding how students determine satisfaction with learning is necessary to facilitate student learning across a range of educational contexts and meet the expectations of diverse stakeholders. To understand undergraduate nursing students' satisfaction with learning. Constructivist grounded theory methodology was used to identify how nursing students determined satisfaction with learning. Two large, multi-campus, nursing schools in Australia. Seventeen demographically diverse undergraduate nursing students studying different stages of a three year program participated in the study. Twenty nine semi-structured interviews were conducted. Students were invited to describe situations where they had been satisfied or dissatisfied with their learning. A constructivist grounded theory approach was used to analyse the data. Students are satisfied with learning when they shape a valued learning journey that accommodates social contexts of self, university and nursing workplace. The theory has three phases. Phase 1 - orienting self to valued learning in the pedagogical landscape; phase 2 - engaging with valued learning experiences across diverse pedagogical terrain; and phase 3 - recognising valued achievement along the way. When students experience a valued learning journey they are satisfied with their learning. Student satisfaction with learning is unique to the individual, changes over time and maybe transient or sustained, mild or intense. Finding from the research indicate areas where nurse academics may facilitate satisfaction with learning in undergraduate nursing programs while mindful of the expectations of other stakeholders such as the university, nurse registering authorities

  2. Employee Learning Theories and Their Organizational Applications

    Directory of Open Access Journals (Sweden)

    Abdussalaam Iyanda Ismail

    2017-12-01

    Full Text Available Empirical evidence identifies that organizational success hinges on employees with the required knowledge, skills, and abilities and that employees’ effectiveness at learning new skills and knowledge is connected with the kind of learning technique the organization adopts. Given this, this work explored employee learning theories and their organizational applications. Using far reaching literature survey and extensive theoretical and logical argument and exposition. This paper revealed that cognitive-based approaches, non-cognitive approach and need-based approaches play vital roles in shrinking the occurrence of unwanted behaviors and upturning the occurrence of desired behaviors in the organization. Proper application of the theories can induce positive employee behaviors such as task performance and organizational citizenship behavior and consequently enhance both individual and organizational performance. This work has hopefully contributed to the enrichment of the existing relevant literature and served as a useful guide for stakeholders on how they can stimulate positive employee behaviors and the consequent enhanced organizational performance.

  3. Mean-field theory of meta-learning

    International Nuclear Information System (INIS)

    Plewczynski, Dariusz

    2009-01-01

    We discuss here the mean-field theory for a cellular automata model of meta-learning. Meta-learning is the process of combining outcomes of individual learning procedures in order to determine the final decision with higher accuracy than any single learning method. Our method is constructed from an ensemble of interacting, learning agents that acquire and process incoming information using various types, or different versions, of machine learning algorithms. The abstract learning space, where all agents are located, is constructed here using a fully connected model that couples all agents with random strength values. The cellular automata network simulates the higher level integration of information acquired from the independent learning trials. The final classification of incoming input data is therefore defined as the stationary state of the meta-learning system using simple majority rule, yet the minority clusters that share the opposite classification outcome can be observed in the system. Therefore, the probability of selecting a proper class for a given input data, can be estimated even without the prior knowledge of its affiliation. The fuzzy logic can be easily introduced into the system, even if learning agents are built from simple binary classification machine learning algorithms by calculating the percentage of agreeing agents

  4. Structural Learning Theory: Current Status and New Perspectives.

    Science.gov (United States)

    Scandura, Joseph M.

    2001-01-01

    Presents the current status and new perspectives on the Structured Learning Theory (SLT), with special consideration given to how SLT has been influenced by recent research in software engineering. Topics include theoretical constructs; content domains; structural analysis; cognition; assessing behavior potential; and teaching and learning issues,…

  5. Rhetorical ways of thinking Vygotskian theory and mathematical learning

    CERN Document Server

    Albert, Lillie R; Macadino, Vittoria

    2012-01-01

    Combining Vygotskian theory with current teaching and learning practices, this volume focuses on how the co-construction of learning models the interpretation of a mathematical situation, providing educationalists with a valuable practical methodology.

  6. Social Learning, Social Control, and Strain Theories: A Formalization of Micro-level Criminological Theories

    OpenAIRE

    Proctor, Kristopher Ryan

    2010-01-01

    This dissertation proposes theoretical formalization as a way of enhancing theory development within criminology. Differential association, social learning, social control, and general strain theories are formalized in order to identify assumptions of human nature, key theoretical concepts, theoretical knowledge claims, and scope conditions. The resulting formalization allows greater comparability between theories in terms of explanatory power, and additionally provides insights into integrat...

  7. Distributed computer systems theory and practice

    CERN Document Server

    Zedan, H S M

    2014-01-01

    Distributed Computer Systems: Theory and Practice is a collection of papers dealing with the design and implementation of operating systems, including distributed systems, such as the amoeba system, argus, Andrew, and grapevine. One paper discusses the concepts and notations for concurrent programming, particularly language notation used in computer programming, synchronization methods, and also compares three classes of languages. Another paper explains load balancing or load redistribution to improve system performance, namely, static balancing and adaptive load balancing. For program effici

  8. Developing Decision-Making Skill: Experiential Learning in Computer Games

    OpenAIRE

    Kurt A. April; Katja M. J. Goebel; Eddie Blass; Jonathan Foster-Pedley

    2012-01-01

    This paper explores the value that computer and video games bring to learning and leadership and explores how games work as learning environments and the impact they have on personal development. The study looks at decisiveness, decision-making ability and styles, and on how this leadership-related skill is learnt through different paradigms. The paper compares the learning from a lecture to the learning from a designed computer game, both of which have the same content through the use of a s...

  9. Computer-Mediated Collaborative Learning

    Science.gov (United States)

    Beatty, Ken; Nunan, David

    2004-01-01

    The study reported here investigates collaborative learning at the computer. Ten pairs of students were presented with a series of comprehension questions about Mary Shelley's novel "Frankenstein or a Modern Prometheus" along with a CD-ROM, "Frankenstein Illuminated," containing the novel and a variety of source material. Five students worked with…

  10. The sociability of computer-supported collaborative learning environments

    NARCIS (Netherlands)

    Kreijns, C.J.; Kirschner, P.A.; Jochems, W.M.G.

    2002-01-01

    There is much positive research on computer-supported collaborative learning (CSCL) environments in asynchronous distributed learning groups (DLGs). There is also research that shows that contemporary CSCL environments do not completely fulfil expectations on supporting interactive group learning,

  11. Understanding feedback: A learning theory perspective

    NARCIS (Netherlands)

    Thurlings, Marieke; Vermeulen, Marjan; Bastiaens, Theo; Stijnen, Sjef

    2018-01-01

    This article aims to review literature on feedback to teachers. Because research has hardly focused on feedback among teachers, the review’s scope also includes feedback in class- rooms. The review proposes that the effectiveness of feedback and feedback processes depend on the learning theory

  12. Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design

    OpenAIRE

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2006-01-01

    Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.

  13. Computer literacy and attitudes towards e-learning among first year medical students.

    Science.gov (United States)

    Link, Thomas Michael; Marz, Richard

    2006-06-19

    At the Medical University of Vienna, most information for students is available only online. In 2005, an e-learning project was initiated and there are plans to introduce a learning management system. In this study, we estimate the level of students' computer skills, the number of students having difficulty with e-learning, and the number of students opposed to e-learning. The study was conducted in an introductory course on computer-based and web-based training (CBT/WBT). Students were asked to fill out a questionnaire online that covered a wide range of relevant attitudes and experiences. While the great majority of students possess sufficient computer skills and acknowledge the advantages of interactive and multimedia-enhanced learning material, a small percentage lacks basic computer skills and/or is very skeptical about e-learning. There is also a consistently significant albeit weak gender difference in available computer infrastructure and Internet access. As for student attitudes toward e-learning, we found that age, computer use, and previous exposure to computers are more important than gender. A sizable number of students, 12% of the total, make little or no use of existing e-learning offerings. Many students would benefit from a basic introduction to computers and to the relevant computer-based resources of the university. Given to the wide range of computer skills among students, a single computer course for all students would not be useful nor would it be accepted. Special measures should be taken to prevent students who lack computer skills from being disadvantaged or from developing computer-hostile attitudes.

  14. Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

    Directory of Open Access Journals (Sweden)

    Johannes Bill

    Full Text Available During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input.

  15. Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

    Science.gov (United States)

    Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

    2015-01-01

    During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

  16. Effects of Modality and Redundancy Principles on the Learning and Attitude of a Computer-Based Music Theory Lesson among Jordanian Primary Pupils

    Science.gov (United States)

    Aldalalah, Osamah Ahmad; Fong, Soon Fook

    2010-01-01

    The purpose of this study was to investigate the effects of modality and redundancy principles on the attitude and learning of music theory among primary pupils of different aptitudes in Jordan. The lesson of music theory was developed in three different modes, audio and image (AI), text with image (TI) and audio with image and text (AIT). The…

  17. Learning Performance Enhancement Using Computer-Assisted Language Learning by Collaborative Learning Groups

    Directory of Open Access Journals (Sweden)

    Ya-huei Wang

    2017-08-01

    Full Text Available This study attempted to test whether the use of computer-assisted language learning (CALL and innovative collaborative learning could be more effective than the use of traditional collaborative learning in improving students’ English proficiencies. A true experimental design was used in the study. Four randomly-assigned groups participated in the study: a traditional collaborative learning group (TCLG, 34 students, an innovative collaborative learning group (ICLG, 31 students, a CALL traditional collaborative learning group (CALLTCLG, 32 students, and a CALL innovative collaborative learning group (CALLICLG, 31 students. TOEIC (Test of English for International Communication listening, reading, speaking, and writing pre-test and post-test assessments were given to all students at an interval of sixteen weeks. Multivariate analysis of covariance (MANCOVA, multivariate analysis of variance (MANOVA, and analysis of variance (ANOVA were used to analyze the data. The results revealed that students who used CALL had significantly better learning performance than those who did not. Students in innovative collaborative learning had significantly better learning performances than those in traditional collaborative learning. Additionally, students using CALL innovative collaborative learning had better learning performances than those in CALL collaborative learning, those in innovative collaborative learning, and those in traditional collaborative learning.

  18. The Fourth Revolution--Computers and Learning.

    Science.gov (United States)

    Bork, Alfred

    The personal computer is sparking a major historical change in the way people learn, a change that could lead to the disappearance of formal education as we know it. The computer can help resolve many of the difficulties now crippling education by enabling expert teachers and curriculum developers to prepare interactive and individualized…

  19. Locus of Control and Academic Achievement: Integrating Social Learning Theory and Expectancy-Value Theory

    Science.gov (United States)

    Youse, Keith Edward

    2012-01-01

    The current study examines predictors of math achievement and college graduation by integrating social learning theory and expectancy-value theory. Data came from a nationally-representative longitudinal database tracking 12,144 students over twelve years from 8th grade forward. Models for math achievement and college graduation were tested…

  20. Evolutionary computation for reinforcement learning

    NARCIS (Netherlands)

    Whiteson, S.; Wiering, M.; van Otterlo, M.

    2012-01-01

    Algorithms for evolutionary computation, which simulate the process of natural selection to solve optimization problems, are an effective tool for discovering high-performing reinforcement-learning policies. Because they can automatically find good representations, handle continuous action spaces,

  1. Mobile learning and computational thinking

    OpenAIRE

    José Manuel Freixo Nunes; Teresa Margarida Loureiro Cardoso

    2017-01-01

    Computational thinking can be thought of as an approach to problem solving which has been applied to different areas of learning and which has become an important field of investigation in the area of educational research. [continue

  2. 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.

  3. 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.

  4. Computer Game-Based Learning: Perceptions and Experiences of Senior Chinese Adults

    Science.gov (United States)

    Wang, Feihong; Lockee, Barbara B.; Burton, John K.

    2012-01-01

    The purpose of this study was to investigate senior Chinese adults' potential acceptance of computer game-based learning (CGBL) by probing their perceptions of computer game play and their perceived impacts of game play on their learning of computer skills and life satisfaction. A total of 60 senior adults from a local senior adult learning center…

  5. First Steps Toward a Computational Theory of Autism

    OpenAIRE

    Balkenius, Christian; Bjorne, Petra

    2004-01-01

    A computational model with three interacting components for context sensitive reinforcement learning, context processing and automation can autonomously learn a focus attention and a shift attention task. The performance of the model is similar to that of normal children, and when a single parameter is changed, the performance on the two tasks approaches that of autistic children.

  6. Towards a Semantic E-Learning Theory by Using a Modelling Approach

    Science.gov (United States)

    Yli-Luoma, Pertti V. J.; Naeve, Ambjorn

    2006-01-01

    In the present study, a semantic perspective on e-learning theory is advanced and a modelling approach is used. This modelling approach towards the new learning theory is based on the four SECI phases of knowledge conversion: Socialisation, Externalisation, Combination and Internalisation, introduced by Nonaka in 1994, and involving two levels of…

  7. Computers and languages theory and practice

    CERN Document Server

    Nijholt, A

    1988-01-01

    A global introduction to language technology and the areas of computer science where language technology plays a role. Surveyed in this volume are issues related to the parsing problem in the fields of natural languages, programming languages, and formal languages.Throughout the book attention is paid to the social forces which influenced the development of the various topics. Also illustrated are the development of the theory of language analysis, its role in compiler construction, and its role in computer applications with a natural language interface between men and machine. Parts of the ma

  8. What Communication Theories Can Teach the Designer of Computer-Based Training.

    Science.gov (United States)

    Larsen, Ronald E.

    1985-01-01

    Reviews characteristics of computer-based training (CBT) that make application of communication theories appropriate and presents principles from communication theory (e.g., general systems theory, symbolic interactionism, rule theories, and interpersonal communication theories) to illustrate how CBT developers can profitably apply them to…

  9. Unsteady Thick Airfoil Aerodynamics: Experiments, Computation, and Theory

    Science.gov (United States)

    Strangfeld, C.; Rumsey, C. L.; Mueller-Vahl, H.; Greenblatt, D.; Nayeri, C. N.; Paschereit, C. O.

    2015-01-01

    An experimental, computational and theoretical investigation was carried out to study the aerodynamic loads acting on a relatively thick NACA 0018 airfoil when subjected to pitching and surging, individually and synchronously. Both pre-stall and post-stall angles of attack were considered. Experiments were carried out in a dedicated unsteady wind tunnel, with large surge amplitudes, and airfoil loads were estimated by means of unsteady surface mounted pressure measurements. Theoretical predictions were based on Theodorsen's and Isaacs' results as well as on the relatively recent generalizations of van der Wall. Both two- and three-dimensional computations were performed on structured grids employing unsteady Reynolds-averaged Navier-Stokes (URANS). For pure surging at pre-stall angles of attack, the correspondence between experiments and theory was satisfactory; this served as a validation of Isaacs theory. Discrepancies were traced to dynamic trailing-edge separation, even at low angles of attack. Excellent correspondence was found between experiments and theory for airfoil pitching as well as combined pitching and surging; the latter appears to be the first clear validation of van der Wall's theoretical results. Although qualitatively similar to experiment at low angles of attack, two-dimensional URANS computations yielded notable errors in the unsteady load effects of pitching, surging and their synchronous combination. The main reason is believed to be that the URANS equations do not resolve wake vorticity (explicitly modeled in the theory) or the resulting rolled-up un- steady flow structures because high values of eddy viscosity tend to \\smear" the wake. At post-stall angles, three-dimensional computations illustrated the importance of modeling the tunnel side walls.

  10. Learning theories and skills in online second language teaching and learning

    DEFF Research Database (Denmark)

    Petersen, Karen Bjerg

    2014-01-01

    For decades foreign and second language teachers have taken advantage of the technology development and ensuing possibilities to use e-learning facilities for language training. Since the 1980s, the use of computer assisted language learning (CALL), Internet, web 2.0, and various kinds of e-learning...... in Denmark with special attention towards the development of web-based materials for Danish pronunciation. This paper sets out to introduce differences between the international and Danish use of web-based language learning and teaching. Finally, dilemmas and challenges for the use of CALL, IT, and web 2.0 in...

  11. Mobile Learning According to Students of Computer Engineering and Computer Education: A Comparison of Attitudes

    Directory of Open Access Journals (Sweden)

    Deniz Mertkan GEZGIN

    2018-01-01

    Full Text Available Mobile learning has started to perform an increasingly significant role in improving learning outcomes in education. Successful and efficient implementation of m-learning in higher education, as with all educational levels, depends on users’ acceptance of this technology. This study focuses on investigating the attitudes of undergraduate students of Computer Engineering (CENG and Computer Education and Instructional Technology (CEIT departments in a Turkish public university towards m-learning from three perspectives; gender, area of study, and mobile device ownership. Using a correlational survey method, a Mobile Learning Attitude Scale (MLAS was administered to 531 students, analysis of which revealed a positive attitude to m-learning in general. A further investigation of the aforementioned three variables showed a more positive attitude for female students in terms of usability, for CEIT students in terms of advantages, usability and independence, and for those owning a mobile device in terms of usability. An important implication from the findings, among others, is supplementing Computer Engineering curriculum with elective courses on the fundamentals of mobile learning, and/or the design and development of m-learning software, so as to create, in the long run, more specialized and complementary teams comprised of trained CENG and CEIT graduates in m-learning sector.

  12. Algebraic computing program for studying the gauge theory

    International Nuclear Information System (INIS)

    Zet, G.

    2005-01-01

    An algebraic computing program running on Maple V platform is presented. The program is devoted to the study of the gauge theory with an internal Lie group as local symmetry. The physical quantities (gauge potentials, strength tensors, dual tensors etc.) are introduced either as equations in terms of previous defined quantities (tensors), or by manual entry of the component values. The components of the strength tensor and of its dual are obtained with respect to a given metric of the space-time used for describing the gauge theory. We choose a Minkowski space-time endowed with spherical symmetry and give some example of algebraic computing that are adequate for studying electroweak or gravitational interactions. The field equations are also obtained and their solutions are determined using the DEtools facilities of the Maple V computing program. (author)

  13. Theory and computation of spheroidal wavefunctions

    International Nuclear Information System (INIS)

    Falloon, P E; Abbott, P C; Wang, J B

    2003-01-01

    In this paper we report on a package, written in the Mathematica computer algebra system, which has been developed to compute the spheroidal wavefunctions of Meixner and Schaefke (1954 Mathieusche Funktionen und Sphaeroidfunktionen) and is available online (physics.uwa.edu.au/~falloon/spheroidal/spheroidal.html). This package represents a substantial contribution to the existing software, since it computes the spheroidal wavefunctions to arbitrary precision for general complex parameters μ, ν, γ and argument z; existing software can only handle integer μ, ν and does not give arbitrary precision. The package also incorporates various special cases and computes analytic power series and asymptotic expansions in the parameter γ. The spheroidal wavefunctions of Flammer (1957 Spheroidal Wave functions) are included as a special case of Meixner's more general functions. This paper presents a concise review of the general theory of spheroidal wavefunctions and a description of the formulae and algorithms used in their computation, and gives high precision numerical examples

  14. Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

    Science.gov (United States)

    Frost, Mary E; Derby, Dustin C; Haan, Andrea G

    2013-01-01

    Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

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

    Science.gov (United States)

    Buscema, Massimo; Sacco, Pier Luigi

    2017-01-01

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

  16. Applications of operant learning theory to the management of challenging behavior after traumatic brain injury.

    Science.gov (United States)

    Wood, Rodger Ll; Alderman, Nick

    2011-01-01

    For more than 3 decades, interventions derived from learning theory have been delivered within a neurobehavioral framework to manage challenging behavior after traumatic brain injury with the aim of promoting engagement in the rehabilitation process and ameliorating social handicap. Learning theory provides a conceptual structure that facilitates our ability to understand the relationship between challenging behavior and environmental contingencies, while accommodating the constraints upon learning imposed by impaired cognition. Interventions derived from operant learning theory have most frequently been described in the literature because this method of associational learning provides good evidence for the effectiveness of differential reinforcement methods. This article therefore examines the efficacy of applying operant learning theory to manage challenging behavior after TBI as well as some of the limitations of this approach. Future developments in the application of learning theory are also considered.

  17. Optimizing physicians' instruction of PACS through e-learning: cognitive load theory applied.

    Science.gov (United States)

    Devolder, P; Pynoo, B; Voet, T; Adang, L; Vercruysse, J; Duyck, P

    2009-03-01

    This article outlines the strategy used by our hospital to maximize the knowledge transfer to referring physicians on using a picture archiving and communication system (PACS). We developed an e-learning platform underpinned by the cognitive load theory (CLT) so that in depth knowledge of PACS' abilities becomes attainable regardless of the user's prior experience with computers. The application of the techniques proposed by CLT optimizes the learning of the new actions necessary to obtain and manipulate radiological images. The application of cognitive load reducing techniques is explained with several examples. We discuss the need to safeguard the physicians' main mental processes to keep the patient's interests in focus. A holistic adoption of CLT techniques both in teaching and in configuration of information systems could be adopted to attain this goal. An overview of the advantages of this instruction method is given both on the individual and organizational level.

  18. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Science.gov (United States)

    Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

    2015-01-01

    Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

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

    Science.gov (United States)

    Hsu, Ching-Kun; Hwang, Gwo-Jen

    2014-01-01

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

  20. Computational Phenotypes: Where the Theory of Computation Meets Evo-Devo

    Directory of Open Access Journals (Sweden)

    Sergio Balari

    2009-03-01

    Full Text Available This article argues that the Chomsky Hierarchy can be reinterpreted as a developmental morphospace constraining the evolution of a discrete and finite series of computational phenotypes. In doing so, the theory of Morphological Evolution as stated by Pere Alberch, a pioneering figure of Evo–Devo thinking, is adhered to.

  1. Evaluating clinical simulations for learning procedural skills: a theory-based approach.

    Science.gov (United States)

    Kneebone, Roger

    2005-06-01

    Simulation-based learning is becoming widely established within medical education. It offers obvious benefits to novices learning invasive procedural skills, especially in a climate of decreasing clinical exposure. However, simulations are often accepted uncritically, with undue emphasis being placed on technological sophistication at the expense of theory-based design. The author proposes four key areas that underpin simulation-based learning, and summarizes the theoretical grounding for each. These are (1) gaining technical proficiency (psychomotor skills and learning theory, the importance of repeated practice and regular reinforcement), (2) the place of expert assistance (a Vygotskian interpretation of tutor support, where assistance is tailored to each learner's needs), (3) learning within a professional context (situated learning and contemporary apprenticeship theory), and (4) the affective component of learning (the effect of emotion on learning). The author then offers four criteria for critically evaluating new or existing simulations, based on the theoretical framework outlined above. These are: (1) Simulations should allow for sustained, deliberate practice within a safe environment, ensuring that recently-acquired skills are consolidated within a defined curriculum which assures regular reinforcement; (2) simulations should provide access to expert tutors when appropriate, ensuring that such support fades when no longer needed; (3) simulations should map onto real-life clinical experience, ensuring that learning supports the experience gained within communities of actual practice; and (4) simulation-based learning environments should provide a supportive, motivational, and learner-centered milieu which is conducive to learning.

  2. Computer-Mediated Counter-Arguments and Individual Learning

    Science.gov (United States)

    Hsu, Jack Shih-Chieh; Huang, Hsieh-Hong; Linden, Lars P.

    2011-01-01

    This study explores a de-bias function for a decision support systems (DSS) that is designed to help a user avoid confirmation bias by increasing the user's learning opportunities. Grounded upon the theory of mental models, the use of DSS is viewed as involving a learning process, whereby a user is directed to build mental models so as to reduce…

  3. Maze learning by a hybrid brain-computer system.

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-13

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  4. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

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

    Directory of Open Access Journals (Sweden)

    Ester López Donoso

    2008-09-01

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

  6. Experiential Learning Theory as a Guide for Effective Teaching.

    Science.gov (United States)

    Murrell, Patricia H.; Claxton, Charles S.

    1987-01-01

    David Kolb's experiential learning theory involves a framework useful in designing courses that meet needs of diverse learners. Course designs providing systematic activities in concrete experience, reflective observations, abstract conceptualization, and active experimentation will be sensitive to students' learning styles while challenging…

  7. The (kinetic) theory of active particles applied to learning dynamics. Comment on "Collective learning modeling based on the kinetic theory of active particles" by D. Burini et al.

    Science.gov (United States)

    Nieto, J.

    2016-03-01

    The learning phenomena, their complexity, concepts, structure, suitable theories and models, have been extensively treated in the mathematical literature in the last century, and [4] contains a very good introduction to the literature describing the many approaches and lines of research developed about them. Two main schools have to be pointed out [5] in order to understand the two -not exclusive- kinds of existing models: the stimulus sampling models and the stochastic learning models. Also [6] should be mentioned as a survey where two methods of learning are pointed out, the cognitive and the social, and where the knowledge looks like a mathematical unknown. Finally, as the authors do, we refer to the works [9,10], where the concept of population thinking was introduced and which motivate the game theory rules as a tool (both included in [4] to develop their theory) and [7], where the ideas of developing a mathematical kinetic theory of perception and learning were proposed.

  8. Mobile learning and computational thinking

    Directory of Open Access Journals (Sweden)

    José Manuel Freixo Nunes

    2017-11-01

    Full Text Available Computational thinking can be thought of as an approach to problem solving which has been applied to different areas of learning and which has become an important field of investigation in the area of educational research. [continue

  9. Computer vision and machine learning for archaeology

    NARCIS (Netherlands)

    van der Maaten, L.J.P.; Boon, P.; Lange, G.; Paijmans, J.J.; Postma, E.

    2006-01-01

    Until now, computer vision and machine learning techniques barely contributed to the archaeological domain. The use of these techniques can support archaeologists in their assessment and classification of archaeological finds. The paper illustrates the use of computer vision techniques for

  10. The Last Planner System Style of Planning: Its Basis in Learning Theory

    Directory of Open Access Journals (Sweden)

    Bo Terje Kalsaas

    2012-07-01

    Full Text Available The objective of this article is to contribute to creating a better understanding of the Last Planner System (LPS – which is associated with Lean Construction – in the light of the learning processes at the basis of knowledge development, and of change and innovation. Founded on a theoretical discussion, three research questions are asked, namely: In what ways can the LPS be expected to alter the learning arenas compared to conventional project management in construction; according to learning theory, what are the main challenges associated with implementing the LPS; and, finally, what kind of learning can be linked to an implemented LPS that functions as intended? The implementation of the LPS is shown to require substantial changes to the technical-organisational learning arena. In order for the implementation to be successful, the work identity has to alter on the individual level so that an overlap occurs with the new work practices prescribed by the LPS. The LPS has an inbuilt experiential learning cycle, and provides a good starting point for single-loop learning, as well as for simple forms of double-loop learning (“routinized learning capability”. However, it is argued that the LPS understood as experiential learning has clear limitations with regard to “evolutionary learning capability”. This is amplified by the context project organisation provides. In terms of theoretical implications, this article promotes an understanding of the planning process informed by the theory describing it as an experiential learning cycle. The conceptualisation which separates the LPS from conventional production control theory is critiqued. Finally, it is argued that an understanding of the LPS grounded in learning theory will improve the possibilities for successful implementation and maximise the learning effects.

  11. Collective learning modeling based on the kinetic theory of active particles

    Science.gov (United States)

    Burini, D.; De Lillo, S.; Gibelli, L.

    2016-03-01

    This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom.

  12. Networks and learning in game theory

    NARCIS (Netherlands)

    Kets, W.

    2008-01-01

    This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network.

  13. Introduction to lattice theory with computer science applications

    CERN Document Server

    Garg, Vijay K

    2015-01-01

    A computational perspective on partial order and lattice theory, focusing on algorithms and their applications This book provides a uniform treatment of the theory and applications of lattice theory. The applications covered include tracking dependency in distributed systems, combinatorics, detecting global predicates in distributed systems, set families, and integer partitions. The book presents algorithmic proofs of theorems whenever possible. These proofs are written in the calculational style advocated by Dijkstra, with arguments explicitly spelled out step by step. The author's intent

  14. Quantum chemistry simulation on quantum computers: theories and experiments.

    Science.gov (United States)

    Lu, Dawei; Xu, Boruo; Xu, Nanyang; Li, Zhaokai; Chen, Hongwei; Peng, Xinhua; Xu, Ruixue; Du, Jiangfeng

    2012-07-14

    It has been claimed that quantum computers can mimic quantum systems efficiently in the polynomial scale. Traditionally, those simulations are carried out numerically on classical computers, which are inevitably confronted with the exponential growth of required resources, with the increasing size of quantum systems. Quantum computers avoid this problem, and thus provide a possible solution for large quantum systems. In this paper, we first discuss the ideas of quantum simulation, the background of quantum simulators, their categories, and the development in both theories and experiments. We then present a brief introduction to quantum chemistry evaluated via classical computers followed by typical procedures of quantum simulation towards quantum chemistry. Reviewed are not only theoretical proposals but also proof-of-principle experimental implementations, via a small quantum computer, which include the evaluation of the static molecular eigenenergy and the simulation of chemical reaction dynamics. Although the experimental development is still behind the theory, we give prospects and suggestions for future experiments. We anticipate that in the near future quantum simulation will become a powerful tool for quantum chemistry over classical computations.

  15. Dual Coding Theory and Computer Education: Some Media Experiments To Examine the Effects of Different Media on Learning.

    Science.gov (United States)

    Alty, James L.

    Dual Coding Theory has quite specific predictions about how information in different media is stored, manipulated and recalled. Different combinations of media are expected to have significant effects upon the recall and retention of information. This obviously may have important consequences in the design of computer-based programs. The paper…

  16. Cryptography and computational number theory

    CERN Document Server

    Shparlinski, Igor; Wang, Huaxiong; Xing, Chaoping; Workshop on Cryptography and Computational Number Theory, CCNT'99

    2001-01-01

    This volume contains the refereed proceedings of the Workshop on Cryptography and Computational Number Theory, CCNT'99, which has been held in Singapore during the week of November 22-26, 1999. The workshop was organized by the Centre for Systems Security of the Na­ tional University of Singapore. We gratefully acknowledge the financial support from the Singapore National Science and Technology Board under the grant num­ ber RP960668/M. The idea for this workshop grew out of the recognition of the recent, rapid development in various areas of cryptography and computational number the­ ory. The event followed the concept of the research programs at such well-known research institutions as the Newton Institute (UK), Oberwolfach and Dagstuhl (Germany), and Luminy (France). Accordingly, there were only invited lectures at the workshop with plenty of time for informal discussions. It was hoped and successfully achieved that the meeting would encourage and stimulate further research in information and computer s...

  17. A Theoretical Analysis of Learning with Graphics--Implications for Computer Graphics Design.

    Science.gov (United States)

    ChanLin, Lih-Juan

    This paper reviews the literature pertinent to learning with graphics. The dual coding theory provides explanation about how graphics are stored and precessed in semantic memory. The level of processing theory suggests how graphics can be employed in learning to encourage deeper processing. In addition to dual coding theory and level of processing…

  18. Internet messenger based smart virtual class learning using ubiquitous computing

    Science.gov (United States)

    Umam, K.; Mardi, S. N. S.; Hariadi, M.

    2017-06-01

    Internet messenger (IM) has become an important educational technology component in college education, IM makes it possible for students to engage in learning and collaborating at smart virtual class learning (SVCL) using ubiquitous computing. However, the model of IM-based smart virtual class learning using ubiquitous computing and empirical evidence that would favor a broad application to improve engagement and behavior are still limited. In addition, the expectation that IM based SVCL using ubiquitous computing could improve engagement and behavior on smart class cannot be confirmed because the majority of the reviewed studies followed instructions paradigms. This article aims to present the model of IM-based SVCL using ubiquitous computing and showing learners’ experiences in improved engagement and behavior for learner-learner and learner-lecturer interactions. The method applied in this paper includes design process and quantitative analysis techniques, with the purpose of identifying scenarios of ubiquitous computing and realize the impressions of learners and lecturers about engagement and behavior aspect and its contribution to learning

  19. Role of Adult Learning Theories in the Development of Corporate Training in the USA

    Directory of Open Access Journals (Sweden)

    Iryna Lytovchenko

    2016-07-01

    Full Text Available The article presents the analysis of the role of adult learning theories in the development of corporate training in the USA. Considering that corporate education is part of the adult education system in this country, the author examines theories of organizational learning in the context of adult learning. The results of the study have revealed that adult education in the US is based on dif erent learning theories which should be viewed from the perspective of several main orientations: behaviorism, cognitivism, humanism, developmental theories, social learning, constructivism, which have dif erent philosophical background and, accordingly, different understanding of the nature and methodology of adult learning. Based on the results of the study it has been concluded that theories of organizational learning which explain motivation of students, their needs and goals, cognitive processes and other aspects of the learning in organizations and have had the main influence on the development of corporate education in the United States should be viewed in the context of the above-mentioned basic orientations to learning, too. From the methodological perspective, the research was based on interdisciplinary and systemic approaches. Thus, we used a set of interrelated research methods: comparative, structural, systemic-functional analyses, comparison and synthesis.

  20. Implementation of the equivalence theory inside the computational chain DRAGON/DONJON-NDF

    International Nuclear Information System (INIS)

    Dufour, P.

    2005-01-01

    The work accomplished in the scope of this master project consists in introducing the equivalence theory inside the computational schema DRAGON/DONJON-NDF. This theory takes into account the possible discontinuity of the homogeneous flux at the surfaces inside problems that involve an homogenisation procedure. To do it, the theory include new factors called discontinuity factors. These factors give, in theory, more exact solutions. Because we use the cell code DRAGON to generate all our homogeneous parameters we also used DRAGON to compute the heterogeneous surface fluxes which are essential to obtain the discontinuity factors. The project has been divided into two parts. The first part consists in computing the heterogeneous surface fluxes with the cell code DRAGON. For the second part of the project we have performed reactor computations using the code DONJON-NDF (over CANDU-6 geometry) with discontinuity factors and we have compared the results thus obtained with those computed without discontinuity factors.

  1. Computer games as a pedagogical tool in education

    OpenAIRE

    Maher, Ken

    1997-01-01

    Designing computer based environments is never easy, especially when considering young learners. Traditionally, computer gaming has been seen as lacking in educational value, but rating highly in satisfaction and motivation. The objective of this dissertation is to look at elements of computer based learning and to ascertain how computer games can be included as a means of improving learning. Various theories are drawn together from psychology, instructional technology and computer gaming, to...

  2. Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.

    Directory of Open Access Journals (Sweden)

    Kristoffer Carl Aberg

    Full Text Available Learning how to gain rewards (approach learning and avoid punishments (avoidance learning is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance learning scored higher on measures of approach (vs. avoidance trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits.

  3. Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

    Science.gov (United States)

    Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

    2016-01-01

    Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807

  4. Game based learning for computer science education

    NARCIS (Netherlands)

    Schmitz, Birgit; Czauderna, André; Klemke, Roland; Specht, Marcus

    2011-01-01

    Schmitz, B., Czauderna, A., Klemke, R., & Specht, M. (2011). Game based learning for computer science education. In G. van der Veer, P. B. Sloep, & M. van Eekelen (Eds.), Computer Science Education Research Conference (CSERC '11) (pp. 81-86). Heerlen, The Netherlands: Open Universiteit.

  5. Learning to consult with computers.

    Science.gov (United States)

    Liaw, S T; Marty, J J

    2001-07-01

    To develop and evaluate a strategy to teach skills and issues associated with computers in the consultation. An overview lecture plus a workshop before and a workshop after practice placements, during the 10-week general practice (GP) term in the 5th year of the University of Melbourne medical course. Pre- and post-intervention study using a mix of qualitative and quantitative methods within a strategic evaluation framework. Self-reported attitudes and skills with clinical applications before, during and after the intervention. Most students had significant general computer experience but little in the medical area. They found the workshops relevant, interesting and easy to follow. The role-play approach facilitated students' learning of relevant communication and consulting skills and an appreciation of issues associated with using the information technology tools in simulated clinical situations to augment and complement their consulting skills. The workshops and exposure to GP systems were associated with an increase in the use of clinical software, more realistic expectations of existing clinical and medical record software and an understanding of the barriers to the use of computers in the consultation. The educational intervention assisted students to develop and express an understanding of the importance of consulting and communication skills in teaching and learning about medical informatics tools, hardware and software design, workplace issues and the impact of clinical computer systems on the consultation and patient care.

  6. Connectivism: A knowledge learning theory for the digital age?

    Science.gov (United States)

    Goldie, John Gerard Scott

    2016-10-01

    The emergence of the internet, particularly Web 2.0 has provided access to the views and opinions of a wide range of individuals opening up opportunities for new forms of communication and knowledge formation. Previous ways of navigating and filtering available information are likely to prove ineffective in these new contexts. Connectivism is one of the most prominent of the network learning theories which have been developed for e-learning environments. It is beginning to be recognized by medical educators. This article aims to examine connectivism and its potential application. The conceptual framework and application of connectivism are presented along with an outline of the main criticisms. Its potential application in medical education is then considered. While connectivism provides a useful lens through which teaching and learning using digital technologies can be better understood and managed, further development and testing is required. There is unlikely to be a single theory that will explain learning in technological enabled networks. Educators have an important role to play in online network learning.

  7. Text Mining Applications and Theory

    CERN Document Server

    Berry, Michael W

    2010-01-01

    Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.  The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning

  8. Aligning Coordination Class Theory with a New Context: Applying a Theory of Individual Learning to Group Learning

    Science.gov (United States)

    Barth-Cohen, Lauren A.; Wittmann, Michael C.

    2017-01-01

    This article presents an empirical analysis of conceptual difficulties encountered and ways students made progress in learning at both individual and group levels in a classroom environment in which the students used an embodied modeling activity to make sense of a specific scientific scenario. The theoretical framework, coordination class theory,…

  9. Learning styles: individualizing computer-based learning environments

    Directory of Open Access Journals (Sweden)

    Tim Musson

    1995-12-01

    Full Text Available While the need to adapt teaching to the needs of a student is generally acknowledged (see Corno and Snow, 1986, for a wide review of the literature, little is known about the impact of individual learner-differences on the quality of learning attained within computer-based learning environments (CBLEs. What evidence there is appears to support the notion that individual differences have implications for the degree of success or failure experienced by students (Ford and Ford, 1992 and by trainee end-users of software packages (Bostrom et al, 1990. The problem is to identify the way in which specific individual characteristics of a student interact with particular features of a CBLE, and how the interaction affects the quality of the resultant learning. Teaching in a CBLE is likely to require a subset of teaching strategies different from that subset appropriate to more traditional environments, and the use of a machine may elicit different behaviours from those normally arising in a classroom context.

  10. Quantum machine learning what quantum computing means to data mining

    CERN Document Server

    Wittek, Peter

    2014-01-01

    Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine L

  11. Development and application of social learning theory.

    Science.gov (United States)

    Price, V; Archbold, J

    This article traces the development of social learning theory over the last 30 years, relating the developments to clinical nursing practice. Particular attention is focused on the contribution of Albert Bandura, the American psychologist, and his work on modelling.

  12. Deep Learning in Visual Computing and Signal Processing

    OpenAIRE

    Xie, Danfeng; Zhang, Lei; Bai, Li

    2017-01-01

    Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data. Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing. In this study, we not only review typical deep learning algorithms in computer vision and signal processing but also provide detailed information on how to apply...

  13. Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision.

    Science.gov (United States)

    Wolff, J Gerard

    2014-01-01

    The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

  14. Talking back to theory: the missed opportunities in learning technology research

    Directory of Open Access Journals (Sweden)

    Martin Oliver

    2011-12-01

    Full Text Available Research into learning technology has developed a reputation for being drivenby rhetoric about the revolutionary nature of new developments, for payingscant attention to theories that might be used to frame and inform research, andfor producing shallow analyses that do little to inform the practice of education.Although there is theoretically-informed research in learning technology, this isin the minority, and has been actively marginalised by calls for applied designwork. This limits opportunities to advance knowledge in the field. Using threeexamples, alternative ways to engage with theory are identified. The paper concludesby calling for greater engagement with theory, and the development of ascholarship of learning technology, in order to enrich practice within the fieldand demonstrate its relevance to other fields of work.

  15. Doping Among Professional Athletes in Iran: A Test of Akers's Social Learning Theory.

    Science.gov (United States)

    Kabiri, Saeed; Cochran, John K; Stewart, Bernadette J; Sharepour, Mahmoud; Rahmati, Mohammad Mahdi; Shadmanfaat, Syede Massomeh

    2018-04-01

    The use of performance-enhancing drugs (PED) is common among Iranian professional athletes. As this phenomenon is a social problem, the main purpose of this research is to explain why athletes engage in "doping" activity, using social learning theory. For this purpose, a sample of 589 professional athletes from Rasht, Iran, was used to test assumptions related to social learning theory. The results showed that there are positive and significant relationships between the components of social learning theory (differential association, differential reinforcement, imitation, and definitions) and doping behavior (past, present, and future use of PED). The structural modeling analysis indicated that the components of social learning theory accounts for 36% of the variance in past doping behavior, 35% of the variance in current doping behavior, and 32% of the variance in future use of PED.

  16. Public Computer Assisted Learning Facilities for Children with Visual Impairment: Universal Design for Inclusive Learning

    Science.gov (United States)

    Siu, Kin Wai Michael; Lam, Mei Seung

    2012-01-01

    Although computer assisted learning (CAL) is becoming increasingly popular, people with visual impairment face greater difficulty in accessing computer-assisted learning facilities. This is primarily because most of the current CAL facilities are not visually impaired friendly. People with visual impairment also do not normally have access to…

  17. Twenty-First Century Learning: Communities, Interaction and Ubiquitous Computing

    Science.gov (United States)

    Leh, Amy S.C.; Kouba, Barbara; Davis, Dirk

    2005-01-01

    Advanced technology makes 21st century learning, communities and interactions unique and leads people to an era of ubiquitous computing. The purpose of this article is to contribute to the discussion of learning in the 21st century. The paper will review literature on learning community, community learning, interaction, 21st century learning and…

  18. Computer Proficiency for Online Learning: Factorial Invariance of Scores among Teachers

    Science.gov (United States)

    Martin, Amy L.; Reeves, Todd D.; Smith, Thomas J.; Walker, David A.

    2016-01-01

    Online learning is variously employed in K-12 education, including for teacher professional development. However, the use of computer-based technologies for learning purposes assumes learner computer proficiency, making this construct an important domain of procedural knowledge in formal and informal online learning contexts. Addressing this…

  19. Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

    Science.gov (United States)

    Ma, Zhanshan (Sam)

    In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three

  20. Dictionary learning in visual computing

    CERN Document Server

    Zhang, Qiang

    2015-01-01

    The last few years have witnessed fast development on dictionary learning approaches for a set of visual computing tasks, largely due to their utilization in developing new techniques based on sparse representation. Compared with conventional techniques employing manually defined dictionaries, such as Fourier Transform and Wavelet Transform, dictionary learning aims at obtaining a dictionary adaptively from the data so as to support optimal sparse representation of the data. In contrast to conventional clustering algorithms like K-means, where a data point is associated with only one cluster c

  1. Thermodynamic and transport properties of nitrogen fluid: Molecular theory and computer simulations

    Science.gov (United States)

    Eskandari Nasrabad, A.; Laghaei, R.

    2018-04-01

    Computer simulations and various theories are applied to compute the thermodynamic and transport properties of nitrogen fluid. To model the nitrogen interaction, an existing potential in the literature is modified to obtain a close agreement between the simulation results and experimental data for the orthobaric densities. We use the Generic van der Waals theory to calculate the mean free volume and apply the results within the modified Cohen-Turnbull relation to obtain the self-diffusion coefficient. Compared to experimental data, excellent results are obtained via computer simulations for the orthobaric densities, the vapor pressure, the equation of state, and the shear viscosity. We analyze the results of the theory and computer simulations for the various thermophysical properties.

  2. E-Learning Content Design Standards Based on Interactive Digital Concepts Maps in the Light of Meaningful and Constructivist Learning Theory

    Science.gov (United States)

    Afify, Mohammed Kamal

    2018-01-01

    The present study aims to identify standards of interactive digital concepts maps design and their measurement indicators as a tool to develop, organize and administer e-learning content in the light of Meaningful Learning Theory and Constructivist Learning Theory. To achieve the objective of the research, the author prepared a list of E-learning…

  3. The Application of Carl Rogers' Person-Centered Learning Theory to Web-Based Instruction.

    Science.gov (United States)

    Miller, Christopher T.

    This paper provides a review of literature that relates research on Carl Rogers' person-centered learning theory to Web-based learning. Based on the review of the literature, a set of criteria is described that can be used to determine how closely a Web-based course matches the different components of Rogers' person-centered learning theory. Using…

  4. An Interactive Learning Environment for Information and Communication Theory

    Science.gov (United States)

    Hamada, Mohamed; Hassan, Mohammed

    2017-01-01

    Interactive learning tools are emerging as effective educational materials in the area of computer science and engineering. It is a research domain that is rapidly expanding because of its positive impacts on motivating and improving students' performance during the learning process. This paper introduces an interactive learning environment for…

  5. Collective learning modeling based on the kinetic theory of active particles.

    Science.gov (United States)

    Burini, D; De Lillo, S; Gibelli, L

    2016-03-01

    This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Social Capital Theory: Implications for Women's Networking and Learning

    Science.gov (United States)

    Alfred, Mary V.

    2009-01-01

    This chapter describes social capital theory as a framework for exploring women's networking and social capital resources. It presents the foundational assumptions of the theory, the benefits and risks of social capital engagement, a feminist critique of social capital, and the role of social capital in adult learning.

  7. Analysis of ensemble learning using simple perceptrons based on online learning theory

    Science.gov (United States)

    Miyoshi, Seiji; Hara, Kazuyuki; Okada, Masato

    2005-03-01

    Ensemble learning of K nonlinear perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. One purpose of statistical learning theory is to theoretically obtain the generalization error. This paper shows that ensemble generalization error can be calculated by using two order parameters, that is, the similarity between a teacher and a student, and the similarity among students. The differential equations that describe the dynamical behaviors of these order parameters are derived in the case of general learning rules. The concrete forms of these differential equations are derived analytically in the cases of three well-known rules: Hebbian learning, perceptron learning, and AdaTron (adaptive perceptron) learning. Ensemble generalization errors of these three rules are calculated by using the results determined by solving their differential equations. As a result, these three rules show different characteristics in their affinity for ensemble learning, that is “maintaining variety among students.” Results show that AdaTron learning is superior to the other two rules with respect to that affinity.

  8. Narrative theories as computational models: reader-oriented theory and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Galloway, P.

    1983-12-01

    In view of the rapid development of reader-oriented theory and its interest in dynamic models of narrative, the author speculates in a serious way about what such models might look like in computational terms. Researchers in artificial intelligence (AI) have already begun to develop models of story understanding as the emphasis in ai research has shifted toward natural language understanding and as ai has allied itself with cognitive psychology and linguistics to become cognitive science. Research in ai and in narrative theory share many common interests and problems and both studies might benefit from an exchange of ideas. 11 references.

  9. Game theory, alive

    CERN Document Server

    Karlin, Anna R

    2016-01-01

    This book presents a rigorous introduction to the mathematics of game theory without losing sight of the joy of the subject. This is done by focusing on theoretical highlights (e.g., at least six Nobel Prize winning results are developed from scratch) and by presenting exciting connections of game theory to other fields, such as computer science, economics, social choice, biology, and learning theory. Both classical topics, such as zero-sum games, and modern topics, such as sponsored search auctions, are covered. Along the way, beautiful mathematical tools used in game theory are introduced, including convexity, fixed-point theorems, and probabilistic arguments. The book is appropriate for a first course in game theory at either the undergraduate or graduate level, whether in mathematics, economics, computer science, or statistics. Game theory's influence is felt in a wide range of disciplines, and the authors deliver masterfully on the challenge of presenting both the breadth and coherence of its underlying ...

  10. Action Learning and Constructivist Grounded Theory: Powerfully Overlapping Fields of Practice

    Science.gov (United States)

    Rand, Jane

    2013-01-01

    This paper considers the shared characteristics between action learning (AL) and the research methodology constructivist grounded theory (CGT). Mirroring Edmonstone's [2011. "Action Learning and Organisation Development: Overlapping Fields of Practice." "Action Learning: Research and Practice" 8 (2): 93-102] article, which…

  11. Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

    Science.gov (United States)

    van Ginneken, Bram

    2017-03-01

    Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

  12. Learning Theories and Skills in Online Second Language Teaching and Learning: Dilemmas and Challenges

    Science.gov (United States)

    Petersen, Karen Bjerg

    2014-01-01

    For decades foreign and second language teachers have taken advantage of the technology development and ensuing possibilities to use e-learning facilities for language training. Since the 1980s, the use of computer assisted language learning (CALL), Internet, web 2.0, and various kinds of e-learning technology has been developed and researched…

  13. Collaborative Learning: Cognitive and Computational Approaches. Advances in Learning and Instruction Series.

    Science.gov (United States)

    Dillenbourg, Pierre, Ed.

    Intended to illustrate the benefits of collaboration between scientists from psychology and computer science, namely machine learning, this book contains the following chapters, most of which are co-authored by scholars from both sides: (1) "Introduction: What Do You Mean by 'Collaborative Learning'?" (Pierre Dillenbourg); (2)…

  14. Motivational Classroom Climate for Learning Mathematics: A Reversal Theory Perspective

    Science.gov (United States)

    Lewis, Gareth

    2015-01-01

    In this article, a case is made that affect is central in determining students' experience of learning or not learning mathematics. I show how reversal theory (Apter, 2001), and particularly its taxonomy of motivations and emotions, provides a basis for a thick description of students' experiences of learning in a mathematics classroom. Using data…

  15. A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

    Science.gov (United States)

    Zendehrouh, Sareh

    2015-11-01

    Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. The Implementation of Cumulative Learning Theory in Calculating Triangular Prism and Tube Volumes

    Science.gov (United States)

    Muklis, M.; Abidin, C.; Pamungkas, M. D.; Masriyah

    2018-01-01

    This study aims at describing the application of cumulative learning theory in calculating the volume of a triangular prism and a tube as well as revealing the students’ responses toward the learning. The research method used was descriptive qualitative with elementary school students as the subjects of the research. Data obtained through observation, field notes, questionnaire, tests, and interviews. The results from the application of cumulative learning theory obtained positive students’ responses in following the learning and students’ learning outcomes was dominantly above the average. This showed that cumulative learning could be used as a reference to be implemented in learning, so as to improve the students’ achievement.

  17. Using Activity Theory to Design Constructivist Online Learning Environments for Higher Order Thinking: A Retrospective Analysis

    Directory of Open Access Journals (Sweden)

    Dirk Morrison

    2003-10-01

    Full Text Available Abstract. This paper examined a particular online learning activity, embedded within a computer supported collaborative learning (CSCL environment incorporated as part of the larger context of participation in a unique national agricultural leadership development program. Process outcomes such as a high level of collaboration and active peer facilitation as well as demonstration by participants of a variety of holistic thinking skills were observed via a transcript analysis of online interactions. This led to speculations that the particular design features embedded within the context of the online collaborative issues analysis project (IAP, were thought to clearly reflect a constructivist approach. Methods to confirm this included evaluating the learning activity in light of nine characteristics of an authentic task in CSCL environments, and using activity theory as a conceptual framework with which to further examine the extent to which the IAP reflected the values and principles of a constructivist online learning environment.

  18. Theory in learning technology

    Directory of Open Access Journals (Sweden)

    Laura Czerniewicz

    2011-12-01

    Full Text Available This special issue is being published at a significant point in time in relation tosimultaneous changes in higher education, in technology and in the field of learningtechnology itself. As the 2011 ALT C conference themes clearly state, learningtechnology needs to learn to thrive in a colder and more challenging climate. In thisdifficult political and economic environment technological trends continue todevelop in terms of mobility, cloud computing, ubiquity and the emergence of whathas been called big data. E-learning has become mainstream and the field of learningtechnology itself is beginning to stabilise as a profession. Profession here isunderstood as a knowledge-based occupation and a form of cultural work where thetasks addressed are human problems amenable to expert advice and distinguishablefrom other kinds of work by the fact that it is underpinned by abstract knowledge(Macdonald, 1995.

  19. Learning about the past with new technologies : Fostering historical reasoning in computer-supported collaborative learning

    NARCIS (Netherlands)

    Drie, J.P. van

    2005-01-01

    Recent technological developments have provided new environments for learning, giving rise to the question of how characteristics of such new learning environments can facilitate the process of learning in specific domains. The focus of this thesis is on computer-supported collaborative learning

  20. A Visual Encapsulation of Adlerian Theory: A Tool for Teaching and Learning.

    Science.gov (United States)

    Osborn, Cynthia J.

    2001-01-01

    A visual diagram is presented in this article to illustrate 6 key concepts of Adlerian theory discussed in corresponding narrative format. It is proposed that in an age of multimedia learning, a pictorial reference can enhance the teaching and learning of Adlerian theory, representing a commitment to humanistic education. (Contains 18 references.)…

  1. Finding the Right Fit: Helping Students Apply Theory to Service-Learning Contexts

    Science.gov (United States)

    Ricke, Audrey

    2018-01-01

    Background: Although past studies of service-learning focus on assessing student growth, few studies address how to support students in applying theory to their service-learning experiences. Yet, the task of applying theory is a central component of critical reflections within the social sciences in higher education and often causes anxiety among…

  2. Vaccination learning experiences of nursing students: a grounded theory study.

    Science.gov (United States)

    Ildarabadi, Eshagh; Karimi Moonaghi, Hossein; Heydari, Abbas; Taghipour, Ali; Abdollahimohammad, Abdolghani

    2015-01-01

    This study aimed to explore the experiences of nursing students being trained to perform vaccinations. The grounded theory method was applied to gather information through semi-structured interviews. The participants included 14 undergraduate nursing students in their fifth and eighth semesters of study in a nursing school in Iran. The information was analyzed according to Strauss and Corbin's method of grounded theory. A core category of experiential learning was identified, and the following eight subcategories were extracted: students' enthusiasm, vaccination sensitivity, stress, proper educational environment, absence of prerequisites, students' responsibility for learning, providing services, and learning outcomes. The vaccination training of nursing students was found to be in an acceptable state. However, some barriers to effective learning were identified. As such, the results of this study may provide empirical support for attempts to reform vaccination education by removing these barriers.

  3. Quantum computing for pattern classification

    OpenAIRE

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2014-01-01

    It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning using the example of pattern classification. We introduce a quantum pattern classification algorithm that draws on Trugenberger's proposal for measuring the Hamming di...

  4. Placing computer security at the heart of learning

    OpenAIRE

    Richards, Mike; Price, Blaine A.; Nuseibeh, Bashar

    2008-01-01

    In this paper we present the approach adopted at the UK’s Open University for teaching computer security to large numbers of students at a distance through supported open learning. We discuss how the production of learning materials at the university has had to change to reflect the ever-increasing rate of technological, legislative and social change within the computing discipline, and how the university has had to rethink the role of the academic in the course development process. We argue ...

  5. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Directory of Open Access Journals (Sweden)

    Xiaolei Ma

    Full Text Available Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS and Internet of Things (IoT, transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  6. Stochastic learning in oxide binary synaptic device for neuromorphic computing.

    Science.gov (United States)

    Yu, Shimeng; Gao, Bin; Fang, Zheng; Yu, Hongyu; Kang, Jinfeng; Wong, H-S Philip

    2013-01-01

    Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on) transition of metal oxide resistive switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochastic SET transition was statistically measured and modeled for a simulation of a winner-take-all network for competitive learning. The simulation illustrates that with such stochastic learning, the orientation classification function of input patterns can be effectively realized. The system performance metrics were compared between the conventional approach using the analog synapse and the approach in this work that employs the binary synapse utilizing the stochastic learning. The feasibility of using binary synapse in the neurormorphic computing may relax the constraints to engineer continuous multilevel intermediate states and widens the material choice for the synaptic device design.

  7. Andragogy And Pedagogy Theories Of Learning In Joint Professional Military Education

    Science.gov (United States)

    2015-09-27

    needs of joint military leaders. This research examines each theory and its fundamental design in an attempt to determine if pedagogy alone can meet... Abraham H. Maslow , known largely for his studies in motivation and personality, saw the goal of learning to be self-actualization, or a person’s...AU/ACSC/MCMAHON, S/AY16 AIR COMMAND AND STAFF COLLEGE AIR UNIVERSITY ANDRAGOGY AND PEDAGOGY THEORIES OF LEARNING IN JOINT PROFESSIONAL

  8. On Wigner's problem, computability theory, and the definition of life

    International Nuclear Information System (INIS)

    Swain, J.

    1998-01-01

    In 1961, Eugene Wigner presented a clever argument that in a world which is adequately described by quantum mechanics, self-reproducing systems in general, and perhaps life in particular, would be incredibly improbable. The problem and some attempts at its solution are examined, and a new solution is presented based on computability theory. In particular, it is shown that computability theory provides limits on what can be known about a system in addition to those which arise from quantum mechanics. (author)

  9. Machine learning and computer vision approaches for phenotypic profiling.

    Science.gov (United States)

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

    2017-01-02

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

  10. Using David Kolb's Experiential Learning Theory in Portfolio Development Courses.

    Science.gov (United States)

    Mark, Michael; Menson, Betty

    1982-01-01

    As personal portfolio assessment matures, practitioners continue to look for techniques that enhance both personal development and the process of seeking academic credit through assessment. Kolb's experiential learning theory and learning style inventory may have applications in this search. (Author)

  11. E-learn Computed Tomographic Angiography

    DEFF Research Database (Denmark)

    Havsteen, Inger; Christensen, Anders; Nielsen, Jens K

    2012-01-01

    BACKGROUND: Computed tomographic angiography (CTA) is widely available in emergency rooms to assess acute stroke patients. To standardize readings and educate new readers, we developed a 3-step e-learning tool based on the test-teach-retest methodology in 2 acute stroke scenarios: vascular...... occlusion and "spot sign" in acute intracerebral hemorrhage. We hypothesized that an e-learning program enhances reading skills in physicians of varying experience. METHODS: We developed an HTML-based program with a teaching segment and 2 matching test segments. Tests were taken before and after...... sign correctly 69% before versus 92% after teaching (P = .009) and reported a median self-perceived diagnostic certainty of 50% versus 75% (P = .030). Self-perceived diagnostic certainty revealed no significant increase for vascular occlusion. CONCLUSIONS: The e-learning program is a useful educational...

  12. Using Active-Learning Pedagogy to Develop Essay-Writing Skills in Introductory Political Theory Tutorials

    Science.gov (United States)

    Murphy, Michael P. A.

    2017-01-01

    Building on prior research into active learning pedagogy in political science, I discuss the development of a new active learning strategy called the "thesis-building carousel," designed for use in political theory tutorials. This use of active learning pedagogy in a graduate student-led political theory tutorial represents the overlap…

  13. Educating Through Exploration: Emerging Evidence for Improved Learning Outcomes Using a New Theory of Digital Learning Design

    Science.gov (United States)

    Anbar, Ariel; Center for Education Through eXploration

    2018-01-01

    Advances in scientific visualization and public access to data have transformed science outreach and communication, but have yet to realize their potential impacts in the realm of education. Computer-based learning is a clear bridge between visualization and education that benefits students through adaptative personalization and enhanced access. Building this bridge requires close partnerships among scientists, technologists, and educators.The Infiniscope project fosters such partnerships to produce exploration-driven online learning experiences that teach basic science concepts using a combination of authentic space science narratives, data, and images, and a personalized guided inquiry approach. Infiniscope includes a web portal to host these digital learning experiences, as well as a teaching network of educators using and modifying these experiences. Infiniscope experiences are built around a new theory of digital learning design that we call “education through exploration” (ETX) developed during the creation of successful online, interactive science courses offered at ASU and other institutions. ETX builds on the research-based practices of active learning and guided inquiry to provide a set of design principles that aim to develop higher order thinking skills in addition to understanding of content. It is employed in these experiences by asking students to solve problems and actively discover relationships, supported by an intelligent tutoring system which provides immediate, personalized feedback and scaffolds scientific thinking and methods. The project is led by ASU’s School of Earth and Space Exploration working with learning designers in the Center for Education Through eXploration, with support from NASA’s Science Mission Directorate as part of the NASA Exploration Connection program.We will present an overview of ETX design, the Infinscope project, and emerging evidence of effectiveness.

  14. Dynamic Scaffolding of Socially Regulated Learning in a Computer-Based Learning Environment

    NARCIS (Netherlands)

    Molenaar, I.; Roda, Claudia; van Boxtel, Carla A.M.; Sleegers, P.J.C.

    2012-01-01

    The aim of this study is to test the effects of dynamically scaffolding social regulation of middle school students working in a computer-based learning environment. Dyads in the scaffolding condition (N = 56) are supported with computer-generated scaffolds and students in the control condition (N =

  15. Prior Knowledge and the Learning of Science. A Review of Ausubel's Theory of This Process

    Science.gov (United States)

    West, L. H. T.; Fensham, P. J.

    1974-01-01

    Examines Ausubel's theory of learning as a model of the role concerning the influence of prior knowledge on how learning occurs. Research evidence for Ausubel's theory is presented and discussed. Implications of Ausubel's theory for teaching are summarized. (PEB)

  16. Identification of Learning Processes by Means of Computer Graphics.

    Science.gov (United States)

    Sorensen, Birgitte Holm

    1993-01-01

    Describes a development project for the use of computer graphics and video in connection with an inservice training course for primary education teachers in Denmark. Topics addressed include research approaches to computers; computer graphics in learning processes; activities relating to computer graphics; the role of the teacher; and student…

  17. The Self-Perception Theory vs. a Dynamic Learning Model

    OpenAIRE

    Swank, Otto H.

    2006-01-01

    Several economists have directed our attention to a finding in the social psychological literature that extrinsic motivation may undermine intrinsic motivation. The self-perception (SP) theory developed by Bem (1972) explains this finding. The crux of this theory is that people remember their past decisions and the extrinsic rewards they received, but they do not recall their intrinsic motives. In this paper I show that the SP theory can be modeled as a variant of a conventional dynamic learn...

  18. Blind Quantum Computation

    DEFF Research Database (Denmark)

    Salvail, Louis; Arrighi, Pablo

    2006-01-01

    We investigate the possibility of "having someone carry out the work of executing a function for you, but without letting him learn anything about your input". Say Alice wants Bob to compute some known function f upon her input x, but wants to prevent Bob from learning anything about x. The situa......We investigate the possibility of "having someone carry out the work of executing a function for you, but without letting him learn anything about your input". Say Alice wants Bob to compute some known function f upon her input x, but wants to prevent Bob from learning anything about x....... The situation arises for instance if client Alice has limited computational resources in comparison with mistrusted server Bob, or if x is an inherently mobile piece of data. Could there be a protocol whereby Bob is forced to compute f(x) "blindly", i.e. without observing x? We provide such a blind computation...... protocol for the class of functions which admit an efficient procedure to generate random input-output pairs, e.g. factorization. The cheat-sensitive security achieved relies only upon quantum theory being true. The security analysis carried out assumes the eavesdropper performs individual attacks....

  19. Presentation-Practice-Production and Task-Based Learning in the Light of Second Language Learning Theories.

    Science.gov (United States)

    Ritchie, Graeme

    2003-01-01

    Features of presentation-practice-production (PPP) and task-based learning (TBL) models for language teaching are discussed with reference to language learning theories. Pre-selection of target structures, use of controlled repetition, and explicit grammar instruction in a PPP lesson are given. Suggests TBL approaches afford greater learning…

  20. Computer-aided classification of lung nodules on computed tomography images via deep learning technique

    Directory of Open Access Journals (Sweden)

    Hua KL

    2015-08-01

    Full Text Available Kai-Lung Hua,1 Che-Hao Hsu,1 Shintami Chusnul Hidayati,1 Wen-Huang Cheng,2 Yu-Jen Chen3 1Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, 2Research Center for Information Technology Innovation, Academia Sinica, 3Department of Radiation Oncology, MacKay Memorial Hospital, Taipei, Taiwan Abstract: Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. Keywords: nodule classification, deep learning, deep belief network, convolutional neural network

  1. Students’ needs of Computer Science: learning about image processing

    Directory of Open Access Journals (Sweden)

    Juana Marlen Tellez Reinoso

    2009-12-01

    Full Text Available To learn the treatment to image, specifically in the application Photoshop Marinates is one of the objectives in the specialty of Degree in Education, Computer Sciencie, guided to guarantee the preparation of the students as future professional, being able to reach in each citizen of our country an Integral General Culture. With that purpose a computer application is suggested, of tutorial type, entitled “Learning Treatment to Image".

  2. Sociocultural Theory Applied to Second Language Learning: Collaborative Learning with Reference to the Chinese Context

    Science.gov (United States)

    Dongyu, Zhang; Fanyu, B.; Wanyi, Du

    2013-01-01

    This paper discusses the sociocultural theory (SCT). In particular, three significant concepts of Vyogtsky's theory: self-regulation, the Zone of Proximal Development (ZPD), and scaffolding all of which have been discussed in numerous second language acquisition (SLA) and second language learning (SLL) research papers. These concepts lay the…

  3. Analysis and Assessment of Computer-Supported Collaborative Learning Conversations

    NARCIS (Netherlands)

    Trausan-Matu, Stefan

    2008-01-01

    Trausan-Matu, S. (2008). Analysis and Assessment of Computer-Supported Collaborative Learning Conversations. Workshop presentation at the symposium Learning networks for professional. November, 14, 2008, Heerlen, Nederland: Open Universiteit Nederland.

  4. Computer-Aided College Algebra: Learning Components that Students Find Beneficial

    Science.gov (United States)

    Aichele, Douglas B.; Francisco, Cynthia; Utley, Juliana; Wescoatt, Benjamin

    2011-01-01

    A mixed-method study was conducted during the Fall 2008 semester to better understand the experiences of students participating in computer-aided instruction of College Algebra using the software MyMathLab. The learning environment included a computer learning system for the majority of the instruction, a support system via focus groups (weekly…

  5. The quality and impact of computer supported collaborative learning (CSCL) in radiology case-based learning

    International Nuclear Information System (INIS)

    Kourdioukova, Elena V.; Verstraete, Koenraad L.; Valcke, Martin

    2011-01-01

    Objective: The aim of this research was to explore (1) clinical years students' perceptions about radiology case-based learning within a computer supported collaborative learning (CSCL) setting, (2) an analysis of the collaborative learning process, and (3) the learning impact of collaborative work on the radiology cases. Methods: The first part of this study focuses on a more detailed analysis of a survey study about CSCL based case-based learning, set up in the context of a broader radiology curriculum innovation. The second part centers on a qualitative and quantitative analysis of 52 online collaborative learning discussions from 5th year and nearly graduating medical students. The collaborative work was based on 26 radiology cases regarding musculoskeletal radiology. Results: The analysis of perceptions about collaborative learning on radiology cases reflects a rather neutral attitude that also does not differ significantly in students of different grade levels. Less advanced students are more positive about CSCL as compared to last year students. Outcome evaluation shows a significantly higher level of accuracy in identification of radiology key structures and in radiology diagnosis as well as in linking the radiological signs with available clinical information in nearly graduated students. No significant differences between different grade levels were found in accuracy of using medical terminology. Conclusion: Students appreciate computer supported collaborative learning settings when tackling radiology case-based learning. Scripted computer supported collaborative learning groups proved to be useful for both 5th and 7th year students in view of developing components of their radiology diagnostic approaches.

  6. The quality and impact of computer supported collaborative learning (CSCL) in radiology case-based learning.

    Science.gov (United States)

    Kourdioukova, Elena V; Verstraete, Koenraad L; Valcke, Martin

    2011-06-01

    The aim of this research was to explore (1) clinical years students' perceptions about radiology case-based learning within a computer supported collaborative learning (CSCL) setting, (2) an analysis of the collaborative learning process, and (3) the learning impact of collaborative work on the radiology cases. The first part of this study focuses on a more detailed analysis of a survey study about CSCL based case-based learning, set up in the context of a broader radiology curriculum innovation. The second part centers on a qualitative and quantitative analysis of 52 online collaborative learning discussions from 5th year and nearly graduating medical students. The collaborative work was based on 26 radiology cases regarding musculoskeletal radiology. The analysis of perceptions about collaborative learning on radiology cases reflects a rather neutral attitude that also does not differ significantly in students of different grade levels. Less advanced students are more positive about CSCL as compared to last year students. Outcome evaluation shows a significantly higher level of accuracy in identification of radiology key structures and in radiology diagnosis as well as in linking the radiological signs with available clinical information in nearly graduated students. No significant differences between different grade levels were found in accuracy of using medical terminology. Students appreciate computer supported collaborative learning settings when tackling radiology case-based learning. Scripted computer supported collaborative learning groups proved to be useful for both 5th and 7th year students in view of developing components of their radiology diagnostic approaches. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  7. Learning computer science by watching video games

    OpenAIRE

    Nagataki, Hiroyuki

    2014-01-01

    This paper proposes a teaching method that utilizes video games in computer science education. The primary characteristic of this approach is that it utilizes video games as observational materials. The underlying idea is that by observing the computational behavior of a wide variety of video games, learners will easily grasp the fundamental architecture, theory, and technology of computers. The results of a case study conducted indicate that the method enhances the motivation of students for...

  8. Learning theory and its application to the use of social media in medical education.

    Science.gov (United States)

    Flynn, Leslie; Jalali, Alireza; Moreau, Katherine A

    2015-10-01

    There is rapidly increasing pressure to employ social media in medical education, but a review of the literature demonstrates that its value and role are uncertain. To determine if medical educators have a conceptual framework that informs their use of social media and whether this framework can be mapped to learning theory. Thirty-six participants engaged in an iterative, consensus building process that identified their conceptual framework and determined if it aligned with one or more learning theories. The results show that the use of social media by the participants could be traced to two dominant theories-Connectivism and Constructivism. They also suggest that many medical educators may not be fully informed of these theories. Medical educators' use of social media can be traced to learning theories, but these theories may not be explicitly utilised in instructional design. It is recommended that formal education (faculty development) around learning theory would further enhance the use of social media in medical education. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  9. Midwifery students learning experiences in labor wards: a grounded theory.

    Science.gov (United States)

    Brunstad, Anne; Hjälmhult, Esther

    2014-12-01

    The labor ward is an important and challenging learning area for midwifery students. It is there the students learn in authentic complex situations, in intimate situations, with potential risk for the life and health of mothers and their babies. The aim of this study was to explore the main concern expressed by midwifery students in labor wards and how they handled this concern. A longitudinal study based on grounded theory methodology was used. The participants were 10 postgraduate midwifery students, from a University College in Norway. Data were gathered and analyzed throughout the 2-year postgraduate program, in the students first, third and fourth semesters. Every student was interviewed three times in a total of 15 single and three focus-group sessions. The grounded theory of "building relationships" explains how students dealt with their main concern: "how to gain access to learning experiences". This theory consisted of three strategies; a) controlling vulnerability, b) cultivating trust and c) obtaining acceptance. Clarifying discussions involving midwives and students may facilitate the process of building relationships and contribute to confident learning. Students appreciate it when the midwives initiate discussions about acute situations and state that a novice may perceive labor and childbirth as more frightening than an experienced midwife would. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. What learning theories can teach us in designing neurofeedback treatments

    Directory of Open Access Journals (Sweden)

    Ute eStrehl

    2014-11-01

    Full Text Available Popular definitions of neurofeedback point out that neurofeedback is a process of operant conditioning which leads to self-regulation of brain activity. Self-regulation of brain activity is considered to be a skill. The aim of this paper is to clarify that not only operant conditioning plays a role in the acquisition of this skill. In order to design the learning process additional references have to be derived from classical conditioning, two-process-theory and in particular from skill learning and research into motivational aspects. The impact of learning by trial and error, cueing of behavior, feedback, reinforcement, and knowledge of results as well as transfer of self-regulation skills into everyday life will be analyzed in this paper. In addition to these learning theory basics this paper tries to summarize the knowledge about acquisition of self-regulation from neurofeedback studies with a main emphasis on clinical populations. As a conclusion it is hypothesized that learning to self-regulate has to be offered in a psychotherapeutic, i.e. behavior therapy framework.

  11. What learning theories can teach us in designing neurofeedback treatments.

    Science.gov (United States)

    Strehl, Ute

    2014-01-01

    Popular definitions of neurofeedback point out that neurofeedback is a process of operant conditioning which leads to self-regulation of brain activity. Self-regulation of brain activity is considered to be a skill. The aim of this paper is to clarify that not only operant conditioning plays a role in the acquisition of this skill. In order to design the learning process additional references have to be derived from classical conditioning, two-process-theory and in particular from skill learning and research into motivational aspects. The impact of learning by trial and error, cueing of behavior, feedback, reinforcement, and knowledge of results as well as transfer of self-regulation skills into everyday life will be analyzed in this paper. In addition to these learning theory basics this paper tries to summarize the knowledge about acquisition of self-regulation from neurofeedback studies with a main emphasis on clinical populations. As a conclusion it is hypothesized that learning to self-regulate has to be offered in a psychotherapeutic, i.e., behavior therapy framework.

  12. Activity theory as a potential framework for technology research in ...

    African Journals Online (AJOL)

    This article attempts to expand and elaborate Activity Theory as a theory for studying human computer interaction in South Africa. It first sketches ways in which. Russian activity theory arising out of the work of Vygotsky may expand understandings of learning before elaborating the theory in terms of Engestrom's

  13. Computer-aided auscultation learning system for nursing technique instruction.

    Science.gov (United States)

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

    2008-01-01

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

  14. Processes of Self-Regulated Learning in Music Theory in Elementary Music Schools in Slovenia

    Science.gov (United States)

    Fritz, Barbara Smolej; Peklaj, Cirila

    2011-01-01

    The aim of our study was determine how students regulate their learning in music theory (MT). The research is based on the socio-cognitive theory of learning. The aim of our study was twofold: first, to design the instruments for measuring (meta)cognitive and affective-motivational processes in learning MT, and, second, to examine the relationship…

  15. Occupational therapy students in the process of interprofessional collaborative learning: a grounded theory study.

    Science.gov (United States)

    Howell, Dana

    2009-01-01

    The purpose of this grounded theory study was to generate a theory of the interprofessional collaborative learning process of occupational therapy (OT) students who were engaged in a collaborative learning experience with students from other allied health disciplines. Data consisted of semi-structured interviews with nine OT students from four different interprofessional collaborative learning experiences at three universities. The emergent theory explained OT students' need to build a culture of mutual respect among disciplines in order to facilitate interprofessional collaborative learning. Occupational therapy students went through a progression of learned skills that included learning how to represent the profession of OT, hold their weight within a team situation, solve problems collaboratively, work as a team, and ultimately, to work in an actual team in practice. This learning process occurred simultaneously as students also learned course content. The students had to contend with barriers and facilitators that influenced their participation and the success of their collaboration. Understanding the interprofessional learning process of OT students will help allied health faculty to design more effective, inclusive interprofessional courses.

  16. Not that Different in Theory: Discussing the Control-Value Theory of Emotions in Online Learning Environments

    Science.gov (United States)

    Daniels, Lia M.; Stupnisky, Robert H.

    2012-01-01

    This commentary investigates the extent to which the control-value theory of emotions (Pekrun, 2006) is applicable in online learning environments. Four empirical studies in this special issue of "The Internet and Higher Education" explicitly used the control-value theory as their theoretical framework and several others have components of the…

  17. An Evaluation of Neurogames®: A Collection of Computer Games Designed to Improve Literacy and Numeracy

    Science.gov (United States)

    Khan, Misbah Mahmood; Reed, Jonathan

    2011-01-01

    Games Based Learning needs to be linked to good learning theory to become an important educational intervention. This study examines the effectiveness of a collection of computer games called Neurogames®. Neurogames are a group of computer games aimed at improving reading and basic maths and are designed using neuropsychological theory. The…

  18. Computing the scattering properties of participating media using Lorenz-Mie theory

    DEFF Research Database (Denmark)

    Frisvad, Jeppe Revall; Christensen, Niels Jørgen; Jensen, Henrik Wann

    2007-01-01

    is capable of handling both absorbing host media and non-spherical particles, which significantly extends the classes of media and materials that can be modeled. We use the theory to compute optical properties for different types of ice and ocean water, and we derive a novel appearance model for milk...... parameterized by the fat and protein contents. Our results show that we are able to match measured scattering properties in cases where the classical Lorenz-Mie theory breaks down, and we can compute properties for media that cannot be measured using existing techniques in computer graphics....

  19. Pervasive Computing and Communication Technologies for U-Learning

    Science.gov (United States)

    Park, Young C.

    2014-01-01

    The development of digital information transfer, storage and communication methods influences a significant effect on education. The assimilation of pervasive computing and communication technologies marks another great step forward, with Ubiquitous Learning (U-learning) emerging for next generation learners. In the evolutionary view the 5G (or…

  20. Kolb's Experiential Learning Theory: A Meta-Model for Career Exploration.

    Science.gov (United States)

    Atkinson, George, Jr.; Murrell, Patricia H.

    1988-01-01

    Kolb's experiential learning theory offers the career counselor a meta-model with which to structure career exploration exercises and ensure a thorough investigation of self and the world of work in a manner that provides the client with an optimal amount of learning and personal development. (Author)

  1. Assessing Student Learning in Academic Advising Using Social Cognitive Theory

    Science.gov (United States)

    Erlich, Richard J.; Russ-Eft, Darlene F.

    2013-01-01

    We investigated whether the social cognitive theory constructs of self-efficacy and self-regulated learning apply to academic advising for measuring student learning outcomes. Community college students (N = 120) participated in an individual academic-advising session. We assessed students' post-intervention self-efficacy in academic planning and…

  2. Benefits of computer screen-based simulation in learning cardiac arrest procedures.

    Science.gov (United States)

    Bonnetain, Elodie; Boucheix, Jean-Michel; Hamet, Maël; Freysz, Marc

    2010-07-01

    What is the best way to train medical students early so that they acquire basic skills in cardiopulmonary resuscitation as effectively as possible? Studies have shown the benefits of high-fidelity patient simulators, but have also demonstrated their limits. New computer screen-based multimedia simulators have fewer constraints than high-fidelity patient simulators. In this area, as yet, there has been no research on the effectiveness of transfer of learning from a computer screen-based simulator to more realistic situations such as those encountered with high-fidelity patient simulators. We tested the benefits of learning cardiac arrest procedures using a multimedia computer screen-based simulator in 28 Year 2 medical students. Just before the end of the traditional resuscitation course, we compared two groups. An experiment group (EG) was first asked to learn to perform the appropriate procedures in a cardiac arrest scenario (CA1) in the computer screen-based learning environment and was then tested on a high-fidelity patient simulator in another cardiac arrest simulation (CA2). While the EG was learning to perform CA1 procedures in the computer screen-based learning environment, a control group (CG) actively continued to learn cardiac arrest procedures using practical exercises in a traditional class environment. Both groups were given the same amount of practice, exercises and trials. The CG was then also tested on the high-fidelity patient simulator for CA2, after which it was asked to perform CA1 using the computer screen-based simulator. Performances with both simulators were scored on a precise 23-point scale. On the test on a high-fidelity patient simulator, the EG trained with a multimedia computer screen-based simulator performed significantly better than the CG trained with traditional exercises and practice (16.21 versus 11.13 of 23 possible points, respectively; p<0.001). Computer screen-based simulation appears to be effective in preparing learners to

  3. Using theories of learning in workplaces to enhance physiotherapy clinical education.

    Science.gov (United States)

    Patton, Narelle; Higgs, Joy; Smith, Megan

    2013-10-01

    Clinical education has long been accepted as integral to the education of physiotherapy students and their preparation for professional practice. The clinical environment, through practice immersion, situates students in a powerful learning context and plays a critical role in students' construction of professional knowledge. Despite this acknowledged centrality of practice and clinical environments to the students' experiential construction of professional knowledge, there has been limited exploration of learning theories underpinning clinical education in the literature. In this paper, we explore a selection of learning theories underpinning physiotherapy clinical education with a view to providing clinical educators with a firm foundation on which to base wise educational practices and potentially enhance physiotherapy students' clinical learning experiences. This exploration has drawn from leading thinkers in the field of education over the past century.

  4. Deep Learning with Dynamic Computation Graphs

    OpenAIRE

    Looks, Moshe; Herreshoff, Marcello; Hutchins, DeLesley; Norvig, Peter

    2017-01-01

    Neural networks that compute over graph structures are a natural fit for problems in a variety of domains, including natural language (parse trees) and cheminformatics (molecular graphs). However, since the computation graph has a different shape and size for every input, such networks do not directly support batched training or inference. They are also difficult to implement in popular deep learning libraries, which are based on static data-flow graphs. We introduce a technique called dynami...

  5. High School Students' Implicit Theories of What Facilitates Science Learning

    Science.gov (United States)

    Parsons, Eileen Carlton; Miles, Rhea; Petersen, Michael

    2011-01-01

    Background: Research has primarily concentrated on adults' implicit theories about high quality science education for all students. Little work has considered the students' perspective. This study investigated high school students' implicit theories about what helped them learn science. Purpose: This study addressed (1) What characterizes high…

  6. Game-Based Learning Theory

    Science.gov (United States)

    Laughlin, Daniel

    2008-01-01

    Persistent Immersive Synthetic Environments (PISE) are not just connection points, they are meeting places. They are the new public squares, village centers, malt shops, malls and pubs all rolled into one. They come with a sense of 'thereness" that engages the mind like a real place does. Learning starts as a real code. The code defines "objects." The objects exist in computer space, known as the "grid." The objects and space combine to create a "place." A "world" is created, Before long, the grid and code becomes obscure, and the "world maintains focus.

  7. Transversity results and computations in symplectic field theory

    International Nuclear Information System (INIS)

    Fabert, Oliver

    2008-01-01

    Although the definition of symplectic field theory suggests that one has to count holomorphic curves in cylindrical manifolds R x V equipped with a cylindrical almost complex structure J, it is already well-known from Gromov-Witten theory that, due to the presence of multiply-covered curves, we in general cannot achieve transversality for all moduli spaces even for generic choices of J. In this thesis we treat the transversality problem of symplectic field theory in two important cases. In the first part of this thesis we are concerned with the rational symplectic field theory of Hamiltonian mapping tori, which is also called the Floer case. For this observe that in the general geometric setup for symplectic field theory, the contact manifolds can be replaced by mapping tori M φ of symplectic manifolds (M,ω M ) with symplectomorphisms φ. While the cylindrical contact homology of M φ is given by the Floer homologies of powers of φ, the other algebraic invariants of symplectic field theory for M φ provide natural generalizations of symplectic Floer homology. For symplectically aspherical M and Hamiltonian φ we study the moduli spaces of rational curves and prove a transversality result, which does not need the polyfold theory by Hofer, Wysocki and Zehnder and allows us to compute the full contact homology of M φ ≅ S 1 x M. The second part of this thesis is devoted to the branched covers of trivial cylinders over closed Reeb orbits, which are the trivial examples of punctured holomorphic curves studied in rational symplectic field theory. Since all moduli spaces of trivial curves with virtual dimension one cannot be regular, we use obstruction bundles in order to find compact perturbations making the Cauchy-Riemann operator transversal to the zero section and show that the algebraic count of elements in the resulting regular moduli spaces is zero. Once the analytical foundations of symplectic field theory are established, our result implies that the

  8. Computer-Based Learning in Open and Distance Learning Institutions in Nigeria: Cautions on Use of Internet for Counseling

    Science.gov (United States)

    Okopi, Fidel Onjefu; Odeyemi, Olajumoke Janet; Adesina, Adewale

    2015-01-01

    The study has identified the areas of strengths and weaknesses in the current use of Computer Based Learning (CBL) tools in Open and Distance Learning (ODL) institutions in Nigeria. To achieve these objectives, the following research questions were proposed: (i) What are the computer-based learning tools (soft and hard ware) that are actually in…

  9. Collaborative Learning in an Undergraduate Theory Course: An Assessment of Goals and Outcomes

    Science.gov (United States)

    McDuff, Elaine

    2012-01-01

    This project was designed to assess whether a collaborative learning approach to teaching sociological theory would be a successful means of improving student engagement in learning theory and of increasing both the depth of students' understanding of theoretical arguments and concepts and the ability of students to theorize for themselves. A…

  10. Implications of Bandura's Observational Learning Theory for a Competency Based Teacher Education Model.

    Science.gov (United States)

    Hartjen, Raymond H.

    Albert Bandura of Stanford University has proposed four component processes to his theory of observational learning: a) attention, b) retention, c) motor reproduction, and d) reinforcement and motivation. This study represents one phase of an effort to relate modeling and observational learning theory to teacher training. The problem of this study…

  11. Computer-based learning for the enhancement of breastfeeding ...

    African Journals Online (AJOL)

    In this study, computer-based learning (CBL) was explored in the context of breastfeeding training for undergraduate Dietetic students. Aim: To adapt and validate an Indian computer-based undergraduate breastfeeding training module for use by South African undergraduate Dietetic students. Methods and materials: The ...

  12. Use of Computer Technology for English Language Learning: Do Learning Styles, Gender, and Age Matter?

    Science.gov (United States)

    Lee, Cynthia; Yeung, Alexander Seeshing; Ip, Tiffany

    2016-01-01

    Computer technology provides spaces and locales for language learning. However, learning style preference and demographic variables may affect the effectiveness of technology use for a desired goal. Adapting Reid's pioneering Perceptual Learning Style Preference Questionnaire (PLSPQ), this study investigated the relations of university students'…

  13. A machine-learning approach for computation of fractional flow reserve from coronary computed tomography.

    Science.gov (United States)

    Itu, Lucian; Rapaka, Saikiran; Passerini, Tiziano; Georgescu, Bogdan; Schwemmer, Chris; Schoebinger, Max; Flohr, Thomas; Sharma, Puneet; Comaniciu, Dorin

    2016-07-01

    Fractional flow reserve (FFR) is a functional index quantifying the severity of coronary artery lesions and is clinically obtained using an invasive, catheter-based measurement. Recently, physics-based models have shown great promise in being able to noninvasively estimate FFR from patient-specific anatomical information, e.g., obtained from computed tomography scans of the heart and the coronary arteries. However, these models have high computational demand, limiting their clinical adoption. In this paper, we present a machine-learning-based model for predicting FFR as an alternative to physics-based approaches. The model is trained on a large database of synthetically generated coronary anatomies, where the target values are computed using the physics-based model. The trained model predicts FFR at each point along the centerline of the coronary tree, and its performance was assessed by comparing the predictions against physics-based computations and against invasively measured FFR for 87 patients and 125 lesions in total. Correlation between machine-learning and physics-based predictions was excellent (0.9994, P machine-learning algorithm with a sensitivity of 81.6%, a specificity of 83.9%, and an accuracy of 83.2%. The correlation was 0.729 (P assessment of FFR. Average execution time went down from 196.3 ± 78.5 s for the CFD model to ∼2.4 ± 0.44 s for the machine-learning model on a workstation with 3.4-GHz Intel i7 8-core processor. Copyright © 2016 the American Physiological Society.

  14. The importance of task appropriateness in computer-supported collaborative learning

    Directory of Open Access Journals (Sweden)

    Kathy Buckner

    1999-12-01

    Full Text Available The study of learning in collaborative electronic environments is becoming established as Computer Supported Collaborative Learning (CSCL - an emergent sub-discipline of the more established Computer Supported Co-operative Work (CSCW discipline (Webb, 1995. Using computers for the development of shared understanding through collaboration has been explored by Crook who suggests that success may depend partly on having a clearly specified purpose or goal (Crook, 1994. It is our view that the appropriateness of the task given to the student is central to the success or otherwise of the learning experience. However, the tasks that are given to facilitate collaborative learning in face-toface situations are not always suitable for direct transfer to the electronic medium. It may be necessary to consider redesigning these tasks in relation to the medium in which they are to be undertaken and the functionality of the electronic conferencing software used.

  15. Games and Diabetes: A Review Investigating Theoretical Frameworks, Evaluation Methodologies, and Opportunities for Design Grounded in Learning Theories.

    Science.gov (United States)

    Lazem, Shaimaa; Webster, Mary; Holmes, Wayne; Wolf, Motje

    2015-09-02

    Here we review 18 articles that describe the design and evaluation of 1 or more games for diabetes from technical, methodological, and theoretical perspectives. We undertook searches covering the period 2010 to May 2015 in the ACM, IEEE, Journal of Medical Internet Research, Studies in Health Technology and Informatics, and Google Scholar online databases using the keywords "children," "computer games," "diabetes," "games," "type 1," and "type 2" in various Boolean combinations. The review sets out to establish, for future research, an understanding of the current landscape of digital games designed for children with diabetes. We briefly explored the use and impact of well-established learning theories in such games. The most frequently mentioned theoretical frameworks were social cognitive theory and social constructivism. Due to the limitations of the reported evaluation methodologies, little evidence was found to support the strong promise of games for diabetes. Furthermore, we could not establish a relation between design features and the game outcomes. We argue that an in-depth discussion about the extent to which learning theories could and should be manifested in the design decisions is required. © 2015 Diabetes Technology Society.

  16. Self Modeling: Expanding the Theories of Learning

    Science.gov (United States)

    Dowrick, Peter W.

    2012-01-01

    Self modeling (SM) offers a unique expansion of learning theory. For several decades, a steady trickle of empirical studies has reported consistent evidence for the efficacy of SM as a procedure for positive behavior change across physical, social, educational, and diagnostic variations. SM became accepted as an extreme case of model similarity;…

  17. Learning Organisation Review--A "Good" Theory Perspective

    Science.gov (United States)

    Santa, Mijalce

    2015-01-01

    Purpose: The purpose of this paper is to perform integrative literature review of the learning organisation (LO) concept, on the basis of the results of the literature review to assess the concept on the principles of "good" theory, and provide future avenues for LO concept clarification and development. Design/methodology/approach: The…

  18. Contextual learning theory: Concrete form and a software prototype to improve early education.

    NARCIS (Netherlands)

    Mooij, Ton

    2016-01-01

    In 'contextual learning theory' three types of contextual conditions (differentiation of learning procedures and materials, integrated ICT support, and improvement of development and learning progress) are related to four aspects of the learning process (diagnostic, instructional, managerial, and

  19. Computer-assisted learning and simulation systems in dentistry--a challenge to society.

    Science.gov (United States)

    Welk, A; Splieth, Ch; Wierinck, E; Gilpatrick, R O; Meyer, G

    2006-07-01

    Computer technology is increasingly used in practical training at universities. However, in spite of their potential, computer-assisted learning (CAL) and computer-assisted simulation (CAS) systems still appear to be underutilized in dental education. Advantages, challenges, problems, and solutions of computer-assisted learning and simulation in dentistry are discussed by means of MEDLINE, open Internet platform searches, and key results of a study among German dental schools. The advantages of computer-assisted learning are seen for example in self-paced and self-directed learning and increased motivation. It is useful for both objective theoretical and practical tests and for training students to handle complex cases. CAL can lead to more structured learning and can support training in evidence-based decision-making. The reasons for the still relatively rare implementation of CAL/CAS systems in dental education include an inability to finance, lack of studies of CAL/CAS, and too much effort required to integrate CAL/CAS systems into the curriculum. To overcome the reasons for the relative low degree of computer technology use, we should strive for multicenter research and development projects monitored by the appropriate national and international scientific societies, so that the potential of computer technology can be fully realized in graduate, postgraduate, and continuing dental education.

  20. Dynamic Scaffolding of Socially Regulated Learning in a Computer-Based Learning Environment

    Science.gov (United States)

    Molenaar, Inge; Roda, Claudia; van Boxtel, Carla; Sleegers, Peter

    2012-01-01

    The aim of this study is to test the effects of dynamically scaffolding social regulation of middle school students working in a computer-based learning environment. Dyads in the scaffolding condition (N=56) are supported with computer-generated scaffolds and students in the control condition (N=54) do not receive scaffolds. The scaffolds are…

  1. Kolb's Experiential Learning Theory and Its Application in Geography in Higher Education.

    Science.gov (United States)

    Healey, Mick; Jenkins, Alan

    2000-01-01

    Describes David Kolb's experiential learning theory focusing on the main features of his theory. Applies Kolb's theory to the teaching of geography addressing ideas such as teaching how theories of gender explain aspects of suburbia, teaching a field course, and encouraging staff to rethink their teaching style. Include references. (CMK)

  2. Equity and Computers for Mathematics Learning: Access and Attitudes

    Science.gov (United States)

    Forgasz, Helen J.

    2004-01-01

    Equity and computer use for secondary mathematics learning was the focus of a three year study. In 2003, a survey was administered to a large sample of grade 7-10 students. Some of the survey items were aimed at determining home access to and ownership of computers, and students' attitudes to mathematics, computers, and computer use for…

  3. How A Flipped Learning Environment Affects Learning In A Course On Theoretical Computer Science

    DEFF Research Database (Denmark)

    Gnaur, Dorina; Hüttel, Hans

    2014-01-01

    This paper reports initial experiences with flipping the classroom in an undergraduate computer science course as part of an overall attempt to enhance the pedagogical support for student learning. Our findings indicate that, just as the flipped classroom implies, a shift of focus in the learning...... context influences the way students engage with the course and their learning strategies....

  4. Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks

    Science.gov (United States)

    Blikstein, Paulo; Worsley, Marcelo

    2016-01-01

    New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

  5. Eye-tracking research in computer-mediated language learning

    NARCIS (Netherlands)

    Michel, Marije; Smith, Bryan

    2017-01-01

    Though eye-tracking technology has been used in reading research for over 100 years, researchers have only recently begun to use it in studies of computer-assisted language learning (CALL). This chapter provides an overview of eye-tracking research to date, which is relevant to computer-mediated

  6. An approach to children's smoking behavior using social cognitive learning theory.

    Science.gov (United States)

    Bektas, Murat; Ozturk, Candan; Armstrong, Merry

    2010-01-01

    This review article discusses the theoretical principles of social cognitive learning theory and children's risk-taking behavior of cigarette smoking, along with preventive initiatives. Social cognitive learning theorists examine the behavior of initiating and sustained smoking using a social systems approach. The authors discuss the reciprocal determinism aspect of the theory as applied to the importance of individual factors, and environment and behavioral interactions that influence smoking behavior. Included is the concept of vicarious capability that suggests that smoking behavior is determined in response to and interaction with feedback provided by the environment. The principle of self-regulatory capability asserts that people have control over their own behavior and thus that behavior change is possible. The principle of self-efficacy proposes that high level of self-efficacy of an individual may decrease the behavior of attempting to or continuing to smoke. Examples of initiatives to be undertaken in order to prevent smoking in accordance with social cognitive learning theory are presented at the end of each principle.

  7. Computer Self-Efficacy and Factors Influencing E-Learning Effectiveness

    Science.gov (United States)

    Chien, Tien-Chen

    2012-01-01

    Purpose: The purpose of this study is to investigate the influences of system and instructor factors on e-learning effectiveness under the interactions of computer self-efficacy. In this study, the factors of the e-learning system are functionality, interaction, and response. The factors of the e-learning instructor are attitude, technical skills,…

  8. Designing the Electronic Classroom: Applying Learning Theory and Ergonomic Design Principles.

    Science.gov (United States)

    Emmons, Mark; Wilkinson, Frances C.

    2001-01-01

    Applies learning theory and ergonomic principles to the design of effective learning environments for library instruction. Discusses features of electronic classroom ergonomics, including the ergonomics of physical space, environmental factors, and workstations; and includes classroom layouts. (Author/LRW)

  9. Learning theories and tools for the assessment of core nursing competencies in simulation: A theoretical review.

    Science.gov (United States)

    Lavoie, Patrick; Michaud, Cécile; Bélisle, Marilou; Boyer, Louise; Gosselin, Émilie; Grondin, Myrian; Larue, Caroline; Lavoie, Stéphan; Pepin, Jacinthe

    2018-02-01

    To identify the theories used to explain learning in simulation and to examine how these theories guided the assessment of learning outcomes related to core competencies in undergraduate nursing students. Nurse educators face the challenge of making explicit the outcomes of competency-based education, especially when competencies are conceptualized as holistic and context dependent. Theoretical review. Research papers (N = 182) published between 1999-2015 describing simulation in nursing education. Two members of the research team extracted data from the papers, including theories used to explain how simulation could engender learning and tools used to assess simulation outcomes. Contingency tables were created to examine the associations between theories, outcomes and tools. Some papers (N = 79) did not provide an explicit theory. The 103 remaining papers identified one or more learning or teaching theories; the most frequent were the National League for Nursing/Jeffries Simulation Framework, Kolb's theory of experiential learning and Bandura's social cognitive theory and concept of self-efficacy. Students' perceptions of simulation, knowledge and self-confidence were the most frequently assessed, mainly via scales designed for the study where they were used. Core competencies were mostly assessed with an observational approach. This review highlighted the fact that few studies examined the use of simulation in nursing education through learning theories and via assessment of core competencies. It also identified observational tools used to assess competencies in action, as holistic and context-dependent constructs. © 2017 John Wiley & Sons Ltd.

  10. Symbolic Computation, Number Theory, Special Functions, Physics and Combinatorics

    CERN Document Server

    Ismail, Mourad

    2001-01-01

    These are the proceedings of the conference "Symbolic Computation, Number Theory, Special Functions, Physics and Combinatorics" held at the Department of Mathematics, University of Florida, Gainesville, from November 11 to 13, 1999. The main emphasis of the conference was Com­ puter Algebra (i. e. symbolic computation) and how it related to the fields of Number Theory, Special Functions, Physics and Combinatorics. A subject that is common to all of these fields is q-series. We brought together those who do symbolic computation with q-series and those who need q-series in­ cluding workers in Physics and Combinatorics. The goal of the conference was to inform mathematicians and physicists who use q-series of the latest developments in the field of q-series and especially how symbolic computa­ tion has aided these developments. Over 60 people were invited to participate in the conference. We ended up having 45 participants at the conference, including six one hour plenary speakers and 28 half hour speakers. T...

  11. An Analysis of Stochastic Game Theory for Multiagent Reinforcement Learning

    National Research Council Canada - National Science Library

    Bowling, Michael

    2000-01-01

    .... In this paper we contribute a comprehensive presentation of the relevant techniques for solving stochastic games from both the game theory community and reinforcement learning communities. We examine the assumptions and limitations of these algorithms, and identify similarities between these algorithms, single agent reinforcement learners, and basic game theory techniques.

  12. Some Consequences of Learning Theory Applied to Division of Fractions

    Science.gov (United States)

    Bidwell, James K.

    1971-01-01

    Reviews the learning theories of Robert Gagne and David Ausubel, and applies these theories to the three most common approaches to teaching division of fractions: common denominator, complex fraction, and inverse operation methods. Such analysis indicates the inverse approach should be most effective for meaningful teaching, as is verified by…

  13. Learning Theories Applied to the Teaching of Business Communication.

    Science.gov (United States)

    Hart, Maxine Barton

    1980-01-01

    Reviews major learning theories that can be followed by business communication instructors, including those by David Ausubel, Albert Bandura, Kurt Lewin, Edward Thorndike, B.F. Skinner, and Robert Gagne. (LRA)

  14. Computer games and learning: The relationship between design, gameplay and outcomes.

    NARCIS (Netherlands)

    Schrader, Claudia; Bastiaens, Theo

    2018-01-01

    This article provides an insight into the effectiveness of edu- cational computer games. Based on a literature research, the effectiveness is illustrated in detail with regard to the ques- tions: what characterize educational computer games, how do learners learn from it and what are the learning

  15. GP and pharmacist inter-professional learning - a grounded theory study.

    Science.gov (United States)

    Cunningham, David E; Ferguson, Julie; Wakeling, Judy; Zlotos, Leon; Power, Ailsa

    2016-05-01

    Practice Based Small Group Learning (PBSGL) is an established learning resource for primary care clinicians in Scotland and is used by one-third of general practitioners (GPs). Scottish Government and UK professional bodies have called for GPs and pharmacists to work more closely together to improve care. To gain GPs' and pharmacists' perceptions and experiences of learning together in an inter-professional PBSGL pilot. Qualitative research methods involving established GP PBSGL groups in NHS Scotland recruiting one or two pharmacists to join them. A grounded theory method was used. GPs were interviewed in focus groups by a fellow GP, and pharmacists were interviewed individually by two researchers, neither being a GP or a pharmacist. Interviews were audio-recorded, transcribed and analysed using grounded theory methods. Data saturation was achieved and confirmed. Three themes were identified: GPs' and pharmacists' perceptions and experiences of inter-professional learning; Inter-professional relationships and team-working; Group identity and purpose of existing GP groups. Pharmacists were welcomed into GP groups and both professions valued inter-professional PBSGL learning. Participants learned from each other and both professions gained a wider perspective of the NHS and of each others' roles in the organisation. Inter-professional relationships, communication and team-working were strengthened and professionals regarded each other as peers and friends.

  16. Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept.

    Science.gov (United States)

    Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E

    2017-01-01

    There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning.

  17. Dual field theories of quantum computation

    International Nuclear Information System (INIS)

    Vanchurin, Vitaly

    2016-01-01

    Given two quantum states of N q-bits we are interested to find the shortest quantum circuit consisting of only one- and two- q-bit gates that would transfer one state into another. We call it the quantum maze problem for the reasons described in the paper. We argue that in a large N limit the quantum maze problem is equivalent to the problem of finding a semiclassical trajectory of some lattice field theory (the dual theory) on an N+1 dimensional space-time with geometrically flat, but topologically compact spatial slices. The spatial fundamental domain is an N dimensional hyper-rhombohedron, and the temporal direction describes transitions from an arbitrary initial state to an arbitrary target state and so the initial and final dual field theory conditions are described by these two quantum computational states. We first consider a complex Klein-Gordon field theory and argue that it can only be used to study the shortest quantum circuits which do not involve generators composed of tensor products of multiple Pauli Z matrices. Since such situation is not generic we call it the Z-problem. On the dual field theory side the Z-problem corresponds to massless excitations of the phase (Goldstone modes) that we attempt to fix using Higgs mechanism. The simplest dual theory which does not suffer from the massless excitation (or from the Z-problem) is the Abelian-Higgs model which we argue can be used for finding the shortest quantum circuits. Since every trajectory of the field theory is mapped directly to a quantum circuit, the shortest quantum circuits are identified with semiclassical trajectories. We also discuss the complexity of an actual algorithm that uses a dual theory prospective for solving the quantum maze problem and compare it with a geometric approach. We argue that it might be possible to solve the problem in sub-exponential time in 2 N , but for that we must consider the Klein-Gordon theory on curved spatial geometry and/or more complicated (than N

  18. Applying Social Cognitive Theory to Academic Advising to Assess Student Learning Outcomes

    Science.gov (United States)

    Erlich, Richard J.; Russ-Eft, Darlene

    2011-01-01

    Review of social cognitive theory constructs of self-efficacy and self-regulated learning is applied to academic advising for the purposes of assessing student learning. A brief overview of the history of student learning outcomes in higher education is followed by an explanation of self-efficacy and self-regulated learning constructs and how they…

  19. Transfer Learning for SSVEP Electroencephalography Based Brain–Computer Interfaces Using Learn++.NSE and Mutual Information

    Directory of Open Access Journals (Sweden)

    Matthew Sybeldon

    2017-01-01

    Full Text Available Brain–Computer Interfaces (BCI using Steady-State Visual Evoked Potentials (SSVEP are sometimes used by injured patients seeking to use a computer. Canonical Correlation Analysis (CCA is seen as state-of-the-art for SSVEP BCI systems. However, this assumes that the user has full control over their covert attention, which may not be the case. This introduces high calibration requirements when using other machine learning techniques. These may be circumvented by using transfer learning to utilize data from other participants. This paper proposes a combination of ensemble learning via Learn++ for Nonstationary Environments (Learn++.NSEand similarity measures such as mutual information to identify ensembles of pre-existing data that result in higher classification. Results show that this approach performed worse than CCA in participants with typical SSVEP responses, but outperformed CCA in participants whose SSVEP responses violated CCA assumptions. This indicates that similarity measures and Learn++.NSE can introduce a transfer learning mechanism to bring SSVEP system accessibility to users unable to control their covert attention.

  20. Trainee Teachers' e-Learning Experiences of Computer Play

    Science.gov (United States)

    Wright, Pam

    2009-01-01

    Pam Wright highlights the role of technology in providing situated learning opportunities for preservice teachers to explore the role commercial computer games may have in primary education. In a study designed to assess the effectiveness of an online unit on gaming incorporated into a course on learning technologies, Wright found that thoughtful…

  1. A "Service-Learning Approach" to Teaching Computer Graphics

    Science.gov (United States)

    Hutzel, Karen

    2007-01-01

    The author taught a computer graphics course through a service-learning framework to undergraduate and graduate students in the spring of 2003 at Florida State University (FSU). The students in this course participated in learning a software program along with youths from a neighboring, low-income, primarily African-American community. Together,…

  2. Social Learning Theory: its application in the context of nurse education.

    Science.gov (United States)

    Bahn, D

    2001-02-01

    Cognitive theories are fundamental to enable problem solving and the ability to understand and apply principles in a variety of situations. This article looks at Social Learning Theory, critically analysing its principles, which are based on observational learning and modelling, and considering its value and application in the context of nurse education. It also considers the component processes that will determine the outcome of observed behaviour, other than reinforcement, as identified by Bandura, namely: attention, retention, motor reproduction, and motivation. Copyright 2001 Harcourt Publishers Ltd.

  3. Designing Opportunities to Learn Mathematics Theory-Building Practices

    Science.gov (United States)

    Bass, Hyman

    2017-01-01

    Mathematicians commonly distinguish two modes of work in the discipline: "Problem solving," and "theory building." Mathematics education offers many opportunities to learn problem solving. This paper explores the possibility, and value, of designing instructional activities that provide supported opportunities for students to…

  4. Scripting intercultural computer-supported collaborative learning in higher education

    NARCIS (Netherlands)

    Popov, V.

    2013-01-01

    Introduction of computer-supported collaborative learning (CSCL), specifically in an intercultural learning environment, creates both challenges and benefits. Among the challenges are the coordination of different attitudes, styles of communication, and patterns of behaving. Among the benefits are

  5. Machine learning, computer vision, and probabilistic models in jet physics

    CERN Multimedia

    CERN. Geneva; NACHMAN, Ben

    2015-01-01

    In this talk we present recent developments in the application of machine learning, computer vision, and probabilistic models to the analysis and interpretation of LHC events. First, we will introduce the concept of jet-images and computer vision techniques for jet tagging. Jet images enabled the connection between jet substructure and tagging with the fields of computer vision and image processing for the first time, improving the performance to identify highly boosted W bosons with respect to state-of-the-art methods, and providing a new way to visualize the discriminant features of different classes of jets, adding a new capability to understand the physics within jets and to design more powerful jet tagging methods. Second, we will present Fuzzy jets: a new paradigm for jet clustering using machine learning methods. Fuzzy jets view jet clustering as an unsupervised learning task and incorporate a probabilistic assignment of particles to jets to learn new features of the jet structure. In particular, we wi...

  6. Transformative Learning: A Case for Using Grounded Theory as an Assessment Analytic

    Science.gov (United States)

    Patterson, Barbara A. B.; Munoz, Leslie; Abrams, Leah; Bass, Caroline

    2015-01-01

    Transformative Learning Theory and pedagogies leverage disruptive experiences as catalysts for learning and teaching. By facilitating processes of critical analysis and reflection that challenge assumptions, transformative learning reframes what counts as knowledge and the sources and processes for gaining and producing it. Students develop a…

  7. Any realistic theory must be computationally realistic: a response to N. Gisin's definition of a Realistic Physics Theory

    OpenAIRE

    Bolotin, Arkady

    2014-01-01

    It is argued that the recent definition of a realistic physics theory by N. Gisin cannot be considered comprehensive unless it is supplemented with requirement that any realistic theory must be computationally realistic as well.

  8. Teaching and Learning of Knot Theory in School Mathematics

    CERN Document Server

    Kawauchi, Akio

    2012-01-01

    This book is the result of a joint venture between Professor Akio Kawauchi, Osaka City University, well-known for his research in knot theory, and the Osaka study group of mathematics education, founded by Professor Hirokazu Okamori and now chaired by his successor Professor Tomoko Yanagimoto, Osaka Kyoiku University. The seven chapters address the teaching and learning of knot theory from several perspectives. Readers will find an extremely clear and concise introduction to the fundamentals of knot theory, an overview of curricular developments in Japan, and in particular a series of teaching

  9. Practical skills teaching in contemporary surgical education: how can educational theory be applied to promote effective learning?

    Science.gov (United States)

    Sadideen, Hazim; Kneebone, Roger

    2012-09-01

    Teaching practical skills is a core component of undergraduate and postgraduate surgical education. It is crucial to optimize our current learning and teaching models, particularly in a climate of decreased clinical exposure. This review explores the role of educational theory in promoting effective learning in practical skills teaching. Peer-reviewed publications, books, and online resources from national bodies (eg, the UK General Medical Council) were reviewed. This review highlights several aspects of surgical education, modeling them on current educational theory. These include the following: (1) acquisition and retention of motor skills (Miller's triangle; Fitts' and Posner's theory), (2) development of expertise after repeated practice and regular reinforcement (Ericsson's theory), (3) importance of the availability of expert assistance (Vygotsky's theory), (4) learning within communities of practice (Lave and Wenger's theory), (5) importance of feedback in learning practical skills (Boud, Schon, and Endes' theories), and (6) affective component of learning. It is hoped that new approaches to practical skills teaching are designed in light of our understanding of educational theory. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. Application of Ausubel's Theory of Meaningful Verbal Learning to Curriculum, Teaching and Learning of Deaf Students.

    Science.gov (United States)

    Biser, Eileen

    Implications of D. Ausubel's Theory of Meaningful Verbal Learning and its derivative, the Advance Organizer Model of Teaching, for deaf students are examined. Ausubel believes that complex intellectual processes (thinking, language, problem-solving, concept formation) are the major aspects of learning, and that primary emphasis should be placed on…

  11. Social Learning Theories--An Important Design Consideration for Geoscience Fieldwork

    Science.gov (United States)

    Streule, M. J.; Craig, L. E.

    2016-01-01

    The nature of field trips in geoscience lends them to the application of social learning theories for three key reasons. First, they provide opportunity for meaningful practical experience and promote effective learning afforded by no other educational vehicle in the subject. Second, they are integral for students creating a strong but changing…

  12. Supporting Alternative Strategies for Learning Chemical Applications of Group Theory

    Science.gov (United States)

    Southam, Daniel C.; Lewis, Jennifer E.

    2013-01-01

    A group theory course for chemists was taught entirely with process oriented guided inquiry learning (POGIL) to facilitate alternative strategies for learning. Students completed a test of one aspect of visuospatial aptitude to determine their individual approaches to solving spatial tasks, and were sorted into groups for analysis on the basis of…

  13. Social Learning Theory and Developmental Psychology: The Legacies of Robert Sears and Albert Bandura.

    Science.gov (United States)

    Grusec, Joan E.

    1992-01-01

    Social learning theory is evaluated from a historical perspective that goes up to the present. Sears and others melded psychoanalytic and stimulus-response learning theory into a comprehensive explanation of human behavior. Bandura emphasized cognitive and information-processing capacities that mediate social behavior. (LB)

  14. Children Balance Theories and Evidence in Exploration, Explanation, and Learning

    Science.gov (United States)

    Bonawitz, Elizabeth Baraff; van Schijndel, Tessa J. P.; Friel, Daniel; Schulz, Laura

    2012-01-01

    We look at the effect of evidence and prior beliefs on exploration, explanation and learning. In Experiment 1, we tested children both with and without differential prior beliefs about balance relationships (Center Theorists, mean: 82 months; Mass Theorists, mean: 89 months; No Theory children, mean: 62 months). Center and Mass Theory children who…

  15. New Concepts and Applications in Soft Computing

    CERN Document Server

    Fodor, János; Várkonyi-Kóczy, Annamária

    2013-01-01

                  The book provides a sample of research on the innovative theory and applications of soft computing paradigms.             The idea of Soft Computing was initiated in 1981 when Professor Zadeh published his first paper on soft data analysis and constantly evolved ever since. Professor Zadeh defined Soft Computing as the fusion of the fields of fuzzy logic (FL), neural network theory (NN) and probabilistic reasoning (PR), with the latter subsuming belief networks, evolutionary computing including DNA computing, chaos theory and parts of learning theory into one multidisciplinary system. As Zadeh said the essence of soft computing is that unlike the traditional, hard computing, soft computing is aimed at an accommodation with the pervasive imprecision of the real world. Thus, the guiding principle of soft computing is to exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better rapport with reality. ...

  16. The Role of the Constructivist Learning Theory and Collaborative Learning Environment on Wiki Classroom, and the Relationship between Them

    Science.gov (United States)

    Alzahrani, Ibraheem; Woollard, John

    2013-01-01

    This paper seeks to discover the relationship between both the social constructivist learning theory and the collaborative learning environment. This relationship can be identified by giving an example of the learning environment. Due to wiki characteristics, Wiki technology is one of the most famous learning environments that can show the…

  17. Review of Affective Computing in Education/Learning: Trends and Challenges

    Science.gov (United States)

    Wu, Chih-Hung; Huang, Yueh-Min; Hwang, Jan-Pan

    2016-01-01

    Affect can significantly influence education/learning. Thus, understanding a learner's affect throughout the learning process is crucial for understanding motivation. In conventional education/learning research, learner motivation can be known through postevent self-reported questionnaires. With the advance of affective computing technology,…

  18. The Learning Organization and Some Other Modern Theories of Management

    International Nuclear Information System (INIS)

    Sugarman, Barry

    2003-01-01

    In the first part, Dr Sugarman reviewed several recent theories of management and their relevance to NPP management. These theories encompass basic aspects like bureaucracy, un-bureaucracy, quality and excellence, re-engineering, knowledge management, emotional intelligence and learning organisation. Dr Sugarman discussed evolution from the Old Paradigm (Bureaucracy) to the New One (Learning Organization), defining the main aspects of both models, that can be summarises primarily in regards to strategy and structure. In terms of strategy, the new paradigm moves away from being largely inflexible to a much more dynamic environment whereby innovation is encouraged as opposed to performing in the prescribed manner whether suitable or not. The structural changes in the new model are also evident. There has been a marked move away from a hierarchical 'top down' approach to a much flatter structure that encourages less empire building and more openness between teams of various. This ensures a much greater understanding by the whole organisation of what is happening. Dr Sugarman centred his talk on the new model and how this has affected the development of the current situation. The Learning Organisation, according to the definition of Peter Senge in The Fifth Discipline (1990), is an organisation where people continually expand their capacity to create results they truly desire, and where the people are continually learning how to learn together. The movements behind increasing quality introduced a new model into industry based on Production, where workers became responsible for quality assurance instead of quality controls being reviewed by inspectors. All the employees share responsibility for learning how to improve continuously. That means, complete involvement of all staff. Following on from this, the Quality Revolution made appearance and was driven by extra attention to the customer. Out-sourcing became common and the 'Internal customer' became more common. All

  19. Four PPPPerspectives on Computational Creativity in theory and in practice

    OpenAIRE

    Jordanous, Anna

    2016-01-01

    Computational creativity is the modelling, simulating or replicating of creativity computationally. In examining and learning from these `creative systems', from what perspective should the creativity of a system be considered? Are we interested in the creativity of the system's output? Or of its creative processes? Features of the system? Or how it operates within its environment? Traditionally computational creativity has focused more on creative systems' products or processes, though this ...

  20. Research Notes ~ Second Language Acquisition Theories as a Framework for Creating Distance Learning Courses

    Directory of Open Access Journals (Sweden)

    Eileen N. Ariza

    2003-10-01

    Full Text Available Moore and Kearsley (1996 maintain distance educators should provide for three types of interaction: a learner-content; b learner-instructor; and c learner-learner. According to interactionist second language acquisition (SLA theories that reflect Krashen’s theory (1994 that comprehensible input is critical for second language acquisition, interaction can enhance second language acquisition and fluency. Effective output is necessary as well. We reviewed the research on distance learning for second language learners and concluded that SLA theories can, and should, be the framework that drives the development of courses for students seeking to learn languages by distance technology. This article delineates issues to consider in support of combining SLA theories and research literature as a guide in creating distance language learning courses.

  1. Disrupted avoidance learning in functional neurological disorder: Implications for harm avoidance theories

    Directory of Open Access Journals (Sweden)

    Laurel S. Morris

    Full Text Available Background: Functional neurological disorder (FND is an elusive disorder characterized by unexplained neurological symptoms alongside aberrant cognitive processing and negative affect, often associated with amygdala reactivity. Methods: We examined the effect of negative conditioning on cognitive function and amygdala reactivity in 25 FND patients and 20 healthy volunteers (HV. Participants were first conditioned to stimuli paired with negative affective or neutral (CS+/CS− information. During functional MRI, subjects then performed an instrumental associative learning task to avoid monetary losses in the context of the previously conditioned stimuli. We expected that FND patients would be better at learning to avoid losses when faced with negatively conditioned stimuli (increased harm avoidance. Multi-echo resting state fMRI was also collected from the same subjects and a robust denoising method was employed, important for removing motion and physiological artifacts. Results: FND subjects were more sensitive to the negative CS+ compared to HV, demonstrated by a reinforcement learning model. Contrary to expectation, FND patients were generally more impaired at learning to avoid losses under both contexts (CS+/CS−, persisting to choose the option that resulted in a negative outcome demonstrated by both behavioural and computational analyses. FND patients showed enhanced amygdala but reduced dorsolateral prefrontal cortex responses when they received negative feedback. Patients also had increased resting state functional connectivity between these two regions. Conclusions: FND patients had impaired instrumental avoidance learning, findings that parallel previous observations of impaired action-outcome binding. FND patients further show enhanced behavioural and neural sensitivity to negative information. However, this did not translate to improved avoidance learning. Put together, our findings do not support the theory of harm avoidance in FND

  2. Computer-based learning: games as an instructional strategy.

    Science.gov (United States)

    Blake, J; Goodman, J

    1999-01-01

    Games are a creative teaching strategy that enhances learning and problem solving. Gaming strategies are being used by the authors to make learning interesting, stimulating and fun. This article focuses on the development and implementation of computer games as an instructional strategy. Positive outcomes have resulted from the use of games in the classroom.

  3. 76 Computer Assisted Language Learning (CALL) Software ...

    African Journals Online (AJOL)

    Ike Odimegwu

    combination with other factors which may enhance or ameliorate the ... form of computer-based learning which carries two important features: .... To take some commonplace examples, a ... photographs, and even full-motion video clips.

  4. The right time to learn: mechanisms and optimization of spaced learning

    Science.gov (United States)

    Smolen, Paul; Zhang, Yili; Byrne, John H.

    2016-01-01

    For many types of learning, spaced training, which involves repeated long inter-trial intervals, leads to more robust memory formation than does massed training, which involves short or no intervals. Several cognitive theories have been proposed to explain this superiority, but only recently have data begun to delineate the underlying cellular and molecular mechanisms of spaced training, and we review these theories and data here. Computational models of the implicated signalling cascades have predicted that spaced training with irregular inter-trial intervals can enhance learning. This strategy of using models to predict optimal spaced training protocols, combined with pharmacotherapy, suggests novel ways to rescue impaired synaptic plasticity and learning. PMID:26806627

  5. SU-E-P-04: Transport Theory Learning Module in the Maple Environment

    Energy Technology Data Exchange (ETDEWEB)

    Both, J [University of Miami, Miller School of Medicine, Department of Radiation Oncology (United States)

    2014-06-01

    Purpose: The medical physics graduate program at the University of Miami is developing a computerized instructional module which provides an interactive mechanism for students to learn transport theory. While not essential in the medical physics curriculum, transport theory should be taught because the conceptual level of transport theory is fundamental, a substantial literature exists and ought to be accessible, and students should understand commercial software which solves the Boltzmann equation.But conventional teaching and learning of transport theory is challenging. Students may be under prepared to appreciate its methods, results, and relevance, and it is not substantially addressed in textbooks for the medical physicists. Other resources an instructor might reasonably use, while excellent, may be too briskly paced for beginning students. The purpose of this work is to render teaching of transport theory more tractable by making learning highly interactive. Methods: The module is being developed in the Maple mathematics environment by instructors and graduate students. It will refresh the students' knowledge of vector calculus and differential equations, and will develop users' intuition for phase space concepts. Scattering concepts will be developed with animated simulations using tunable parameters characterizing interactions, so that students may develop a “feel” for cross section. Transport equations for one and multiple types of radiation will be illustrated with phase space animations. Numerical methods of solution will be illustrated. Results: Attempts to teach rudiments of transport theory in radiation physics and dosimetry courses using conventional classroom techniques at the University of Miami have had small success, because classroom time is limited and the material has been hard for our students to appreciate intuitively. Conclusion: A joint effort of instructor and students to teach and learn transport theory by building an

  6. SU-E-P-04: Transport Theory Learning Module in the Maple Environment

    International Nuclear Information System (INIS)

    Both, J

    2014-01-01

    Purpose: The medical physics graduate program at the University of Miami is developing a computerized instructional module which provides an interactive mechanism for students to learn transport theory. While not essential in the medical physics curriculum, transport theory should be taught because the conceptual level of transport theory is fundamental, a substantial literature exists and ought to be accessible, and students should understand commercial software which solves the Boltzmann equation.But conventional teaching and learning of transport theory is challenging. Students may be under prepared to appreciate its methods, results, and relevance, and it is not substantially addressed in textbooks for the medical physicists. Other resources an instructor might reasonably use, while excellent, may be too briskly paced for beginning students. The purpose of this work is to render teaching of transport theory more tractable by making learning highly interactive. Methods: The module is being developed in the Maple mathematics environment by instructors and graduate students. It will refresh the students' knowledge of vector calculus and differential equations, and will develop users' intuition for phase space concepts. Scattering concepts will be developed with animated simulations using tunable parameters characterizing interactions, so that students may develop a “feel” for cross section. Transport equations for one and multiple types of radiation will be illustrated with phase space animations. Numerical methods of solution will be illustrated. Results: Attempts to teach rudiments of transport theory in radiation physics and dosimetry courses using conventional classroom techniques at the University of Miami have had small success, because classroom time is limited and the material has been hard for our students to appreciate intuitively. Conclusion: A joint effort of instructor and students to teach and learn transport theory by building an interactive

  7. Reexamining Theories of Adult Learning and Adult Development through the Lenses of Public Pedagogy

    Science.gov (United States)

    Sandlin, Jennifer A.; Wright, Robin Redmon; Clark, Carolyn

    2013-01-01

    The authors examine the modernist underpinnings of traditional adult learning and development theories and evaluate elements of those theories through more contemporary lenses. Drawing on recent literature focused on "public pedagogy," the authors argue that much learning takes place outside of formal educational institutions. They look beyond…

  8. Adoption of computer-assisted learning in medical education: the educators' perspective.

    Science.gov (United States)

    Schifferdecker, Karen E; Berman, Norm B; Fall, Leslie H; Fischer, Martin R

    2012-11-01

    Computer-assisted learning (CAL) in medical education has been shown to be effective in the achievement of learning outcomes, but requires the input of significant resources and development time. This study examines the key elements and processes that led to the widespread adoption of a CAL program in undergraduate medical education, the Computer-assisted Learning in Paediatrics Program (CLIPP). It then considers the relative importance of elements drawn from existing theories and models for technology adoption and other studies on CAL in medical education to inform the future development, implementation and testing of CAL programs in medical education. The study used a mixed-methods explanatory design. All paediatric clerkship directors (CDs) using CLIPP were recruited to participate in a self-administered, online questionnaire. Semi-structured interviews were then conducted with a random sample of CDs to further explore the quantitative results. Factors that facilitated adoption included CLIPP's ability to fill gaps in exposure to core clinical problems, the use of a national curriculum, development by CDs, and the meeting of CDs' desires to improve teaching and student learning. An additional facilitating factor was that little time and effort were needed to implement CLIPP within a clerkship. The quantitative findings were mostly corroborated by the qualitative findings. This study indicates issues that are important in the consideration and future exploration of the development and implementation of CAL programs in medical education. The promise of CAL as a method of enhancing the process and outcomes of medical education, and its cost, increase the need for future CAL funders and developers to pay equal attention to the needs of potential adopters and the development process as they do to the content and tools in the CAL program. Important questions that remain on the optimal design, use and integration of CAL should be addressed in order to adequately inform

  9. Cultural Historical Activity Theory, Expansive Learning and Agency ...

    African Journals Online (AJOL)

    The paper focuses on how contradictions were used as sources of learning and development leading to 'real life expansions'. This demonstrates and reflects on the value of an interventionist research theory and methodology employed in the study to enhance participants' agency in sustainable agriculture workplaces.

  10. Designing Ubiquitous Computing to Enhance Children's Learning in Museums

    Science.gov (United States)

    Hall, T.; Bannon, L.

    2006-01-01

    In recent years, novel paradigms of computing have emerged, which enable computational power to be embedded in artefacts and in environments in novel ways. These developments may create new possibilities for using computing to enhance learning. This paper presents the results of a design process that set out to explore interactive techniques,…

  11. A theory of causal learning in children: causal maps and Bayes nets.

    Science.gov (United States)

    Gopnik, Alison; Glymour, Clark; Sobel, David M; Schulz, Laura E; Kushnir, Tamar; Danks, David

    2004-01-01

    The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

  12. Learning to perceive in the sensorimotor approach: Piaget's theory of equilibration interpreted dynamically.

    Science.gov (United States)

    Di Paolo, Ezequiel Alejandro; Barandiaran, Xabier E; Beaton, Michael; Buhrmann, Thomas

    2014-01-01

    if understanding is required for perception, how can we learn to perceive something new, something we do not yet understand? According to the sensorimotor approach, perception involves mastery of regular sensorimotor co-variations that depend on the agent and the environment, also known as the "laws" of sensorimotor contingencies (SMCs). In this sense, perception involves enacting relevant sensorimotor skills in each situation. It is important for this proposal that such skills can be learned and refined with experience and yet up to this date, the sensorimotor approach has had no explicit theory of perceptual learning. The situation is made more complex if we acknowledge the open-ended nature of human learning. In this paper we propose Piaget's theory of equilibration as a potential candidate to fulfill this role. This theory highlights the importance of intrinsic sensorimotor norms, in terms of the closure of sensorimotor schemes. It also explains how the equilibration of a sensorimotor organization faced with novelty or breakdowns proceeds by re-shaping pre-existing structures in coupling with dynamical regularities of the world. This way learning to perceive is guided by the equilibration of emerging forms of skillful coping with the world. We demonstrate the compatibility between Piaget's theory and the sensorimotor approach by providing a dynamical formalization of equilibration to give an explicit micro-genetic account of sensorimotor learning and, by extension, of how we learn to perceive. This allows us to draw important lessons in the form of general principles for open-ended sensorimotor learning, including the need for an intrinsic normative evaluation by the agent itself. We also explore implications of our micro-genetic account at the personal level.

  13. A Human/Computer Learning Network to Improve Biodiversity Conservation and Research

    OpenAIRE

    Kelling, Steve; Gerbracht, Jeff; Fink, Daniel; Lagoze, Carl; Wong, Weng-Keen; Yu, Jun; Damoulas, Theodoros; Gomes, Carla

    2012-01-01

    In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network,...

  14. Learning to perceive in the sensorimotor approach: Piaget's theory of equilibration interpreted dynamically

    Directory of Open Access Journals (Sweden)

    Ezequiel Alejandro Di Paolo

    2014-07-01

    Full Text Available Learning to perceive faces a classical paradox: if understanding is required for perception, how can we learn to perceive something new, something we do not yet understand? According to the sensorimotor approach, perception involves mastery of regular sensorimotor co-variations that depend on the agent and the environment, also known as the ‘laws’ of sensorimotor contingencies. In this sense, perception involves enacting relevant sensorimotor skills in each situation. It is important for this proposal that such skills can be learned and refined with experience and yet up to this date, the sensorimotor approach has had no explicit theory of perceptual learning. The situation is made more complex if we acknowledge the open-ended nature of human learning. In this paper we propose Piaget’s theory of equilibration as a potential candidate to fulfill this role. This theory highlights the importance of intrinsic sensorimotor norms, in terms of the closure of sensorimotor schemes. It also explains how the equilibration of a sensorimotor organization faced with novelty or breakdowns proceeds by re-shaping pre-existing structures in coupling with dynamical regularities of the world. This way learning to perceive is guided by the equilibration of emerging forms of skillful coping with the world. We demonstrate the compatibility between Piaget’s theory and the sensorimotor approach by providing a dynamical formalization of equilibration to give an explicit micro-genetic account of sensorimotor learning and, by extension, of how we learn to perceive. This allows us to draw important lessons in the form of general principles for open-ended sensorimotor learning, including the need for an intrinsic normative evaluation by the agent itself. We also explore implications of our micro-genetic account at the personal level.

  15. Transversity results and computations in symplectic field theory

    Energy Technology Data Exchange (ETDEWEB)

    Fabert, Oliver

    2008-02-21

    Although the definition of symplectic field theory suggests that one has to count holomorphic curves in cylindrical manifolds R x V equipped with a cylindrical almost complex structure J, it is already well-known from Gromov-Witten theory that, due to the presence of multiply-covered curves, we in general cannot achieve transversality for all moduli spaces even for generic choices of J. In this thesis we treat the transversality problem of symplectic field theory in two important cases. In the first part of this thesis we are concerned with the rational symplectic field theory of Hamiltonian mapping tori, which is also called the Floer case. For this observe that in the general geometric setup for symplectic field theory, the contact manifolds can be replaced by mapping tori M{sub {phi}} of symplectic manifolds (M,{omega}{sub M}) with symplectomorphisms {phi}. While the cylindrical contact homology of M{sub {phi}} is given by the Floer homologies of powers of {phi}, the other algebraic invariants of symplectic field theory for M{sub {phi}} provide natural generalizations of symplectic Floer homology. For symplectically aspherical M and Hamiltonian {phi} we study the moduli spaces of rational curves and prove a transversality result, which does not need the polyfold theory by Hofer, Wysocki and Zehnder and allows us to compute the full contact homology of M{sub {phi}} {approx_equal} S{sup 1} x M. The second part of this thesis is devoted to the branched covers of trivial cylinders over closed Reeb orbits, which are the trivial examples of punctured holomorphic curves studied in rational symplectic field theory. Since all moduli spaces of trivial curves with virtual dimension one cannot be regular, we use obstruction bundles in order to find compact perturbations making the Cauchy-Riemann operator transversal to the zero section and show that the algebraic count of elements in the resulting regular moduli spaces is zero. Once the analytical foundations of symplectic

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

    Science.gov (United States)

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

    2018-01-01

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

  17. Quantum computing without wavefunctions: time-dependent density functional theory for universal quantum computation.

    Science.gov (United States)

    Tempel, David G; Aspuru-Guzik, Alán

    2012-01-01

    We prove that the theorems of TDDFT can be extended to a class of qubit Hamiltonians that are universal for quantum computation. The theorems of TDDFT applied to universal Hamiltonians imply that single-qubit expectation values can be used as the basic variables in quantum computation and information theory, rather than wavefunctions. From a practical standpoint this opens the possibility of approximating observables of interest in quantum computations directly in terms of single-qubit quantities (i.e. as density functionals). Additionally, we also demonstrate that TDDFT provides an exact prescription for simulating universal Hamiltonians with other universal Hamiltonians that have different, and possibly easier-to-realize two-qubit interactions. This establishes the foundations of TDDFT for quantum computation and opens the possibility of developing density functionals for use in quantum algorithms.

  18. Learning relationships from theory to design

    Directory of Open Access Journals (Sweden)

    C. J.H. Fowler

    1999-12-01

    Full Text Available Over the last five years we have seen a very significant increase in the use of Information Communication Technologies (ICT in schools, colleges and university. For example in 1998, there were over 195 accredited US universities offering a thousand or more distance learning courses (Philips and Yager, 1998. By no means were all of these new courses associated with educational innovation. The speed and ease of implementation of Webbased approaches, in particular, is resulting in design by imitation of current courses and methods, with a real lack of innovation or utilization of the power inherent in technologybased learning. Although matters are improving (see for example Brown, 1999, part of the reason for this failure to innovate is, we argue, because of the large gap between theory and practice.

  19. The Role of Spirituality in Transition to Parenthood: Qualitative Research Using Transformative Learning Theory.

    Science.gov (United States)

    Klobučar, Nataša Rijavec

    2016-08-01

    This article presents results of a qualitative study of 12 adult couples making transition to parenthood. The aim of the study was to research the meaning of transition to parenthood through the lens of transformative learning theory. Transformative learning theory explains learning through meaning-making of that life experience. In this paper, the spiritual dimension of learning is emphasized. An important part of research methodology included biographical method, using semi-structured interviews before and after the birth of the first child. The research showed that transformative learning occurs in different spheres of life during transition to parenthood. This paper discusses the spiritual dimension of learning, meaning-making and presents results of the research.

  20. Computer-based learning--an aid to successful teaching of pharmacology?

    Science.gov (United States)

    E Hughes, Ian

    2002-07-01

    Various types of software have been developed for use in pharmacology courses. These include: simple drill (question and answer) software; electronic books; video material; tutorial type programs; simulations; and electronic learning environments for course organisation and delivery. These different types of software can be used in different ways to achieve very different learning objectives and gains in teaching efficiency. For example, software can be used: in tutorial and small group teaching; in lectures; to better prepare students for practical work; as a replacement for practicals; to provide options within a limited course structure; to supplement lectures and enable students to work at their own pace; to provide ongoing access to self-assessment throughout a course; to aid distance learning; as remedial teaching and to extend the student learning experience in areas which are too expensive or too time consuming or for which staff expertise does not exist. Evidence indicates that it is insufficient simply to make computer based learning material available to students. Like a laboratory class, it must be fully integrated into a module if real benefits are to be obtained. Students need to be taught how to learn from computer-based learning materials and how to integrate this learning tool in their learning strategy. Teachers need to be supported not only with information about the availability of software but, equally importantly, about how it can be integrated into modules. We are all delivering teaching and facilitating learning in a changing environment and subject to a variety of increasing pressures. It may well be that computer based learning materials may help to maintain a high quality of pharmacology teaching within this changing environment but we need more pedagogical research at the discipline level to establish how this can best be done.

  1. The Relative Effect of Team-Based Learning on Motivation and Learning: A Self-Determination Theory Perspective

    Science.gov (United States)

    Jeno, Lucas M.; Raaheim, Arild; Kristensen, Sara Madeleine; Kristensen, Kjell Daniel; Hole, Torstein Nielsen; Haugland, Mildrid J.; Mæland, Silje

    2017-01-01

    We investigate the effects of team-based learning (TBL) on motivation and learning in a quasi-experimental study. The study employs a self-determination theory perspective to investigate the motivational effects of implementing TBL in a physiotherapy course in higher education. We adopted a one-group pretest-posttest design. The results show that…

  2. Learning Theory Expertise in the Design of Learning Spaces: Who Needs a Seat at the Table?

    Science.gov (United States)

    Rook, Michael M.; Choi, Koun; McDonald, Scott P.

    2015-01-01

    This study highlights the impact of including stakeholders with expertise in learning theory in a learning space design process. We present the decision-making process during the design of the Krause Innovation Studio on the campus of the Pennsylvania State University to draw a distinction between the architect and faculty member's decision-making…

  3. Improved Off-Shell Scattering Amplitudes in String Field Theory and New Computational Methods

    CERN Document Server

    Park, I Y; Bars, Itzhak

    2004-01-01

    We report on new results in Witten's cubic string field theory for the off-shell factor in the 4-tachyon amplitude that was not fully obtained explicitly before. This is achieved by completing the derivation of the Veneziano formula in the Moyal star formulation of Witten's string field theory (MSFT). We also demonstrate detailed agreement of MSFT with a number of on-shell and off-shell computations in other approaches to Witten's string field theory. We extend the techniques of computation in MSFT, and show that the j=0 representation of SL(2,R) generated by the Virasoro operators $L_{0},L_{\\pm1}$ is a key structure in practical computations for generating numbers. We provide more insight into the Moyal structure that simplifies string field theory, and develop techniques that could be applied more generally, including nonperturbative processes.

  4. PAL driven organizational learning theory and practices a light on learning journey of organizations

    CERN Document Server

    Chuah, Kong

    2015-01-01

    Presenting an innovative concept and approach for organization management, this book serves to document an organization’s journey towards the ultimate goal of learning organization. This book also shares the experience on how a OL framework built on established learning theories, could be used effectively, overcoming many of the barriers in a real industrial setting. Utilizing a ready-to-use tool called Project Action Learning (PAL) to analyze real life case studies, the authors introduce a framework that allows teams of people to work and learn over the course of business projects. Equal emphasis is placed on the achievement of pre-set project outcomes and the learning objectives of the participants. In addition, a long term organizational learning strategy is put forward and the necessary supporting infrastructure, in the form of four ‘PAL Pillars’, is described. The concepts and development of the PAL driven Organizational Learning model are inspired by, and grounded in, Western and Eastern business ...

  5. Aligning Kolb's Experiential Learning Theory with a Comprehensive Agricultural Education Model

    Science.gov (United States)

    Baker, Marshall A.; Robinson, J. Shane; Kolb, David A.

    2012-01-01

    Experiential learning has been a foundational tenant of agricultural education since its inception. However, the theory of experiential education has received limited attention in the permanent agricultural education literature base. As such, this philosophical manuscript examined Kolb's experiential learning process further, and considered the…

  6. Enhancing Student Learning in Knowledge-Based Courses: Integrating Team-Based Learning in Mass Communication Theory Classes

    Science.gov (United States)

    Han, Gang; Newell, Jay

    2014-01-01

    This study explores the adoption of the team-based learning (TBL) method in knowledge-based and theory-oriented journalism and mass communication (J&MC) courses. It first reviews the origin and concept of TBL, the relevant theories, and then introduces the TBL method and implementation, including procedures and assessments, employed in an…

  7. Applications of potential theory computations to transonic aeroelasticity

    Science.gov (United States)

    Edwards, J. W.

    1986-01-01

    Unsteady aerodynamic and aeroelastic stability calculations based upon transonic small disturbance (TSD) potential theory are presented. Results from the two-dimensional XTRAN2L code and the three-dimensional XTRAN3S code are compared with experiment to demonstrate the ability of TSD codes to treat transonic effects. The necessity of nonisentropic corrections to transonic potential theory is demonstrated. Dynamic computational effects resulting from the choice of grid and boundary conditions are illustrated. Unsteady airloads for a number of parameter variations including airfoil shape and thickness, Mach number, frequency, and amplitude are given. Finally, samples of transonic aeroelastic calculations are given. A key observation is the extent to which unsteady transonic airloads calculated by inviscid potential theory may be treated in a locally linear manner.

  8. Mastering Cognitive Development Theory in Computer Science Education

    Science.gov (United States)

    Gluga, Richard; Kay, Judy; Lister, Raymond; Kleitman, Simon; Kleitman, Sabina

    2013-01-01

    To design an effective computer science curriculum, educators require a systematic method of classifying the difficulty level of learning activities and assessment tasks. This is important for curriculum design and implementation and for communication between educators. Different educators must be able to use the method consistently, so that…

  9. Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

    Science.gov (United States)

    Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

    2018-01-11

    By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

  10. Graphical Model Theory for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Davis, William B.

    2002-01-01

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm

  11. Relationships among Learning Styles and Motivation with Computer-Aided Instruction in an Agronomy Course

    Science.gov (United States)

    McAndrews, Gina M.; Mullen, Russell E.; Chadwick, Scott A.

    2005-01-01

    Multi-media learning tools were developed to enhance student learning for an introductory agronomy course at Iowa State University. During fall 2002, the new interactive computer program, called Computer Interactive Multimedia Program for Learning Enhancement (CIMPLE) was incorporated into the teaching, learning, and assessment processes of the…

  12. The application of learning theory in horse training

    DEFF Research Database (Denmark)

    McLean, Andrew N.; Christensen, Janne Winther

    2017-01-01

    additional techniques (approach conditioning and stimulus blending). The salience of different types of cues, the interaction of operant and classical conditioning and the impact of stress are also discussed. This paper also exposes the inflexibility and occasional inadequacy of the terminology of learning...... on the correct application of learning theory, and safety and welfare benefits for people and horses would follow. Finally it is also proposed that the term ‘conflict theory’ be taken up in equitation science to facilitate diagnosis of training-related behaviour disorders and thus enable the emergence...

  13. A Reflective Journey through Theory and Research in Mathematical Learning and Development

    Science.gov (United States)

    Belbase, Shashidhar

    2010-01-01

    This paper is an attempt to reflect on class sessions during the fall 2010 in a course "Theory and Research in Mathematical Learning and Development". This reflection as a learning journey portrays discussions based on foundational perspectives (FP), historical highlights (HH), and guiding questions (GQ) related to mathematics learning and…

  14. Learning and the cooperative computational universe

    NARCIS (Netherlands)

    Adriaans, P.; Adriaans, P.; van Benthem, J.

    2008-01-01

    In the summer of 1956, a number of scientists gathered at the Dartmouth College in Hanover, New Hampshire. Their goal was to study human intelligence with the help of computers. Their central hypothesis was: "that every aspect of learning or any other feature of intelligence can in principle be so

  15. The effects of integrating service learning into computer science: an inter-institutional longitudinal study

    Science.gov (United States)

    Payton, Jamie; Barnes, Tiffany; Buch, Kim; Rorrer, Audrey; Zuo, Huifang

    2015-07-01

    This study is a follow-up to one published in computer science education in 2010 that reported preliminary results showing a positive impact of service learning on student attitudes associated with success and retention in computer science. That paper described how service learning was incorporated into a computer science course in the context of the Students & Technology in Academia, Research, and Service (STARS) Alliance, an NSF-supported broadening participation in computing initiative that aims to diversify the computer science pipeline through innovative pedagogy and inter-institutional partnerships. The current paper describes how the STARS Alliance has expanded to diverse institutions, all using service learning as a vehicle for broadening participation in computing and enhancing attitudes and behaviors associated with student success. Results supported the STARS model of service learning for enhancing computing efficacy and computing commitment and for providing diverse students with many personal and professional development benefits.

  16. Computer Use by School Teachers in Teaching-Learning Process

    Science.gov (United States)

    Bhalla, Jyoti

    2013-01-01

    Developing countries have a responsibility not merely to provide computers for schools, but also to foster a habit of infusing a variety of ways in which computers can be integrated in teaching-learning amongst the end users of these tools. Earlier researches lacked a systematic study of the manner and the extent of computer-use by teachers. The…

  17. Computer-Assisted Foreign Language Teaching and Learning: Technological Advances

    Science.gov (United States)

    Zou, Bin; Xing, Minjie; Wang, Yuping; Sun, Mingyu; Xiang, Catherine H.

    2013-01-01

    Computer-Assisted Foreign Language Teaching and Learning: Technological Advances highlights new research and an original framework that brings together foreign language teaching, experiments and testing practices that utilize the most recent and widely used e-learning resources. This comprehensive collection of research will offer linguistic…

  18. Gradient Learning Algorithms for Ontology Computing

    Science.gov (United States)

    Gao, Wei; Zhu, Linli

    2014-01-01

    The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting. PMID:25530752

  19. Gradient Learning Algorithms for Ontology Computing

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-01-01

    Full Text Available The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting.

  20. Successful Implementation of a Computer-Supported Collaborative Learning System in Teaching E-Commerce

    Science.gov (United States)

    Ngai, E. W. T.; Lam, S. S.; Poon, J. K. L.

    2013-01-01

    This paper describes the successful application of a computer-supported collaborative learning system in teaching e-commerce. The authors created a teaching and learning environment for 39 local secondary schools to introduce e-commerce using a computer-supported collaborative learning system. This system is designed to equip students with…