WorldWideScience

Sample records for computational learning theory

  1. 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…

  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. 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...

  4. 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

  5. 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...

  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. 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

  8. 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)

  9. 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 ...

  10. 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

  11. 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…

  12. 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

  13. 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.)

  14. 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 ...

  15. 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.

  16. 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.

  17. Enabling Students to Construct Theories of Collaborative Inquiry and Reflective Learning: Computer Support for Metacognitive Development

    OpenAIRE

    White, Barbara Y.; Shimoda, Todd A.; Frederiksen, John R.

    1999-01-01

    Part II of the Special Issue on Authoring Systems for Intelligent Tutoring Systems (editors: Tom Murray and Stephen Blessing); To develop lifelong learning skills, we argue that students need to learn how to learn via inquiry and understand the sociocognitive and metacognitive processes that are involved. We illustrate how software could play a central role in enabling students to develop such expertise. Our hypothesis is that sociocognitive systems, such as those needed for collaborative inq...

  18. 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…

  19. 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

  20. 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…

  1. 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.

  2. 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...

  3. 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.

  4. 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.)

  5. 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…

  6. Theory and Computation

    Data.gov (United States)

    Federal Laboratory Consortium — Flexible computational infrastructure, software tools and theoretical consultation are provided to support modeling and understanding of the structure and properties...

  7. Theory of computational complexity

    CERN Document Server

    Du, Ding-Zhu

    2011-01-01

    DING-ZHU DU, PhD, is a professor in the Department of Computer Science at the University of Minnesota. KER-I KO, PhD, is a professor in the Department of Computer Science at the State University of New York at Stony Brook.

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Dynasting Theory: Lessons in learning grounded theory

    Directory of Open Access Journals (Sweden)

    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

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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)

  1. 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.

  2. [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.

  3. 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…

  4. 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...

  5. 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...

  6. 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.

  7. 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…

  8. 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…

  9. 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…

  10. Teachability in Computational Learning

    OpenAIRE

    Shinohara, Ayumi; Miyano, Satoru

    1990-01-01

    This paper considers computationai learning from the viewpoint of teaching. We introduce a notion of teachability with which we establish a relationship between the learnability and teachability. We also discuss the complexity issues of a teacher in relation to learning.

  11. My Computer Is Learning.

    Science.gov (United States)

    Good, Ron

    1986-01-01

    Describes instructional uses of computer programs found in David Heiserman's book "Projects in Machine Intelligence for Your Home Computer." The programs feature "creatures" of various colors that move around within a rectangular white border. (JN)

  12. 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

  13. 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,

  14. 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

  15. 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 ...

  16. 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.

  17. 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…

  18. 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…

  19. 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…

  20. Learning with Ubiquitous Computing

    Science.gov (United States)

    Rosenheck, Louisa

    2008-01-01

    If ubiquitous computing becomes a reality and is widely adopted, it will inevitably have an impact on education. This article reviews the background of ubiquitous computing and current research projects done involving educational "ubicomp." Finally it explores how ubicomp may and may not change education in both formal and informal settings and…

  1. 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

  2. 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.

  3. 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)

  4. 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)

  5. Make Computer Learning Stick.

    Science.gov (United States)

    Casella, Vicki

    1985-01-01

    Teachers are using computer programs in conjunction with many classroom staples such as art supplies, math manipulatives, and science reference books. Twelve software programs and related activities are described which teach visual and auditory memory and spatial relations, as well as subject areas such as anatomy and geography. (MT)

  6. 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

  7. 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…

  8. Surface electrostatics: theory and computations

    KAUST Repository

    Chatzigeorgiou, G.; Javili, A.; Steinmann, P.

    2014-01-01

    are also expressed in a consistent manner. The theory is accompanied by numerical examples on porous materials using the finite-element method, where the influence of the surface electric permittivity on the electric displacement, the polarization stress

  9. 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

  10. 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.

  11. 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.

  12. 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,…

  13. 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…

  14. 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

  15. 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)

  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. 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...

  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. 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.

  20. 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…

  1. 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.

  2. 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.

  3. 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

  4. Generalized inverses theory and computations

    CERN Document Server

    Wang, Guorong; Qiao, Sanzheng

    2018-01-01

    This book begins with the fundamentals of the generalized inverses, then moves to more advanced topics. It presents a theoretical study of the generalization of Cramer's rule, determinant representations of the generalized inverses, reverse order law of the generalized inverses of a matrix product, structures of the generalized inverses of structured matrices, parallel computation of the generalized inverses, perturbation analysis of the generalized inverses, an algorithmic study of the computational methods for the full-rank factorization of a generalized inverse, generalized singular value decomposition, imbedding method, finite method, generalized inverses of polynomial matrices, and generalized inverses of linear operators. This book is intended for researchers, postdocs, and graduate students in the area of the generalized inverses with an undergraduate-level understanding of linear algebra.

  5. 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...

  6. 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

  7. 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

  8. 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

  9. 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…

  10. 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

  11. 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...

  12. 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...

  13. 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 ...

  14. 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.

  15. 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.

  16. Surface electrostatics: theory and computations

    KAUST Repository

    Chatzigeorgiou, G.

    2014-02-05

    The objective of this work is to study the electrostatic response of materials accounting for boundary surfaces with their own (electrostatic) constitutive behaviour. The electric response of materials with (electrostatic) energetic boundary surfaces (surfaces that possess material properties and constitutive structures different from those of the bulk) is formulated in a consistent manner using a variational framework. The forces and moments that appear due to bulk and surface electric fields are also expressed in a consistent manner. The theory is accompanied by numerical examples on porous materials using the finite-element method, where the influence of the surface electric permittivity on the electric displacement, the polarization stress and the Maxwell stress is examined.

  17. 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 ...

  18. 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…

  19. 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.

  20. 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)

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  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. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. Learned Helplessness: Theory and Evidence

    Science.gov (United States)

    Maier, Steven F.; Seligman, Martin E. P.

    1976-01-01

    Authors believes that three phenomena are all instances of "learned helplessness," instances in which an organism has learned that outcomes are uncontrollable by his responses and is seriously debilitated by this knowledge. This article explores the evidence for the phenomena of learned helplessness, and discussed a variety of theoretical…

  19. 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

  20. 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.

  1. 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.

  2. 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...

  3. 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…

  4. 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…

  5. 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.

  6. 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

  7. 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

  8. Computing on Encrypted Data: Theory and Application

    Science.gov (United States)

    2016-01-01

    permits short ciphertexts – e.g., encrypted using AES – to be de-compressed to longer ciphertexts that permit homomorphic operations. Bootstrapping...allows us to save memory by storing data encrypted in the compressed form – e.g., under AES . Here, we revisit bootstrapping, viewing it as an...COMPUTING ON ENCRYPTED DATA: THEORY AND APPLICATION MASSACHUSETTS INSTITUTE OF TECHNOLOGY JANUARY 2016 FINAL TECHNICAL REPORT

  9. Learning automata theory and applications

    CERN Document Server

    Najim, K

    1994-01-01

    Learning systems have made a significant impact on all areas of engineering problems. They are attractive methods for solving many problems which are too complex, highly non-linear, uncertain, incomplete or non-stationary, and have subtle and interactive exchanges with the environment where they operate. The main aim of the book is to give a systematic treatment of learning automata and to produce a guide to a wide variety of ideas and methods that can be used in learning systems, including enough theoretical material to enable the user of the relevant techniques and concepts to understand why

  10. 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

  11. 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

  12. 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,

  13. 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.

  14. 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.

  15. 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

  16. 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 ...

  17. 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…

  18. 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.

  19. 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…

  20. 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.

  1. 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

  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. 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)

  4. 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…

  5. Computational hemodynamics theory, modelling and applications

    CERN Document Server

    Tu, Jiyuan; Wong, Kelvin Kian Loong

    2015-01-01

    This book discusses geometric and mathematical models that can be used to study fluid and structural mechanics in the cardiovascular system.  Where traditional research methodologies in the human cardiovascular system are challenging due to its invasive nature, several recent advances in medical imaging and computational fluid and solid mechanics modelling now provide new and exciting research opportunities. This emerging field of study is multi-disciplinary, involving numerical methods, computational science, fluid and structural mechanics, and biomedical engineering. Certainly any new student or researcher in this field may feel overwhelmed by the wide range of disciplines that need to be understood. This unique book is one of the first to bring together knowledge from multiple disciplines, providing a starting point to each of the individual disciplines involved, attempting to ease the steep learning curve. This book presents elementary knowledge on the physiology of the cardiovascular system; basic knowl...

  6. Connectionism vs. Computational Theory of Mind

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available

    Usually, the problems in AI may be many times related to Philosophy of Mind, and perhaps because this reason may be in essence very disputable. So, for instance, the famous question: Can a machine think? It was proposed by Alan Turing [16]. And it may be the more decisive question, but for many people it would be a nonsense. So, two of the very fundamental and more confronted positions usually considered according this line include the Connectionism and the Computational Theory of Mind. We analyze here its content, with their past disputes, and current situation.

  7. Statistical theory applications and associated computer codes

    International Nuclear Information System (INIS)

    Prince, A.

    1980-01-01

    The general format is along the same lines as that used in the O.M. Session, i.e. an introduction to the nature of the physical problems and methods of solution based on the statistical model of the nucleus. Both binary and higher multiple reactions are considered. The computer codes used in this session are a combination of optical model and statistical theory. As with the O.M. sessions, the preparation of input and analysis of output are thoroughly examined. Again, comparison with experimental data serves to demonstrate the validity of the results and possible areas for improvement. (author)

  8. High performance computations using dynamical nucleation theory

    International Nuclear Information System (INIS)

    Windus, T L; Crosby, L D; Kathmann, S M

    2008-01-01

    Chemists continue to explore the use of very large computations to perform simulations that describe the molecular level physics of critical challenges in science. In this paper, we describe the Dynamical Nucleation Theory Monte Carlo (DNTMC) model - a model for determining molecular scale nucleation rate constants - and its parallel capabilities. The potential for bottlenecks and the challenges to running on future petascale or larger resources are delineated. A 'master-slave' solution is proposed to scale to the petascale and will be developed in the NWChem software. In addition, mathematical and data analysis challenges are described

  9. Quantum algorithms and learning theory

    NARCIS (Netherlands)

    Arunachalam, S.

    2018-01-01

    This thesis studies strengths and weaknesses of quantum computers. In the first part we present three contributions to quantum algorithms. 1) consider a search space of N elements. One of these elements is "marked" and our goal is to find this. We describe a quantum algorithm to solve this problem

  10. 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…

  11. 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…

  12. 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…

  13. 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…

  14. 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…

  15. 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.

  16. 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…

  17. 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;…

  18. 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.

  19. 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

  20. 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…

  1. 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.

  2. Toward a computational theory of conscious processing.

    Science.gov (United States)

    Dehaene, Stanislas; Charles, Lucie; King, Jean-Rémi; Marti, Sébastien

    2014-04-01

    The study of the mechanisms of conscious processing has become a productive area of cognitive neuroscience. Here we review some of the recent behavioral and neuroscience data, with the specific goal of constraining present and future theories of the computations underlying conscious processing. Experimental findings imply that most of the brain's computations can be performed in a non-conscious mode, but that conscious perception is characterized by an amplification, global propagation and integration of brain signals. A comparison of these data with major theoretical proposals suggests that firstly, conscious access must be carefully distinguished from selective attention; secondly, conscious perception may be likened to a non-linear decision that 'ignites' a network of distributed areas; thirdly, information which is selected for conscious perception gains access to additional computations, including temporary maintenance, global sharing, and flexible routing; and finally, measures of the complexity, long-distance correlation and integration of brain signals provide reliable indices of conscious processing, clinically relevant to patients recovering from coma. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Computer Learning Through Piaget's Eyes.

    Science.gov (United States)

    Huber, Leonard N.

    1985-01-01

    Discusses Piaget's pre-operational, concrete operational, and formal operational stages and shows how this information sheds light on how children approach computers and computing, particularly with the LOGO programming language. (JN)

  4. 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.

  5. Soft computing in machine learning

    CERN Document Server

    Park, Jooyoung; Inoue, Atsushi

    2014-01-01

    As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. Neural Computation and the Computational Theory of Cognition

    Science.gov (United States)

    Piccinini, Gualtiero; Bahar, Sonya

    2013-01-01

    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…

  11. Multistategy Learning for Computer Vision

    National Research Council Canada - National Science Library

    Bhanu, Bir

    1998-01-01

    .... With the goal of achieving robustness, our research at UCR is directed towards learning parameters, feedback, contexts, features, concepts, and strategies of IU algorithms for model-based object recognition...

  12. Computational mate choice: theory and empirical evidence.

    Science.gov (United States)

    Castellano, Sergio; Cadeddu, Giorgia; Cermelli, Paolo

    2012-06-01

    The present review is based on the thesis that mate choice results from information-processing mechanisms governed by computational rules and that, to understand how females choose their mates, we should identify which are the sources of information and how they are used to make decisions. We describe mate choice as a three-step computational process and for each step we present theories and review empirical evidence. The first step is a perceptual process. It describes the acquisition of evidence, that is, how females use multiple cues and signals to assign an attractiveness value to prospective mates (the preference function hypothesis). The second step is a decisional process. It describes the construction of the decision variable (DV), which integrates evidence (private information by direct assessment), priors (public information), and value (perceived utility) of prospective mates into a quantity that is used by a decision rule (DR) to produce a choice. We make the assumption that females are optimal Bayesian decision makers and we derive a formal model of DV that can explain the effects of preference functions, mate copying, social context, and females' state and condition on the patterns of mate choice. The third step of mating decision is a deliberative process that depends on the DRs. We identify two main categories of DRs (absolute and comparative rules), and review the normative models of mate sampling tactics associated to them. We highlight the limits of the normative approach and present a class of computational models (sequential-sampling models) that are based on the assumption that DVs accumulate noisy evidence over time until a decision threshold is reached. These models force us to rethink the dichotomy between comparative and absolute decision rules, between discrimination and recognition, and even between rational and irrational choice. Since they have a robust biological basis, we think they may represent a useful theoretical tool for

  13. Denuded Data! Grounded Theory Using the NUDIST Computer Analysis Program: In Researching the Challenge to Teacher Self-Efficacy Posed by Students with Learning Disabilities in Australian Education.

    Science.gov (United States)

    Burroughs-Lange, Sue G.; Lange, John

    This paper evaluates the effects of using the NUDIST (Non-numerical, Unstructured Data Indexing, Searching and Theorising) computer program to organize coded, qualitative data. The use of the software is discussed within the context of the study for which it was used: an Australian study that aimed to develop a theoretical understanding of the…

  14. 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.

  15. 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…

  16. 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…

  17. A computational theory of visual receptive fields.

    Science.gov (United States)

    Lindeberg, Tony

    2013-12-01

    A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space-time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative

  18. Computational modeling of epiphany learning.

    Science.gov (United States)

    Chen, Wei James; Krajbich, Ian

    2017-05-02

    Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit at all. Our findings suggest that EL is driven by a latent evidence accumulation process that can be revealed with eye-tracking data.

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Stochastic linear programming models, theory, and computation

    CERN Document Server

    Kall, Peter

    2011-01-01

    This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...

  5. 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.

  6. Excessive online computer use and learning disabilities

    OpenAIRE

    Griffiths, MD

    2010-01-01

    Online gaming has become a very popular leisure activity among adolescents. Research suggests that a small minority of adolescents may display problematic gaming behaviour and that some of these individuals may be addicted to online games, including those who have learning disabilities. This article begins by examining a case study of a 15-year old adolescent with a learning disability who appeared to be addicted to various computer and internet applications. Despite the potential negative ef...

  7. 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

  8. 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.

  9. 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...

  10. 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…

  11. 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

  12. 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)

  13. Recursion theory computational aspects of definability

    CERN Document Server

    Chong, Chi Tat

    2015-01-01

    This monograph presents recursion theory from a generalized and largely global point of view. A major theme is the study of the structures of degrees arising from two key notions of reducibility, the Turing degrees and the hyperdegrees, using ideas and techniques beyond those of classical recursion theory. These include structure theory, hyperarithmetic determinacy and rigidity, basis theorems, independence results on Turing degrees, as well as applications to higher randomness.

  14. 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.…

  15. 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

  16. Learning and Teaching with a Computer Scanner

    Science.gov (United States)

    Planinsic, G.; Gregorcic, B.; Etkina, E.

    2014-01-01

    This paper introduces the readers to simple inquiry-based activities (experiments with supporting questions) that one can do with a computer scanner to help students learn and apply the concepts of relative motion in 1 and 2D, vibrational motion and the Doppler effect. We also show how to use these activities to help students think like…

  17. 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…

  18. 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…

  19. 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.

  20. 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

  1. 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

  2. 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...

  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. 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

  5. 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…

  6. 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.

  7. 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)

  8. HYPERCOMPOSITIONAL STRUCTURES FROM THE COMPUTER THEORY

    Directory of Open Access Journals (Sweden)

    Geronimos G. Massouros

    1999-02-01

    Full Text Available Abstract This paper presents the several types of hypercompositional structures that have been introduced and used for the approach and solution of problems in the theory of languages and automata.

  9. 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…

  10. 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.

  11. 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

  12. 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.

  13. 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...

  14. Competitive Argumentation in Computational Theories of Cognition.

    Science.gov (United States)

    1982-12-01

    elements of number competence are present much earlier than strict Piagetian theory would predict (Gelman & Gallistel , 1978). A successful style of...caused considerable attention to be focused on counting. Observations by Gelman and Gallistell (1978), and others. provided evidence that significant...certain principles of counting. These premises formalized and extended a particular decomposition of counting competence proposed by Gelman and Gallistel

  15. 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,

  16. 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

  17. 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

  18. 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.

  19. Morphing continuum theory for turbulence: Theory, computation, and visualization

    Science.gov (United States)

    Chen, James

    2017-10-01

    A high order morphing continuum theory (MCT) is introduced to model highly compressible turbulence. The theory is formulated under the rigorous framework of rational continuum mechanics. A set of linear constitutive equations and balance laws are deduced and presented from the Coleman-Noll procedure and Onsager's reciprocal relations. The governing equations are then arranged in conservation form and solved through the finite volume method with a second-order Lax-Friedrichs scheme for shock preservation. A numerical example of transonic flow over a three-dimensional bump is presented using MCT and the finite volume method. The comparison shows that MCT-based direct numerical simulation (DNS) provides a better prediction than Navier-Stokes (NS)-based DNS with less than 10% of the mesh number when compared with experiments. A MCT-based and frame-indifferent Q criterion is also derived to show the coherent eddy structure of the downstream turbulence in the numerical example. It should be emphasized that unlike the NS-based Q criterion, the MCT-based Q criterion is objective without the limitation of Galilean invariance.

  20. 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)

  1. 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

  2. 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.

  3. 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.

  4. 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...

  5. 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

  6. Theory of automata, formal languages and computation

    CERN Document Server

    Xavier, SPE

    2004-01-01

    This book is aimed at providing an introduction to the basic models of computability to the undergraduate students. This book is devoted to Finite Automata and their properties. Pushdown Automata provides a class of models and enables the analysis of context-free languages. Turing Machines have been introduced and the book discusses computability and decidability. A number of problems with solutions have been provided for each chapter. A lot of exercises have been given with hints/answers to most of these tutorial problems.

  7. 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

  8. Computation of Hyperbolic Structures in Knot Theory

    OpenAIRE

    Weeks, Jeffrey R.

    2003-01-01

    This chapter from the upcoming Handbook of Knot Theory (eds. Menasco and Thistlethwaite) shows how to construct hyperbolic structures on link complements and perform hyperbolic Dehn filling. Along with a new elementary exposition of the standard ideas from Thurston's work, the article includes never-before-published explanations of SnapPea's algorithms for triangulating a link complement efficiently and for converging quickly to the hyperbolic structure while avoiding singularities in the par...

  9. 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…

  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. 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. 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…

  13. 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…

  14. 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…

  15. 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)

  16. Computers and Languages: Theory and Practice

    NARCIS (Netherlands)

    Nijholt, Antinus

    A global introduction to language technology and the areas of computer science where language technology plays a role. Surveyed in this volume are issueas related to the parsing problem in the fields of natural languages, programming languages, and formal languages. Throughout the book attention is

  17. 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

  18. 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.

  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. Lattice gauge theory on a parallel computer

    International Nuclear Information System (INIS)

    Flower, J.W.

    1987-01-01

    The results of several numerical simulations of QCD by Monte Carlo lattice gauge theory are presented. Studying the mesonic potential on a 20 4 lattice, we conclude that asymptotic scaling does not hold over the range 6.1 ≤ β ≤ 6.7, although we are not able to quantify the discrepancies. The effect of discrete rotational symmetry on physical parameters is examined and seems to modify the string tension by 15% at β = 6.1, while at β = 6.3 the change was less than 1%. The potential between three charges is studied and yields a string tension of .18 GeV 2 , consistent with mesonic calculations and relativized potential models. Contributions to the potential from low-energy string vibrations appear small in the range x ≤ .5 fm. We perform energy density measurements in the color fields surrounding both mesons and baryons, which provide strong evidence in favor of the dual superconductor picture of confinement. It is also suggested that the confining strings in the baryon meet at a central point rather than joining the quarks pairwise. Several algorithms are explored in an attempt to develop simulation methods which are able to directly account for the currents generated by color sources. The extension of the Langevin equation to complex degrees of freedom is derived leading to a Fokker-Planck equation for a complex 'Probability distribution'. Using this technique we are then able to calculate energy densities in U(1) gauge theory at large charge separations. The extension of the method to non-Abelian theories comes up against an unresolved problem in segregation for certain types of observable. 145 refs., 36 figs

  1. Visual Hemispheric Specialization: A Computational Theory.

    Science.gov (United States)

    1985-10-31

    magnitude of difficulty of this problem becomes evident if you look at a digitized representation of a picture, with numbers representing the intensity...brain is not a digital computer; it does not pass discrete symbols back and forth. Rather, we assume that modules produce patterns of activity, which... Comercio Dr. David E. Clement Lisbon Department of Psychology PORTUGAL University of South Carolina Columbia, SC 29208 M.C.S. Louis Crocq Secretariat

  2. Learning Theory and the Typewriter Teacher

    Science.gov (United States)

    Wakin, B. Bertha

    1974-01-01

    Eight basic principles of learning are described and discussed in terms of practical learning strategies for typewriting. Described are goal setting, preassessment, active participation, individual differences, reinforcement, practice, transfer of learning, and evaluation. (SC)

  3. 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…

  4. 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…

  5. 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…

  6. Constructivist Learning Theory and Climate Science Communication

    Science.gov (United States)

    Somerville, R. C.

    2012-12-01

    Communicating climate science is a form of education. A scientist giving a television interview or testifying before Congress is engaged in an educational activity, though one not identical to teaching graduate students. Knowledge, including knowledge about climate science, should never be communicated as a mere catalogue of facts. Science is a process, a way of regarding the natural world, and a fascinating human activity. A great deal is already known about how to do a better job of science communication, but implementing change is not easy. I am confident that improving climate science communication will involve the paradigm of constructivist learning theory, which traces its roots to the 20th-century Swiss epistemologist Jean Piaget, among others. This theory emphasizes the role of the teacher as supportive facilitator rather than didactic lecturer, "a guide on the side, not a sage on the stage." It also stresses the importance of the teacher making a serious effort to understand and appreciate the prior knowledge and viewpoint of the student, recognizing that students' minds are not empty vessels to be filled or blank slates to be written on. Instead, students come to class with a background of life experiences and a body of existing knowledge, of varying degrees of correctness or accuracy, about almost any topic. Effective communication is also usually a conversation rather than a monologue. We know too that for many audiences, the most trusted messengers are those who share the worldview and cultural values of those with whom they are communicating. Constructivist teaching methods stress making use of the parallels between learning and scientific research, such as the analogies between assessing prior knowledge of the audience and surveying scientific literature for a research project. Meanwhile, a well-funded and effective professional disinformation campaign has been successful in sowing confusion, and as a result, many people mistakenly think climate

  7. 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.

  8. 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.

  9. 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.

  10. Adaptive vs. eductive learning : Theory and evidence

    NARCIS (Netherlands)

    Bao, T.; Duffy, J.

    2014-01-01

    Adaptive learning and eductive learning are two widely used ways of modeling learning behavior in macroeconomics. Both approaches yield restrictions on model parameters under which agents are able to learn a rational expectation equilibrium (REE) but these restrictions do not always overlap with one

  11. Computer games: Apprehension of learning strategies

    Directory of Open Access Journals (Sweden)

    Carlos Antonio Bruno da Silva

    2003-12-01

    Full Text Available Computer games and mainly videogames have proved to be an important tendency in Brazilian children’s play. They are part of the playful culture, which associates modern technology to traditional play preserving the importance of the latter. Based on Vygotsky and Chadwick’s ideas, this work studies the alternatives in the use of videogame by the occupational therapist, educator or parents, aiming prevention of learning difficulty by means of apprehension of learning strategies. Sixty children were investigated under dialectic, descriptive qualitative/quantitative focus. There was a semi-structured interview, direct observation and focused group applied to this intentional sample. Out of the 60 children playing in 3 videogame rental shops in Fortaleza-CE and Quixadá-CE, 30 aged 4 to 6 years old and the other 30 aged 7 and 8. Results indicate that the determination that the videogame is played in-group favors the apprehension of learning and affective strategies, processing, and meta-cognition. Therefore, videogame can be considered an excellent resource in terms of preventing learning difficulties, enabling children to their reality.

  12. 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.…

  13. 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.

  14. Computational ghost imaging using deep learning

    Science.gov (United States)

    Shimobaba, Tomoyoshi; Endo, Yutaka; Nishitsuji, Takashi; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Shiraki, Atsushi; Ito, Tomoyoshi

    2018-04-01

    Computational ghost imaging (CGI) is a single-pixel imaging technique that exploits the correlation between known random patterns and the measured intensity of light transmitted (or reflected) by an object. Although CGI can obtain two- or three-dimensional images with a single or a few bucket detectors, the quality of the reconstructed images is reduced by noise due to the reconstruction of images from random patterns. In this study, we improve the quality of CGI images using deep learning. A deep neural network is used to automatically learn the features of noise-contaminated CGI images. After training, the network is able to predict low-noise images from new noise-contaminated CGI images.

  15. 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.

  16. 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...

  17. 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…

  18. 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…

  19. 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.

  20. 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...

  1. 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...

  2. 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…

  3. 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

  4. A Critical Theory Perspective on Accelerated Learning.

    Science.gov (United States)

    Brookfield, Stephen D.

    2003-01-01

    Critically analyzes accelerated learning using concepts from Herbert Marcuse (rebellious subjectivity) and Erich Fromm (automaton conformity). Concludes that, by providing distance and separation, accelerated learning has more potential to stimulate critical autonomous thought. (SK)

  5. 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....

  6. 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.

  7. 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.

  8. Computer Models and Automata Theory in Biology and Medicine

    CERN Document Server

    Baianu, I C

    2004-01-01

    The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

  9. Complexity vs energy: theory of computation and theoretical physics

    International Nuclear Information System (INIS)

    Manin, Y I

    2014-01-01

    This paper is a survey based upon the talk at the satellite QQQ conference to ECM6, 3Quantum: Algebra Geometry Information, Tallinn, July 2012. It is dedicated to the analogy between the notions of complexity in theoretical computer science and energy in physics. This analogy is not metaphorical: I describe three precise mathematical contexts, suggested recently, in which mathematics related to (un)computability is inspired by and to a degree reproduces formalisms of statistical physics and quantum field theory.

  10. 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,

  11. A Computer Learning Center for Environmental Sciences

    Science.gov (United States)

    Mustard, John F.

    2000-01-01

    In the fall of 1998, MacMillan Hall opened at Brown University to students. In MacMillan Hall was the new Computer Learning Center, since named the EarthLab which was outfitted with high-end workstations and peripherals primarily focused on the use of remotely sensed and other spatial data in the environmental sciences. The NASA grant we received as part of the "Centers of Excellence in Applications of Remote Sensing to Regional and Global Integrated Environmental Assessments" was the primary source of funds to outfit this learning and research center. Since opening, we have expanded the range of learning and research opportunities and integrated a cross-campus network of disciplines who have come together to learn and use spatial data of all kinds. The EarthLab also forms a core of undergraduate, graduate, and faculty research on environmental problems that draw upon the unique perspective of remotely sensed data. Over the last two years, the Earthlab has been a center for research on the environmental impact of water resource use in and regions, impact of the green revolution on forest cover in India, the design of forest preserves in Vietnam, and detailed assessments of the utility of thermal and hyperspectral data for water quality analysis. It has also been used extensively for local environmental activities, in particular studies on the impact of lead on the health of urban children in Rhode Island. Finally, the EarthLab has also served as a key educational and analysis center for activities related to the Brown University Affiliated Research Center that is devoted to transferring university research to the private sector.

  12. 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)

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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…

  18. Lay Theories Regarding Computer-Mediated Communication in Remote Collaboration

    Science.gov (United States)

    Parke, Karl; Marsden, Nicola; Connolly, Cornelia

    2017-01-01

    Computer-mediated communication and remote collaboration has become an unexceptional norm as an educational modality for distance and open education, therefore the need to research and analyze students' online learning experience is necessary. This paper seeks to examine the assumptions and expectations held by students in regard to…

  19. Developing the next generation of diverse computer scientists: the need for enhanced, intersectional computing identity theory

    Science.gov (United States)

    Rodriguez, Sarah L.; Lehman, Kathleen

    2017-10-01

    This theoretical paper explores the need for enhanced, intersectional computing identity theory for the purpose of developing a diverse group of computer scientists for the future. Greater theoretical understanding of the identity formation process specifically for computing is needed in order to understand how students come to understand themselves as computer scientists. To ensure that the next generation of computer scientists is diverse, this paper presents a case for examining identity development intersectionally, understanding the ways in which women and underrepresented students may have difficulty identifying as computer scientists and be systematically oppressed in their pursuit of computer science careers. Through a review of the available scholarship, this paper suggests that creating greater theoretical understanding of the computing identity development process will inform the way in which educational stakeholders consider computer science practices and policies.

  20. 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…

  1. Automated computation of one-loop integrals in massless theories

    International Nuclear Information System (INIS)

    Hameren, A. van; Vollinga, J.; Weinzierl, S.

    2005-01-01

    We consider one-loop tensor and scalar integrals, which occur in a massless quantum field theory, and we report on the implementation into a numerical program of an algorithm for the automated computation of these one-loop integrals. The number of external legs of the loop integrals is not restricted. All calculations are done within dimensional regularization. (orig.)

  2. Theories of willpower affect sustained learning.

    Directory of Open Access Journals (Sweden)

    Eric M Miller

    Full Text Available Building cognitive abilities often requires sustained engagement with effortful tasks. We demonstrate that beliefs about willpower-whether willpower is viewed as a limited or non-limited resource-impact sustained learning on a strenuous mental task. As predicted, beliefs about willpower did not affect accuracy or improvement during the initial phases of learning; however, participants who were led to view willpower as non-limited showed greater sustained learning over the full duration of the task. These findings highlight the interactive nature of motivational and cognitive processes: motivational factors can substantially affect people's ability to recruit their cognitive resources to sustain learning over time.

  3. Theories of willpower affect sustained learning.

    Science.gov (United States)

    Miller, Eric M; Walton, Gregory M; Dweck, Carol S; Job, Veronika; Trzesniewski, Kali H; McClure, Samuel M

    2012-01-01

    Building cognitive abilities often requires sustained engagement with effortful tasks. We demonstrate that beliefs about willpower-whether willpower is viewed as a limited or non-limited resource-impact sustained learning on a strenuous mental task. As predicted, beliefs about willpower did not affect accuracy or improvement during the initial phases of learning; however, participants who were led to view willpower as non-limited showed greater sustained learning over the full duration of the task. These findings highlight the interactive nature of motivational and cognitive processes: motivational factors can substantially affect people's ability to recruit their cognitive resources to sustain learning over time.

  4. 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.

  5. 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.

  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. 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…

  8. 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…

  9. 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,…

  10. 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

  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. 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.

  13. 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…

  14. 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…

  15. 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…

  16. 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)

  17. Juggling with Language Learning Theories. [Videotape

    Science.gov (United States)

    Murphey, Tim

    2005-01-01

    Learning to juggle has become popular among corporate training programs because it shows participants how to appreciate mistakes and use "Intelligent Fast Failure" (learning quickly by daring to make a lot of simple mistakes at the beginning of a process). Big business also likes the way juggling can get executives "out of the…

  18. 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...

  19. 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

  20. 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

  1. 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...

  2. 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.

  3. 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...

  4. 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…

  5. 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…

  6. 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.

  7. 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…

  8. 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…

  9. 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.

  10. 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.…

  11. 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…

  12. 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…

  13. 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…

  14. 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…

  15. 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.

  16. Adventure Learning: Theory and Implementation of Hybrid Learning

    Science.gov (United States)

    Doering, A.

    2008-12-01

    Adventure Learning (AL), a hybrid distance education approach, provides students and teachers with the opportunity to learn about authentic curricular content areas while interacting with adventurers, students, and content experts at various locations throughout the world within an online learning environment (Doering, 2006). An AL curriculum and online environment provides collaborative community spaces where traditional hierarchical classroom roles are blurred and learning is transformed. AL has most recently become popular in K-12 classrooms nationally and internationally with millions of students participating online. However, in the literature, the term "adventure learning" many times gets confused with phrases such as "virtual fieldtrip" and activities where someone "exploring" is posting photos and text. This type of "adventure learning" is not "Adventure Learning" (AL), but merely a slideshow of their activities. The learning environment may not have any curricular and/or social goals, and if it does, the environment design many times does not support these objectives. AL, on the other hand, is designed so that both teachers and students understand that their online and curriculum activities are in synch and supportive of the curricular goals. In AL environments, there are no disparate activities as the design considers the educational, social, and technological affordances (Kirschner, Strijbos, Kreijns, & Beers, 2004); in other words, the artifacts of the learning environment encourage and support the instructional goals, social interactions, collaborative efforts, and ultimately learning. AL is grounded in two major theoretical approaches to learning - experiential and inquiry-based learning. As Kolb (1984) noted, in experiential learning, a learner creates meaning from direct experiences and reflections. Such is the goal of AL within the classroom. Additionally, AL affords learners a real-time authentic online learning experience concurrently as they

  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. 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)

  19. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-26

    RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp.

  20. Implications of Information Theory for Computational Modeling of Schizophrenia.

    Science.gov (United States)

    Silverstein, Steven M; Wibral, Michael; Phillips, William A

    2017-10-01

    Information theory provides a formal framework within which information processing and its disorders can be described. However, information theory has rarely been applied to modeling aspects of the cognitive neuroscience of schizophrenia. The goal of this article is to highlight the benefits of an approach based on information theory, including its recent extensions, for understanding several disrupted neural goal functions as well as related cognitive and symptomatic phenomena in schizophrenia. We begin by demonstrating that foundational concepts from information theory-such as Shannon information, entropy, data compression, block coding, and strategies to increase the signal-to-noise ratio-can be used to provide novel understandings of cognitive impairments in schizophrenia and metrics to evaluate their integrity. We then describe more recent developments in information theory, including the concepts of infomax, coherent infomax, and coding with synergy, to demonstrate how these can be used to develop computational models of schizophrenia-related failures in the tuning of sensory neurons, gain control, perceptual organization, thought organization, selective attention, context processing, predictive coding, and cognitive control. Throughout, we demonstrate how disordered mechanisms may explain both perceptual/cognitive changes and symptom emergence in schizophrenia. Finally, we demonstrate that there is consistency between some information-theoretic concepts and recent discoveries in neurobiology, especially involving the existence of distinct sites for the accumulation of driving input and contextual information prior to their interaction. This convergence can be used to guide future theory, experiment, and treatment development.

  1. 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.

  2. An Intelligent Computer Assisted Language Learning System for Arabic Learners

    Science.gov (United States)

    Shaalan, Khaled F.

    2005-01-01

    This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning…

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Regression modeling methods, theory, and computation with SAS

    CERN Document Server

    Panik, Michael

    2009-01-01

    Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

  10. 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.

  11. Teaching Density Functional Theory Through Experiential Learning

    International Nuclear Information System (INIS)

    Narasimhan, Shobhana

    2015-01-01

    Today, quantum mechanical density functional theory is often the method of choice for performing accurate calculations on atomic, molecular and condensed matter systems. Here, I share some of my experiences in teaching the necessary basics of solid state physics, as well as the theory and practice of density functional theory, in a number of workshops held in developing countries over the past two decades. I discuss the advantages of supplementing the usual mathematically formal teaching methods, characteristic of graduate courses, with the use of visual imagery and analogies. I also describe a successful experiment we carried out, which resulted in a joint publication co-authored by 67 lecturers and students participating in a summer school. (paper)

  12. The Social Life of Learning Theory

    DEFF Research Database (Denmark)

    Ratner, Helene Gad

    2013-01-01

    There is a growing understanding that public institutions need to be proactive in not only developing their welfare services but doing so continually through various concepts of learning. This article presents an ethnographic study of a public school that aims at working strategically...... with organizational learning through Donald Schön's concept of “the reflective practitioner.” Schön's concepts provide the school manager with a vocabulary to criticize the destructive effects of New Public Management's linear steering technologies. The study also illustrates that expectations of reflective...

  13. 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.

  14. 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.

  15. Schoenfeld's problem solving theory in a student controlled learning environment

    NARCIS (Netherlands)

    Harskamp, E.; Suhre, C.

    2007-01-01

    This paper evaluates the effectiveness of a student controlled computer program for high school mathematics based on instruction principles derived from Schoenfeld's theory of problem solving. The computer program allows students to choose problems and to make use of hints during different episodes

  16. 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.

  17. 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.

  18. Transformative Learning Theory in Gerontology: Nontraditional Students

    Science.gov (United States)

    Brown, Pamela Pitman; Brown, Candace S.

    2015-01-01

    Mezirow (1978) applied and used Transformative Learning Theoretical (TLT) processes while studying women who reentered academics during the 1970s. Similar to Mezirow's original 1975 work, we identify "factors that impeded or facilitated" participants' progress to obtain their undergraduate degree during the traditional student…

  19. The Social Life of Learning Theory

    DEFF Research Database (Denmark)

    Ratner, Helene Gad

    2013-01-01

    with organizational learning through Donald Schön's concept of “the reflective practitioner.” Schön's concepts provide the school manager with a vocabulary to criticize the destructive effects of New Public Management's linear steering technologies. The study also illustrates that expectations of reflective...

  20. Contemporary Privacy Theory Contributions to Learning Analytics

    Science.gov (United States)

    Heath, Jennifer

    2014-01-01

    With the continued adoption of learning analytics in higher education institutions, vast volumes of data are generated and "big data" related issues, including privacy, emerge. Privacy is an ill-defined concept and subject to various interpretations and perspectives, including those of philosophers, lawyers, and information systems…

  1. 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.

  2. 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

  3. 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.

  4. 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…

  5. Singular problems in shell theory. Computing and asymptotics

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez-Palencia, Evariste [Institut Jean Le Rond d' Alembert, Paris (France); Millet, Olivier [La Rochelle Univ. (France). LEPTIAB; Bechet, Fabien [Metz Univ. (France). LPMM

    2010-07-01

    It is known that deformations of thin shells exhibit peculiarities such as propagation of singularities, edge and internal layers, piecewise quasi inextensional deformations, sensitive problems and others, leading in most cases to numerical locking phenomena under several forms, and very poor quality of computations for small relative thickness. Most of these phenomena have a local and often anisotropic character (elongated in some directions), so that efficient numerical schemes should take them in consideration. This book deals with various topics in this context: general geometric formalism, analysis of singularities, numerical computing of thin shell problems, estimates for finite element approximation (including non-uniform and anisotropic meshes), mathematical considerations on boundary value problems in connection with sensitive problems encountered for very thin shells; and others. Most of numerical computations presented here use an adaptive anisotropic mesh procedure which allows a good computation of the physical peculiarities on one hand, and the possibility to perform automatic computations (without a previous mathematical description of the singularities) on the other. The book is recommended for PhD students, postgraduates and researchers who want to improve their knowledge in shell theory and in particular in the areas addressed (analysis of singularities, numerical computing of thin and very thin shell problems, sensitive problems). The lecture of the book may not be continuous and the reader may refer directly to the chapters concerned. (orig.)

  6. 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

  7. 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.

  8. 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…

  9. 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,…

  10. Computational intelligence for technology enhanced learning

    Energy Technology Data Exchange (ETDEWEB)

    Xhafa, Fatos [Polytechnic Univ. of Catalonia, Barcelona (Spain). Dept. of Languages and Informatics Systems; Caballe, Santi; Daradoumis, Thanasis [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Computer Sciences Multimedia and Telecommunications; Abraham, Ajith [Machine Intelligence Research Labs (MIR Labs), Auburn, WA (United States). Scientific Network for Innovation and Research Excellence; Juan Perez, Angel Alejandro (eds.) [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Information Sciences

    2010-07-01

    E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners' performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity. (orig.)

  11. Computerized adaptive testing in computer assisted learning?

    NARCIS (Netherlands)

    Veldkamp, Bernard P.; Matteucci, Mariagiulia; Eggen, Theodorus Johannes Hendrikus Maria; De Wannemacker, Stefan; Clarebout, Geraldine; De Causmaecker, Patrick

    2011-01-01

    A major goal in computerized learning systems is to optimize learning, while in computerized adaptive tests (CAT) efficient measurement of the proficiency of students is the main focus. There seems to be a common interest to integrate computerized adaptive item selection in learning systems and

  12. 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...

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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...

  18. 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…

  19. Decision theory, reinforcement learning, and the brain.

    Science.gov (United States)

    Dayan, Peter; Daw, Nathaniel D

    2008-12-01

    Decision making is a core competence for animals and humans acting and surviving in environments they only partially comprehend, gaining rewards and punishments for their troubles. Decision-theoretic concepts permeate experiments and computational models in ethology, psychology, and neuroscience. Here, we review a well-known, coherent Bayesian approach to decision making, showing how it unifies issues in Markovian decision problems, signal detection psychophysics, sequential sampling, and optimal exploration and discuss paradigmatic psychological and neural examples of each problem. We discuss computational issues concerning what subjects know about their task and how ambitious they are in seeking optimal solutions; we address algorithmic topics concerning model-based and model-free methods for making choices; and we highlight key aspects of the neural implementation of decision making.

  20. 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.

  1. 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

  2. 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...

  3. Competences, Learning Theories and MOOCs: Recent Developments in Lifelong Learning

    Science.gov (United States)

    Steffens, Karl

    2015-01-01

    Our societies have come to be known as knowledge societies in which lifelong learning is becoming increasingly important. In this context, competences have become a much discussed topic. Many documents were published by international organisations (UNESCO, World Bank, European Commission) which enumerated 21st century key competences. The field of…

  4. Perceptual learning: toward a comprehensive theory.

    Science.gov (United States)

    Watanabe, Takeo; Sasaki, Yuka

    2015-01-03

    Visual perceptual learning (VPL) is long-term performance increase resulting from visual perceptual experience. Task-relevant VPL of a feature results from training of a task on the feature relevant to the task. Task-irrelevant VPL arises as a result of exposure to the feature irrelevant to the trained task. At least two serious problems exist. First, there is the controversy over which stage of information processing is changed in association with task-relevant VPL. Second, no model has ever explained both task-relevant and task-irrelevant VPL. Here we propose a dual plasticity model in which feature-based plasticity is a change in a representation of the learned feature, and task-based plasticity is a change in processing of the trained task. Although the two types of plasticity underlie task-relevant VPL, only feature-based plasticity underlies task-irrelevant VPL. This model provides a new comprehensive framework in which apparently contradictory results could be explained.

  5. Computer Access and Flowcharting as Variables in Learning Computer Programming.

    Science.gov (United States)

    Ross, Steven M.; McCormick, Deborah

    Manipulation of flowcharting was crossed with in-class computer access to examine flowcharting effects in the traditional lecture/laboratory setting and in a classroom setting where online time was replaced with manual simulation. Seventy-two high school students (24 male and 48 female) enrolled in a computer literacy course served as subjects.…

  6. 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.

  7. A Grounded Theory Analysis of Introductory Computer Science Pedagogy

    Directory of Open Access Journals (Sweden)

    Jonathan Wellons

    2011-12-01

    Full Text Available Planning is a critical, early step on the path to successful program writing and a skill that is often lacking in novice programmers. As practitioners we are continually searching for or creating interventions to help our students, particularly those who struggle in the early stages of their computer science education. In this paper we report on our ongoing research of novice programming skills that utilizes the qualitative research method of grounded theory to develop theories and inform the construction of these interventions. We describe how grounded theory, a popular research method in the social sciences since the 1960’s, can lend formality and structure to the common practice of simply asking students what they did and why they did it. Further, we aim to inform the reader not only about our emerging theories on interventions for planning but also how they might collect and analyze their own data in this and other areas that trouble novice programmers. In this way those who lecture and design CS1 interventions can do so from a more informed perspective.

  8. Providing Learning Computing Labs using Hosting and Virtualization Technologies

    Directory of Open Access Journals (Sweden)

    Armide González

    2011-05-01

    Full Text Available This paper presents a computing hosting system to provide virtual computing laboratories for learning activities. This system is based on hosting and virtualization technologies. All the components used in its development are free software tools. The computing lab model provided by the system is a more sustainable and scalable alternative than the traditional academic computing lab, and it requires lower costs of installation and operation.

  9. 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.

  10. Constructivist Teaching/Learning Theory and Participatory Teaching Methods

    Science.gov (United States)

    Fernando, Sithara Y. J. N.; Marikar, Faiz M. M. T.

    2017-01-01

    Evidence for the teaching involves transmission of knowledge, superiority of guided transmission is explained in the context of our knowledge, but it is also much more that. In this study we have examined General Sir John Kotelawala Defence University's cadet and civilian students' response to constructivist learning theory and participatory…

  11. 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…

  12. Writing for publication: faculty development initiative using social learning theory.

    Science.gov (United States)

    Sanderson, Bonnie K; Carter, Matt; Schuessler, Jenny B

    2012-01-01

    Demonstrating scholarly competency is an expectation for nurse faculty. However, there is hesitancy among some faculty to fully engage in scholarly activities. To strengthen a school of nursing's culture of scholarship, a faculty development writing initiative based on Social Learning Theory was implemented. The authors discuss this initiative to facilitate writing for publication productivity among faculty and the successful outcomes.

  13. Social Learning Theory: A Vanishing or Expanding Presence?

    Science.gov (United States)

    Stuart, Richard B.

    1989-01-01

    Reviews history and current status of social learning theory (SLT) including present conflict between "cognitive behaviorists" within the movement. Makes suggestions on how to resolve conflict in a way that will further secure the future role of SLT. Offers prescription for adoption of a multifaceted "indirect" approach to…

  14. Adult Basic Skills Instructor Training and Experiential Learning Theory.

    Science.gov (United States)

    Marlowe, Mike; And Others

    1991-01-01

    Competency-based training workshops based on Kolb's experiential learning theory were held for North Carolina adult basic education teachers; 251 attended 1-day sessions and 91 a week-long summer institute. Topics included interpersonal communication, reading, numeracy, language arts, math, assessment, and program evaluation. (SK)

  15. Gestalt-A Learning Theory for Graphic Design Education

    Science.gov (United States)

    Jackson, Ian

    2008-01-01

    This article will begin by seeking to define the notion of learning "by, through" and "from" experience. A linkage will then be established between these notions of experiences and gestalt theory. This will be explored within a subject specific context of graphic design. Links will be highlighted between the inherent nature of graphic design and…

  16. The Interdependence of Pedagogy, Learning Theory, Morality and Metaphysics.

    Science.gov (United States)

    Blunden, Ralph

    1997-01-01

    Explores the incompatibility between constructivist theories of learning and realist metaphysics (belief that knowledge and skills exist in mind-independent workplace practices). Shows how this results in conflict between constructivist teaching approaches and the transmission or banking mode favored by realist metaphysics. (SK)

  17. A Lifespan Perspective on Cooperative Education Learning: A Grounded Theory

    Science.gov (United States)

    Linn, Patricia

    2015-01-01

    This qualitative study sits at the intersection of two trends in vocational education. The first trend is a narrative approach to understanding cooperative education learning; the second is a movement away from career development theories toward the view that individuals use work experiences to help construct their lives. Both trends view learning…

  18. Children balance theories and evidence in exploration, explanation, and learning

    NARCIS (Netherlands)

    Bonawitz, E.B.; van Schijndel, T.J.P.; Friel, D.; Schulz, L.

    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,

  19. 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…

  20. 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.

  1. Amidst Multiple Theories of Learning in Mathematics Education

    Science.gov (United States)

    Simon, Martin A.

    2009-01-01

    Currently, there are more theories of learning in use in mathematics education research than ever before (Lerman & Tsatsaroni, 2004). Although this is a positive sign for the field, it also has brought with it a set of challenges. In this article, I identify some of these challenges and consider how mathematics education researchers might think…

  2. Conversations, Individuals and Knowables: Toward a Theory of Learning

    Science.gov (United States)

    Daniel, John S.

    1975-01-01

    Presents a learning theory in the language of cybernetics based on the tenet that the minimal experimental situation for making psychological observations is a conversation. The account is directed at generating interest in the original work by G. Pask, et al. (GS)

  3. Learning and Emotion: Perspectives for Theory and Research

    Science.gov (United States)

    Hascher, Tina

    2010-01-01

    There is growing interest in and knowledge about the interplay of learning and emotion. However, the different approaches and empirical studies correspond to each other only to a low extent. To prevent this research field from increasing fragmentation, a shared basis of theory and research is needed. The presentation aims at giving an overview of…

  4. Quantum field theory and coalgebraic logic in theoretical computer science.

    Science.gov (United States)

    Basti, Gianfranco; Capolupo, Antonio; Vitiello, Giuseppe

    2017-11-01

    We suggest that in the framework of the Category Theory it is possible to demonstrate the mathematical and logical dual equivalence between the category of the q-deformed Hopf Coalgebras and the category of the q-deformed Hopf Algebras in quantum field theory (QFT), interpreted as a thermal field theory. Each pair algebra-coalgebra characterizes a QFT system and its mirroring thermal bath, respectively, so to model dissipative quantum systems in far-from-equilibrium conditions, with an evident significance also for biological sciences. Our study is in fact inspired by applications to neuroscience where the brain memory capacity, for instance, has been modeled by using the QFT unitarily inequivalent representations. The q-deformed Hopf Coalgebras and the q-deformed Hopf Algebras constitute two dual categories because characterized by the same functor T, related with the Bogoliubov transform, and by its contravariant application T op , respectively. The q-deformation parameter is related to the Bogoliubov angle, and it is effectively a thermal parameter. Therefore, the different values of q identify univocally, and label the vacua appearing in the foliation process of the quantum vacuum. This means that, in the framework of Universal Coalgebra, as general theory of dynamic and computing systems ("labelled state-transition systems"), the so labelled infinitely many quantum vacua can be interpreted as the Final Coalgebra of an "Infinite State Black-Box Machine". All this opens the way to the possibility of designing a new class of universal quantum computing architectures based on this coalgebraic QFT formulation, as its ability of naturally generating a Fibonacci progression demonstrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. 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.

  6. Computer-mediated interdisciplinary teams: theory and reality.

    Science.gov (United States)

    Vroman, Kerryellen; Kovacich, Joann

    2002-05-01

    The benefit of experience, tempered with the wisdom of hindsight and 5 years of text-based, asynchronous, computer-mediated, interdisciplinary team communications, provides the energy, insights and data shared in this article. Through the theoretical lens of group dynamics and the epistemology of interdisciplinary teaming, we analyze the interactions of a virtual interdisciplinary team to provide an understanding and appreciation of collaborative interdisciplinary communication in the context of interactive technologies. Whilst interactive technologies may require new patterns of language similar to that of learning a foreign language, what is communicated in the interdisciplinary team process does not change. Most important is the recognition that virtual teams, similar to their face-to-face counterparts, undergo the same challenges of interdisciplinary teaming and group developmental processes of formation: forming, storming, norming, performing, and transforming. After examining these dynamics of communication and collaboration in the context of the virtual team, the article concludes with guidelines facilitating interdisciplinary team computer-mediated communication.

  7. National Computational Infrastructure for Lattice Gauge Theory: Final Report

    International Nuclear Information System (INIS)

    Richard Brower; Norman Christ; Michael Creutz; Paul Mackenzie; John Negele; Claudio Rebbi; David Richards; Stephen Sharpe; Robert Sugar

    2006-01-01

    This is the final report of Department of Energy SciDAC Grant ''National Computational Infrastructure for Lattice Gauge Theory''. It describes the software developed under this grant, which enables the effective use of a wide variety of supercomputers for the study of lattice quantum chromodynamics (lattice QCD). It also describes the research on and development of commodity clusters optimized for the study of QCD. Finally, it provides some high lights of research enabled by the infrastructure created under this grant, as well as a full list of the papers resulting from research that made use of this infrastructure

  8. 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.

  9. 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…

  10. Control of magnetotransport in quantum billiards theory, computation and applications

    CERN Document Server

    Morfonios, Christian V

    2017-01-01

    In this book the coherent quantum transport of electrons through two-dimensional mesoscopic structures is explored in dependence of the interplay between the confining geometry and the impact of applied magnetic fields, aiming at conductance controllability. After a top-down, insightful presentation of the elements of mesoscopic devices and transport theory, a computational technique which treats multiterminal structures of arbitrary geometry and topology is developed. The method relies on the modular assembly of the electronic propagators of subsystems which are inter- or intra-connected providing large flexibility in system setups combined with high computational efficiency. Conductance control is first demonstrated for elongated quantum billiards and arrays thereof where a weak magnetic field tunes the current by phase modulation of interfering lead-coupled states geometrically separated from confined states. Soft-wall potentials are then employed for efficient and robust conductance switching by isolating...

  11. Novel theory of the HD dipole moment. II. Computations

    International Nuclear Information System (INIS)

    Thorson, W.R.; Choi, J.H.; Knudson, S.K.

    1985-01-01

    In the preceding paper we derived a new theory of the dipole moments of homopolar but isotopically asymmetric molecules (such as HD, HT, and DT) in which the electrical asymmetry appears directly in the electronic Hamiltonian (in an appropriate Born-Oppenheimer separation) and the dipole moment may be computed as a purely electronic property. In the present paper we describe variation-perturbation calculations and convergence studies on the dipole moment for HD, which is found to have the value 8.51 x 10 -4 debye at 1.40 a.u. Using the two alternative formulations of the electronic problem, we can provide a test of basis-set adequacy and convergence of the results, and such convergence studies are reported here. We have also computed vibration-rotation transition matrix elements and these are compared with experimental and other theoretical results

  12. 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…

  13. 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…

  14. Mobile human-computer interaction perspective on mobile learning

    CSIR Research Space (South Africa)

    Botha, Adèle

    2010-10-01

    Full Text Available Applying a Mobile Human Computer Interaction (MHCI) view to the domain of education using Mobile Learning (Mlearning), the research outlines its understanding of the influences and effects of different interactions on the use of mobile technology...

  15. 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

  16. COMPUTER LEARNING SIMULATOR WITH VIRTUAL REALITY FOR OPHTHALMOLOGY

    Directory of Open Access Journals (Sweden)

    Valeria V. Gribova

    2013-01-01

    Full Text Available A toolset of a medical computer learning simulator for ophthalmology with virtual reality and its implementation are considered in the paper. The simulator is oriented for professional skills training for students of medical universities. 

  17. 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.

  18. 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.

  19. 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.

  20. 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…

  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. 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 ...

  3. 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.

  4. 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…

  5. Evaluating the Effectiveness of Computer Applications in Developing English Learning

    Science.gov (United States)

    Whitaker, James Todd

    2016-01-01

    I examined the effectiveness of self-directed learning and English learning with computer applications on college students in Bangkok, Thailand, in a control-group experimental-group pretest-posttest design. The hypothesis was tested using a t test: two-sample assuming unequal variances to establish the significance of mean scores between the two…

  6. 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…

  7. 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.

  8. 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…

  9. 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,…

  10. 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.

  11. What propels sexual murderers: a proposed integrated theory of social learning and routine activities theories.

    Science.gov (United States)

    Chan, Heng Choon Oliver; Heide, Kathleen M; Beauregard, Eric

    2011-04-01

    Despite the great interest in the study of sexual homicide, little is known about the processes involved in an individual's becoming motivated to sexually kill, deciding to sexually kill, and acting on that desire, intention, and opportunity. To date, no comprehensive model of sexual murdering from the offending perspective has been proposed in the criminological literature. This article incorporates the works of Akers and Cohen and Felson regarding their social learning theory and routine activities theory, respectively, to construct an integrated conceptual offending framework in sexual homicide. This integrated model produces a stronger and more comprehensive explanation of sexual murder than any single theory currently available.

  12. 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,…

  13. 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.

  14. 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.

  15. A computational theory of the hippocampal cognitive map.

    Science.gov (United States)

    O'Keefe, J

    1990-01-01

    Evidence from single unit and lesion studies suggests that the hippocampal formation acts as a spatial or cognitive map (O'Keefe and Nadel, 1978). In this chapter, I summarise some of the unit recording data and then outline the most recent computational version of the cognitive map theory. The novel aspects of the present version of the theory are that it identifies two allocentric parameters, the centroid and the eccentricity, which can be calculated from the array of cues in an environment and which can serve as the bases for an allocentric polar co-ordinate system. Computations within this framework enable the animal to identify its location within an environment, to predict the location which will be reached as a result of any specific movement from that location, and conversely, to calculate the spatial transformation necessary to go from the current location to a desired location. Aspects of the model are identified with the information provided by cells in the hippocampus and dorsal presubiculum. The hippocampal place cells are involved in the calculation of the centroid and the presubicular direction cells in the calculation of the eccentricity.

  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. Gaming mindsets: implicit theories in serious game learning.

    Science.gov (United States)

    Lee, Yu-Hao; Heeter, Carrie; Magerko, Brian; Medler, Ben

    2012-04-01

    Individuals' beliefs about the malleability of their abilities may predict their response and outcome in learning from serious games. Individuals with growth mindsets believe their abilities can develop with practice and effort, whereas individuals with fixed mindsets believe their abilities are static and cannot improve. This study uses survey and gameplay server data to examine the implicit theory of intelligence in the context of serious game learning. The findings show that growth mindset players performed better than fixed mindset players, their mistakes did not affect their attention to the game, and they read more learning feedback than fixed mindset players. In addition, growth mindset players were more likely to actively seek difficult challenges, which is often essential to self-directed learning. General mindset measurements and domain-specific measurements were also compared. These findings suggest that players' psychological attributes should be considered when designing and applying serious games.

  18. 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…

  19. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-01

    In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information

  20. DIALOGIC LEARNING AND ITS CONTRIBUTIONS TO EDUCATIONAL THEORY

    Directory of Open Access Journals (Sweden)

    Óscar Prieto

    2009-11-01

    Full Text Available This article highlights the contributions of the dialogic learning approach toeducational theory, with the aim of providing some orientations in order to promoteegalitarian and scientific educational practice. The seven principles of dialogic learningare discussed, along with other reproductionist theories and practices from the educationalfield, demonstrating how the former both surpass the latter. The article also reflectsopen dialogue with the critical theories of education which the dialogic learningtheory is based on. These basic theories are, on the one hand, by authors who are distantin time but very close in their educational approach, such as Ferrer i Guàrdia, Vygotsky,or Paulo Freire, and, on the other hand, by other contemporary authors in critical pedagogy.Each of the seven principles presented are provided along with a critical examinationof a specific educational practice. The consequences of the implementation of dialogiclearning are underlined here through an analysis of innovative and critical educationalprojects which are academically successful.

  1. 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…

  2. 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....

  3. 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'…

  4. 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.

  5. Learning Disabilities and the Auditory and Visual Matching Computer Program

    Science.gov (United States)

    Tormanen, Minna R. K.; Takala, Marjatta; Sajaniemi, Nina

    2008-01-01

    This study examined whether audiovisual computer training without linguistic material had a remedial effect on different learning disabilities, like dyslexia and ADD (Attention Deficit Disorder). This study applied a pre-test-intervention-post-test design with students (N = 62) between the ages of 7 and 19. The computer training lasted eight weeks…

  6. 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 ...

  7. The visual simulators for architecture and computer organization learning

    OpenAIRE

    Nikolić Boško; Grbanović Nenad; Đorđević Jovan

    2009-01-01

    The paper proposes a method of an effective distance learning of architecture and computer organization. The proposed method is based on a software system that is possible to be applied in any course in this field. Within this system students are enabled to observe simulation of already created computer systems. The system provides creation and simulation of switch systems, too.

  8. 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

  9. A Computer-Aided Writing Program for Learning Disabled Adolescents.

    Science.gov (United States)

    Fais, Laurie; Wanderman, Richard

    The paper describes the application of a computer-assisted writing program in a special high school for learning disabled and dyslexic students and reports on a study of the program's effectiveness. Particular advantages of the Macintosh Computer for such a program are identified including use of the mouse pointing tool, graphic icons to identify…

  10. 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...

  11. 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.

  12. 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 ...

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. A Peer-Assisted Learning Experience in Computer Programming Language Learning and Developing Computer Programming Skills

    Science.gov (United States)

    Altintas, Tugba; Gunes, Ali; Sayan, Hamiyet

    2016-01-01

    Peer learning or, as commonly expressed, peer-assisted learning (PAL) involves school students who actively assist others to learn and in turn benefit from an effective learning environment. This research was designed to support students in becoming more autonomous in their learning, help them enhance their confidence level in tackling computer…

  18. 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…

  19. 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.

  20. 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...

  1. Theory-generating practice. Proposing a principle for learning design

    DEFF Research Database (Denmark)

    Buhl, Mie

    2016-01-01

    This contribution proposes a principle for learning design – Theory-Generating Practice (TGP) – as an alternative to the way university courses are traditionally taught and structured, with a series of theoretical lectures isolated from practical experience and concluding with an exam or a project...... building, and takes tacit knowledge into account. The article introduces TGP, contextualizes it to a Danish tradition of didactics, and discusses it in relation to contemporary conceptual currents of didactic design and learning design. This is followed by a theoretical framing of TGP. Finally, three...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Structured brain computing and its learning

    International Nuclear Information System (INIS)

    Ae, Tadashi; Araki, Hiroyuki; Sakai, Keiichi

    1999-01-01

    We have proposed a two-level architecture for brain computing, where two levels are introduced for processing of meta-symbol. At level 1 a conventional pattern recognition is performed, where neural computation is included, and its output gives the meta-symbol which is a symbol enlarged from a symbol to a kind of pattern. At Level 2 an algorithm acquisition is made by using a machine for abstract states. We are also developing the VLSI chips at each level for SBC (Structured Brain Computer) Ver.1.0

  10. 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…

  11. 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

  12. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-01

    -transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three

  13. GRG computer algebra system in gravitation and general relativity theory

    International Nuclear Information System (INIS)

    Zhitnikov, V.V.; Obukhova, I.G.

    1985-01-01

    The main concepts and capabilities of the GRG specialized computer agebra system intended for performing calculations in the gravitation theory are described. The GRG system is written in the STANDARD LISP language. The program consists of two parts: the first one - for setting initial data, the second one - for specifying a consequence of calculations. The system can function in three formalisms: a coordinate, a tetradic with the Lorentz basis and a spinor ones. The major capabilities of the GRG system are the following: calculation of connectivity and curvature according to the specified metrics, tetrad and torsion; metric type determination according to Petrov; calculation of the Bianchi indentities; operation with an electromagnetic field; tetradic rotations; coordinate conversions

  14. Statistical physics and computational methods for evolutionary game theory

    CERN Document Server

    Javarone, Marco Alberto

    2018-01-01

    This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems. Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algor...

  15. Tutorial Computer-Assisted Language Learning

    Science.gov (United States)

    Heift, Trude; Schulze, Mathias

    2015-01-01

    "Sometimes maligned for its allegedly behaviorist connotations but critical for success in many fields from music to sport to mathematics and language learning, 'practice' is undergoing something of a revival in the applied linguistics literature" (Long & Richards 2007, p. xi). This research timeline provides a systematic overview of…

  16. UNIVERSITY TEACHING-LEARNING PROCESS: REFLECTIONS THROUGHOUT THE AGENCY THEORY

    Directory of Open Access Journals (Sweden)

    Víctor Jacques Parraguez

    2011-04-01

    Full Text Available This work analyses some reasons that might explain the insufficient academic level which is perceived in universities of developing countries. The discussion element is the teacher-student relationship which is studied under the perspective of the agency theory. It is concluded that in absence of efficient monitoring mechanisms of the teacher and student’s behavior might proliferate gaps of due diligence which attempts against the quality of the teaching-learning process.

  17. 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.

  18. Theory-Generating Practice: Proposing a principle for learning design

    Directory of Open Access Journals (Sweden)

    Mie Buhl

    2016-06-01

    Full Text Available This contribution proposes a principle for learning design: Theory-Generating Practice (TGP as an alternative to the way university courses often are taught and structured with a series of theoretical lectures separate from practical experience and concluding with an exam or a project. The aim is to contribute to a development of theoretical frameworks for learning designs by suggesting TGP which may lead to new practices and turn the traditional dramaturgy for teaching upside down. TGP focuses on embodied experience prior to text reading and lectures to enhance theoretical knowledge building and takes tacit knowledge into account. The article introduces TGP and contextualizes it to a Danish tradition of didactics as well as discusses it in relation to contemporary conceptual currents of didactic design and learning design. This is followed by a theoretical framing of TGP, and is discussed through three empirical examples from bachelor and master programs involving technology, and showing three ways of practicing it.

  19. Theory-Generating Practice: Proposing a principle for learning design

    Directory of Open Access Journals (Sweden)

    Mie Buhl

    2016-05-01

    Full Text Available This contribution proposes a principle for learning design: Theory-Generating Practice (TGP as an alternative to the way university courses often are taught and structured with a series of theoretical lectures separate from practical experience and concluding with an exam or a project. The aim is to contribute to a development of theoretical frameworks for learning designs by suggesting TGP which may lead to new practices and turn the traditional dramaturgy for teaching upside down. TGP focuses on embodied experience prior to text reading and lectures to enhance theoretical knowledge building and takes tacit knowledge into account. The article introduces TGP and contextualizes it to a Danish tradition of didactics as well as discusses it in relation to contemporary conceptual currents of didactic design and learning design. This is followed by a theoretical framing of TGP, and is discussed through three empirical examples from bachelor and master programs involving technology, and showing three ways of practicing it.

  20. 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...

  1. National Computational Infrastructure for Lattice Gauge Theory: Final report

    International Nuclear Information System (INIS)

    Reed, Daniel A.

    2008-01-01

    In this document we describe work done under the SciDAC-1 Project National Computerational Infrastructure for Lattice Gauge Theory. The objective of this project was to construct the computational infrastructure needed to study quantum chromodynamics (QCD). Nearly all high energy and nuclear physicists in the United States working on the numerical study of QCD are involved in the project, as are Brookhaven National Laboratory (BNL), Fermi National Accelerator Laboratory (FNAL), and Thomas Jefferson National Accelerator Facility (JLab). A list of the senior participants is given in Appendix A.2. The project includes the development of community software for the effective use of the terascale computers, and the research and development of commodity clusters optimized for the study of QCD. The software developed as part of this effort is publicly available, and is being widely used by physicists in the United States and abroad. The prototype clusters built with SciDAC-1 fund have been used to test the software, and are available to lattice gauge theorists in the United States on a peer reviewed basis

  2. Learning Analytics: The next frontier for computer assisted language learning in big data age

    Directory of Open Access Journals (Sweden)

    Yu Qinglan

    2015-01-01

    Full Text Available Learning analytics (LA has been applied to various learning environments, though it is quite new in the field of computer assisted language learning (CALL. This article attempts to examine the application of learning analytics in the upcoming big data age. It starts with an introduction and application of learning analytics in other fields, followed by a retrospective review of historical interaction between learning and media in CALL, and a penetrating analysis on why people would go to learning analytics to increase the efficiency of foreign language education. As approved in previous research, new technology, including big data mining and analysis, would inevitably enhance the learning of foreign languages. Potential changes that learning analytics would bring to Chinese foreign language education and researches are also presented in the article.

  3. Computational Modeling of Statistical Learning: Effects of Transitional Probability versus Frequency and Links to Word Learning

    Science.gov (United States)

    Mirman, Daniel; Estes, Katharine Graf; Magnuson, James S.

    2010-01-01

    Statistical learning mechanisms play an important role in theories of language acquisition and processing. Recurrent neural network models have provided important insights into how these mechanisms might operate. We examined whether such networks capture two key findings in human statistical learning. In Simulation 1, a simple recurrent network…

  4. Editorial - Keeping the Learning in Computer-Based Learning

    Directory of Open Access Journals (Sweden)

    William Kilbride

    2002-09-01

    Full Text Available Political rhetoric about knowledge economies and learning societies really ought to be an educationalist's dream. Add to that the revolutionary power of electronic media, and an insatiable hunger for archaeology among the public, archaeology teaching should be well placed to flourish. In England, the Department for Culture Media and Sport has just closed its call for interest in the multi-million pound Culture Online programme. The New Opportunities Fund has already spent fifty million pounds on digitisation alone, while the Heritage Lottery Fund is encouraging heritage agencies to distribute their data sets online. The JISC continues to expand its information environment, investing most recently in virtual learning environments. In Europe, the 6th Framework promises a single European Research Area, and grid technologies allow high quantities of data to empower an information society - supported by the millions of euros already invested in 'e-content'. All of these programmes, and many many more, provide openings for archaeologists to invest in training, teaching and learning. How can archaeology, in particular staff and students in our educational establishments, take best advantage of this information-rich, digitally-empowered learning society?

  5. Why (we think) facilitation works: insights from organizational learning theory.

    Science.gov (United States)

    Berta, Whitney; Cranley, Lisa; Dearing, James W; Dogherty, Elizabeth J; Squires, Janet E; Estabrooks, Carole A

    2015-10-06

    Facilitation is a guided interactional process that has been popularized in health care. Its popularity arises from its potential to support uptake and application of scientific knowledge that stands to improve clinical and managerial decision-making, practice, and ultimately patient outcomes and organizational performance. While this popular concept has garnered attention in health services research, we know that both the content of facilitation and its impact on knowledge implementation vary. The basis of this variation is poorly understood, and understanding is hampered by a lack of conceptual clarity. In this paper, we argue that our understanding of facilitation and its effects is limited in part by a lack of clear theoretical grounding. We propose a theoretical home for facilitation in organizational learning theory. Referring to extant literature on facilitation and drawing on theoretical literature, we discuss the features of facilitation that suggest its role in contributing to learning capacity. We describe how facilitation may contribute to generating knowledge about the application of new scientific knowledge in health-care organizations. Facilitation's promise, we suggest, lies in its potential to stimulate higher-order learning in organizations through experimenting with, generating learning about, and sustaining small-scale adaptations to organizational processes and work routines. The varied effectiveness of facilitation observed in the literature is associated with the presence or absence of factors known to influence organizational learning, since facilitation itself appears to act as a learning mechanism. We offer propositions regarding the relationships between facilitation processes and key organizational learning concepts that have the potential to guide future work to further our understanding of the role that facilitation plays in learning and knowledge generation.

  6. Cloud Computing Based E-Learning System

    Science.gov (United States)

    Al-Zoube, Mohammed; El-Seoud, Samir Abou; Wyne, Mudasser F.

    2010-01-01

    Cloud computing technologies although in their early stages, have managed to change the way applications are going to be developed and accessed. These technologies are aimed at running applications as services over the internet on a flexible infrastructure. Microsoft office applications, such as word processing, excel spreadsheet, access database…

  7. Efficacy of Computer Games on Language Learning

    Science.gov (United States)

    Klimova, Blanka; Kacet, Jaroslav

    2017-01-01

    Information and communication technologies (ICT) have become an inseparable part of people's lives. For children the use of ICT is as natural as breathing and therefore they find the use of ICT in school education as normal as the use of textbooks. The purpose of this review study is to explore the efficacy of computer games on language learning…

  8. How Computer Games Help Children Learn

    Science.gov (United States)

    Shaffer, David Williamson

    2008-01-01

    This book looks at how particular video and computer games--such as "Digital Zoo", "The Pandora Project", "SodaConstructor", and more--can help teach children and students to think like doctors, lawyers, engineers, urban planners, journalists, and other professionals. In the process, new "smart games" will give them the knowledge and skills they…

  9. Computational Investigations of Multiword Chunks in Language Learning.

    Science.gov (United States)

    McCauley, Stewart M; Christiansen, Morten H

    2017-07-01

    Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first- versus second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks in online language processing, we explore the hypothesis that children rely more heavily on multiword units in language learning than do adults learning a second language. To this end, we take an initial step toward using large-scale, corpus-based computational modeling as a tool for exploring the granularity of speakers' linguistic units. Employing a computational model of language learning, the Chunk-Based Learner, we compare the usefulness of chunk-based knowledge in accounting for the speech of second-language learners versus children and adults speaking their first language. Our findings suggest that while multiword units are likely to play a role in second-language learning, adults may learn less useful chunks, rely on them to a lesser extent, and arrive at them through different means than children learning a first language. Copyright © 2017 Cognitive Science Society, Inc.

  10. Computational advantages of reverberating loops for sensorimotor learning.

    Science.gov (United States)

    Fortney, Kristen; Tweed, Douglas B

    2012-03-01

    When we learn something new, our brain may store the information in synapses or in reverberating loops of electrical activity, but current theories of motor learning focus almost entirely on the synapses. Here we show that loops could also play a role and would bring advantages: loop-based algorithms can learn complex control tasks faster, with exponentially fewer neurons, and avoid the problem of weight transport. They do all this at a cost: in the presence of long feedback delays, loop algorithms cannot control very fast movements, but in this case, loop and synaptic mechanisms can complement each other-mixed systems quickly learn to make accurate but not very fast motions and then gradually speed up. Loop algorithms explain aspects of consolidation, the role of attention, and the relapses that are sometimes seen after a task has apparently been learned, and they make further predictions.

  11. The Tarsoft software: A computer program to learn the elemental theory for the urban wastewater treatment; Tarsoft: programa de ordenador para el aprendizaje de la teoria basica sobre la depuracion de las aguas residuales urbanas

    Energy Technology Data Exchange (ETDEWEB)

    Parra Narvaez, R.; Baldasano Recio, J.M. [Universitat Politecnica de Catalunya. Barcelona (Spain)

    1998-12-31

    It` ve been developed a first version of the computer program Tarsoft, with the objective to be a Informatic contribution for the education and training of the knowledge about the urban wastewater treatment. This article describe in general form, the main characteristic of this computer program, the minimal hardware and software requirements, the theoretical topics than it include, the presentation form of the variety alfanumerical and graphical interactive information and design modules of the different treatment process. (Author) 20 refs.

  12. 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

  13. Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology.

    Science.gov (United States)

    Schultz, Wolfram

    2004-04-01

    Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

  14. Economics of Distance and Online Learning Theory, Practice and Research

    Directory of Open Access Journals (Sweden)

    reviewed by TOJDE

    2009-10-01

    Full Text Available Economics of Distance and Online LearningTheory, Practice and ResearchBy William Bramble & Santosh PandaPrice: $125.00ISBN: 978-0-415-96388-6, Binding: Hardback, Publishedby: Routledge, New York, Publication Date: March 2008, Pages: 312TOJDEABOUT THE BOOKThis book provides a comprehensive overview of theorganizational models of distance and online learning froman international perspective and from the point of view ofeconomic planning, costing and management decisionmaking.The book points to directions for the further research anddevelopment in this area, and will promote furtherunderstanding and critical reflection on the part ofadministrators, practitioners and researchers of distanceeducation.The experiences and perspectives in distance education inthe US are balanced with those in other areas of the world.Table of ContentsPrefaceSECTION ONE: INTRODUCTIONChapter 1: Organizational and Cost Structures for Distanceand Online Learning, William J. Bramble and Santosh PandaSECTION TWO: PLANNING AND MANAGEMENTChapter 2: Changing Distance Education andChanging Organizational Issues, D. Randy Garrison and Heather KanukaChapter 3: Online Learning and the University, Chris Curran217Chapter 4: Virtual Schooling and Basic Education, Thomas ClarkChapter 5: Historical Perspectives on Distance Education in the United States, Paul J.Edelson and Von PittmanSECTION THREE: FUNDINGChapter 6: Funding of Distance and Online Learning in the United States, Mark J. Smithand William J. BrambleChapter 7: Funding Distance Education: A Regional Perspective, Santosh Panda andAshok GabaSECTION FOUR: COST STRUCTURES AND MODELSChapter 8: Costs and Quality of Online Learning, Alistair InglisChapter 9: Costing Virtual University Education, Insung JungChapter 10: Cost-Benefit of Student Retention Policies and Practices, Ormond SimpsonSECTION FIVE: DISTANCE TRAININGChapter 11: Cost Benefit of Online Learning, Zane Berge and Charlotte DonaldsonChapter 12: Transforming Workplace

  15. Academic learning for specialist nurses: a grounded theory study.

    Science.gov (United States)

    Millberg, Lena German; Berg, Linda; Brämberg, Elisabeth Björk; Nordström, Gun; Ohlén, Joakim

    2014-11-01

    The aim was to explore the major concerns of specialist nurses pertaining to academic learning during their education and initial professional career. Specialist nursing education changed in tandem with the European educational reform in 2007. At the same time, greater demands were made on the healthcare services to provide evidence-based and safe patient-care. These changes have influenced specialist nursing programmes and consequently the profession. Grounded Theory guided the study. Data were collected by means of a questionnaire with open-ended questions distributed at the end of specialist nursing programmes in 2009 and 2010. Five universities were included. Further, individual, pair and group interviews were used to collect data from 12 specialist nurses, 5-14 months after graduation. A major concern for specialist nurses was that academic learning should be "meaningful" for their professional future. The specialist nurses' "meaningful academic learning process" was characterised by an ambivalence of partly believing in and partly being hesitant about the significance of academic learning and partly receiving but also lacking support. Specialist nurses were influenced by factors in two areas: curriculum and healthcare context. They felt that the outcome of contribution to professional confidence was critical in making academic learning meaningful. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. 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.

  17. Turing’s algorithmic lens: From computability to complexity theory

    Directory of Open Access Journals (Sweden)

    Díaz, Josep

    2013-12-01

    Full Text Available The decidability question, i.e., whether any mathematical statement could be computationally proven true or false, was raised by Hilbert and remained open until Turing answered it in the negative. Then, most efforts in theoretical computer science turned to complexity theory and the need to classify decidable problems according to their difficulty. Among others, the classes P (problems solvable in polynomial time and NP (problems solvable in non-deterministic polynomial time were defined, and one of the most challenging scientific quests of our days arose: whether P = NP. This still open question has implications not only in computer science, mathematics and physics, but also in biology, sociology and economics, and it can be seen as a direct consequence of Turing’s way of looking through the algorithmic lens at different disciplines to discover how pervasive computation is.La cuestión de la decidibilidad, es decir, si es posible demostrar computacionalmente que una expresión matemática es verdadera o falsa, fue planteada por Hilbert y permaneció abierta hasta que Turing la respondió de forma negativa. Establecida la no-decidibilidad de las matemáticas, los esfuerzos en informática teórica se centraron en el estudio de la complejidad computacional de los problemas decidibles. En este artículo presentamos una breve introducción a las clases P (problemas resolubles en tiempo polinómico y NP (problemas resolubles de manera no determinista en tiempo polinómico, al tiempo que exponemos la dificultad de establecer si P = NP y las consecuencias que se derivarían de que ambas clases de problemas fueran iguales. Esta cuestión tiene implicaciones no solo en los campos de la informática, las matemáticas y la física, sino también para la biología, la sociología y la economía. La idea seminal del estudio de la complejidad computacional es consecuencia directa del modo en que Turing abordaba problemas en diferentes ámbitos mediante lo

  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. Computation in the Learning System of Cephalopods.

    Science.gov (United States)

    Young, J Z

    1991-04-01

    The memory mechanisms of cephalopods consist of a series of matrices of intersecting axes, which find associations between the signals of input events and their consequences. The tactile memory is distributed among eight such matrices, and there is also some suboesophageal learning capacity. The visual memory lies in the optic lobe and four matrices, with some re-exciting pathways. In both systems, damage to any part reduces proportionally the effectiveness of the whole memory. These matrices are somewhat like those in mammals, for instance those in the hippocampus. The first matrix in both visual and tactile systems receives signals of vision and taste, and its output serves to increase the tendency to attack or to take with the arms. The second matrix provides for the correlation of groups of signals on its neurons, which pass signals to the third matrix. Here large cells find clusters in the sets of signals. Their output re-excites those of the first lobe, unless pain occurs. In that case, this set of cells provides a record that ensures retreat. There is experimental evidence that these distributed memory systems allow for the identification of categories of visual and tactile inputs, for generalization, and for decision on appropriate behavior in the light of experience. The evidence suggests that learning in cephalopods is not localized to certain layers or "grandmother cells" but is distributed with high redundance in serial networks, with recurrent circuits.

  20. Psychological theory and pedagogical effectiveness: the learning promotion potential framework.

    Science.gov (United States)

    Tomlinson, Peter

    2008-12-01

    After a century of educational psychology, eminent commentators are still lamenting problems besetting the appropriate relating of psychological insights to teaching design, a situation not helped by the persistence of crude assumptions concerning the nature of pedagogical effectiveness. To propose an analytical or meta-theoretical framework based on the concept of learning promotion potential (LPP) as a basis for understanding the basic relationship between psychological insights and teaching strategies, and to draw out implications for psychology-based pedagogical design, development and research. This is a theoretical and meta-theoretical paper relying mainly on conceptual analysis, though also calling on psychological theory and research. Since teaching consists essentially in activity designed to promote learning, it follows that a teaching strategy has the potential in principle to achieve particular kinds of learning gains (LPP) to the extent that it embodies or stimulates the relevant learning processes on the part of learners and enables the teacher's functions of on-line monitoring and assistance for such learning processes. Whether a teaching strategy actually does realize its LPP by way of achieving its intended learning goals depends also on the quality of its implementation, in conjunction with other factors in the situated interaction that teaching always involves. The core role of psychology is to provide well-grounded indication of the nature of such learning processes and the teaching functions that support them, rather than to directly generate particular ways of teaching. A critically eclectic stance towards potential sources of psychological insight is argued for. Applying this framework, the paper proposes five kinds of issue to be attended to in the design and evaluation of psychology-based pedagogy. Other work proposing comparable ideas is briefly reviewed, with particular attention to similarities and a key difference with the ideas of Oser

  1. 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.

  2. Machine learning based Intelligent cognitive network using fog computing

    Science.gov (United States)

    Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

    2017-05-01

    In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

  3. 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

  4. Learning general phonological rules from distributional information: a computational model.

    Science.gov (United States)

    Calamaro, Shira; Jarosz, Gaja

    2015-04-01

    Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. Copyright © 2014 Cognitive Science Society, Inc.

  5. A qualitative study of middle school students' perceptions of factors facilitating the learning of science: Grounded theory and existing theory

    Science.gov (United States)

    Spector, Barbara S.; Gibson, Charles W.

    The purpose of this study was to explore middle school students' perceptions of what factors facilitated their learning of science. Florida's Educational Reform Act of 1983 funded programs providing the state's precollege students with summer learning opportunities in science. mathematics, and computers. The programs were intended to encourage the development of creative approaches to the teaching of these disciplines. Under this program, between 50 and 60 high-achieving middle school students were in residence on the University of South Florida campus for 12 consecutive days of study in the World of Water (WOW) program. There were two sessions per summer involving a total of 572 participants. Eighi specially trained teachers were in residence with the students. Between 50 and 70 experts from the university, government. business, and industry interacted with the students each year in an innovative science/technology/society (STS) program. An assignment toward the close of the program asked students to reflect on their experiences in residence at the university and write an essay comparing learning in the WOW program to learning in their schools. Those essays were the base for this study. This was a qualitative study using a discursive approach to emergent design to generate grounded theory. Document review, participant observation, and open-ended interviews were used to gather and triangulate data in five phases. Some of the factors that middle school students perceived as helpful to learning science were (a) experiencing the situations about which they were learning; (b) having live presentations by professional experts; (c) doing hands-on activities: (d) being active learners; (e) using inductive reasoning to generate new knowledge; (f) exploring transdisciplinary approaches to problem solving; (g) having adult mentors; (h) interacting with peers and adults; (i) establishing networks; (j) having close personal friends who shared their interest in learning; (k

  6. 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.

  7. Teaching Theory Construction With Initial Grounded Theory Tools: A Reflection on Lessons and Learning.

    Science.gov (United States)

    Charmaz, Kathy

    2015-12-01

    This article addresses criticisms of qualitative research for spawning studies that lack analytic development and theoretical import. It focuses on teaching initial grounded theory tools while interviewing, coding, and writing memos for the purpose of scaling up the analytic level of students' research and advancing theory construction. Adopting these tools can improve teaching qualitative methods at all levels although doctoral education is emphasized here. What teachers cover in qualitative methods courses matters. The pedagogy presented here requires a supportive environment and relies on demonstration, collective participation, measured tasks, progressive analytic complexity, and accountability. Lessons learned from using initial grounded theory tools are exemplified in a doctoral student's coding and memo-writing excerpts that demonstrate progressive analytic development. The conclusion calls for increasing the number and depth of qualitative methods courses and for creating a cadre of expert qualitative methodologists. © The Author(s) 2015.

  8. Transitional clerkship: an experiential course based on workplace learning theory.

    Science.gov (United States)

    Chittenden, Eva H; Henry, Duncan; Saxena, Varun; Loeser, Helen; O'Sullivan, Patricia S

    2009-07-01

    Starting clerkships is anxiety provoking for medical students. To ease the transition from preclerkship to clerkship curricula, schools offer classroom-based courses which may not be the best model for preparing learners. Drawing from workplace learning theory, the authors developed a seven-day transitional clerkship (TC) in 2007 at the University of California, San Francisco School of Medicine in which students spent half of the course in the hospital, learning routines and logistics of the wards along with their roles and responsibilities as members of ward teams. Twice, they admitted and followed a patient into the next day as part of a shadow team that had no patient-care responsibilities. Dedicated preceptors gave feedback on oral presentations and patient write-ups. Satisfaction with the TC was higher than with the previous year's classroom-based course. TC students felt clearer about their roles and more confident in their abilities as third-year students compared with previous students. TC students continued to rate the transitional course highly after their first clinical rotation. Preceptors were enthusiastic about the course and expressed willingness to commit to future TC preceptorships. The transitional course models an approach to translating workplace learning theory into practice and demonstrates improved satisfaction, better understanding of roles, and increased confidence among new third-year students.

  9. 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…

  10. 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.

  11. Learning in Context: Technology Integration in a Teacher Preparation Program Informed by Situated Learning Theory

    Science.gov (United States)

    Bell, Randy L.; Maeng, Jennifer L.; Binns, Ian C.

    2013-01-01

    This investigation explores the effectiveness of a teacher preparation program aligned with situated learning theory on preservice science teachers' use of technology during their student teaching experiences. Participants included 26 preservice science teachers enrolled in a 2-year Master of Teaching program. A specific program goal was to…

  12. 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)…

  13. 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,…

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. [Role of the implicit theories of intelligence in learning situations].

    Science.gov (United States)

    Da Fonseca, D; Cury, F; Bailly, D; Rufo, M

    2004-01-01

    Most studies have tried to explain the school difficulties by analysing the intellectual factors that lead to school failure. However in addition to the instrumental capacities, authors also recognize the role played by other factors such as motivation. More specifically, the theory of achievement motivation aims to determine motivational factors involved in achievement situations when the students have to demonstrate their competencies. This paradigm attributes a central place to beliefs in order to explain children's behavior in academic situations. According to Dweck, it seems that beliefs about the nature of intelligence have a very powerful impact on behavior. These implicit theories of intelligence create a meaning system or conceptual framework that influences the individual interpretation of school situations. Thus, an entity theory of intelligence is the belief that intelligence is a fixed trait, a personal quality that cannot be changed. Students who subscribe to this theory believe that although people can learn new things, their underlying intelligence remains the same. In contrast, an incremental theory of intelligence is the belief that intelligence is a malleable quality that can increase through efforts. The identification of these two theories allows us to understand the cognition and behavior of individuals in achievement situations. Many studies carried out in the academic area show that students who hold an entity theory of intelligence (ie they consider intelligence like a stable quality) have a strong tendency to attribute their failures to a fixed trait. They are more likely to blame their intelligence for ne-gative outcomes and to attribute failures to their bad intellectual ability. In contrast, students who hold an incremental theory of intelligence (ie they consider intelligence as a malleable quality) are more likely to understand the same ne-gative outcomes in terms of specific factors: they attribute them to a lack of effort. This

  19. Action learning in virtual higher education: applying leadership theory.

    Science.gov (United States)

    Curtin, Joseph

    2016-05-03

    This paper reports the historical foundation of Northeastern University's course, LDR 6100: Developing Your Leadership Capability, a partial literature review of action learning (AL) and virtual action learning (VAL), a course methodology of LDR 6100 requiring students to apply leadership perspectives using VAL as instructed by the author, questionnaire and survey results of students who evaluated the effectiveness of their application of leadership theories using VAL and insights believed to have been gained by the author administering VAL. Findings indicate most students thought applying leadership perspectives using AL was better than considering leadership perspectives not using AL. In addition as implemented in LDR 6100, more students evaluated VAL positively than did those who assessed VAL negatively.

  20. 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.