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Sample records for support adaptive learning

  1. Supporting Student Learning in Computer Science Education via the Adaptive Learning Environment ALMA

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    Alexandra Gasparinatou

    2015-10-01

    Full Text Available This study presents the ALMA environment (Adaptive Learning Models from texts and Activities. ALMA supports the processes of learning and assessment via: (1 texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2 activities corresponding to different levels of comprehension which prompt the student to practically implement different text-reading strategies, with the recommended activity sequence adapted to the student’s learning style; (3 an overall framework for informing, guiding, and supporting students in performing the activities; and; (4 individualized support and guidance according to student specific characteristics. ALMA also, supports students in distance learning or in blended learning in which students are submitted to face-to-face learning supported by computer technology. The adaptive techniques provided via ALMA are: (a adaptive presentation and (b adaptive navigation. Digital learning material, in accordance with the text comprehension model described by Kintsch, was introduced into the ALMA environment. This material can be exploited in either distance or blended learning.

  2. Learner Open Modeling in Adaptive Mobile Learning System for Supporting Student to Learn English

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    Van Cong Pham

    2011-10-01

    Full Text Available This paper represents a personalized context-aware mobile learning architecture for supporting student to learn English as foreign language in order to prepare for TOEFL test. We consider how to apply open learner modeling techniques to adapt contents for different learners based on context, which includes location, amount of time to learn, the manner as well as learner's knowledge in learning progress. Through negotiation with system, the editable learner model will be updated to support adaptive engine to select adaptive contents meeting learner's demands. Empirical testing results for students who used application prototype indicate that interaction user modeling is helpful in supporting learner to learn adaptive materials.

  3. Different Futures of Adaptive Collaborative Learning Support

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    Rummel, Nikol; Walker, Erin; Aleven, Vincent

    2016-01-01

    In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…

  4. OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

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    Pedrazzoli, Attilio

    2010-06-01

    AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

  5. Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

    Science.gov (United States)

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2012-01-01

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

  6. Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

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    Demetriadis, Stavros; Xhafa, Fatos

    2012-01-01

    Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

  7. A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

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    Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

    2016-01-01

    Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

  8. Supporting Adaptive Learning Pathways through the Use of Learning Analytics: Developments, Challenges and Future Opportunities

    Science.gov (United States)

    Mavroudi, Anna; Giannakos, Michail; Krogstie, John

    2018-01-01

    Learning Analytics (LA) and adaptive learning are inextricably linked since they both foster technology-supported learner-centred education. This study identifies developments focusing on their interplay and emphasises insufficiently investigated directions which display a higher innovation potential. Twenty-one peer-reviewed studies are…

  9. How Language Supports Adaptive Teaching through a Responsive Learning Culture

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    Johnston, Peter; Dozier, Cheryl; Smit, Julie

    2016-01-01

    For students to learn optimally, teachers must design classrooms that are responsive to the full range of student development. The teacher must be adaptive, but so must each student and the learning culture itself. In other words, adaptive teaching means constructing a responsive learning culture that accommodates and even capitalizes on diversity…

  10. Mobile Adaptive Communication Support for Vocabulary Acquisition

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    Epp, Carrie Demmans

    2014-01-01

    This work explores the use of an adaptive mobile tool for language learning. A school-based deployment study showed that the tool supported learning. A second study is being conducted in informal learning environments. Current work focuses on building models that increase our understanding of the relationship between application usage and learning.

  11. Towards adaptation in e-learning 2.0

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    Cristea, Alexandra I.; Ghali, Fawaz

    2011-04-01

    This paper presents several essential steps from an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning and adaptation (in particular, personalisation to the learner). These novel teaching and learning ways-the latter focus of this paper-are reflected in and finally adding to various versions of the My Online Teacher 2.0 adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to "simple" learning in a system with a minimum of Web 2.0 support. Overall, the results of adding peer recommendation and adaptive content presentation were encouraging, and are further discussed in detail in this paper.

  12. Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities.

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    Bryant, D P; Bryant, B R

    1998-01-01

    Cooperative learning (CL) is a common instructional arrangement that is used by classroom teachers to foster academic achievement and social acceptance of students with and without learning disabilities. Cooperative learning is appealing to classroom teachers because it can provide an opportunity for more instruction and feedback by peers than can be provided by teachers to individual students who require extra assistance. Recent studies suggest that students with LD may need adaptations during cooperative learning activities. The use of assistive technology adaptations may be necessary to help some students with LD compensate for their specific learning difficulties so that they can engage more readily in cooperative learning activities. A process for integrating technology adaptations into cooperative learning activities is discussed in terms of three components: selecting adaptations, monitoring the use of the adaptations during cooperative learning activities, and evaluating the adaptations' effectiveness. The article concludes with comments regarding barriers to and support systems for technology integration, technology and effective instructional practices, and the need to consider technology adaptations for students who have learning disabilities.

  13. Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

    Science.gov (United States)

    Sardi, Shira; Vardi, Roni; Goldental, Amir; Sheinin, Anton; Uzan, Herut; Kanter, Ido

    2018-03-23

    Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.

  14. MEAT: An Authoring Tool for Generating Adaptable Learning Resources

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    Kuo, Yen-Hung; Huang, Yueh-Min

    2009-01-01

    Mobile learning (m-learning) is a new trend in the e-learning field. The learning services in m-learning environments are supported by fundamental functions, especially the content and assessment services, which need an authoring tool to rapidly generate adaptable learning resources. To fulfill the imperious demand, this study proposes an…

  15. Designing monitoring arrangements for collaborative learning about adaptation pathways

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    Hermans, L.M.; Haasnoot, M.; ter Maat, Judith; Kwakkel, J.H.

    2017-01-01

    Adaptation pathways approaches support long-term planning under uncertainty. The use of adaptation pathways implies a systematic monitoring effort to inform future adaptation decisions. Such monitoring should feed into a long-term collaborative learning process between multiple actors at various

  16. Web-Based Learning Support System

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    Fan, Lisa

    Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

  17. ADAPTATION OF TEACHING PROCESS BASED ON A STUDENTS INDIVIDUAL LEARNING NEEDS

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    TAKÁCS, Ondřej

    2011-03-01

    Full Text Available Development of current society requires integration of information technology to every sector, including education. The idea of adaptive teaching in e-learning environment is based on paying attention and giving support to various learning styles. More effective, user friendly thus better quality education can be achieved through such an environment. Learning can be influenced by many factors. In the paper we deal with such factors as student’s personality and qualities – particularly learning style and motivation. In addition we want to prepare study materials and study environment which respects students’ differences. Adaptive e-learning means an automated way of teaching which adapts to different qualities of students which are characteristic for their learning styles. In the last few years we can see a gradual individualization of study not only in distance forms of study but also with full-time study students. Instructional supports, namely those of e-learning, should take this trend into account and adapt the educational processes to individual students’ qualities. The present learning management systems (LMS offers this possibility only to a very limited extent. This paper deals with a design of intelligent virtual tutor behavior, which would adapt its learning ability to both static and dynamically changing student’s qualities. Virtual tutor, in order to manage all that, has to have a sufficiently rich supply of different styles and forms of teaching, with enough information about styles of learning, kinds of memory and other student’s qualities. This paper describes a draft adaptive education model and the results of the first part of the solution – definition of learning styles, pilot testing on students and an outline of further research.

  18. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

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    Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

    2017-01-01

    Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

  19. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Qi Huang

    2017-06-01

    Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

  20. Adapting a Technology-Based Implementation Support Tool for Community Mental Health: Challenges and Lessons Learned.

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    Livet, Melanie; Fixsen, Amanda

    2018-01-01

    With mental health services shifting to community-based settings, community mental health (CMH) organizations are under increasing pressure to deliver effective services. Despite availability of evidence-based interventions, there is a gap between effective mental health practices and the care that is routinely delivered. Bridging this gap requires availability of easily tailorable implementation support tools to assist providers in implementing evidence-based intervention with quality, thereby increasing the likelihood of achieving the desired client outcomes. This study documents the process and lessons learned from exploring the feasibility of adapting such a technology-based tool, Centervention, as the example innovation, for use in CMH settings. Mixed-methods data on core features, innovation-provider fit, and organizational capacity were collected from 44 CMH providers. Lessons learned included the need to augment delivery through technology with more personal interactions, the importance of customizing and integrating the tool with existing technologies, and the need to incorporate a number of strategies to assist with adoption and use of Centervention-like tools in CMH contexts. This study adds to the current body of literature on the adaptation process for technology-based tools and provides information that can guide additional innovations for CMH settings.

  1. Usability of clinical decision support system as a facilitator for learning the assistive technology adaptation process.

    Science.gov (United States)

    Danial-Saad, Alexandra; Kuflik, Tsvi; Weiss, Patrice L Tamar; Schreuer, Naomi

    2016-01-01

    The aim of this study was to evaluate the usability of Ontology Supported Computerized Assistive Technology Recommender (OSCAR), a Clinical Decision Support System (CDSS) for the assistive technology adaptation process, its impact on learning the matching process, and to determine the relationship between its usability and learnability. Two groups of expert and novice clinicians (total, n = 26) took part in this study. Each group filled out system usability scale (SUS) to evaluate OSCAR's usability. The novice group completed a learning questionnaire to assess OSCAR's effect on their ability to learn the matching process. Both groups rated OSCAR's usability as "very good", (M [SUS] = 80.7, SD = 11.6, median = 83.7) by the novices, and (M [SUS] = 81.2, SD = 6.8, median = 81.2) by the experts. The Mann-Whitney results indicated that no significant differences were found between the expert and novice groups in terms of OSCAR's usability. A significant positive correlation existed between the usability of OSCAR and the ability to learn the adaptation process (rs = 0.46, p = 0.04). Usability is an important factor in the acceptance of a system. The successful application of user-centered design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically in developing other systems. Implications for Rehabilitation Creating a CDSS with a focus on its usability is an important factor for its acceptance by its users. Successful usability outcomes can impact the learning process of the subject matter in general, and the AT prescription process in particular. The successful application of User-Centered Design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically. The study emphasizes the importance of close collaboration between the developers and

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

    OpenAIRE

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2006-01-01

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

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

    NARCIS (Netherlands)

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2006-01-01

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

  4. Integrative learning for practicing adaptive resource management

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    Craig A. McLoughlin

    2015-03-01

    Full Text Available Adaptive resource management is a learning-by-doing approach to natural resource management. Its effective practice involves the activation, completion, and regeneration of the "adaptive management cycle" while working toward achieving a flexible set of collaboratively identified objectives. This iterative process requires application of single-, double-, and triple-loop learning, to strategically modify inputs, outputs, assumptions, and hypotheses linked to improving policies, management strategies, and actions, along with transforming governance. Obtaining an appropriate balance between these three modes of learning has been difficult to achieve in practice and building capacity in this area can be achieved through an emphasis on reflexive learning, by employing adaptive feedback systems. A heuristic reflexive learning framework for adaptive resource management is presented in this manuscript. It is built on the conceptual pillars of the following: stakeholder driven adaptive feedback systems; strategic adaptive management (SAM; and hierarchy theory. The SAM Reflexive Learning Framework (SRLF emphasizes the types, roles, and transfer of information within a reflexive learning context. Its adaptive feedback systems enhance the facilitation of single-, double-, and triple-loop learning. Focus on the reflexive learning process is further fostered by streamlining objectives within and across all governance levels; incorporating multiple interlinked adaptive management cycles; having learning as an ongoing, nested process; recognizing when and where to employ the three-modes of learning; distinguishing initiating conditions for this learning; and contemplating practitioner mandates for this learning across governance levels. The SRLF is a key enabler for implementing the "adaptive management cycle," and thereby translating the theory of adaptive resource management into practice. It promotes the heuristics of adaptive management within a cohesive

  5. Selecting Learning Tasks: Effects of Adaptation and Shared Control on Learning Efficiency and Task Involvement

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    Corbalan, Gemma; Kester, Liesbeth; van Merrienboer, Jeroen J. G.

    2008-01-01

    Complex skill acquisition by performing authentic learning tasks is constrained by limited working memory capacity [Baddeley, A. D. (1992). Working memory. "Science, 255", 556-559]. To prevent cognitive overload, task difficulty and support of each newly selected learning task can be adapted to the learner's competence level and perceived task…

  6. Toward Personalized Vibrotactile Support When Learning Motor Skills

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    Olga C. Santos

    2017-01-01

    Full Text Available Personal tracking technologies allow sensing of the physical activity carried out by people. Data flows collected with these sensors are calling for big data techniques to support data collection, integration and analysis, aimed to provide personalized support when learning motor skills through varied multisensorial feedback. In particular, this paper focuses on vibrotactile feedback as it can take advantage of the haptic sense when supporting the physical interaction to be learnt. Despite each user having different needs, when providing this vibrotactile support, personalization issues are hardly taken into account, but the same response is delivered to each and every user of the system. The challenge here is how to design vibrotactile user interfaces for adaptive learning of motor skills. TORMES methodology is proposed to facilitate the elicitation of this personalized support. The resulting systems are expected to dynamically adapt to each individual user’s needs by monitoring, comparing and, when appropriate, correcting in a personalized way how the user should move when practicing a predefined movement, for instance, when performing a sport technique or playing a musical instrument.

  7. Learning to Adapt. Organisational Adaptation to Climate Change Impacts

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    Berkhout, F.; Hertin, J.; Gann, D.M.

    2006-01-01

    Analysis of human adaptation to climate change should be based on realistic models of adaptive behaviour at the level of organisations and individuals. The paper sets out a framework for analysing adaptation to the direct and indirect impacts of climate change in business organisations with new evidence presented from empirical research into adaptation in nine case-study companies. It argues that adaptation to climate change has many similarities with processes of organisational learning. The paper suggests that business organisations face a number of obstacles in learning how to adapt to climate change impacts, especially in relation to the weakness and ambiguity of signals about climate change and the uncertainty about benefits flowing from adaptation measures. Organisations rarely adapt 'autonomously', since their adaptive behaviour is influenced by policy and market conditions, and draws on resources external to the organisation. The paper identifies four adaptation strategies that pattern organisational adaptive behaviour

  8. Creating adaptive environment for e-learning courses

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    Bozidar Radenkovic

    2009-06-01

    Full Text Available In this paper we provide an approach to creating adaptive environment for e-learning courses. In the context of e-education, successful adaptation has to be performed upon learners’ characteristics. Currently, modeling and discovering users’ needs, goals, knowledge preferences and motivations is one of the most challenging tasks in e-learning systems that deal with large volumes of information. Primary goal of the research is to perform personalizing of distance education system, according to students’ learning styles. Main steps and requirements in applying business intelligence techniques in process of personalization are identified. In addition, we propose generic model and architecture of an adaptive e-learning system by describing the structure of an adaptive course and exemplify correlations among e-learning course content and different learning styles. Moreover, research that dealt with application of data mining technique in a real e-learning system was carried out. We performed adaptation of our e-learning courses using the results from the research.

  9. ADAPTIVE E-LEARNING AND ITS EVALUATION

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    KOSTOLÁNYOVÁ, Katerina

    2012-12-01

    Full Text Available This paper introduces a complex plan for a complete system of individualized electronic instruction. The core of the system is a computer program to control teaching, the so called “virtual teacher”. The virtual teacher automatically adapts to individual student’s characteristics and their learning style. It adapts to static as well as to dynamic characteristics of the student. To manage all this it needs a database of various styles and forms of teaching as well as a sufficient amount of information about the learning style, type of memory and other characteristics of the student. The information about these characteristics, the structure of data storage and its use by the virtual teacher are also part of this paper. We also outline a methodology of adaptive study materials. We define basic rules and forms to create adaptive study materials. This adaptive e-learning system was pilot tested in learning of more than 50 students. These students filled in a learning style questionnaire at the beginning of the study and they had the option to fill in an adaptive evaluation questionnaire at the end of the study. Results of these questionnaires were analyzed. Several conclusions were concluded from this analysis to alter the methodology of adaptive study materials.

  10. Adaptation Criteria for the Personalised Delivery of Learning Materials: A Multi-Stage Empirical Investigation

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    Thalmann, Stefan

    2014-01-01

    Personalised e-Learning represents a major step-change from the one-size-fits-all approach of traditional learning platforms to a more customised and interactive provision of learning materials. Adaptive learning can support the learning process by tailoring learning materials to individual needs. However, this requires the initial preparation of…

  11. Computerized adaptive testing item selection in computerized adaptive learning systems

    NARCIS (Netherlands)

    Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

    2012-01-01

    Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

  12. A New Mobile Learning Adaptation Model

    OpenAIRE

    Mohamd Hassan Hassan; Jehad Al-Sadi

    2009-01-01

    This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...

  13. Supporting online learning with games

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    Yao, JingTao; Kim, DongWon; Herbert, Joseph P.

    2007-04-01

    This paper presents a study on Web-based learning support systems that is enhanced with two major subsystems: a Web-based learning game and a learning-oriented Web search. The Internet and theWeb may be considered as a first resource for students seeking for information and help. However, much of the information available online is not related to the course contents or is wrong in the worse case. The search subsystem aims to provide students with precise, relative and adaptable documents about certain courses or classes. Therefore, students do not have to spend time to verify the relationship of documents to the class. The learning game subsystem stimulates students to study, enables students to review their studies and to perform self-evaluation through a Web-based learning game such as a treasure hunt game. During the challenge and entertaining learning and evaluation process, it is hoped that students will eventually understand and master the course concepts easily. The goal of developing such a system is to provide students with an efficient and effective learning environment.

  14. Recommendation System for Adaptive Learning.

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    Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

    2018-01-01

    An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

  15. Analysis of an Interactive Technology Supported Problem-Based Learning STEM Project Using Selected Learning Sciences Interest Areas (SLSIA)

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    Kumar, David Devraj

    2017-01-01

    This paper reports an analysis of an interactive technology-supported, problem-based learning (PBL) project in science, technology, engineering and mathematics (STEM) from a Learning Sciences perspective using the Selected Learning Sciences Interest Areas (SLSIA). The SLSIA was adapted from the "What kinds of topics do ISLS [International…

  16. Student Modelling in Adaptive E-Learning Systems

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    Clemens Bechter

    2011-09-01

    Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

  17. 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

  18. Adaptive learning in agents behaviour: A framework for electricity markets simulation

    DEFF Research Database (Denmark)

    Pinto, Tiago; Vale, Zita; Sousa, Tiago M.

    2014-01-01

    decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology...... that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management...... allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides...

  19. Learning to Control Advanced Life Support Systems

    Science.gov (United States)

    Subramanian, Devika

    2004-01-01

    Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for

  20. Support patient search on pathology reports with interactive online learning based data extraction.

    Science.gov (United States)

    Zheng, Shuai; Lu, James J; Appin, Christina; Brat, Daniel; Wang, Fusheng

    2015-01-01

    Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user's interaction with minimal human effort. We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system's data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users' corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of tests. Extracting data from pathology reports could enable

  1. Supporting learning skills in visual art classes: The benefits of teacher awareness

    Directory of Open Access Journals (Sweden)

    Helen Arov

    2017-09-01

    Full Text Available This study focused on middle school art teachers supporting the development of students learning skills, specifically their awareness of the framework of learning skills. It also looked at the relations between the teaching practices teachers use for supporting learning skills and students' learning motivation in art classes. The study combined qualitative and quantitative research methods. The class observations and interviews were conducted with ten Estonian middle school art teachers. One hundred and forty-eight students from the observed classes filled out the learning motivation questionnaire about their interest and achievement goals in visual arts. The study draws attention to the importance of teachers being aware of and valuing learning skills alongside subject specific knowledge, as it could enhance students autonomous motivation and support adaptive goal setting.

  2. Anticipatory Learning for Climate Change Adaptation and Resilience

    Directory of Open Access Journals (Sweden)

    Petra Tschakert

    2010-06-01

    Full Text Available This paper is a methodological contribution to emerging debates on the role of learning, particularly forward-looking (anticipatory learning, as a key element for adaptation and resilience in the context of climate change. First, we describe two major challenges: understanding adaptation as a process and recognizing the inadequacy of existing learning tools, with a specific focus on high poverty contexts and complex livelihood-vulnerability risks. Then, the article examines learning processes from a dynamic systems perspective, comparing theoretical aspects and conceptual advances in resilience thinking and action research/learning (AR/AL. Particular attention is paid to learning loops (cycles, critical reflection, spaces for learning, and power. Finally, we outline a methodological framework to facilitate iterative learning processes and adaptive decision making in practice. We stress memory, monitoring of key drivers of change, scenario planning, and measuring anticipatory capacity as crucial ingredients. Our aim is to identify opportunities and obstacles for forward-looking learning processes at the intersection of climatic uncertainty and development challenges in Africa, with the overarching objective to enhance adaptation and resilient livelihood pathways, rather than learning by shock.

  3. Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

    Science.gov (United States)

    Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

    2014-05-01

    We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the

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

    Science.gov (United States)

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

    2017-01-01

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

  5. A knowledge representation approach using fuzzy cognitive maps for better navigation support in an adaptive learning system.

    Science.gov (United States)

    Chrysafiadi, Konstantina; Virvou, Maria

    2013-12-01

    In this paper a knowledge representation approach of an adaptive and/or personalized tutoring system is presented. The domain knowledge should be represented in a more realistic way in order to allow the adaptive and/or personalized tutoring system to deliver the learning material to each individual learner dynamically taking into account her/his learning needs and her/his different learning pace. To succeed this, the domain knowledge representation has to depict the possible increase or decrease of the learner's knowledge. Considering that the domain concepts that constitute the learning material are not independent from each other, the knowledge representation approach has to allow the system to recognize either the domain concepts that are already partly or completely known for a learner, or the domain concepts that s/he has forgotten, taking into account the learner's knowledge level of the related concepts. In other words, the system should be informed about the knowledge dependencies that exist among the domain concepts of the learning material, as well as the strength on impact of each domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically this kind of information. The suggested knowledge representation approach has been implemented in an e-learning adaptive system for teaching computer programming. The particular system was used by the students of a postgraduate program in the field of Informatics in the University of Piraeus and was compared with a corresponding system, in which the domain knowledge was represented using the most common used technique of network of concepts. The results of the evaluation were very encouraging.

  6. Adaptive and perceptual learning technologies in medical education and training.

    Science.gov (United States)

    Kellman, Philip J

    2013-10-01

    Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

  7. Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

    Science.gov (United States)

    Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

    2011-01-01

    When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

  8. Adaptive representations for reinforcement learning

    NARCIS (Netherlands)

    Whiteson, S.

    2010-01-01

    This book presents new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks a control policy for a sequential decision task. Since current methods typically rely on manually designed solution representations, agents that automatically adapt their own

  9. Studying citizen science through adaptive management and learning feedbacks as mechanisms for improving conservation.

    Science.gov (United States)

    Jordan, Rebecca; Gray, Steven; Sorensen, Amanda; Newman, Greg; Mellor, David; Newman, Greg; Hmelo-Silver, Cindy; LaDeau, Shannon; Biehler, Dawn; Crall, Alycia

    2016-06-01

    Citizen science has generated a growing interest among scientists and community groups, and citizen science programs have been created specifically for conservation. We examined collaborative science, a highly interactive form of citizen science, which we developed within a theoretically informed framework. In this essay, we focused on 2 aspects of our framework: social learning and adaptive management. Social learning, in contrast to individual-based learning, stresses collaborative and generative insight making and is well-suited for adaptive management. Adaptive-management integrates feedback loops that are informed by what is learned and is guided by iterative decision making. Participants engaged in citizen science are able to add to what they are learning through primary data collection, which can result in the real-time information that is often necessary for conservation. Our work is particularly timely because research publications consistently report a lack of established frameworks and evaluation plans to address the extent of conservation outcomes in citizen science. To illustrate how our framework supports conservation through citizen science, we examined how 2 programs enacted our collaborative science framework. Further, we inspected preliminary conservation outcomes of our case-study programs. These programs, despite their recent implementation, are demonstrating promise with regard to positive conservation outcomes. To date, they are independently earning funds to support research, earning buy-in from local partners to engage in experimentation, and, in the absence of leading scientists, are collecting data to test ideas. We argue that this success is due to citizen scientists being organized around local issues and engaging in iterative, collaborative, and adaptive learning. © 2016 Society for Conservation Biology.

  10. Support patient search on pathology reports with interactive online learning based data extraction

    Directory of Open Access Journals (Sweden)

    Shuai Zheng

    2015-01-01

    Full Text Available Background: Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user′s interaction with minimal human effort. Methods : We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system′s data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users′ corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. Results: We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of

  11. E-Learning and Personalized Learning Path: A Proposal Based on the Adaptive Educational Hypermedia System

    Directory of Open Access Journals (Sweden)

    Francesco Colace

    2014-03-01

    Full Text Available The E-Learning is becoming an effective approach for the improving of quality of learning. Many institutions are adopting this approach both to improve their traditional courses both to increase the potential audience. In the last period great attention is paid in the introduction of methodologies and techniques for the adaptation of learning process to the real needs of students. In this scenario the Adaptive Educational Hypermedia System can be an effective approach. Adaptive hypermedia is a promising area of research at the crossroads of hypermedia and adaptive systems. One of the most important fields where this approach can be applied is just the e-Learning. In this context the adaptive learning resources selection and sequencing is recognized as among one of the most interesting research questions. An Adaptive Educational Hypermedia System is composed by services for the management of the Knowledge Space, the definition of a User Model, the observation of student during his learning period and, as previously said, the adaptation of the learning path according to the real needs of the students. In particular the use of ontologyཿs formalism for the modeling of the ཿknowledge space࿝ related to the course can increase the sharable of learning objects among similar courses or better contextualize their role in the course. This paper addresses the design problem of an Adaptive hypermedia system by the definition of methodologies able to manage each its components, In particular an original user, learning contents, tracking strategies and adaptation model are developed. The proposed Adaptive Educational Hypermedia System has been integrated in an e-Learning platform and an experimental campaign has been conducted. In particular the proposed approach has been introduced in three different blended courses. A comparison with traditional approach has been described and the obtained results seem to be very promising.

  12. Adaptive Learning Systems: Beyond Teaching Machines

    Science.gov (United States)

    Kara, Nuri; Sevim, Nese

    2013-01-01

    Since 1950s, teaching machines have changed a lot. Today, we have different ideas about how people learn, what instructor should do to help students during their learning process. We have adaptive learning technologies that can create much more student oriented learning environments. The purpose of this article is to present these changes and its…

  13. In their own words: Student stories of seeking learning support

    Directory of Open Access Journals (Sweden)

    Mark Brown

    2013-11-01

    Full Text Available Many Open and Distance Learning (ODL providers report that their students are prone to lower rates of retention and completion than campus-based students. Against this background, there is growing interest around distance-specific learning support. The current research investigated the experiences of students during their first semester as distance learners at Massey University in New Zealand. The overarching methodology was Design-Based Research, within which phenomenological data gathering methods were used to study the experiences of twenty participants from their own point of view. Using video cameras, over twentytwo hours of self-reflections were gathered between July and November 2011 using a technique adapted from previous studies. A grounded theory approach was applied to the process of thematic data analysis. Results revealed how participants varied in their engagement with learning supports, including orientation events, outreach activity, cultural services, learning consultants, library services, fellow students, lecturers, residential courses, and other people. The discussion reflects on clusters of participants who utilised learning supports effectively, moderately and barely. The paper concludes by summarizing how the current research has had an impact on the design of learning support services at one of the world’s leading providers of distance education.

  14. Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

    Directory of Open Access Journals (Sweden)

    Wenjie Lou

    2016-02-01

    Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

  15. 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

  16. Inference in models with adaptive learning

    NARCIS (Netherlands)

    Chevillon, G.; Massmann, M.; Mavroeidis, S.

    2010-01-01

    Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be

  17. Deep reinforcement learning for automated radiation adaptation in lung cancer.

    Science.gov (United States)

    Tseng, Huan-Hsin; Luo, Yi; Cui, Sunan; Chien, Jen-Tzung; Ten Haken, Randall K; Naqa, Issam El

    2017-12-01

    escalation/de-escalation between 1.5 and 3.8 Gy, a range similar to that used in the clinical protocol. The same DQN yielded two patterns of dose escalation for the 34 test patients, but with different reward variants. First, using the baseline P+ reward function, individual adaptive fraction doses of the DQN had similar tendencies to the clinical data with an RMSE = 0.76 Gy; but adaptations suggested by the DQN were generally lower in magnitude (less aggressive). Second, by adjusting the P+ reward function with higher emphasis on mitigating local failure, better matching of doses between the DQN and the clinical protocol was achieved with an RMSE = 0.5 Gy. Moreover, the decisions selected by the DQN seemed to have better concordance with patients eventual outcomes. In comparison, the traditional temporal difference (TD) algorithm for reinforcement learning yielded an RMSE = 3.3 Gy due to numerical instabilities and lack of sufficient learning. We demonstrated that automated dose adaptation by DRL is a feasible and a promising approach for achieving similar results to those chosen by clinicians. The process may require customization of the reward function if individual cases were to be considered. However, development of this framework into a fully credible autonomous system for clinical decision support would require further validation on larger multi-institutional datasets. © 2017 American Association of Physicists in Medicine.

  18. Understanding Students' Adaptation to Graduate School: An Integration of Social Support Theory and Social Learning Theory

    Science.gov (United States)

    Tsay, Crystal Han-Huei

    2012-01-01

    The contemporary business world demands adaptive individuals (Friedman & Wyman, 2005). Adaptation is essential for any life transition. It often involves developing coping mechanisms, strategies, and seeking of social support. Adaptation occurs in many settings from moving to a new culture, taking a new job, starting or finishing an…

  19. Teacher-Led Design of an Adaptive Learning Environment

    Science.gov (United States)

    Mavroudi, Anna; Hadzilacos, Thanasis; Kalles, Dimitris; Gregoriades, Andreas

    2016-01-01

    This paper discusses a requirements engineering process that exemplifies teacher-led design in the case of an envisioned system for adaptive learning. Such a design poses various challenges and still remains an open research issue in the field of adaptive learning. Starting from a scenario-based elicitation method, the whole process was highly…

  20. Adaptive e-learning methods and IMS Learning Design. An integrated approach

    NARCIS (Netherlands)

    Burgos, Daniel; Specht, Marcus

    2006-01-01

    Please, cite this publication as: Burgos, D., & Specht, M. (2006). Adaptive e-learning methods and IMS Learning Design. In Kinshuk, R. Koper, P. Kommers, P. Kirschner, D. G. Sampson & W. Didderen (Eds.), Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies (pp.

  1. A Web-Based Learning Support System for Inquiry-Based Learning

    Science.gov (United States)

    Kim, Dong Won; Yao, Jingtao

    The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

  2. Improving Flood Plain Management through Adaptive Learning ...

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

    This project will explore how an adaptive learning approach can improve CBO governance ... for improving resource sustainability and productivity, and facilitate learning and an exchange ... Middlesex University Higher Education Corporation.

  3. Using Data to Understand How to Better Design Adaptive Learning

    Science.gov (United States)

    Liu, Min; Kang, Jina; Zou, Wenting; Lee, Hyeyeon; Pan, Zilong; Corliss, Stephanie

    2017-01-01

    There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior…

  4. Reinforcement Learning Based Novel Adaptive Learning Framework for Smart Grid Prediction

    Directory of Open Access Journals (Sweden)

    Tian Li

    2017-01-01

    Full Text Available Smart grid is a potential infrastructure to supply electricity demand for end users in a safe and reliable manner. With the rapid increase of the share of renewable energy and controllable loads in smart grid, the operation uncertainty of smart grid has increased briskly during recent years. The forecast is responsible for the safety and economic operation of the smart grid. However, most existing forecast methods cannot account for the smart grid due to the disabilities to adapt to the varying operational conditions. In this paper, reinforcement learning is firstly exploited to develop an online learning framework for the smart grid. With the capability of multitime scale resolution, wavelet neural network has been adopted in the online learning framework to yield reinforcement learning and wavelet neural network (RLWNN based adaptive learning scheme. The simulations on two typical prediction problems in smart grid, including wind power prediction and load forecast, validate the effectiveness and the scalability of the proposed RLWNN based learning framework and algorithm.

  5. Beyond adaptive-critic creative learning for intelligent mobile robots

    Science.gov (United States)

    Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

    2001-10-01

    Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

  6. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  7. Adaptation of mathematical educational content in e-learning resources

    Directory of Open Access Journals (Sweden)

    Yuliya V. Vainshtein

    2017-01-01

    Full Text Available Modern trends in the world electronic educational system development determine the necessity of adaptive learning intellectual environments and resources’ development and implementation. An upcoming trend in improvement the quality of studying mathematical disciplines is the development and application of adaptive electronic educational resources. However, the development and application experience of adaptive technologies in higher education is currently extremely limited and does not imply the usage flexibility. Adaptive educational resources in the electronic environment are electronic educational resources that provide the student with a personal educational space, filled with educational content that “adapts” to the individual characteristics of the students and provides them with the necessary information.This article focuses on the mathematical educational content adaptation algorithms development and their implementation in the e-learning system. The peculiarity of the proposed algorithms is the possibility of their application and distribution for adaptive e-learning resources construction. The novelty of the proposed approach is the three-step content organization of the adaptive algorithms for the educational content: “introductory adaptation of content”, “the current adaptation of content”, “estimative and a corrective adaptation”. For each stage of the proposed system, mathematical algorithms for educational content adaptation in adaptive e-learning resources are presented.Due to the high level of abstraction and complexity perception of mathematical disciplines, educational content is represented in the various editions of presentation that correspond to the levels of assimilation of the course material. Adaptation consists in the selection of the optimal edition of the material that best matches the individual characteristics of the student. The introduction of a three-step content organization of the adaptive

  8. Adaptive Social Learning Based on Crowdsourcing

    Science.gov (United States)

    Karataev, Evgeny; Zadorozhny, Vladimir

    2017-01-01

    Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via…

  9. Fractal Adaptive Web Service for Mobile Learning

    Directory of Open Access Journals (Sweden)

    Ichraf Tirellil

    2006-06-01

    Full Text Available This paper describes our proposition for adaptive web services which is based on configurable, re-usable adaptive/personalized services. To realize our ideas, we have developed an approach for designing, implementing and maintaining personal service. This approach enables the user to accomplish an activity with a set of services answering to his preferences, his profiles and to a personalized context. In this paper, we describe the principle of our approach that we call fractal adaptation approach, and we discuss the implementation of personalization services in the context of mobile and collaborative scenario of learning. We have realized a platform in this context -a platform for mobile and collaborative learning- based on fractal adaptable web services. The platform is tested with a population of students and tutors, in order to release the gaps and the advantages of the approach suggested.

  10. Online EEG-Based Workload Adaptation of an Arithmetic Learning Environment.

    Science.gov (United States)

    Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Gerjets, Peter; Spüler, Martin

    2017-01-01

    In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning. The amount of cognitive workload during learning is crucial for successful learning and should be held in the optimal range for each learner. Based on EEG data from 10 subjects, we created a prediction model that estimates the learner's workload to obtain an unobtrusive workload measure. Furthermore, we developed an interactive learning environment that uses the prediction model to estimate the learner's workload online based on the EEG data and adapt the difficulty of the learning material to keep the learner's workload in an optimal range. The EEG-based learning environment was used by 13 subjects to learn arithmetic addition in the octal number system, leading to a significant learning effect. The results suggest that it is feasible to use EEG as an unobtrusive measure of cognitive workload to adapt the learning content. Further it demonstrates that a promptly workload prediction is possible using a generalized prediction model without the need for a user-specific calibration.

  11. An adaptive deep Q-learning strategy for handwritten digit recognition.

    Science.gov (United States)

    Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

    2018-02-22

    Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Adaptive learning fuzzy control of a mobile robot

    International Nuclear Information System (INIS)

    Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

    1989-11-01

    In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

  13. Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Directory of Open Access Journals (Sweden)

    Radhika M. Pai

    2016-03-01

    Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

  14. Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Directory of Open Access Journals (Sweden)

    Radhika M. Pai

    2016-04-01

    Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

  15. Adaptive Hypermedia Systems for E-Learning

    Directory of Open Access Journals (Sweden)

    Aammou Souhaib

    2010-11-01

    Full Text Available The domain of traditional hypermedia is revolutionized by the arrival of the concept of adaptation. Currently the domain of Adaptive Hypermedia Systems (AHS is constantly growing. A major goal of current research is to provide a personalized educational experience that meets the needs specific to each learner (knowledge level, goals, motivation etc.... In this article we have studied the possibility of implementing traditional features of adaptive hypermedia in an open environment, and discussed the standards for describing learning objects and architectural models based on the use of ontologies as a prerequisite for such an adaptation.

  16. Learning analytics in practice: The effects of adaptive educational technology Snappet on students' arithmetic skills

    NARCIS (Netherlands)

    Molenaar, I.; Knoop-van Campen, C.A.N.

    2016-01-01

    Even though the recent influx of tablets in primary education goes together with the vision that educational technology empowered with learning analytics will revolutionize education, empirical results supporting this claim are scares. Adaptive educational technology Snappet combines extracted and

  17. Adaptive learning and complex dynamics

    International Nuclear Information System (INIS)

    Gomes, Orlando

    2009-01-01

    In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady state. This long-term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the degree of inefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and a-periodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. One macroeconomic model is used to illustrate how the formation of expectations through learning may eventually lead to awkward long-term outcomes.

  18. SupportNet: a novel incremental learning framework through deep learning and support data

    KAUST Repository

    Li, Yu; Li, Zhongxiao; Ding, Lizhong; Hu, Yuhui; Chen, Wei; Gao, Xin

    2018-01-01

    Motivation: In most biological data sets, the amount of data is regularly growing and the number of classes is continuously increasing. To deal with the new data from the new classes, one approach is to train a classification model, e.g., a deep learning model, from scratch based on both old and new data. This approach is highly computationally costly and the extracted features are likely very different from the ones extracted by the model trained on the old data alone, which leads to poor model robustness. Another approach is to fine tune the trained model from the old data on the new data. However, this approach often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as the catastrophic forgetting problem. To our knowledge, this problem has not been studied in the field of bioinformatics despite its existence in many bioinformatic problems. Results: Here we propose a novel method, SupportNet, to solve the catastrophic forgetting problem efficiently and effectively. SupportNet combines the strength of deep learning and support vector machine (SVM), where SVM is used to identify the support data from the old data, which are fed to the deep learning model together with the new data for further training so that the model can review the essential information of the old data when learning the new information. Two powerful consolidation regularizers are applied to ensure the robustness of the learned model. Comprehensive experiments on various tasks, including enzyme function prediction, subcellular structure classification and breast tumor classification, show that SupportNet drastically outperforms the state-of-the-art incremental learning methods and reaches similar performance as the deep learning model trained from scratch on both old and new data. Availability: Our program is accessible at: \\url{https://github.com/lykaust15/SupportNet}.

  19. SupportNet: a novel incremental learning framework through deep learning and support data

    KAUST Repository

    Li, Yu

    2018-05-08

    Motivation: In most biological data sets, the amount of data is regularly growing and the number of classes is continuously increasing. To deal with the new data from the new classes, one approach is to train a classification model, e.g., a deep learning model, from scratch based on both old and new data. This approach is highly computationally costly and the extracted features are likely very different from the ones extracted by the model trained on the old data alone, which leads to poor model robustness. Another approach is to fine tune the trained model from the old data on the new data. However, this approach often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as the catastrophic forgetting problem. To our knowledge, this problem has not been studied in the field of bioinformatics despite its existence in many bioinformatic problems. Results: Here we propose a novel method, SupportNet, to solve the catastrophic forgetting problem efficiently and effectively. SupportNet combines the strength of deep learning and support vector machine (SVM), where SVM is used to identify the support data from the old data, which are fed to the deep learning model together with the new data for further training so that the model can review the essential information of the old data when learning the new information. Two powerful consolidation regularizers are applied to ensure the robustness of the learned model. Comprehensive experiments on various tasks, including enzyme function prediction, subcellular structure classification and breast tumor classification, show that SupportNet drastically outperforms the state-of-the-art incremental learning methods and reaches similar performance as the deep learning model trained from scratch on both old and new data. Availability: Our program is accessible at: \\\\url{https://github.com/lykaust15/SupportNet}.

  20. A METHODOLOGICAL APPROACH FOR IMPLEMENTATION OF ADAPTIVE E-LEARNING

    OpenAIRE

    Valia Arnaudova; Todorka Terzieva; Asen Rahnev

    2016-01-01

    The purpose of adaptive e-Learning is to ensure effective teaching by providing an opportunity for students to connect with an environment that suits their needs, behavior, and knowledge. The reason adaptive e-Learning is important is that, for a learning process to be successful, it is necessary to consider teaching materials that address specific characteristics of the student, such as their particular goals, preferences, knowledge, and style of studying, to provide an appropriate teaching ...

  1. Adapting online learning for Canada's Northern public health workforce

    Directory of Open Access Journals (Sweden)

    Marnie Bell

    2013-08-01

    Full Text Available Background . Canada's North is a diverse, sparsely populated land, where inequalities and public health issues are evident, particularly for Aboriginal people. The Northern public health workforce is a unique mix of professional and paraprofessional workers. Few have formal public health education. From 2009 to 2012, the Public Health Agency of Canada (PHAC collaborated with a Northern Advisory Group to develop and implement a strategy to strengthen public health capacity in Canada's 3 northern territories. Access to relevant, effective continuing education was identified as a key issue. Challenges include diverse educational and cultural backgrounds of public health workers, geographical isolation and variable technological infrastructure across the north. Methods . PHAC's Skills Online program offers Internet-based continuing education modules for public health professionals. In partnership with the Northern Advisory Group, PHAC conducted 3 pilots between 2008 and 2012 to assess the appropriateness of the Skills Online program for Northern/Aboriginal public health workers. Module content and delivery modalities were adapted for the pilots. Adaptations included adding Inuit and Northern public health examples and using video and teleconference discussions to augment the online self-study component. Results . Findings from the pilots were informative and similar to those from previous Skills Online pilots with learners in developing countries. Online learning is effective in bridging the geographical barriers in remote locations. Incorporating content on Northern and Aboriginal health issues facilitates engagement in learning. Employer support facilitates the recruitment and retention of learners in an online program. Facilitator assets included experience as a public health professional from the north, and flexibility to use modified approaches to support and measure knowledge acquisition and application, especially for First Nations, Inuit and

  2. Adapting online learning for Canada's Northern public health workforce.

    Science.gov (United States)

    Bell, Marnie; MacDougall, Karen

    2013-01-01

    Canada's North is a diverse, sparsely populated land, where inequalities and public health issues are evident, particularly for Aboriginal people. The Northern public health workforce is a unique mix of professional and paraprofessional workers. Few have formal public health education. From 2009 to 2012, the Public Health Agency of Canada (PHAC) collaborated with a Northern Advisory Group to develop and implement a strategy to strengthen public health capacity in Canada's 3 northern territories. Access to relevant, effective continuing education was identified as a key issue. Challenges include diverse educational and cultural backgrounds of public health workers, geographical isolation and variable technological infrastructure across the north. PHAC's Skills Online program offers Internet-based continuing education modules for public health professionals. In partnership with the Northern Advisory Group, PHAC conducted 3 pilots between 2008 and 2012 to assess the appropriateness of the Skills Online program for Northern/Aboriginal public health workers. Module content and delivery modalities were adapted for the pilots. Adaptations included adding Inuit and Northern public health examples and using video and teleconference discussions to augment the online self-study component. Findings from the pilots were informative and similar to those from previous Skills Online pilots with learners in developing countries. Online learning is effective in bridging the geographical barriers in remote locations. Incorporating content on Northern and Aboriginal health issues facilitates engagement in learning. Employer support facilitates the recruitment and retention of learners in an online program. Facilitator assets included experience as a public health professional from the north, and flexibility to use modified approaches to support and measure knowledge acquisition and application, especially for First Nations, Inuit and Metis learners. Results demonstrate that

  3. INTUITEL and the Hypercube Model - Developing Adaptive Learning Environments

    Directory of Open Access Journals (Sweden)

    Kevin Fuchs

    2016-06-01

    Full Text Available In this paper we introduce an approach for the creation of adaptive learning environments that give human-like recommendations to a learner in the form of a virtual tutor. We use ontologies defining pedagogical, didactic and learner-specific data describing a learner's progress, learning history, capabilities and the learner's current state within the learning environment. Learning recommendations are based on a reasoning process on these ontologies and can be provided in real-time. The ontologies may describe learning content from any domain of knowledge. Furthermore, we describe an approach to store learning histories as spatio-temporal trajectories and to correlate them with influencing didactic factors. We show how such analysis of spatiotemporal data can be used for learning analytics to improve future adaptive learning environments.

  4. Active and Adaptive Learning from Biased Data with Applications in Astronomy

    DEFF Research Database (Denmark)

    Kremer, Jan

    This thesis addresses the problem of machine learning from biased datasets in the context of astronomical applications. In astronomy there are many cases in which the training sample does not follow the true distribution. The thesis examines different types of biases and proposes algorithms...... set. Against this background, the thesis begins with a survey of active learning algorithms for the support vector machine. If the cost of additional labeling is prohibitive, unlabeled data can often be utilized instead and the sample selection bias can be overcome through domain adaptation, that is...... to handle them. During learning and when applying the predictive model, active learning enables algorithms to select training examples from a pool of unlabeled data and to request the labels. This allows for selecting examples that maximize the algorithm's accuracy despite an initial bias in the training...

  5. Intelligent and Adaptive Educational-Learning Systems Achievements and Trends

    CERN Document Server

    2013-01-01

    The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form.  This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research.  After a rigorous revision process twenty manuscripts were accepted and organized into four parts as follows: ·     Modeling: The first part embraces five chapters oriented to: 1) shape the affective behavior; 2) depict the adaptive learning curriculum; 3) predict learning achievements; 4) mine learner models to outcome optimized and adaptive e-learning objects; 5) classify learning preferences of learners. ·     Content: The second part encompas...

  6. Pedagogical Support Components of Students' Social Adaptation

    Science.gov (United States)

    Vlasova, Vera K.; Simonova, Galina I.; Soleymani, Nassim

    2016-01-01

    The urgency of the problem stated in the article is caused by the need of pedagogical support of students' social adaptation on the basis of systematicity, which is achieved if we correctly define the components of the process. The aim of the article is to determine the pedagogical support components of students' social adaptation. The leading…

  7. Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning

    Science.gov (United States)

    2015-03-01

    ARL-SR-0318 ● MAR 2015 US Army Research Laboratory Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated...Adaptive Intelligent Tutoring Systems for Self-Regulated Learning by Robert A Sottilare Human Research and Engineering Directorate, ARL...TITLE AND SUBTITLE Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

  8. An Adaptive E-Learning System Based on Students' Learning Styles: An Empirical Study

    Science.gov (United States)

    Drissi, Samia; Amirat, Abdelkrim

    2016-01-01

    Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

  9. How adaptive learning affects evolution: reviewing theory on the Baldwin effect

    NARCIS (Netherlands)

    Sznajder, B.; Sabelis, M.W.; Egas, M.

    2012-01-01

    We review models of the Baldwin effect, i.e., the hypothesis that adaptive learning (i.e., learning to improve fitness) accelerates genetic evolution of the phenotype. Numerous theoretical studies scrutinized the hypothesis that a non-evolving ability of adaptive learning accelerates evolution of

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

    Science.gov (United States)

    Squires, David R.

    2014-01-01

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

  11. Implementing Adaptive Educational Methods with IMS Learning Design

    NARCIS (Netherlands)

    Specht, Marcus; Burgos, Daniel

    2006-01-01

    Please, cite this publication as: Specht, M. & Burgos, D. (2006). Implementing Adaptive Educational Methods with IMS Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org

  12. PERSO: Towards an Adaptive e-Learning System

    Science.gov (United States)

    Chorfi, Henda; Jemni, Mohamed

    2004-01-01

    In today's information technology society, members are increasingly required to be up to date on new technologies, particularly for computers, regardless of their background social situation. In this context, our aim is to design and develop an adaptive hypermedia e-learning system, called PERSO (PERSOnalizing e-learning system), where learners…

  13. Lessons Learned from the First Decade of Adaptive Management in Comprehensive Everglades Restoration

    Directory of Open Access Journals (Sweden)

    Andrew J. LoSchiavo

    2013-12-01

    Full Text Available Although few successful examples of large-scale adaptive management applications are available to ecosystem restoration scientists and managers, examining where and how the components of an adaptive management program have been successfully implemented yields insight into what approaches have and have not worked. We document five key lessons learned during the decade-long development and implementation of the Comprehensive Everglades Restoration Plan (CERP Collaborative Adaptive Management Program that might be useful to other adaptive management practitioners. First, legislative and regulatory authorities that require the development of an adaptive management program are necessary to maintain funding and support to set up and implement adaptive management. Second, integration of adaptive management activities into existing institutional processes, and development of technical guidance, helps to ensure that adaptive management activities are understood and roles and responsibilities are clearly articulated so that adaptive management activities are implemented successfully. Third, a strong applied science framework is critical for establishing a prerestoration ecosystem reference condition and understanding of how the system works, as well as for providing a conduit for incorporating new scientific information into the decision-making process. Fourth, clear identification of uncertainties that pose risks to meeting restoration goals helps with the development of hypothesis-driven strategies to inform restoration planning and implementation. Tools such as management options matrices can provide a coherent way to link hypotheses to specific monitoring efforts and options to adjust implementation if performance goals are not achieved. Fifth, independent external peer review of an adaptive management program provides important feedback critical to maintaining and improving adaptive management implementation for ecosystem restoration. These lessons

  14. The Influence of Learning Behaviour on Team Adaptability

    Science.gov (United States)

    Murray, Peter A.; Millett, Bruce

    2011-01-01

    Multiple contexts shape team activities and how they learn, and group learning is a dynamic construct that reflects a repertoire of potential behaviour. The purpose of this developmental paper is to examine how better learning behaviours in semi-autonomous teams improves the level of team adaptability and performance. The discussion suggests that…

  15. Better economics: supporting adaptation with stakeholder analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chambwera, Muyeye; Zou, Ye; Boughlala, Mohamed

    2011-11-15

    Across the developing world, decision makers understand the need to adapt to climate change — particularly in agriculture, which supports a large proportion of low-income groups who are especially vulnerable to impacts such as increasing water scarcity or more erratic weather. But policymakers are often less clear about what adaptation action to take. Cost-benefit analyses can provide information on the financial feasibility and economic efficiency of a given policy. But such methods fail to capture the non-monetary benefits of adaptation, which can be even more important than the monetary ones. Ongoing work in Morocco shows how combining cost-benefit analysis with a more participatory stakeholder analysis can support effective decision making by identifying cross-sector benefits, highlighting areas of mutual interest among different stakeholders and more effectively assessing impacts on adaptive capacity.

  16. Biomimetic molecular design tools that learn, evolve, and adapt

    Science.gov (United States)

    2017-01-01

    A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine. PMID:28694872

  17. Biomimetic molecular design tools that learn, evolve, and adapt

    Directory of Open Access Journals (Sweden)

    David A Winkler

    2017-06-01

    Full Text Available A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

  18. Adaptive Management of Communication in the Chamilo System of Distant Learning

    OpenAIRE

    Yatsenko Roman Nikolaevich; Polevich Olesya V.

    2012-01-01

    The article considers the communication management within an adaptive system of distance learning. We present two-circuit interaction system of the adaptive system. We consider the implementation of management communication in distance learning system based on the platform Chamilo.

  19. Adapting the Survivor Game to Create a Group Learning Term Project in Business Finance

    Science.gov (United States)

    Campbell, Robert D.

    2017-01-01

    A large and growing body of research supports the view that the small-group learning structure can be an effective tool to enhance student performance and encourage innovative problem solving. This paper explains in detail how the framework of the popular television reality show Survivor has been adapted to form a vehicle for a college level group…

  20. Soft systems thinking and social learning for adaptive management.

    Science.gov (United States)

    Cundill, G; Cumming, G S; Biggs, D; Fabricius, C

    2012-02-01

    The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning. ©2011 Society for Conservation Biology.

  1. Supporting Adaptation of Wireless Communication Protocols

    International Nuclear Information System (INIS)

    Dhomeja, L.D.; Soomro, I.A.; Malkani, Y.A.

    2016-01-01

    Pervasive devices such as mobile phones and PDAs (Personal Digital Assistants) come with different wireless communication capabilities, for example, WiFi (Wireless Fidelity), Bluetooth, IrDA (Infrared), etc. In order for pervasive devices to interact with each other, they need to have matching (alike) communication capabilities, otherwise such heterogeneous devices would not be able to interact with each other. In this paper we address this issue and propose a system that makes devices with heterogeneous wireless communication capabilities communicate with each other. The proposed system supports adaptation of wireless communication protocols through a proxy, which sits between a client and a server, and supports adaptation of wireless communication protocols. Its functionality involves intercepting a request made by a client with a different wireless communication capability (e.g. Bluetooth) from what the server has (e.g. WiFi), connecting to the server and then sending results back to the client. We have tested the system by implementing a messaging service application and running it on the system. The proxy supports all Bluetooth protocols, i.e. OBEX (Object Exchange), L2CAP (Logical Link Control and Adaptation Protocol), RFCOM (Radio Frequency Communication) and WiFi protocol and can run on (J2MW (Java 2 Micro Edition) enabled mobile phones which support both Bluetooth and WiFi capabilities. (author)

  2. 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

  3. The utility of adaptive eLearning in cervical cytopathology education.

    Science.gov (United States)

    Samulski, T Danielle; Taylor, Laura A; La, Teresa; Mehr, Chelsea R; McGrath, Cindy M; Wu, Roseann I

    2018-02-01

    Adaptive eLearning allows students to experience a self-paced, individualized curriculum based on prior knowledge and learning ability. The authors investigated the effectiveness of adaptive online modules in teaching cervical cytopathology. eLearning modules were created that covered basic concepts in cervical cytopathology, including artifacts and infections, squamous lesions (SL), and glandular lesions (GL). The modules used student responses to individualize the educational curriculum and provide real-time feedback. Pathology trainees and faculty from the authors' institution were randomized into 2 groups (SL or GL), and identical pre-tests and post-tests were used to compare the efficacy of eLearning modules versus traditional study methods (textbooks and slide sets). User experience was assessed with a Likert scale and free-text responses. Sixteen of 17 participants completed the SL module, and 19 of 19 completed the GL module. Participants in both groups had improved post-test scores for content in the adaptive eLearning module. Users indicated that the module was effective in presenting content and concepts (Likert scale [from 1 to 5], 4.3 of 5.0), was an efficient and convenient way to review the material (Likert scale, 4.4 of 5.0), and was more engaging than lectures and texts (Likert scale, 4.6 of 5.0). Users favored the immediate feedback and interactivity of the module. Limitations included the inability to review prior content and slow upload time for images. Learners demonstrated improvement in their knowledge after the use of adaptive eLearning modules compared with traditional methods. Overall, the modules were viewed positively by participants. Adaptive eLearning modules can provide an engaging and effective adjunct to traditional teaching methods in cervical cytopathology. Cancer Cytopathol 2018;126:129-35. © 2017 American Cancer Society. © 2017 American Cancer Society.

  4. Enhancing Adaptive Capacity in Food Systems: Learning at Farmers' Markets in Sweden

    Directory of Open Access Journals (Sweden)

    Rebecka Milestad

    2010-09-01

    Full Text Available This article examines how local food systems in the form of farmers' markets can enhance adaptive capacity and build social-ecological resilience. It does this by exploring the learning potential among farmers and customers. Learning can enable actors to adapt successfully and thus build adaptive capacity. Three forms of learning are investigated: instrumental, communicative, and emancipatory. These forms of learning constitute the foundation for lasting changes of behaviors. Local food systems are characterized by close links and opportunities for face-to-face interactions between consumers and producers of food, and are also institutions where farmers and customers can express and act upon their ethical values concerning food. However, local food systems are still a marginal phenomenon and cannot be accessed by all consumers. Interviews were held with customers and farmers, and the interactions between farmers and customers were observed at two farmers' markets in Sweden. Customers and farmers were found to learn and adapt to each other due to the opportunities offered by the farmers' markets. We found that farmers and customers learned in the instrumental and communicative domains, but could not confirm emancipatory learning. We concluded that the feedback between customers and farmers offers the potential for learning, which in turn contributes to adaptive capacity. This can be a driving force for building resilience in the food system.

  5. Climate change adaptation among Tibetan pastoralists: challenges in enhancing local adaptation through policy support.

    Science.gov (United States)

    Fu, Yao; Grumbine, R Edward; Wilkes, Andreas; Wang, Yun; Xu, Jian-Chu; Yang, Yong-Ping

    2012-10-01

    While researchers are aware that a mix of Local Ecological Knowledge (LEK), community-based resource management institutions, and higher-level institutions and policies can facilitate pastoralists' adaptation to climate change, policy makers have been slow to understand these linkages. Two critical issues are to what extent these factors play a role, and how to enhance local adaptation through government support. We investigated these issues through a case study of two pastoral communities on the Tibetan Plateau in China employing an analytical framework to understand local climate adaptation processes. We concluded that LEK and community-based institutions improve adaptation outcomes for Tibetan pastoralists through shaping and mobilizing resource availability to reduce risks. Higher-level institutions and policies contribute by providing resources from outside communities. There are dynamic interrelationships among these factors that can lead to support, conflict, and fragmentation. Government policy could enhance local adaptation through improvement of supportive relationships among these factors. While central government policies allow only limited room for overt integration of local knowledge/institutions, local governments often have some flexibility to buffer conflicts. In addition, government policies to support market-based economic development have greatly benefited adaptation outcomes for pastoralists. Overall, in China, there are still questions over how to create innovative institutions that blend LEK and community-based institutions with government policy making.

  6. Swarm-based adaptation: wayfinding support for lifelong learners

    NARCIS (Netherlands)

    Tattersall, Colin; Van den Berg, Bert; Van Es, René; Janssen, José; Manderveld, Jocelyn; Koper, Rob

    2004-01-01

    Please refer to the orinigal publication in: Tattersall, C. Van den Berg, B., Van Es, R., Janssen, J., Manderveld, J., Koper, R. (2004). Swarm-based adaptation: wayfinding support for lifelong learners. In P. de Bra & W. Nejdl, Adaptive Hypermedia and Adaptive Web-Based Systems (LNCS3137), (pp.

  7. Adaptive Learning in Weighted Network Games

    NARCIS (Netherlands)

    Bayer, Péter; Herings, P. Jean-Jacques; Peeters, Ronald; Thuijsman, Frank

    2017-01-01

    This paper studies adaptive learning in the class of weighted network games. This class of games includes applications like research and development within interlinked firms, crime within social networks, the economics of pollution, and defense expenditures within allied nations. We show that for

  8. Adaptive Learning in Medical Education: The Final Piece of Technology Enhanced Learning?

    Science.gov (United States)

    Sharma, Neel; Doherty, Iain; Dong, Chaoyan

    2017-09-01

    Technology enhanced learning (TEL) is now common practice in the field of medical education. One of the primary examples of its use is that of high fidelity simulation and computerised mannequins. Further examples include online learning modules, electronic portfolios, virtual patient interactions, massive open online courses and the flipped classroom movement. The rise of TEL has occurred primarily due to the ease of internet access enabling the retrieval and sharing of information in an instant. Furthermore, the compact nature of internet ready devices such as smartphones and laptops has meant that access to information can occur anytime and anywhere. From an educational perspective however, the current utilisation of TEL has been hindered by its lack of understanding of learners' needs. This is concerning, particularly as evidence highlights that during medical training, each individual learner has their own learning requirements and often achieves competency at different rates. In view of this, there has been interest in ensuring TEL is more learner aware and that the learning process should be more personalised. Adaptive learning can aim to achieve this by ensuring content is delivered according to the needs of the learner. This commentary highlights the move towards adaptive learning and the benefits of such an intervention.

  9. A Fuzzy Logic-Based Personalized Learning System for Supporting Adaptive English Learning

    Science.gov (United States)

    Hsieh, Tung-Cheng; Wang, Tzone-I; Su, Chien-Yuan; Lee, Ming-Che

    2012-01-01

    As a nearly global language, English as a Foreign Language (EFL) programs are essential for people wishing to learn English. Researchers have noted that extensive reading is an effective way to improve a person's command of English. Choosing suitable articles in accordance with a learner's needs, interests and ability using an e-learning system…

  10. Learning to bridge the gap between adaptive management and organisational culture

    Directory of Open Access Journals (Sweden)

    Richard J. Stirzaker

    2011-05-01

    Full Text Available Adaptive management is the problem-solving approach of choice proposed for complex and multistakeholder environments, which are, at best, only partly predictable. We discuss the implications of this approach as applicable to scientists, who have to overcome certain entrained behaviour patterns in order to participate effectively in an adaptive management process. The challenge does not end there. Scientists and managers soon discover that an adaptive management approach does not only challenge conventional scientific and management behaviour but also clashes with contemporary organisational culture. We explore the shortcomings and requirements of organisations with regard to enabling adaptive management. Our overall conclusion relates to whether organisations are learning-centred or not. Do we continue to filter out unfamiliar information which does not fit our world view and avoid situations where we might fail, or do we use new and challenging situations to reframe the question and prepare ourselves for continued learning? Conservation implications: For an organisation to effectively embrace adaptive management, its mangers and scientists may first have to adapt their own beliefs regarding their respective roles. Instead of seeking certainty for guiding decisions, managers and scientists should acknowledge a degree of uncertainty inherent to complex social and ecological systems and seek to learn from the patterns emerging from every decision and action. The required organisational culture is one of ongoing and purposeful learning with all relevant stakeholders. Such a learning culture is often talked about but rarely practised in the organisational environment.

  11. Learning Experiences Reuse Based on an Ontology Modeling to Improve Adaptation in E-Learning Systems

    Science.gov (United States)

    Hadj M'tir, Riadh; Rumpler, Béatrice; Jeribi, Lobna; Ben Ghezala, Henda

    2014-01-01

    Current trends in e-Learning focus mainly on personalizing and adapting the learning environment and learning process. Although their increasingly number, theses researches often ignore the concepts of capitalization and reuse of learner experiences which can be exploited later by other learners. Thus, the major challenge of distance learning is…

  12. The influence of student characteristics on the use of adaptive e-learning material

    NARCIS (Netherlands)

    van Seters, J. R.; Ossevoort, M. A.; Tramper, J.; Goedhart, M. J.

    Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive e-learning materials. Ninety-four students participated in the study. We determined characteristics

  13. An adaptive case management system to support integrated care services: Lessons learned from the NEXES project.

    Science.gov (United States)

    Cano, Isaac; Alonso, Albert; Hernandez, Carme; Burgos, Felip; Barberan-Garcia, Anael; Roldan, Jim; Roca, Josep

    2015-06-01

    Extensive deployment and sustainability of integrated care services (ICS) constitute an unmet need to reduce the burden of chronic conditions. The European Union project NEXES (2008-2013) assessed the deployment of four ICS encompassing the spectrum of severity of chronic patients. The current study aims to (i) describe the open source Adaptive Case Management (ACM) system (Linkcare®) developed to support the deployment of ICS at the level of healthcare district; (ii) to evaluate its performance; and, (iii) to identify key challenges for regional deployment of ICS. We first defined a conceptual model for ICS management and execution composed of five main stages. We then specified an associated logical model considering the dynamic runtime of ACM. Finally, we implemented the four ICS as a physical model with an ICS editor to allow professionals (case managers) to play active roles in adapting the system to their needs. Instances of ICS were then run in Linkcare®. Four ICS provided a framework for evaluating the system: Wellness and Rehabilitation (W&R) (number of patients enrolled in the study (n)=173); Enhanced Care (EC) in frail chronic patients to prevent hospital admissions, (n=848); Home Hospitalization and Early Discharge (HH/ED) (n=2314); and, Support to remote diagnosis (Support) (n=7793). The method for assessment of telemedicine applications (MAST) was used for iterative evaluation. Linkcare® supports ACM with shared-care plans across healthcare tiers and offers integration with provider-specific electronic health records. Linkcare® successfully contributed to the deployment of the four ICS: W&R facilitated long-term sustainability of training effects (p<0.01) and active life style (p<0.03); EC showed significant positive outcomes (p<0.05); HH/ED reduced on average 5 in-hospital days per patient with a 30-d re-admission rate of 10%; and, Support, enhanced community-based quality forced spirometry testing (p<0.01). Key challenges for regional deployment

  14. Adaptability and Life Satisfaction: The Moderating Role of Social Support.

    Science.gov (United States)

    Zhou, Mi; Lin, Weipeng

    2016-01-01

    The purpose of this study was to investigate the moderating role of social support in the relationship between adaptability and life satisfaction. Data were collected from 99 undergraduate freshmen in a Chinese university using a lagged design with a 1-month interval. Results demonstrated that social support moderated the relation between adaptability and life satisfaction, such that the positive relation between adaptability and life satisfaction was stronger for individuals with higher levels of social support than for individuals with lower levels of social support. The theoretical and practical implications of this result are discussed.

  15. Learning for Climate Change Adaptation among Selected ...

    African Journals Online (AJOL)

    Learning for Climate Change Adaptation among Selected Communities of Lusaka ... This research was aimed at surveying perceptions of climate change and ... This work is licensed under a Creative Commons Attribution 3.0 License.

  16. Heterogeneous Users in MOOC and their Adaptive Learning Needs

    Directory of Open Access Journals (Sweden)

    María Luisa SEIN-ECHALUCE LACLETA

    2017-02-01

    Full Text Available Many research works point out the overcrowding and the heterogeneity of participant’s profiles in Massive Open Online Courses (MOOC as the main causes of their low completion rate. On the other hand, the methodologies of personalization of the learning, along next to the technologies of the information, that allows to realize techniques of adaptativity, appear in international reports as an effective way to improve the learning. This paper explores the participante’ perception of their adaptive needs in this tupe of course, as well as their relationship with different aspects of the participants, such as: profiles (gender, age, geographical location and academic level, previous experience and knowledge about the topic of the MOOC and motivation to enroll the MOOC. The study is carried out through a survey completes by the participants in the MOOC Campus of Educational Innovation. We conclude that the age or gender of the participants does not significantly influence their need for adaptive techniques in a MOOC. However, living in a Latin American country, working as a manager or enrolling in a MOOC with a specific motivation, are some of the factors that influence in the desire for adaptive techniques in a MOOC. The obtained results will contribute to improve the adaptive designs of the MOOC and will be easily transferable to any online training course, in blended or virtual learning.

  17. promoting self directed learning in simulation based discovery learning environments through intelligent support.

    NARCIS (Netherlands)

    Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter

    2000-01-01

    Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for

  18. Adaptive polymeric system for Hebbian type learning

    OpenAIRE

    2011-01-01

    Abstract We present the experimental realization of an adaptive polymeric system displaying a ?learning behaviour?. The system consists on a statistically organized networks of memristive elements (memory-resitors) based on polyaniline. In a such network the path followed by the current increments its conductivity, a property which makes the system able to mimic Hebbian type learning and have application in hardware neural networks. After discussing the working principle of ...

  19. Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation

    OpenAIRE

    Chen, Tianyi; Ling, Qing; Giannakis, Georgios B.

    2017-01-01

    Network resource allocation shows revived popularity in the era of data deluge and information explosion. Existing stochastic optimization approaches fall short in attaining a desirable cost-delay tradeoff. Recognizing the central role of Lagrange multipliers in network resource allocation, a novel learn-and-adapt stochastic dual gradient (LA-SDG) method is developed in this paper to learn the sample-optimal Lagrange multiplier from historical data, and accordingly adapt the upcoming resource...

  20. Creating a supportive learning environment for students with learning difficulties

    OpenAIRE

    Grah, Jana

    2013-01-01

    Co-building of supporting learning environment for the learners with learning difficulties is one of the 21st century inclusive school’s elements. Since the physical presence of learners with learning difficulties in the classroom does not self-evidently lead to an effective co-operation and implementation of 21st century inclusive school, I have dedicated my doctor thesis to the establishment of supporting learning environment for the learners with learning difficulties in primary school wit...

  1. Learning Transferable Features with Deep Adaptation Networks

    OpenAIRE

    Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

    2015-01-01

    Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

  2. Psychosocial Adjustment over a Two-Year Period in Children Referred for Learning Problems: Risk, Resilience, and Adaptation.

    Science.gov (United States)

    Sorensen, Lisa G.; Forbes, Peter W.; Bernstein, Jane H.; Weiler, Michael D.; Mitchell, William M.; Waber, Deborah P.

    2003-01-01

    A 2-year study evaluated the relationship among psychosocial adjustment, changes in academic skills, and contextual factors in 100 children (ages 7-11) with learning problems. Contextual variables were significantly associated with psychosocial adaptation, including the effectiveness of the clinical assessment, extent of academic support, and the…

  3. A planning quality evaluation tool for prostate adaptive IMRT based on machine learning

    International Nuclear Information System (INIS)

    Zhu Xiaofeng; Ge Yaorong; Li Taoran; Thongphiew, Danthai; Yin Fangfang; Wu, Q Jackie

    2011-01-01

    Purpose: To ensure plan quality for adaptive IMRT of the prostate, we developed a quantitative evaluation tool using a machine learning approach. This tool generates dose volume histograms (DVHs) of organs-at-risk (OARs) based on prior plans as a reference, to be compared with the adaptive plan derived from fluence map deformation. Methods: Under the same configuration using seven-field 15 MV photon beams, DVHs of OARs (bladder and rectum) were estimated based on anatomical information of the patient and a model learned from a database of high quality prior plans. In this study, the anatomical information was characterized by the organ volumes and distance-to-target histogram (DTH). The database consists of 198 high quality prostate plans and was validated with 14 cases outside the training pool. Principal component analysis (PCA) was applied to DVHs and DTHs to quantify their salient features. Then, support vector regression (SVR) was implemented to establish the correlation between the features of the DVH and the anatomical information. Results: DVH/DTH curves could be characterized sufficiently just using only two or three truncated principal components, thus, patient anatomical information was quantified with reduced numbers of variables. The evaluation of the model using the test data set demonstrated its accuracy ∼80% in prediction and effectiveness in improving ART planning quality. Conclusions: An adaptive IMRT plan quality evaluation tool based on machine learning has been developed, which estimates OAR sparing and provides reference in evaluating ART.

  4. Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

    Science.gov (United States)

    Choi, Woojae; Jacobs, Ronald L.

    2011-01-01

    While workplace learning includes formal and informal learning, the relationship between the two has been overlooked, because they have been viewed as separate entities. This study investigated the effects of formal learning, personal learning orientation, and supportive learning environment on informal learning among 203 middle managers in Korean…

  5. Adaptability and Life Satisfaction: The Moderating Role of Social Support

    Science.gov (United States)

    Zhou, Mi; Lin, Weipeng

    2016-01-01

    The purpose of this study was to investigate the moderating role of social support in the relationship between adaptability and life satisfaction. Data were collected from 99 undergraduate freshmen in a Chinese university using a lagged design with a 1-month interval. Results demonstrated that social support moderated the relation between adaptability and life satisfaction, such that the positive relation between adaptability and life satisfaction was stronger for individuals with higher levels of social support than for individuals with lower levels of social support. The theoretical and practical implications of this result are discussed. PMID:27516753

  6. Adaptive learning by extremal dynamics and negative feedback

    International Nuclear Information System (INIS)

    Bak, Per; Chialvo, Dante R.

    2001-01-01

    We describe a mechanism for biological learning and adaptation based on two simple principles: (i) Neuronal activity propagates only through the network's strongest synaptic connections (extremal dynamics), and (ii) the strengths of active synapses are reduced if mistakes are made, otherwise no changes occur (negative feedback). The balancing of those two tendencies typically shapes a synaptic landscape with configurations which are barely stable, and therefore highly flexible. This allows for swift adaptation to new situations. Recollection of past successes is achieved by punishing synapses which have once participated in activity associated with successful outputs much less than neurons that have never been successful. Despite its simplicity, the model can readily learn to solve complicated nonlinear tasks, even in the presence of noise. In particular, the learning time for the benchmark parity problem scales algebraically with the problem size N, with an exponent k∼1.4

  7. Adaptive E-learning System in Secondary Education

    Directory of Open Access Journals (Sweden)

    Sofija Tosheva

    2012-02-01

    Full Text Available In this paper we describe an adaptive web application E-school, where students can adjust some features according to their preferences and learning style. This e-learning environment enables monitoring students progress, total time students have spent in the system, their activity on the forums, the overall achievements in lessons learned, tests performed and solutions to given projects. Personalized assistance that teacher provides in a traditional classroom is not easy to implement. Students have regular contact with teachers using e-mail tools and conversation, so teacher get mentoring role for each student. The results of exploitation of the e-learning system show positive impact in acquiring the material and improvement of student’s achievements.

  8. Evolutionary and adaptive learning in complex markets: a brief summary

    Science.gov (United States)

    Hommes, Cars H.

    2007-06-01

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

  9. Stimulating the cerebellum affects visuomotor adaptation but not intermanual transfer of learning.

    Science.gov (United States)

    Block, Hannah; Celnik, Pablo

    2013-12-01

    When systematic movement errors occur, the brain responds with a systematic change in motor behavior. This type of adaptive motor learning can transfer intermanually; adaptation of movements of the right hand in response to training with a perturbed visual signal (visuomotor adaptation) may carry over to the left hand. While visuomotor adaptation has been studied extensively, it is unclear whether the cerebellum, a structure involved in adaptation, is important for intermanual transfer as well. We addressed this question with three experiments in which subjects reached with their right hands as a 30° visuomotor rotation was introduced. Subjects received anodal or sham transcranial direct current stimulation on the trained (experiment 1) or untrained (experiment 2) hemisphere of the cerebellum, or, for comparison, motor cortex (M1). After the training period, subjects reached with their left hand, without visual feedback, to assess intermanual transfer of learning aftereffects. Stimulation of the right cerebellum caused faster adaptation, but none of the stimulation sites affected transfer. To ascertain whether cerebellar stimulation would increase transfer if subjects learned faster as well as a larger amount, in experiment 3 anodal and sham cerebellar groups experienced a shortened training block such that the anodal group learned more than sham. Despite the difference in adaptation magnitude, transfer was similar across these groups, although smaller than in experiment 1. Our results suggest that intermanual transfer of visuomotor learning does not depend on cerebellar activity and that the number of movements performed at plateau is an important predictor of transfer.

  10. How assessment and reflection relate to more effective learning in adaptive management

    Directory of Open Access Journals (Sweden)

    Harry Biggs

    2011-05-01

    Two other studies in the Kruger National Park, which have examined learning specifically, are also discussed. One of them suggests that in a complex environment, learning necessarily has a dual nature, with each component of seven contrasting pairs of the aspects of learning in partial tension with the other. We use these dualities to further probe assessment, reflection, inter-relatedness and learning in the cases presented. Each contrasting aspect of a ‘learning duality’ turns out to emphasise either assessment or reflection, which reinforces the idea that both are needed to facilitate sufficient learning for successful adaptive management. We hope this analysis can act as a springboard for further study, practice and reflection on these important and often underrated components of adaptive management. Conservation implications: The better understanding of assessment and reflection as being largely separate but complementary actions will assist adaptive management practitioners to give explicit attention to both, and to relate them better to each other.

  11. Farming System Evolution and Adaptive Capacity: Insights for Adaptation Support

    Directory of Open Access Journals (Sweden)

    Jami L. Dixon

    2014-02-01

    Full Text Available Studies of climate impacts on agriculture and adaptation often provide current or future assessments, ignoring the historical contexts farming systems are situated within. We investigate how historical trends have influenced farming system adaptive capacity in Uganda using data from household surveys, semi-structured interviews, focus-group discussions and observations. By comparing two farming systems, we note three major findings: (1 similar trends in farming system evolution have had differential impacts on the diversity of farming systems; (2 trends have contributed to the erosion of informal social and cultural institutions and an increasing dependence on formal institutions; and (3 trade-offs between components of adaptive capacity are made at the farm-scale, thus influencing farming system adaptive capacity. To identify the actual impacts of future climate change and variability, it is important to recognize the dynamic nature of adaptation. In practice, areas identified for further adaptation support include: shift away from one-size-fits-all approach the identification and integration of appropriate modern farming method; a greater focus on building inclusive formal and informal institutions; and a more nuanced understanding regarding the roles and decision-making processes of influential, but external, actors. More research is needed to understand farm-scale trade-offs and the resulting impacts across spatial and temporal scales.

  12. Organizational Support in Online Learning Environments: Examination of Support Factors in Corporate Online Learning Implementation

    Science.gov (United States)

    Schultz, Thomas L.; Correia, Ana-Paula

    2015-01-01

    This article explores the role of different types of support in corporate online learning programs. Most research has not specifically focused on all of the support factors required to provide a corporate online learning program, although many research studies address several in regards to the research outcome. An effort was made in this article…

  13. Adaptation and learning: characteristic time scales of performance dynamics.

    Science.gov (United States)

    Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

    2009-12-01

    A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

  14. Applications of Adaptive Learning Controller to Synthetic Aperture Radar.

    Science.gov (United States)

    1985-02-01

    TERMS (Continue on retuerse if necessary and identify by block num ber) FIELD YGROUP SUB. GR. Adaptive control, aritificial intelligence , synthetic aetr1...application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning...wavelength Al SE!RI M RADAR DIVISION REFERENCES 1. Barto, A.G. and R.S. Sutton, Goal Seeking Components for Adaptive Intelligence : An Initial Assessment

  15. The Dynamics of Learning and the Emergence of Distributed Adaption

    National Research Council Canada - National Science Library

    Crutchfield, James P

    2006-01-01

    .... The second goal was to adapt this single-agent learning theory and associated learning algorithms to the distributed setting in which a population of autonomous agents communicate to achieve a desired group task...

  16. SU-D-BRB-05: Quantum Learning for Knowledge-Based Response-Adaptive Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    El Naqa, I; Ten, R [Haken University of Michigan, Ann Arbor, MI (United States)

    2016-06-15

    Purpose: There is tremendous excitement in radiotherapy about applying data-driven methods to develop personalized clinical decisions for real-time response-based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics-inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient’s characteristics and optimize outcomes. Methods: We studied 88 liver SBRT patients with 35 on non-adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split-course of 3+2 fractions with a month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5-variable state represented by patient’s clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision-making to adapt at one month was considered. The MDP objective was defined by the complication-free tumor control (P{sup +}=TCPx(1-NTCP)). A simple regression model represented state-action mapping. Single bit in classical MDP and a qubit of 2-superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q-learning and quantum searching was performed using Grover’s algorithm, which applies uniform superposition over possible states and yields quadratic speed-up. Results: Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous-courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while the

  17. Neural predictors of sensorimotor adaptation rate and savings.

    Science.gov (United States)

    Cassady, Kaitlin; Ruitenberg, Marit; Koppelmans, Vincent; Reuter-Lorenz, Patricia; De Dios, Yiri; Gadd, Nichole; Wood, Scott; Riascos Castenada, Roy; Kofman, Igor; Bloomberg, Jacob; Mulavara, Ajitkumar; Seidler, Rachael

    2018-04-01

    In this study, we investigate whether individual variability in the rate of visuomotor adaptation and multiday savings is associated with differences in regional gray matter volume and resting-state functional connectivity. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. Functional connectivity strength between sensorimotor, dorsal cingulate, and temporoparietal regions of the brain was found to predict the rate of learning during the early phase of the adaptation task. In contrast, default mode network connectivity strength was found to predict both the rate of learning during the late adaptation phase and savings. As for structural predictors, greater gray matter volume in temporoparietal and occipital regions predicted faster early learning, whereas greater gray matter volume in superior posterior regions of the cerebellum predicted faster late learning. These findings suggest that the offline neural predictors of early adaptation may facilitate the cognitive aspects of sensorimotor adaptation, supported by the involvement of temporoparietal and cingulate networks. The offline neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations. © 2017 Wiley Periodicals, Inc.

  18. Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System

    Science.gov (United States)

    Chen, Ching-Huei; Chang, Shu-Wei

    2015-01-01

    The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…

  19. Adaptive support for user interface customization : a study in radiology

    NARCIS (Netherlands)

    Jorritsma, Wiard; Cnossen, Fokie; van Ooijen, Peter M. A.

    Objectives: This study aimed to evaluate the usefulness of adaptive customization support in a natural work environment: the Picture Archiving and Communication System (PACS) in radiology. Methods: Adaptive support was given in the form of customization suggestions, generated based on behavioral

  20. A Framework for Creating Semantically Adaptive Collaborative E-learning Environments

    Directory of Open Access Journals (Sweden)

    Marija Cubric

    2009-09-01

    Full Text Available In this paper we present a framework that can be used to generate web-based, semantically adaptive, e-learning and computer-assisted assessment (CAA tools for any given knowledge domain, based upon dynamic ontological modeling. We accomplish this by generating “learning ontologies” for a given knowledge domain. The generated learning ontologies are built upon our previous work on a domain “Glossary” ontology and augmented with additional conceptual relations from the WordNet 3.0 lexical database, using Text2Onto, an open source ontology extraction tool. The main novelty of this work is in “on the fly” generation of computer assisted assessments based on the underlying ontology and pre-defined question templates that are founded on the Bloom’s taxonomy of educational objectives. The main deployment scenario for the framework is a web-service providing collaborative e- learning and knowledge management capabilities to various learning communities. The framework can be extended to provide collection and exploitation of the users’ learning behaviour metrics, in order to further adapt the generated e-learning environment to the learners’ needs.

  1. Breast image feature learning with adaptive deconvolutional networks

    Science.gov (United States)

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  2. Supporting Learning with Wireless Sensor Data

    Directory of Open Access Journals (Sweden)

    Arttu Perttula

    2013-03-01

    Full Text Available In this article, learning is studied in in situ applications that involve sensors. The main questions are how to conceptualize experiential learning involving sensors and what kinds of learning applications using sensors already exist or could be designed. It is claimed that experiential learning, context information and sensor data supports twenty first century learning. The concepts of context, technology-mediated experiences, shared felt experiences and experiential learning theory will be used to describe a framework for sensor-based mobile learning environments. Several scenarios and case examples using sensors and sensor data will be presented, and they will be analyzed using the framework. Finally, the article contributes to the discussion concerning the role of technology-mediated learning experiences and collective sensor data in developing twenty first century learning by characterizing what kinds of skills and competences are supported in learning situations that involve sensors.

  3. Integrating Adaptive Games in Student-Centered Virtual Learning Environments

    Science.gov (United States)

    del Blanco, Angel; Torrente, Javier; Moreno-Ger, Pablo; Fernandez-Manjon, Baltasar

    2010-01-01

    The increasing adoption of e-Learning technology is facing new challenges, such as how to produce student-centered systems that can be adapted to each student's needs. In this context, educational video games are proposed as an ideal medium to facilitate adaptation and tracking of students' performance for assessment purposes, but integrating the…

  4. Adaptive Learning and Thinking Style to Improve E-Learning Environment Using Neural Network (ALTENN) Model

    OpenAIRE

    Dagez, Hanan Ettaher; Ambarka, Ali Elghali

    2015-01-01

     In recent years we have witnessed an increasingly heightened awareness of the potential benefits of adaptively in e-learning. This has been mainly driven by the realization that the ideal of individualized learning (i.e., learning tailored to the specific requirements and preferences of the individual) cannot be achieved, especially at a “massive” scale, using traditional approaches. In e-learning when the learning style of the student is not compatible with the teaching style of the teacher...

  5. The influence of student characteristics on the use of adaptive e-learning material

    NARCIS (Netherlands)

    Seters, van J.R.; Ossevoort, M.A.; Tramper, J.; Goedhart, M.J.

    2012-01-01

    Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive elearning materials. Ninety-four students participated in the study. We determined characteristics

  6. Adaptive Knowledge Management of Project-Based Learning

    Science.gov (United States)

    Tilchin, Oleg; Kittany, Mohamed

    2016-01-01

    The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…

  7. Statistical Learning Framework with Adaptive Retraining for Condition-Based Maintenance

    International Nuclear Information System (INIS)

    An, Sang Ha; Chang, Soon Heung; Heo, Gyun Young; Seo, Ho Joon; Kim, Su Young

    2009-01-01

    As systems become more complex and more critical in our daily lives, the need for the maintenance based on the reliable monitoring and diagnosis has become more apparent. However, in reality, the general opinion has been that 'maintenance is a necessary evil' or 'nothing can be done to improve maintenance costs'. Perhaps these were true statements twenty years ago when many of the diagnostic technologies were not fully developed. The developments of microprocessor or computer based instrumentation that can be used to monitor the operating condition of plant equipment, machinery and systems have provided the means to manage the maintenance operation. They have provided the means to reduce or eliminate unnecessary repairs, prevent catastrophic machine failures and reduce the negative impact of the maintenance operation on the profitability of manufacturing and production plants. Condition-based maintenance (CBM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. Most of the statistical learning techniques are only valid as long as the physics of a system does not change. If any significant change such as the replacement of a component or equipment occurs in the system, the statistical learning model should be re-trained or re-developed to adapt the new system. In this research, authors will propose a statistical learning framework which can be applicable for various CBMs, and the concept of the adaptive retraining technique will be described to support the execution of the framework so that the monitoring system does not need to be re-developed or re-trained even though there are any significant changes in the system or component

  8. Basal ganglia-dependent processes in recalling learned visual-motor adaptations.

    Science.gov (United States)

    Bédard, Patrick; Sanes, Jerome N

    2011-03-01

    Humans learn and remember motor skills to permit adaptation to a changing environment. During adaptation, the brain develops new sensory-motor relationships that become stored in an internal model (IM) that may be retained for extended periods. How the brain learns new IMs and transforms them into long-term memory remains incompletely understood since prior work has mostly focused on the learning process. A current model suggests that basal ganglia, cerebellum, and their neocortical targets actively participate in forming new IMs but that a cerebellar cortical network would mediate automatization. However, a recent study (Marinelli et al. 2009) reported that patients with Parkinson's disease (PD), who have basal ganglia dysfunction, had similar adaptation rates as controls but demonstrated no savings at recall tests (24 and 48 h). Here, we assessed whether a longer training session, a feature known to increase long-term retention of IM in healthy individuals, could allow PD patients to demonstrate savings. We recruited PD patients and age-matched healthy adults and used a visual-motor adaptation paradigm similar to the study by Marinelli et al. (2009), doubling the number of training trials and assessed recall after a short and a 24-h delay. We hypothesized that a longer training session would allow PD patients to develop an enhanced representation of the IM as demonstrated by savings at the recall tests. Our results showed that PD patients had similar adaptation rates as controls but did not demonstrate savings at both recall tests. We interpret these results as evidence that fronto-striatal networks have involvement in the early to late phase of motor memory formation, but not during initial learning.

  9. Supporting Children with Learning Disabilities

    OpenAIRE

    John k. McNamara

    2010-01-01

    This paper presents a prevention model for supporting children with learning disabilities. The model holds that children can be identified as at-risk for learning disabilities by identifying and supporting potential academic failure early in their elementary years. A prevention model includes two elements, identification and instruction. Identification entails recognizing those children at-risk for poor achievement in the early primary grades. The second component of the model is to...

  10. Climate change, mitigation and adaptation with uncertainty and learning

    International Nuclear Information System (INIS)

    Ingham, Alan; Ma Jie; Ulph, Alistair

    2007-01-01

    One of the major issues in climate change policy is how to deal with the considerable uncertainty that surrounds many of the elements. Some of these uncertainties will be resolved through the process of further research. This process of learning raises a crucial timing question: should society delay taking action in anticipation of obtaining better information, or should it accelerate action, because we might learn that climate change is much more serious than expected. Much of the analysis to date has focussed on the case where the actions available to society are just the mitigation of emissions, and where there is little or no role for learning. We extend the analysis to allow for both mitigation and adaptation. We show that including adaptation weakens the effect of the irreversibility constraint and so, for this model, makes it more likely that the prospect of future learning should lead to less action now to deal with climate change. We review the empirical literature on climate change policy with uncertainty, learning, and irreversibility, and show that to date the effects on current policy are rather small, though this may reflect the particular choice of models employed

  11. ACT-R Electronic Bookshelf: An Adaptive System To Support Learning ACT-R on the Web.

    Science.gov (United States)

    Brusilovsky, Peter; Anderson, John

    This paper describes the electronic ACT-R Bookshelf, a system which supports learning ACT-R, a well-known theory in the field of cognitive psychology, over the World Wide Web. ACT-R Bookshelf is a collection of electronic books on various aspects of ACT-R. The primary role of ACT-R Bookshelf is to serve as a 24-hour information resource for…

  12. Three Philosophical Pillars That Support Collaborative Learning.

    Science.gov (United States)

    Maltese, Ralph

    1991-01-01

    Discusses three philosophical pillars that support collaborative learning: "spaces of appearance," active engagement, and ownership. Describes classroom experiences with collaborative learning supported by these pillars. (PRA)

  13. A Module for Adaptive Course Configuration and Assessment in Moodle

    Science.gov (United States)

    Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia

    Personalization and Adaptation are among the main challenges in the field of e-learning, where currently just few Learning Management Systems, mostly experimental ones, support such features. In this work we present an architecture that allows Moodle to interact with the Lecomps system, an adaptive learning system developed earlier by our research group, that has been working in a stand-alone modality so far. In particular, the Lecomps responsibilities are circumscribed to the sole production of personalized learning objects sequences and to the management of the student model, leaving to Moodle all the rest of the activities for course delivery. The Lecomps system supports the "dynamic" adaptation of learning objects sequences, basing on the student model, i.e., learner's Cognitive State and Learning Style. Basically, this work integrates two main Lecomps tasks into Moodle, to be directly managed by it: Authentication and Quizzes.

  14. An Adaptive Web-Based Support to e-Education in Robotics and Automation

    Science.gov (United States)

    di Giamberardino, Paolo; Temperini, Marco

    The paper presents the hardware and software architecture of a remote laboratory, with robotics and automation applications, devised to support e-teaching and e-learning activities, at an undergraduate level in computer engineering. The hardware is composed by modular structures, based on the Lego Mindstorms components: they are reasonably sophisticated in terms of functions, pretty easy to use, and sufficiently affordable in terms of cost. Moreover, being the robots intrinsically modular, wrt the number and distribution of sensors and actuators, they are easily and quickly reconfigurable. A web application makes the laboratory and its robots available via internet. The software framework allows the teacher to define, for the course under her/his responsibility, a learning path made of different and differently complex exercises, graduated in terms of the "difficulty" they require to meet and of the "competence" that the solver is supposed to have shown. The learning path of exercises is adapted to the individual learner's progressively growing competence: at any moment, only a subset of the exercises is available (depending on how close their levels of competence and difficulty are to those of the exercises already solved by the learner).

  15. Adaptive Global Innovative Learning Environment for Glioblastoma: GBM AGILE.

    Science.gov (United States)

    Alexander, Brian M; Ba, Sujuan; Berger, Mitchel S; Berry, Donald A; Cavenee, Webster K; Chang, Susan M; Cloughesy, Timothy F; Jiang, Tao; Khasraw, Mustafa; Li, Wenbin; Mittman, Robert; Poste, George H; Wen, Patrick Y; Yung, W K Alfred; Barker, Anna D

    2018-02-15

    Glioblastoma (GBM) is a deadly disease with few effective therapies. Although much has been learned about the molecular characteristics of the disease, this knowledge has not been translated into clinical improvements for patients. At the same time, many new therapies are being developed. Many of these therapies have potential biomarkers to identify responders. The result is an enormous amount of testable clinical questions that must be answered efficiently. The GBM Adaptive Global Innovative Learning Environment (GBM AGILE) is a novel, multi-arm, platform trial designed to address these challenges. It is the result of the collective work of over 130 oncologists, statisticians, pathologists, neurosurgeons, imagers, and translational and basic scientists from around the world. GBM AGILE is composed of two stages. The first stage is a Bayesian adaptively randomized screening stage to identify effective therapies based on impact on overall survival compared with a common control. This stage also finds the population in which the therapy shows the most promise based on clinical indication and biomarker status. Highly effective therapies transition in an inferentially seamless manner in the identified population to a second confirmatory stage. The second stage uses fixed randomization to confirm the findings from the first stage to support registration. Therapeutic arms with biomarkers may be added to the trial over time, while others complete testing. The design of GBM AGILE enables rapid clinical testing of new therapies and biomarkers to speed highly effective therapies to clinical practice. Clin Cancer Res; 24(4); 737-43. ©2017 AACR . ©2017 American Association for Cancer Research.

  16. Information systems supported organizational learning as a competitive advantage

    Directory of Open Access Journals (Sweden)

    Jose Manuel Arias

    2013-07-01

    Full Text Available Purpose: The purpose of this paper is to analyze the characteristics that make information systems useful in gathering and processing information with the aim of organizational learning and subsequent structural adaptation for better fitting to market requirements. Design/methodology/approach: Adaptation is a must when turning to foster the competitiveness and sustainability of the organization. Findings and Originality/value: It is clear that information systems can really create a difference in the way an organization acquires information from its environment and from itself in order to achieve a high-quality decision taking process. Research limitations/implications: Organizations have to look inside themselves in order to ensure the comprehension of their core competencies and the way they carry them out. Practical implications: Organizational learning is one of the means employed by organizations to get adapted to their surrounding environment. Social implications: Systems engineering techniques can be applied in order to leverage these core competencies and make organizations adaptable to the organizational environment requirements through the use of information systems. Originality/value: To obtain competitive advantages in the market. Keywords: competitive advantage, information systems, knowledge management, & the learning organization.

  17. An Adaptive Approach to Managing Knowledge Development in a Project-Based Learning Environment

    Science.gov (United States)

    Tilchin, Oleg; Kittany, Mohamed

    2016-01-01

    In this paper we propose an adaptive approach to managing the development of students' knowledge in the comprehensive project-based learning (PBL) environment. Subject study is realized by two-stage PBL. It shapes adaptive knowledge management (KM) process and promotes the correct balance between personalized and collaborative learning. The…

  18. Extensible Adaptive System for STEM Learning

    Science.gov (United States)

    2013-07-16

    Copyright 2013 Raytheon BBN Technologies Corp. All Rights Reserved ONR STEM Grand Challenge Extensible Adaptive System for STEM Learning ...Contract # N00014-12-C-0535 Raytheon BBN Technologies Corp. (BBN) Reference # 14217 In partial fulfillment of contract deliverable item # A001...Quarterly Progress Report #2 April 7, 2013 –July 6, 2013 Submitted July 16, 2013 BBN Technical POC: John Makhoul Raytheon BBN Technologies

  19. Fast But Fleeting: Adaptive Motor Learning Processes Associated with Aging and Cognitive Decline

    Science.gov (United States)

    Trewartha, Kevin M.; Garcia, Angeles; Wolpert, Daniel M.

    2014-01-01

    Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly—and that has been linked to explicit memory—and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. PMID:25274819

  20. Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

    Science.gov (United States)

    Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

    2014-10-01

    Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.

  1. Understanding, Evaluating, and Supporting Self-Regulated Learning Using Learning Analytics

    Science.gov (United States)

    Roll, Ido; Winne, Philip H.

    2015-01-01

    Self-regulated learning is an ongoing process rather than a single snapshot in time. Naturally, the field of learning analytics, focusing on interactions and learning trajectories, offers exciting opportunities for analyzing and supporting self-regulated learning. This special section highlights the current state of research at the intersection of…

  2. A Framework for Adaptive Learning Design in a Web-Conferencing Environment

    Science.gov (United States)

    Bower, Matt

    2016-01-01

    Many recent technologies provide the ability to dynamically adjust the interface depending on the emerging cognitive and collaborative needs of the learning episode. This means that educators can adaptively re-design the learning environment during the lesson, rather than purely relying on preemptive learning design thinking. Based on a…

  3. A neural learning classifier system with self-adaptive constructivism for mobile robot control.

    Science.gov (United States)

    Hurst, Jacob; Bull, Larry

    2006-01-01

    For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

  4. Evaluation framework based on fuzzy measured method in adaptive learning systems

    OpenAIRE

    Houda Zouari Ounaies, ,; Yassine Jamoussi; Henda Hajjami Ben Ghezala

    2008-01-01

    Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners’ needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase. Adaptation methods are a basic factor to guaranty an effective adaptation. This issue is referred as meta-adaptation in numerous researches. In our research...

  5. 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…

  6. Design Framework for an Adaptive MOOC Enhanced by Blended Learning

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2016-01-01

    The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional...

  7. Learning and adaptation: neural and behavioural mechanisms behind behaviour change

    Science.gov (United States)

    Lowe, Robert; Sandamirskaya, Yulia

    2018-01-01

    This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

  8. Optical implementations of associative networks with versatile adaptive learning capabilities.

    Science.gov (United States)

    Fisher, A D; Lippincott, W L; Lee, J N

    1987-12-01

    Optical associative, parallel-processing architectures are being developed using a multimodule approach, where a number of smaller, adaptive, associative modules are nonlinearly interconnected and cascaded under the guidance of a variety of organizational principles to structure larger architectures for solving specific problems. A number of novel optical implementations with versatile adaptive learning capabilities are presented for the individual associative modules, including holographic configurations and five specific electrooptic configurations. The practical issues involved in real optical architectures are analyzed, and actual laboratory optical implementations of associative modules based on Hebbian and Widrow-Hoff learning rules are discussed, including successful experimental demonstrations of their operation.

  9. Enhancing Brigade Combat Team Adaptability

    Science.gov (United States)

    2010-06-11

    Developing Learning Infrastructures (Training, Education , Practice, Research, Doctrine) -Create a shared vision -Build the business case (assess/Buy...To effectively respond to the characteristics of the operational environment, Brigade Combat Teams must be able to learn constantly from experience...behavior. Organizational adaptive behavior consists of three supporting emergent behaviors which are: self-organization, learning , and organizational

  10. 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…

  11. Enhancing Student Adaption to a Case Based Learning Environment

    DEFF Research Database (Denmark)

    Jensen, Lars Peter

    2010-01-01

    these at the end of the semester, showing the development of the student in terms of adapting to the learning model. The idea will be explained more closely in the final paper. RESEARCH METHOD The research part of the experiment was carried out as action research, as the teacher of the course in the same time......INTRODUCTION Since Aalborg University (AAU) was started it has been using an educational model, where Problem Based Learning is the turning point. Each semester the students on the Engineering Educations form groups of 3-6 persons, which uses half of the study time within the semester to solve......) in groups. It appeared to be difficult for the students to adapt to two different PBL approaches at the same time, and with the project being the most popular the learning outcome of the case studies was not satisfactory after the first semester, but improved on the following semesters. In 2009...

  12. Robust Visual Knowledge Transfer via Extreme Learning Machine Based Domain Adaptation.

    Science.gov (United States)

    Zhang, Lei; Zhang, David

    2016-08-10

    We address the problem of visual knowledge adaptation by leveraging labeled patterns from source domain and a very limited number of labeled instances in target domain to learn a robust classifier for visual categorization. This paper proposes a new extreme learning machine based cross-domain network learning framework, that is called Extreme Learning Machine (ELM) based Domain Adaptation (EDA). It allows us to learn a category transformation and an ELM classifier with random projection by minimizing the -norm of the network output weights and the learning error simultaneously. The unlabeled target data, as useful knowledge, is also integrated as a fidelity term to guarantee the stability during cross domain learning. It minimizes the matching error between the learned classifier and a base classifier, such that many existing classifiers can be readily incorporated as base classifiers. The network output weights cannot only be analytically determined, but also transferrable. Additionally, a manifold regularization with Laplacian graph is incorporated, such that it is beneficial to semi-supervised learning. Extensively, we also propose a model of multiple views, referred as MvEDA. Experiments on benchmark visual datasets for video event recognition and object recognition, demonstrate that our EDA methods outperform existing cross-domain learning methods.

  13. Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

    Science.gov (United States)

    Lee, Chuen-Chien

    1991-01-01

    Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

  14. 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,

  15. A New Approach to Teaching Biomechanics Through Active, Adaptive, and Experiential Learning.

    Science.gov (United States)

    Singh, Anita

    2017-07-01

    Demand of biomedical engineers continues to rise to meet the needs of healthcare industry. Current training of bioengineers follows the traditional and dominant model of theory-focused curricula. However, the unmet needs of the healthcare industry warrant newer skill sets in these engineers. Translational training strategies such as solving real world problems through active, adaptive, and experiential learning hold promise. In this paper, we report our findings of adding a real-world 4-week problem-based learning unit into a biomechanics capstone course for engineering students. Surveys assessed student perceptions of the activity and learning experience. While students, across three cohorts, felt challenged to solve a real-world problem identified during the simulation lab visit, they felt more confident in utilizing knowledge learned in the biomechanics course and self-directed research. Instructor evaluations indicated that the active and experiential learning approach fostered their technical knowledge and life-long learning skills while exposing them to the components of adaptive learning and innovation.

  16. Impact of Adapted Hypermedia on Undergraduate Students' Learning of Astronomy in an Elearning Environment

    Science.gov (United States)

    Zuel, Brian

    The purpose of this dissertation was to examine the effectiveness of matching learners' optimal learning styles to their overall knowledge retention. The study attempted to determine if learners who are placed in an online learning environment that matches their optimal learning styles will retain the information at a higher rate than those learners who are not in an adapted learning environment. There were 56 participants that took one of two lessons; the first lesson was textual based, had no hypertext, and was not influenced heavily by the coherence principle, while the second lesson was multimedia based utilizing hypermedia guided by the coherence principle. Each participant took Felder and Soloman's (1991, 2000) Index of Learning Styles (ILS) questionnaire and was classified using the Felder-Silverman Learning Style Model (FSLSM; 1998) into four individual categories. Groups were separated using the Visual/Verbal section of the FSLSM with 55% (n = 31) of participants going to the adapted group, and 45% (n =25) of participants going to the non-adapted group. Each participant completed an immediate posttest directly after the lesson and a retention posttest a week later. Several repeated measures MANOVA tests were conducted to measure the significance of differences in the tests between groups and within groups. Repeated measures MANOVA tests were conducted to determine if significance existed between the immediate posttest results and the retention posttest results. Also, participants were asked their perspectives if the lesson type they received was beneficial to their perceived learning of the material. Of the 56 students who took part in this study, 31 students were placed in the adapted group and 25 in the non-adapted group based on outcomes of the ILS and the FLSSM. No significant differences were found between groups taking the multimedia lesson and the textual lesson in the immediate posttest. No significant differences were found between the adapted and

  17. Educational Multimedia Profiling Recommendations for Device-Aware Adaptive Mobile Learning

    Science.gov (United States)

    Moldovan, Arghir-Nicolae; Ghergulescu, Ioana; Muntean, Cristina Hava

    2014-01-01

    Mobile learning is seeing a fast adoption with the increasing availability and affordability of mobile devices such as smartphones and tablets. As the creation and consumption of educational multimedia content on mobile devices is also increasing fast, educators and mobile learning providers are faced with the challenge to adapt multimedia type…

  18. Adaptive and accelerated tracking-learning-detection

    Science.gov (United States)

    Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

    2013-08-01

    An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

  19. Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

    Science.gov (United States)

    Hsu, Pi-Shan

    2012-01-01

    This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

  20. Individual Learner and Team Modeling for Adaptive Training and Education in Support of the US Army Learning Model: Research Outline

    Science.gov (United States)

    2015-09-01

    system to include the learner, domain, and pedagogical models needed to deliver this training via an ITS. 4 3.1 Self-Regulated Learning and the US...elements and also to highlight their relationships : Adaptive Tutoring: also known as intelligent tutoring; tailored instructional methods to...asserts that through the use of case study examples, instruction can provide the pedagogical foundation for decision-making under uncertainty

  1. 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…

  2. Learning with Support Vector Machines

    CERN Document Server

    Campbell, Colin

    2010-01-01

    Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such a

  3. Adaptive Landmark-Based Navigation System Using Learning Techniques

    DEFF Research Database (Denmark)

    Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin

    2014-01-01

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

  4. Masters of adaptation: learning in late life adjustments.

    Science.gov (United States)

    Roberson, Donald N

    2005-01-01

    The purpose of this research is to understand the relationship between human development in older adults and personal learning. Personal or self-directed learning (SDL) refers to a style of learning where the individual directs, controls, and evaluates what is learned. It may occur with formal classes, but most often takes place in non-formal situations. This study employed a descriptive qualitative design incorporating in-depth, semistructured interviews for data collection. The sample of 10 purposefully selected older adults from a rural area reflected diversity in gender, race, education, and employment. Data analysis was guided by the constant comparative method. The primary late life adjustments of these older adults were in response to having extra time, changes in family, and social and physical loss. This research also indicated that late life adjustments are a primary incentive for self-directed learning. The results of this study indicated that older adults become masters of adaptation through the use of self-directed learning activities.

  5. Towards Increased Relevance: Context-Adapted Models of the Learning Organization

    Science.gov (United States)

    Örtenblad, Anders

    2015-01-01

    Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

  6. Impact of learning adaptability and time management disposition on study engagement among Chinese baccalaureate nursing students.

    Science.gov (United States)

    Liu, Jing-Ying; Liu, Yan-Hui; Yang, Ji-Peng

    2014-01-01

    The aim of this study was to explore the relationships among study engagement, learning adaptability, and time management disposition in a sample of Chinese baccalaureate nursing students. A convenient sample of 467 baccalaureate nursing students was surveyed in two universities in Tianjin, China. Students completed a questionnaire that included their demographic information, Chinese Utrecht Work Engagement Scale-Student Questionnaire, Learning Adaptability Scale, and Adolescence Time Management Disposition Scale. One-way analysis of variance tests were used to assess the relationship between certain characteristics of baccalaureate nursing students. Pearson correlation was performed to test the correlation among study engagement, learning adaptability, and time management disposition. Hierarchical linear regression analyses were performed to explore the mediating role of time management disposition. The results revealed that study engagement (F = 7.20, P < .01) and learning adaptability (F = 4.41, P < .01) differed across grade groups. Learning adaptability (r = 0.382, P < .01) and time management disposition (r = 0.741, P < .01) were positively related with study engagement. Time management disposition had a partially mediating effect on the relationship between study engagement and learning adaptability. The findings implicate that educators should not only promote interventions to increase engagement of baccalaureate nursing students but also focus on development, investment in adaptability, and time management. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. 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…

  8. Thai nursing students' adaption to problem-based learning: a qualitative study.

    Science.gov (United States)

    Klunklin, Areewan; Subpaiboongid, Pornpun; Keitlertnapha, Pongsri; Viseskul, Nongkran; Turale, Sue

    2011-11-01

    Student-centred forms of learning have gained favour internationally over the last few decades including problem based learning, an approach now incorporated in medicine, nursing and other disciplines' education in many countries. However, it is still new in Thailand and being piloted to try to offset traditional forms of didactic, teacher-centred forms of teaching. In this qualitative study, 25 undergraduate nursing students in northern Thailand were interviewed about their experiences with problem-based learning in a health promotion subject. Content analysis was used to interrogate interview data, which revealed four categories: adapting, seeking assistance, self-development, and thinking process development. Initially participants had mixed emotions of confusion, negativity or boredom in the adaption process, but expressed satisfaction with creativity in learning, group work, and leadership development. They described increased abilities to problem solve and think critically, but struggled to develop questioning behaviours in learning. Socio-culturally in Thai education, students have great respect for teachers, but rarely question or challenge them or their learning. We conclude that problem-based learning has great potential in Thai nursing education, but educators and systems need to systematically prepare appropriate learning environments, their staff and students, to incorporate this within curricula. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Sally Krasne

    2013-01-01

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

  10. Adapting Progress Feedback and Emotional Support to Learner Personality

    Science.gov (United States)

    Dennis, Matt; Masthoff, Judith; Mellish, Chris

    2016-01-01

    As feedback is an important part of learning and motivation, we investigate how to adapt the feedback of a conversational agent to learner personality (as well as to learner performance, as we expect an interaction effect between personality and performance on feedback). We investigate two aspects of feedback. Firstly, we investigate whether the…

  11. Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

    Science.gov (United States)

    Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

    2011-07-01

    In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Synthesizing Learning on Adaptation to Climate Change | IDRC ...

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

    Climate Change Adaptation in Africa (CCAA), a program is supported by IDRC and the United Kingdom's Department for International Development (DFID), supports three kinds of activity: research, capacity building and networking. Since 2006, CCAA has supported more than 30 participatory action research projects.

  13. Learning to push and learning to move: The adaptive control of contact forces

    Directory of Open Access Journals (Sweden)

    Maura eCasadio

    2015-11-01

    Full Text Available To be successful at manipulating objects one needs to apply simultaneously well controlled movements and contact forces. We present a computational theory of how the brain may successfully generate a vast spectrum of interactive behaviors by combining two independent processes. One process is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in compatible pairs connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, we describe motor learning as a process leading to the discovery of compatible force/motion pairs. The learned compatible pairs constitute a local representation of the environment's mechanics. Experiments on force field adaptation have already provided us with evidence that the brain is able to predict and compensate the forces encountered when one is attempting to generate a motion. Here, we tested the theory in the dual case, i.e. when one attempts at applying a desired contact force against a simulated rigid surface. If the surface becomes unexpectedly compliant, the contact point moves as a function of the applied force and this causes the applied force to deviate from its desired value. We found that, through repeated attempts at generating the desired contact force, subjects discovered the unique compatible hand motion. When, after learning, the rigid contact was unexpectedly restored, subjects displayed after effects of learning, consistent with the concurrent operation of a motion control system and a force control system. Together, theory and experiment support a new and broader view of modularity in the coordinated control of forces and

  14. Computer-Supported Collaborative Learning in Higher Education

    Science.gov (United States)

    Roberts, Tim, Ed.

    2005-01-01

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

  15. The use of and obstacles to social learning in climate change adaptation initiatives in South Africa

    Directory of Open Access Journals (Sweden)

    Shakespear Mudombi

    2017-03-01

    Full Text Available Global environmental change will have major impacts on ecosystems and human livelihoods while challenging the adaptive capacity of individuals and communities. Social learning, an ongoing adaptive process of knowledge generation, reflection and synthesis, may enhance people’s awareness about climate change and its impacts, with positive outcomes for their adaptive capacity. The objectives of this study were to assess the prevalence of factors promoting social learning in climate change adaptation initiatives in South Africa. An online survey was used to obtain the views of decision makers in government and non-governmental organisations about the presence of personal factors and organisational factors that promote social learning. Descriptive analysis was used to assess these issues. The findings provide some evidence of social learning in climate change adaptation projects in South Africa, with the majority of respondents indicating that personal social learning indicators were present. Mechanisms for improved conflict resolution were, however, less prevalent. The organisational and governance-related barriers to implementation also presented significant challenges. Some of the main organisational barriers were short timeframes for implementing projects, inadequate financial resources, political interference, shortcomings in governance systems and lack of knowledge and expertise in organisations. There is a need for organisations to promote social learning by ensuring that their organisational environment and governance structures are conducive for their employees to embrace social learning. This will help contribute to the overall success of climate change adaptation initiatives.

  16. Collaborative adaptations in social work intervention research in real-world settings: lessons learned from the field.

    Science.gov (United States)

    Blank Wilson, Amy; Farkas, Kathleen

    2014-01-01

    Social work research has identified the crucial role that service practitioners play in the implementation of evidence-based practices. This has led some researchers to suggest that intervention research needs to incorporate collaborative adaptation strategies in the design and implementation of studies focused on adapting evidence-based practices to real-world practice settings. This article describes a collaborative approach to service adaptations that was used in an intervention study that integrated evidence-based mental health and correctional services in a jail reentry program for people with serious mental illness. This description includes a discussion of the nature of the collaboration engaged in this study, the implementation strategies that were used to support this collaboration, and the lessons that the research team has learned about engaging a collaborative approach to implementing interventions in research projects being conducted in real-world social service delivery settings.

  17. Distance learning education for mitigation/adaptation policy: a case study

    Science.gov (United States)

    Slini, T.; Giama, E.; Papadopoulou, Ch.-O.

    2016-02-01

    The efficient training of young environmental scientists has proven to be a challenging goal over the last years, while several dynamic initiatives have been developed aiming to provide complete and consistent education. A successful example is the e-learning course for participants mainly coming from emerging economy countries 'Development of mitigation/adaptation policy portfolios' organised in the frame of the project Promitheas4: Knowledge transfer and research needs for preparing mitigation/adaptation policy portfolios, aiming to provide knowledge transfer, enhance new skills and competencies, using modern didactic approaches and learning technologies. The present paper addresses the experience and the results of these actions, which seem promising and encouraging and were broadly welcomed by the participants.

  18. Sleep benefits consolidation of visuo-motor adaptation learning in older adults.

    Science.gov (United States)

    Mantua, Janna; Baran, Bengi; Spencer, Rebecca M C

    2016-02-01

    Sleep is beneficial for performance across a range of memory tasks in young adults, but whether memories are similarly consolidated in older adults is less clear. Performance benefits have been observed following sleep in older adults for declarative learning tasks, but this benefit may be reduced for non-declarative, motor skill learning tasks. To date, studies of sleep-dependent consolidation of motor learning in older adults are limited to motor sequence tasks. To examine whether reduced sleep-dependent consolidation in older adults is generalizable to other forms of motor skill learning, we examined performance changes over intervals of sleep and wake in young (n = 62) and older adults (n = 61) using a mirror-tracing task, which assesses visuo-motor adaptation learning. Participants learned the task either in the morning or in evening, and performance was assessed following a 12-h interval containing overnight sleep or daytime wake. Contrary to our prediction, both young adults and older adults exhibited sleep-dependent gains in visuo-motor adaptation. There was a correlation between performance improvement over sleep and percent of the night in non-REM stage 2 sleep. These results indicate that motor skill consolidation remains intact with increasing age although this relationship may be limited to specific forms of motor skill learning.

  19. Becoming a Coach in Developmental Adaptive Sailing: A Lifelong Learning Perspective.

    Science.gov (United States)

    Duarte, Tiago; Culver, Diane M

    2014-10-02

    Life-story methodology and innovative methods were used to explore the process of becoming a developmental adaptive sailing coach. Jarvis's (2009) lifelong learning theory framed the thematic analysis. The findings revealed that the coach, Jenny, was exposed from a young age to collaborative environments. Social interactions with others such as mentors, colleagues, and athletes made major contributions to her coaching knowledge. As Jenny was exposed to a mixture of challenges and learning situations, she advanced from recreational para-swimming instructor to developmental adaptive sailing coach. The conclusions inform future research in disability sport coaching, coach education, and applied sport psychology.

  20. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  1. Providing QoS through machine-learning-driven adaptive multimedia applications.

    Science.gov (United States)

    Ruiz, Pedro M; Botía, Juan A; Gómez-Skarmeta, Antonio

    2004-06-01

    We investigate the optimization of the quality of service (QoS) offered by real-time multimedia adaptive applications through machine learning algorithms. These applications are able to adapt in real time their internal settings (i.e., video sizes, audio and video codecs, among others) to the unpredictably changing capacity of the network. Traditional adaptive applications just select a set of settings to consume less than the available bandwidth. We propose a novel approach in which the selected set of settings is the one which offers a better user-perceived QoS among all those combinations which satisfy the bandwidth restrictions. We use a genetic algorithm to decide when to trigger the adaptation process depending on the network conditions (i.e., loss-rate, jitter, etc.). Additionally, the selection of the new set of settings is done according to a set of rules which model the user-perceived QoS. These rules are learned using the SLIPPER rule induction algorithm over a set of examples extracted from scores provided by real users. We will demonstrate that the proposed approach guarantees a good user-perceived QoS even when the network conditions are constantly changing.

  2. e-Learning initiatives to support prescribing

    Science.gov (United States)

    Maxwell, Simon; Mucklow, John

    2012-01-01

    Preparing medical students to prescribe is a major challenge of undergraduate education. They must develop an understanding of clinical pharmacology and acquire knowledge about drugs and therapeutics, as well as the skills to prescribe for individual patients in the face of multiple variables. The task of delivering the learning required to achieve these attributes relies upon limited numbers of teachers, who have increasingly busy clinical commitments. There is evidence that training is currently insufficient to meet the demands of the workplace. e-Learning provides an opportunity to improve the learning experience. The advantages for teachers are improved distribution of learning content, ease of update, standardization and tracking of learner activities. The advantages for learners are ease of access, greater interactivity and individual choice concerning the pace and mix of learning. Important disadvantages are the considerable resource required to develop e-Learning projects and difficulties in simulating some aspects of the real world prescribing experience. Pre-requisites for developing an e-Learning programme to support prescribing include academic expertise, institutional support, learning technology services and an effective virtual learning environment. e-Learning content might range from complex interactive learning sessions through to static web pages with links. It is now possible to simulate and provide feedback on prescribing decisions and this will improve with advances in virtual reality. Other content might include a student formulary, self-assessment exercises (e.g. calculations), a glossary and an on-line library. There is some evidence for the effectiveness of e-Learning but better research is required into its potential impact on prescribing. PMID:22509885

  3. Social and Academic Support and Adaptation to College: Exploring the Relationships between Indicators' College Students

    Science.gov (United States)

    Turkpour, Azita; Mehdinezhad, Vali

    2016-01-01

    The aim of this study was to demonstrate the relation between social and academic support on student ability to adapt to college. Results demonstrated a weak and reverse relation between expression of support and personal ability to adapt and total adaptation. A direct relation was determined between emotional support and social adaptation and…

  4. Adaptive sampling program support for expedited site characterization

    International Nuclear Information System (INIS)

    Johnson, R.

    1993-01-01

    Expedited site characterizations offer substantial savings in time and money when assessing hazardous waste sites. Key to some of these savings is the ability to adapt a sampling program to the ''real-time'' data generated by an expedited site characterization. This paper presents a two-prong approach to supporting adaptive sampling programs: a specialized object-oriented database/geographical information system for data fusion, management and display; and combined Bayesian/geostatistical methods for contamination extent estimation and sample location selection

  5. A Case-Study for Life-Long Learning and Adaptation in Cooperative Robot Teams

    International Nuclear Information System (INIS)

    Parker, L.E.

    1999-01-01

    While considerable progress has been made in recent years toward the development of multi-robot teams, much work remains to be done before these teams are used widely in real-world applications. Two particular needs toward this end are the development of mechanisms that enable robot teams to generate cooperative behaviors on their own, and the development of techniques that allow these teams to autonomously adapt their behavior over time as the environment or the robot team changes. This paper proposes the use of the Cooperative Multi-Robot Observation of Multiple Moving Targets (CMOMMT) application as a rich domain for studying the issues of multi-robot learning and adaptation. After discussing the need for learning and adaptation in multi-robot teams, this paper describes the CMOMMT application and its relevance to multi-robot learning. We discuss the results of the previously- developed, hand-generated algorithm for CMOMMT and the potential for learning that was discovered from the hand-generated approach. We then describe the early work that has been done (by us and others) to generate multi- robot learning techniques for the CMOMMT application, as well as our ongoing research to develop approaches that give performance as good, or better, than the hand-generated approach. The ultimate goal of this research is to develop techniques for multi-robot learning and adaptation in the CMOMMT application domain that will generalize to cooperative robot applications in other domains, thus making the practical use of multi-robot teams in a wide variety of real-world applications much closer to reality

  6. Effects of Percutaneous LVAD Support on Right Ventricular Load and Adaptation.

    Science.gov (United States)

    Yourshaw, Jeffrey P; Mishra, Prabodh; Armstrong, M Christopher; Ramu, Bhavadharini; Craig, Michael L; Van Bakel, Adrian B; Steinberg, Daniel H; DiSalvo, Thomas G; Tedford, Ryan J; Houston, Brian A

    2018-04-30

    Both operative and hemodynamic mechanisms have been implicated in right heart failure (RHF) following surgical left ventricular assist device (LVAD) implantation. We investigated the effects of percutaneous LVAD (pLVAD; Impella®, Abiomed) support on right ventricular (RV) load and adaptation. We reviewed all patients receiving a pLVAD for cardiogenic shock at our institution between July 2014 and April 2017, including only those with pre- and post-pLVAD invasive hemodynamic measurements. Hemodynamic data was recorded immediately prior to pLVAD implantation and up to 96 h post-implantation. Twenty-five patients were included. Cardiac output increased progressively during pLVAD support. PAWP improved early post-pLVAD but did not further improve during continued support. Markers of RV adaptation (right ventricular stroke work index, right atrial pressure (RAP), and RAP to pulmonary artery wedge pressure ratio (RAP:PAWP)) were unchanged acutely implant but progressively improved during continued pLVAD support. Total RV load (pulmonary effective arterial elastance; E A ) and resistive RV load (pulmonary vascular resistance; PVR) both declined progressively. The relationship between RV load and RV adaptation (E A /RAP and E A /RAP:PAWP) was constant throughout. Median vasoactive-inotrope score declined after pLVAD placement and continued to decline throughout support. Percutaneous LVAD support in patients with cardiogenic shock did not acutely worsen RV adaptation, in contrast to previously described hemodynamic effects of surgically implanted durable LVADs. Further, RV load progressively declined during support, and the noted RV adaptation improvement was load-dependent as depicted by constant E A /RA and E A /RAP:PAWP relationships. These findings further implicate the operative changes associated with surgical LVAD implantation in early RHF following durable LVAD.

  7. Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization

    International Nuclear Information System (INIS)

    Yu, Kunjie; Chen, Xu; Wang, Xin; Wang, Zhenlei

    2017-01-01

    Highlights: • SATLBO is proposed to identify the PV model parameters efficiently. • In SATLBO, the learners self-adaptively select different learning phases. • An elite learning is developed in teacher phase to perform local searching. • A diversity learning is proposed in learner phase to maintain population diversity. • SATLBO achieves the first in ranking on overall performance among nine algorithms. - Abstract: Parameters identification of photovoltaic (PV) model based on measured current-voltage characteristic curves plays an important role in the simulation and evaluation of PV systems. To accurately and reliably identify the PV model parameters, a self-adaptive teaching-learning-based optimization (SATLBO) is proposed in this paper. In SATLBO, the learners can self-adaptively select different learning phases based on their knowledge level. The better learners are more likely to choose the learner phase for improving the population diversity, while the worse learners tend to choose the teacher phase to enhance the convergence rate. Thus, learners at different levels focus on different searching abilities to efficiently enhance the performance of algorithm. In addition, to improve the searching ability of different learning phases, an elite learning strategy and a diversity learning method are introduced into the teacher phase and learner phase, respectively. The performance of SATLBO is firstly evaluated on 34 benchmark functions, and experimental results show that SATLBO achieves the first in ranking on the overall performance among nine algorithms. Then, SATLBO is employed to identify parameters of different PV models, i.e., single diode, double diode, and PV module. Experimental results indicate that SATLBO exhibits high accuracy and reliability compared with other parameter extraction methods.

  8. Social support and child protection: Lessons learned and learning.

    Science.gov (United States)

    Thompson, Ross A

    2015-03-01

    Social support has been a topic of research for nearly 50 years, and its applications to prevention and intervention have grown significantly, including programs advancing child protection. This article summarizes the central conclusions of the 1994 review of research on social support and the prevention of child maltreatment prepared for the U.S. Advisory Board on Child Abuse and Neglect, and surveys advances in the field since its publication. Among the lessons learned twenty years ago are (a) the diversity of the social support needs of at-risk families and their association with child endangerment, (b) the need to supplement the emotionally affirmative aspects of social support with efforts to socialize parenting practices and monitor child well-being, (c) the desirability of integrating formal and informal sources of social support for recipients, and (d) the importance of considering the complex recipient reactions to receiving support from others. The lessons we are now learning derive from research exploring the potential of online communication to enhance social support, the neurobiology of stress and its buffering through social support, and the lessons of evaluation research that are identifying the effective ingredients of social support interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Supporting Learning from Illustrated Texts: Conceptualizing and Evaluating a Learning Strategy

    Science.gov (United States)

    Schlag, Sabine; Ploetzner, Rolf

    2011-01-01

    Texts and pictures are often combined in order to improve learning. Many students, however, have difficulty to appropriately process text-picture combinations. We have thus conceptualized a learning strategy which supports learning from illustrated texts. By inducing the processes of information selection, organization, integration, and…

  10. On the problem of first year students adaptation to the learning ...

    African Journals Online (AJOL)

    The relevance of the studied problem is the fact that successful adaptation of a first year student to life and academic activity in a university is the key to the further development of each student as a personality ... Keywords: Adaptation, students, learning process, means of physical education, sports ans mass sports events.

  11. Using a social learning configuration to increase Vietnamese smallholder farmers’ adaptive capacity to respond to climate change

    NARCIS (Netherlands)

    Phuong, Le Thi Hong; Wals, Arjen; Sen, Le Thi Hoa; Hoa, Nguyen Quoc; Lu, Van Phan; Biesbroek, Robbert

    2018-01-01

    Social learning is crucial for local smallholder farmers in developing countries to improve their adaptive capacity and to adapt to the current and projected impacts of climate change. While it is widely acknowledged that social learning is a necessary condition for adaptation, few studies have

  12. A service based adaptive U-learning system using UX.

    Science.gov (United States)

    Jeong, Hwa-Young; Yi, Gangman

    2014-01-01

    In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

  13. Invited Reaction: Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

    Science.gov (United States)

    Cseh, Maria; Manikoth, Nisha N.

    2011-01-01

    As the authors of the preceding article (Choi and Jacobs, 2011) have noted, the workplace learning literature shows evidence of the complementary and integrated nature of formal and informal learning in the development of employee competencies. The importance of supportive learning environments in the workplace and of employees' personal learning…

  14. Evaluation Framework Based on Fuzzy Measured Method in Adaptive Learning Systems

    Science.gov (United States)

    Ounaies, Houda Zouari; Jamoussi, Yassine; Ben Ghezala, Henda Hajjami

    2008-01-01

    Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners' needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase.…

  15. e-Learning initiatives to support prescribing.

    Science.gov (United States)

    Maxwell, Simon; Mucklow, John

    2012-10-01

    Preparing medical students to prescribe is a major challenge of undergraduate education. They must develop an understanding of clinical pharmacology and acquire knowledge about drugs and therapeutics, as well as the skills to prescribe for individual patients in the face of multiple variables. The task of delivering the learning required to achieve these attributes relies upon limited numbers of teachers, who have increasingly busy clinical commitments. There is evidence that training is currently insufficient to meet the demands of the workplace. e-Learning provides an opportunity to improve the learning experience. The advantages for teachers are improved distribution of learning content, ease of update, standardization and tracking of learner activities. The advantages for learners are ease of access, greater interactivity and individual choice concerning the pace and mix of learning. Important disadvantages are the considerable resource required to develop e-Learning projects and difficulties in simulating some aspects of the real world prescribing experience. Pre-requisites for developing an e-Learning programme to support prescribing include academic expertise, institutional support, learning technology services and an effective virtual learning environment. e-Learning content might range from complex interactive learning sessions through to static web pages with links. It is now possible to simulate and provide feedback on prescribing decisions and this will improve with advances in virtual reality. Other content might include a student formulary, self-assessment exercises (e.g. calculations), a glossary and an on-line library. There is some evidence for the effectiveness of e-Learning but better research is required into its potential impact on prescribing. © 2012 The Authors. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.

  16. Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

    Science.gov (United States)

    Wang, Ding; Liu, Derong

    2018-06-01

    The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Ecological information systems and support of learning: Coupling work domain information to user characteristics

    DEFF Research Database (Denmark)

    Pejtersen, Annelise Mark; Rasmussen, Jens

    1997-01-01

    This chapter presents a framework for design of work support systems for a modern, dynamic work environment in which stable work procedures are replaced with discretionary tasks and the request of continuous learning and adaptation to change. In this situation, classic task analysis is less effec...... in a dynamic environment is therefore a human-work interface directed towards a transparent presentation of the action possibilities and functional/intentional boundaries and constraints of the work domain relevant for typical task situations and user categories....

  18. Context-Adaptive Learning Designs by Using Semantic Web Services

    Science.gov (United States)

    Dietze, Stefan; Gugliotta, Alessio; Domingue, John

    2007-01-01

    IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources--whether data or services--within the learning design is done manually at design-time on the basis of the subjective appraisals…

  19. Virtual Learning Factory on VR-Supported Factory Planning

    OpenAIRE

    Weidig , Christian; Menck , Nicole; Winkes , Pascal ,; Aurich , Jan ,

    2014-01-01

    Part 13: Virtual Reality and Simulation; International audience; Learning Factories are becoming popular as tangible measures to teach engineering methods while making use of them in an industrial-like environment. Their core component is usually a factory demonstrator, users are physically working with. For factory planning such approaches can hardly be adapted, due to long lasting realization phases.To overcome this obstacle a virtual learning factory has been developed whose core component...

  20. Uninformative contexts support word learning for high-skill spellers.

    Science.gov (United States)

    Eskenazi, Michael A; Swischuk, Natascha K; Folk, Jocelyn R; Abraham, Ashley N

    2018-04-30

    The current study investigated how high-skill spellers and low-skill spellers incidentally learn words during reading. The purpose of the study was to determine whether readers can use uninformative contexts to support word learning after forming a lexical representation for a novel word, consistent with instance-based resonance processes. Previous research has found that uninformative contexts damage word learning; however, there may have been insufficient exposure to informative contexts (only one) prior to exposure to uninformative contexts (Webb, 2007; Webb, 2008). In Experiment 1, participants read sentences with one novel word (i.e., blaph, clurge) embedded in them in three different conditions: Informative (six informative contexts to support word learning), Mixed (three informative contexts followed by three uninformative contexts), and Uninformative (six uninformative contexts). Experiment 2 added a new condition with only three informative contexts to further clarify the conclusions of Experiment 1. Results indicated that uninformative contexts can support word learning, but only for high-skill spellers. Further, when participants learned the spelling of the novel word, they were more likely to learn the meaning of that word. This effect was much larger for high-skill spellers than for low-skill spellers. Results are consistent with the Lexical Quality Hypothesis (LQH) in that high-skill spellers form stronger orthographic representations which support word learning (Perfetti, 2007). Results also support an instance-based resonance process of word learning in that prior informative contexts can be reactivated to support word learning in future contexts (Bolger, Balass, Landen, & Perfetti, 2008; Balass, Nelson, & Perfetti, 2010; Reichle & Perfetti, 2003). (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  1. Generalized projective synchronization of chaotic systems via adaptive learning control

    International Nuclear Information System (INIS)

    Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang

    2010-01-01

    In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)

  2. Parents Supporting Learning: A Non-Intensive Intervention Supporting Literacy and Numeracy in the Home Learning Environment

    Science.gov (United States)

    Niklas, Frank; Cohrssen, Caroline; Tayler, Collette

    2016-01-01

    In Australia, emphasis in early childhood education policy is placed on the importance of the role of the family as a child's first educator, and finding effective ways to raise the effectiveness of parents in supporting children's learning, development and well-being. International studies demonstrate that the home learning environment (HLE)…

  3. Exploring the Effects of Intercultural Learning on Cross-Cultural Adaptation in a Study Abroad Context

    Science.gov (United States)

    Tsai, Yau

    2011-01-01

    This study targets Asian students studying abroad and explores the effects of intercultural learning on their cross-cultural adaptation by drawing upon a questionnaire survey. On the one hand, the results of this study find that under the influence of intercultural learning, students respond differently in their cross-cultural adaptation and no…

  4. Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

    DEFF Research Database (Denmark)

    Sousa, Tiago; Pinto, Tiago; Praca, Isabel

    2014-01-01

    This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi...

  5. Socio-Pedagogical Complex as a Pedagogical Support Technology of Students' Social Adaptation

    Science.gov (United States)

    Sadovaya, Victoriya V.; Simonova, Galina I.

    2016-01-01

    The relevance of the problem stated in the article is determined by the need of developing technological approaches to pedagogical support of students' social adaptation. The purpose of this paper is to position the technological sequence of pedagogical support of students' social adaptation in the activities of the socio-pedagogical complex. The…

  6. A Service Based Adaptive U-Learning System Using UX

    Directory of Open Access Journals (Sweden)

    Hwa-Young Jeong

    2014-01-01

    Full Text Available In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users’ tailored materials according to their learning style. That is, we analyzed the user’s data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

  7. The role of learning technologists in supporting e-research

    Directory of Open Access Journals (Sweden)

    Susi Peacock

    2009-12-01

    Full Text Available This article explores how the role of learning technologists, a professional group that has emerged during the last 15 to 20 years, may be diversifying to include supporting e-research. It contributes to the current debate about the emerging profession and the roles it should play in contemporary higher education. Previous studies have shown that, typically, the profession's role has focussed almost exclusively on curriculum development; traditionally, learning technologists work with students and tutors to enhance the learning environment with technology. This article presents two case studies of PhD research that used a standard e-learning tool, the virtual learning environment (VLE, to conduct focus groups online. The case studies demonstrate the expert role of the learning technologist in supporting researchers to make informed decisions about whether and how to use e-learning tools to conduct qualitative e-research. The learning technologist advised on the potential advantages and limitations of using the VLE for research and fostered collaborative, working relationships with the researchers, acquiring extensive background knowledge about their projects. This required the learning technologist to draw upon her own experience with research into e-learning and on her professional experience gained from supporting curriculum developments. It is suggested that many learning technologists could extend their roles, transferring their knowledge to include supporting e-research. A more inclusive model of the learning technologist's role in academia could help address the potential polarisation of the profession into researchers and practitioners.

  8. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  10. Supporting Adaptive and Adaptable Hypermedia Presentation Semantics

    NARCIS (Netherlands)

    D.C.A. Bulterman (Dick); L. Rutledge (Lloyd); L. Hardman (Lynda); J.R. van Ossenbruggen (Jacco)

    1999-01-01

    textabstractHaving the content of a presentation adapt to the needs, resources and prior activities of a user can be an important benefit of electronic documents. While part of this adaptation is related to the encodings of individual data streams, much of the adaptation can/should be guided by the

  11. Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

    Science.gov (United States)

    Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

    2017-01-01

    Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

  12. Active learning and adaptive sampling for non-parametric inference

    NARCIS (Netherlands)

    Castro, R.M.

    2007-01-01

    This thesis presents a general discussion of active learning and adaptive sampling. In many practical scenarios it is possible to use information gleaned from previous observations to focus the sampling process, in the spirit of the "twenty-questions" game. As more samples are collected one can

  13. Learning as You Journey: Anishinaabe Perception of Social-ecological Environments and Adaptive Learning

    Directory of Open Access Journals (Sweden)

    Iain Davidson-Hunt

    2003-12-01

    Full Text Available This paper explores the linkages between social-ecological resilience and adaptive learning. We refer to adaptive learning as a method to capture the two-way relationship between people and their social-ecological environment. In this paper, we focus on traditional ecological knowledge. Research was undertaken with the Anishinaabe people of Iskatewizaagegan No. 39 Independent First Nation, in northwestern Ontario, Canada. The research was carried out over two field seasons, with verification workshops following each field season. The methodology was based on site visits and transects determined by the elders as appropriate to answer a specific question, find specific plants, or locate plant communities. During site visits and transect walks, research themes such as plant nomenclature, plant use, habitat descriptions, biogeophysical landscape vocabulary, and place names were discussed. Working with elders allowed us to record a rich set of vocabulary to describe the spatial characteristics of the biogeophysical landscape. However, elders also directed our attention to places they knew through personal experiences and journeys and remembered from stories and collective history. We documented elders' perceptions of the temporal dynamics of the landscape through discussion of disturbance events and cycles. Again, elders drew our attention to the ways in which time was marked by cultural references to seasons and moons. The social memory of landscape dynamics was documented as a combination of biogeophysical structures and processes, along with the stories by which Iskatewizaagegan people wrote their histories upon the land. Adaptive learning for social-ecological resilience, as suggested by this research, requires maintaining the web of relationships of people and places. Such relationships allow social memory to frame creativity, while allowing knowledge to evolve in the face of change. Social memory does not actually evolve directly out of

  14. A Team Formation and Project-based Learning Support Service for Social Learning Networks

    NARCIS (Netherlands)

    Spoelstra, Howard; Van Rosmalen, Peter; Van de Vrie, Evert; Obreza, Matija; Sloep, Peter

    2014-01-01

    The Internet affords new approaches to learning. Geographically dispersed self-directed learners can learn in computer-supported communities, forming social learning networks. However, self-directed learners can suffer from a lack of continuous motivation. And surprisingly, social learning networks

  15. The use of and obstacles to social learning in climate change adaptation initiatives in South Africa

    OpenAIRE

    Mudombi, Shakespear; Fabricius, Christo; Van Zyl-Bulitta, Verena; Patt, Anthony

    2017-01-01

    Global environmental change will have major impacts on ecosystems and human livelihoods while challenging the adaptive capacity of individuals and communities. Social learning, an ongoing adaptive process of knowledge generation, reflection and synthesis, may enhance people’s awareness about climate change and its impacts, with positive outcomes for their adaptive capacity. The objectives of this study were to assess the prevalence of factors promoting social learning in climate change adapta...

  16. Cooperative Learning Groups and the Evolution of Human Adaptability : (Another Reason) Why Hermits Are Rare in Tonga and Elsewhere.

    Science.gov (United States)

    Bell, Adrian Viliami; Hernandez, Daniel

    2017-03-01

    Understanding the prevalence of adaptive culture in part requires understanding the dynamics of learning. Here we explore the adaptive value of social learning in groups and how formal social groups function as effective mediums of information exchange. We discuss the education literature on Cooperative Learning Groups (CLGs), which outlines the potential of group learning for enhancing learning outcomes. Four qualities appear essential for CLGs to enhance learning: (1) extended conversations, (2) regular interactions, (3) gathering of experts, and (4) incentives for sharing knowledge. We analyze these four qualities within the context of a small-scale agricultural society using data we collected in 2010 and 2012. Through an analysis of surveys, interviews, and observations in the Tongan islands, we describe the role CLGs likely plays in facilitating individuals' learning of adaptive information. Our analysis of group affiliation, membership, and topics of conversation suggest that the first three CLG qualities reflect conditions for adaptive learning in groups. We utilize ethnographic anecdotes to suggest the fourth quality is also conducive to adaptive group learning. Using an evolutionary model, we further explore the scope for CLGs outside the Tongan socioecological context. Model analysis shows that environmental volatility and migration rates among human groups mediate the scope for CLGs. We call for wider attention to how group structure facilitates learning in informal settings, which may be key to assessing the contribution of groups to the evolution of complex, adaptive culture.

  17. Modeling posttraumatic growth among cancer patients: The roles of social support, appraisals, and adaptive coping.

    Science.gov (United States)

    Cao, Weidan; Qi, Xiaona; Cai, Deborah A; Han, Xuanye

    2018-01-01

    The purpose of the study was to build a model to explain the relationships between social support, uncontrollability appraisal, adaptive coping, and posttraumatic growth (PTG) among cancer patients in China. The participants who were cancer patients in a cancer hospital in China filled out a survey. The final sample size was 201. Structural equation modeling was used to build a model explaining PTG. Structural equation modeling results indicated that higher levels of social support predicted higher levels of adaptive coping, higher levels of uncontrollability appraisal predicted lower levels of adaptive coping, and higher levels of adaptive coping predicted higher levels of PTG. Moreover, adaptive coping was a mediator between social support and growth, as well as a mediator between uncontrollability and growth. The direct effects of social support and uncontrollability on PTG were insignificant. The model demonstrated the relationships between social support, uncontrollability appraisal, adaptive coping, and PTG. It could be concluded that uncontrollability appraisal was a required but not sufficient condition for PTG. Neither social support nor uncontrollability appraisal had direct influence on PTG. However, social support and uncontrollability might indirectly influence PTG, through adaptive coping. It implies that both internal factors (eg, cognitive appraisal and coping) and external factors (eg, social support) are required in order for growth to happen. Copyright © 2017 John Wiley & Sons, Ltd.

  18. The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

    Science.gov (United States)

    Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

    2017-09-01

    Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

  19. The Optimization by Using the Learning Styles in the Adaptive Hypermedia Applications

    Science.gov (United States)

    Hamza, Lamia; Tlili, Guiassa Yamina

    2018-01-01

    This article addresses the learning style as a criterion for optimization of adaptive content in hypermedia applications. First, the authors present the different optimization approaches proposed in the area of adaptive hypermedia systems whose goal is to define the optimization problem in this type of system. Then, they present the architecture…

  20. Information systems supported organizational learning as a competitive advantage

    OpenAIRE

    Arias, Jose Manuel; Solana, Julian Miguel

    2013-01-01

    Purpose: The purpose of this paper is to analyze the characteristics that make information systems useful in gathering and processing information with the aim of organizational learning and subsequent structural adaptation for better fitting to market requirements. Design/methodology/approach: Adaptation is a must when turning to foster the competitiveness and sustainability of the organization. Findings and Originality/value: It is clear that information systems can really create a differenc...

  1. Ambient Learning Displays - Distributed Mixed Reality Information Mash-ups to support Ubiquitous Learning

    NARCIS (Netherlands)

    Börner, Dirk

    2010-01-01

    Börner, D. (2010, 19-21 March). Ambient Learning Displays Distributed Mixed Reality Information Mash-ups to support Ubiquitous Learning. Presented at the IADIS International Conference Mobile Learning 2010, Porto, Portugal.

  2. Adaptive Learning in Psychology: Wayfinding in the Digital Age

    Science.gov (United States)

    Dziuban, Charles D.; Moskal, Patsy D.; Cassisi, Jeffrey; Fawcett, Alexis

    2016-01-01

    This paper presents the results of a pilot study investigating the use of the Realizeit adaptive learning platform to deliver a fully online General Psychology course across two semesters. Through mutual cooperation, UCF and vendor (CCKF) researchers examined students' affective, behavioral, and cognitive reactions to the system. Student survey…

  3. Learner Profile Management for Collaborative Adaptive eLearning Application

    DEFF Research Database (Denmark)

    Alrifai, Mohammad; Dolog, Peter; Nejdl, Wolfgang

    2006-01-01

    Adaptive Learning Systems would perform better if they would be able to exchange as many relevant fragments of information about the learner as possible. The use of Web Services standards is recently gaining the attention of many researches as a promising solution for the problem of interfacing a...

  4. Sharing and Adaptation of Educational Documents in E-Learning

    Directory of Open Access Journals (Sweden)

    Chekry Abderrahman

    2012-03-01

    Full Text Available Few documents can be reused among the huge number of the educational documents on the web. The exponential increase of these documents makes it almost impossible to search for relevant documents. In addition to this, e-learning is designed for public users who have different levels of knowledge and varied skills so they should be given a content that sees to their needs. This work is about adapting the content of learning with learners preferences, and give the teachers the ability to reuse a given content.

  5. Learners' experiences of learning support in selected Western Cape schools

    Directory of Open Access Journals (Sweden)

    Olaniyi Bojuwoye

    2014-01-01

    Full Text Available The study explored Western Cape primary and secondary school learners' experiences regarding the provision and utilization of support services for improving learning. A qualitative interpretive approach was adopted and data gathered through focus group interviews involving 90 learners. Results revealed that learners received and utilized various forms of learning support from their schools, teachers, and peers. The learning support assisted in meeting learners' academic, social and emotional needs by addressing barriers to learning, creating conducive learning environments, enhancing learners' self-esteem and improving learners' academic performance.

  6. Using Ontology to Drive an Adaptive Learning Interface

    Directory of Open Access Journals (Sweden)

    Andrew Crapo

    2004-10-01

    Full Text Available Intelligent, adaptive interfaces are a pre-requisite to elevating computer-based applications to the realm of collaborative decision support in complex, relatively open-ended domains such as logistics and planning. This is because the composition and effective presentation of even the most useful information must be tailored to constantly changing circumstances. Our objective is to not only achieve an adaptive human-machine interface, but to imbue the software with a significant portion of the responsibility for effectively controlling the adaptation, freeing the user from unnecessary distraction and making the human-machine relationship more collaborative in nature. The foundational concepts of interface adaptation are discussed and a specific logistics application is described as an example.

  7. Personal and situational variables, and career concerns: predicting career adaptability in young adults.

    Science.gov (United States)

    Yousefi, Zahra; Abedi, Mohammadreza; Baghban, Iran; Eatemadi, Ozra; Abedi, Ahmade

    2011-05-01

    This study examined relationships among career adaptability and career concerns, social support and goal orientation. We surveyed 304 university students using measures of career concerns, adaptability (career planning, career exploration, self-exploration, decision-making, self-regulation), goal-orientation (learning, performance-prove, performance-avoid) and social support (family, friends, significant others). Multiple regression analysis revealed career concerns, learning and performance-prove goal orientations emerged relatively as the most important contributors. Other variables did not contribute significantly.

  8. Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning

    NARCIS (Netherlands)

    Miao, Yongwu; Burgos, Daniel; Griffiths, David; Koper, Rob

    2007-01-01

    Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and

  9. GP Supervisors' Experience in Supporting Self-Regulated Learning: A Balancing Act

    Science.gov (United States)

    Sagasser, Margaretha H.; Kramer, Anneke W. M.; van Weel, Chris; van der Vleuten, Cees P. M.

    2015-01-01

    Self-regulated learning is essential for professional development and lifelong learning. As self-regulated learning has many inaccuracies, the need to support self-regulated learning has been recommended. Supervisors can provide such support. In a prior study trainees reported on the variation in received supervisor support. This study aims at…

  10. What Can We Learn from a Well-Adapted Enterprise System? A Case Study Approach

    DEFF Research Database (Denmark)

    Svejvig, Per; Jensen, Tina Blegind

    how the system was highly integrated, accepted by its users, and well-aligned to the work processes. This leads to the research question: Why is the enterprise system so well-adapted in SCANDI and what can we learn from this case study? Building on the structural model of technology to investigate...... as a long-term institutionalization and legitimization course of events leading to secondary socialization as the key lessons learned in achieving successful ES adaptations....

  11. 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.

  12. Populists as Chameleons? An Adaptive Learning Approach to the Rise of Populist Politicians

    Directory of Open Access Journals (Sweden)

    Jasper Muis

    2015-04-01

    Full Text Available This paper envisions populism as a vote- and attention-maximizing strategy. It applies an adaptive learning approach to understand successes of populist party leaders. I assume that populists are ideologically flexible and continually search for a more beneficial policy position, in terms of both electoral support and media attention, by retaining political claims that yield positive feedback and discard those that encounter negative feedback. This idea is empirically tested by analyzing the Dutch populist leader Pim Fortuyn and the development of his stance about immigration and integration issues. In contrast to the conventional wisdom, the results do not show any empirical support for the claim that Fortuyn was ideologically driven by the opinion polls or by media publicity during the 2002 Dutch parliamentary election campaign. The findings thus suggest that populist parties are perhaps less distinctive in their strategies from mainstream parties than often claimed.

  13. Supporting Fieldwork Learning by Visual Documentation and Reflection

    DEFF Research Database (Denmark)

    Saltofte, Margit

    2017-01-01

    Photos can be used as a supplements to written fieldnotes and as a sources for mediating reflection during fieldwork and analysis. As part of a field diary, photos can support the recall of experiences and a reflective distance to the events. Photography, as visual representation, can also lead...... to reflection on learning and knowledge production in the process of learning how to conduct fieldwork. Pictures can open the way for abstractions and hidden knowledge, which might otherwise be difficult to formulate in words. However, writing and written field notes cannot be fully replaced by photos...... the role played by photos in their learning process. For students, photography is an everyday documentation form that can support their memory of field experience and serve as a vehicle for the analysis of data. The article discusses how photos and visual representations support fieldwork learning...

  14. Personal Learning Environments for Supporting Out-of-Class Language Learning

    Science.gov (United States)

    Reinders, Hayo

    2014-01-01

    A Personal Learning Environment (PLE) it is a combination of tools (usually digital) and resources chosen by the learner to support different aspects of the learning process, from goal setting to materials selection to assessment. The importance of PLEs for teachers lies in their ability to help students develop autonomy and prepare them for…

  15. The Study of Reinforcement Learning for Traffic Self-Adaptive Control under Multiagent Markov Game Environment

    Directory of Open Access Journals (Sweden)

    Lun-Hui Xu

    2013-01-01

    Full Text Available Urban traffic self-adaptive control problem is dynamic and uncertain, so the states of traffic environment are hard to be observed. Efficient agent which controls a single intersection can be discovered automatically via multiagent reinforcement learning. However, in the majority of the previous works on this approach, each agent needed perfect observed information when interacting with the environment and learned individually with less efficient coordination. This study casts traffic self-adaptive control as a multiagent Markov game problem. The design employs traffic signal control agent (TSCA for each signalized intersection that coordinates with neighboring TSCAs. A mathematical model for TSCAs’ interaction is built based on nonzero-sum markov game which has been applied to let TSCAs learn how to cooperate. A multiagent Markov game reinforcement learning approach is constructed on the basis of single-agent Q-learning. This method lets each TSCA learn to update its Q-values under the joint actions and imperfect information. The convergence of the proposed algorithm is analyzed theoretically. The simulation results show that the proposed method is convergent and effective in realistic traffic self-adaptive control setting.

  16. A study on online learner profile for supporting personalized learning

    Directory of Open Access Journals (Sweden)

    Jie Yang

    2013-09-01

    Full Text Available Digital learning as a popular learning approach has received increasing attention in modern education. The learner profile in online learning plays a critical role in supporting personalized learning. This article uses an information flow-based approach to build the learner profile for supporting personalized learning. The learner profile includes the individual profile to capture the personal features and the community profile to capture the social features in online learning environment.

  17. Towards more efficient e-learning, intelligence and adapted teaching material

    Directory of Open Access Journals (Sweden)

    Damir Kalpić

    2010-12-01

    Full Text Available This article presents results of a research project in which we attempted to determine the relationship between efficient E-learning and teaching materials adapted based on students’ structure of intelligence. The project was conducted on approximately 500 students, 23 classes, nine elementary schools, with ten teachers of history, informatics and several licensed psychologists. E-teaching material was prepared for the subject of History for eight-grade students of elementary school. Students were tested for the structure of intelligence, and based on their most prominent component, they were divided into groups, using teaching materials adapted to their most prominent intelligence component. The results have shown that use of the adapted teaching materials achieved 6-12% better results than E-materials not adapted to students’ structure of intelligence.

  18. Learning from sensory and reward prediction errors during motor adaptation.

    Science.gov (United States)

    Izawa, Jun; Shadmehr, Reza

    2011-03-01

    Voluntary motor commands produce two kinds of consequences. Initially, a sensory consequence is observed in terms of activity in our primary sensory organs (e.g., vision, proprioception). Subsequently, the brain evaluates the sensory feedback and produces a subjective measure of utility or usefulness of the motor commands (e.g., reward). As a result, comparisons between predicted and observed consequences of motor commands produce two forms of prediction error. How do these errors contribute to changes in motor commands? Here, we considered a reach adaptation protocol and found that when high quality sensory feedback was available, adaptation of motor commands was driven almost exclusively by sensory prediction errors. This form of learning had a distinct signature: as motor commands adapted, the subjects altered their predictions regarding sensory consequences of motor commands, and generalized this learning broadly to neighboring motor commands. In contrast, as the quality of the sensory feedback degraded, adaptation of motor commands became more dependent on reward prediction errors. Reward prediction errors produced comparable changes in the motor commands, but produced no change in the predicted sensory consequences of motor commands, and generalized only locally. Because we found that there was a within subject correlation between generalization patterns and sensory remapping, it is plausible that during adaptation an individual's relative reliance on sensory vs. reward prediction errors could be inferred. We suggest that while motor commands change because of sensory and reward prediction errors, only sensory prediction errors produce a change in the neural system that predicts sensory consequences of motor commands.

  19. Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks.

    Science.gov (United States)

    Passot, Jean-Baptiste; Luque, Niceto R; Arleo, Angelo

    2013-01-01

    The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body-environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models), and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories.

  20. Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks

    Directory of Open Access Journals (Sweden)

    Jean-Baptiste ePassot

    2013-07-01

    Full Text Available The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body–environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models, and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories.

  1. Applying a Framework for Student Modeling in Exploratory Learning Environments: Comparing Data Representation Granularity to Handle Environment Complexity

    Science.gov (United States)

    Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido

    2017-01-01

    Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…

  2. Advancing Capacity to Support Climate Change Adaptation : Five ...

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

    Chargé(e) de projet. Mamadou Moussa Diakhité. Institution. United Nations Institute for Training and Research. Pays d' institution. Switzerland. Site internet. http://www.unitar.org. Extrants. Rapports. Advancing Capacity to Support Climate Change Adaptation (ACCCA) through five pilot actions in Africa : final project report.

  3. L1-norm locally linear representation regularization multi-source adaptation learning.

    Science.gov (United States)

    Tao, Jianwen; Wen, Shiting; Hu, Wenjun

    2015-09-01

    In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Adaptive eLearning modules for cytopathology education: A review and approach.

    Science.gov (United States)

    Samulski, T Danielle; La, Teresa; Wu, Roseann I

    2016-11-01

    Clinical training imposes time and resource constraints on educators and learners, making it difficult to provide and absorb meaningful instruction. Additionally, innovative and personalized education has become an expectation of adult learners. Fortunately, the development of web-based educational tools provides a possible solution to these challenges. Within this review, we introduce the utility of adaptive eLearning platforms in pathology education. In addition to a review of the current literature, we provide the reader with a suggested approach for module creation, as well as a critical assessment of an available platform, based on our experience in creating adaptive eLearning modules for teaching basic concepts in gynecologic cytopathology. Diagn. Cytopathol. 2016;44:944-951. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  5. Organizational Support for Action Learning in South Korean Organizations

    Science.gov (United States)

    Cho, Yonjoo; Egan, Toby

    2013-01-01

    The purpose of this study was (1) to examine the impact of organizational support on employee learning and performance and (2) to elaborate on the context of organizational support for action learning in South Korean organizations. For this inquiry, two central questions were posed: What are employee reactions to organizational support for action…

  6. OpenU: design of an integrated system to support lifelong learning

    NARCIS (Netherlands)

    Hermans, Henry

    2015-01-01

    This thesis describes the design and first implementation of an online system for lifelong learning, that enables educational institutions to adapt the learning process to identifiable groups of adult learners. The design of this system is situated in the context of a distance teaching university

  7. Low-Back Pain Patients Learn to Adapt Motor Behavior with Adverse Secondary Consequences

    NARCIS (Netherlands)

    van Dieën, Jaap H.; Flor, Herta; Hodges, Paul W.

    2017-01-01

    ABSTRACT: We hypothesize that changes in motor behavior in individuals with low-back pain are adaptations aimed at minimizing the real or perceived risk of further pain. Through reinforcement learning, pain and subsequent adaptions result in less dynamic motor behavior, leading to increased loading

  8. Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method

    Directory of Open Access Journals (Sweden)

    Wei Xue

    2016-08-01

    Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.

  9. Technology and Products Supporting E-learning by Knowledge Management - A Review

    Directory of Open Access Journals (Sweden)

    Ying Wang

    2014-06-01

    Full Text Available Abstract—Knowledge management is supported by many strategies such as business intelligence, collaboration, document management and e-learning. With the development of modern information technology and the increases of demand for building and maintaining dynamic capabilities, E-learning has played more and more important role of all the technologies in the supporting knowledge management. A successful e-learning system is supported by many critical success factors and technology has become the key factor among these factors. Consequently, the review of basic technologies and corresponding products that support e-learning will be in favor of further study on e-learning. From perspective of knowledge management, this paper makes a review about the relationship between e-learning and knowledge management and advanced technologies and corresponding products that support the design and operation of e-learning system. At the end of this paper, we analyze the main trends of the development direction of e-learning technology.

  10. A Cybernetic Design Methodology for 'Intelligent' Online Learning Support

    Science.gov (United States)

    Quinton, Stephen R.

    The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.

  11. Impact of Nursing Learning Environments on Adaptive Competency Development in Baccalaureate Nursing Students.

    Science.gov (United States)

    Laschinger, Heather K. Spence

    1992-01-01

    Kolb's experiential learning theory was used as a framework to study 179 generic baccalaureate students' perceptions of the different types of learning environments and adaptive competencies. Clinical experience and preceptorships contributed more to competency development than did nursing or nonnursing classes. (JOW)

  12. Evolutionary online behaviour learning and adaptation in real robots.

    Science.gov (United States)

    Silva, Fernando; Correia, Luís; Christensen, Anders Lyhne

    2017-07-01

    Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm.

  13. Learning to Support Learning Together: An Experience with the Soft Systems Methodology

    Science.gov (United States)

    Sanchez, Adolfo; Mejia, Andres

    2008-01-01

    An action research approach called soft systems methodology (SSM) was used to foster organisational learning in a school regarding the role of the learning support department within the school and its relation with the normal teaching-learning activities. From an initial situation of lack of coordination as well as mutual misunderstanding and…

  14. Lifelong Learning Organisers: Requirements for Tools for Supporting Episodic and Semantic Learning

    Science.gov (United States)

    Vavoula, Giasemi; Sharples, Mike

    2009-01-01

    We propose Lifelong Learning Organisers (LLOs) as tools to support the capturing, organisation and retrieval of personal learning experiences, resources and notes, over a range of learning topics, at different times and places. The paper discusses general requirements for the design of LLOs based on findings from a diary-based study of everyday…

  15. LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

    Directory of Open Access Journals (Sweden)

    Amit Kumar

    2017-12-01

    Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

  16. RLAM: A Dynamic and Efficient Reinforcement Learning-Based Adaptive Mapping Scheme in Mobile WiMAX Networks

    Directory of Open Access Journals (Sweden)

    M. Louta

    2014-01-01

    Full Text Available WiMAX (Worldwide Interoperability for Microwave Access constitutes a candidate networking technology towards the 4G vision realization. By adopting the Orthogonal Frequency Division Multiple Access (OFDMA technique, the latest IEEE 802.16x amendments manage to provide QoS-aware access services with full mobility support. A number of interesting scheduling and mapping schemes have been proposed in research literature. However, they neglect a considerable asset of the OFDMA-based wireless systems: the dynamic adjustment of the downlink-to-uplink width ratio. In order to fully exploit the supported mobile WiMAX features, we design, develop, and evaluate a rigorous adaptive model, which inherits its main aspects from the reinforcement learning field. The model proposed endeavours to efficiently determine the downlink-to-uplinkwidth ratio, on a frame-by-frame basis, taking into account both the downlink and uplink traffic in the Base Station (BS. Extensive evaluation results indicate that the model proposed succeeds in providing quite accurate estimations, keeping the average error rate below 15% with respect to the optimal sub-frame configurations. Additionally, it presents improved performance compared to other learning methods (e.g., learning automata and notable improvements compared to static schemes that maintain a fixed predefined ratio in terms of service ratio and resource utilization.

  17. Lifelong Learning and its support with new technologies

    NARCIS (Netherlands)

    Kalz, Marco

    2014-01-01

    This chapter provides an overview about the use of new technologies for lifelong learning. While in the past learning technologies were mostly provided by educational institutions to support a specific lifetime or shorter learning episodes nowadays more personal technologies are used for lifelong

  18. Adapting to managed care by becoming a learning organization.

    Science.gov (United States)

    O'Sullivan, M J

    1999-03-01

    In the tumultuous and chaotic environment of managed health care, hospital-based mental health providers need to change in fundamental ways. The traditional view of mental health organizations is a professional-bureaucratic one where actions and outcomes of planning are thought to be highly predictable. The author proposes an alternative paradigm for viewing mental health provider organizations, one based on learning theory, which accepts that the future is unknowable because of its complexity and the probabilistic nature of the world. Within this perspective, mental health care providers need to become "learning organizations" to successfully adapt to the new and evolving conditions.

  19. Climate finance: Mobilizing the private sector to support adaptation ...

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

    2016-10-26

    Oct 26, 2016 ... Find out about the knowledge, innovation, and solutions we are bringing ... The Private Finance Gap: Challenges and Opportunities in Funding Adaptation ... IDRC supports results-based research that has real impacts on the ...

  20. Panorama of Recommender Systems to Support Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga C.; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender

  1. Organisational Culture: Electronic Support for Occupational Learning.

    Science.gov (United States)

    Saunders, Murray

    1998-01-01

    Outlines the interrelationship between telematic learning support and organizational culture of the workplace, defines occupational learning and types of organizationally generated knowledge, identifies concepts of organizational culture, and assesses the argument that telematics can effect changes in culture. Contextualizes these issues in new…

  2. Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

    Science.gov (United States)

    Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

    2018-05-01

    In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

  3. Observations to support adaptation: Principles, scales and decision-making

    Science.gov (United States)

    Pulwarty, R. S.

    2012-12-01

    As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks

  4. Supporting Problem Solving with Case-Stories Learning Scenario and Video-based Collaborative Learning Technology

    Directory of Open Access Journals (Sweden)

    Chun Hu

    2004-04-01

    Full Text Available In this paper, we suggest that case-based resources, which are used for assisting cognition during problem solving, can be structured around the work of narratives in social cultural psychology. Theories and other research methods have proposed structures within narratives and stories which may be useful to the design of case-based resources. Moreover, embedded within cases are stories which are contextually rich, supporting the epistemological groundings of situated cognition. Therefore the purposes of this paper are to discuss possible frameworks of case-stories; derive design principles as to “what” constitutes a good case story or narrative; and suggest how technology can support story-based learning. We adopt video-based Computer-Supported Collaborative Learning (CSCL technology to support problem solving with case-stories learning scenarios. Our hypothesis in this paper is that well-designed case-based resources are able to aid in the cognitive processes undergirding problem solving and meaning making. We also suggest the use of an emerging video-based collaborative learning technology to support such an instructional strategy.

  5. Adaptivity in GRAPPLE: Adaptation in any way you like (Poster)

    NARCIS (Netherlands)

    De Bra, P.M.E.; Smits, D.; Pechenizkiy, M.; Vasilyeva, E.; Bonk, C.J.; et al., xx

    2008-01-01

    GRAPPLE is an EU funded IST FP7 project that brings together a group of researchers into adaptive learning technology and environments and developers of learning management systems (LMSs), in order to offer adaptive learning as a standard feature of future LMSs. This paper presents the adaptation

  6. A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks

    NARCIS (Netherlands)

    De Jong, Tim; Fuertes, Alba; Schmeits, Tally; Specht, Marcus; Koper, Rob

    2008-01-01

    De Jong, T., Fuertes, A., Schmeits, T., Specht, M., & Koper, R. (2009). A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks. In D. Goh (Ed.), Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education (pp.

  7. Identification of critical timeconsuming student support activities in e-learning

    Directory of Open Access Journals (Sweden)

    Fred J. de Vries

    2005-12-01

    Full Text Available Higher education staff involved in e-learning often struggle with organising their student support activities. To a large extent this is due to the high workload involved with such activities. We distinguish support related to learning content, learning processes and student products. At two different educational institutions, surveys were conducted to identify the most critical support activities, using the Nominal Group Method. The results are discussed and brought to bear on the distinction between content-related, process-related and product-related support activities.

  8. Assessing Management Regimes in Transboundary River Basins: Do They Support Adaptive Management?

    Directory of Open Access Journals (Sweden)

    G.T. (Tom Raadgever

    2008-06-01

    Full Text Available River basin management is faced with complex problems that are characterized by uncertainty and change. In transboundary river basins, historical, legal, and cultural differences add to the complexity. The literature on adaptive management gives several suggestions for handling this complexity. It recognizes the importance of management regimes as enabling or limiting adaptive management, but there is no comprehensive overview of regime features that support adaptive management. This paper presents such an overview, focused on transboundary river basin management. It inventories the features that have been claimed to be central to effective transboundary river basin management and refines them using adaptive management literature. It then collates these features into a framework describing actor networks, policy processes, information management, and legal and financial aspects. Subsequently, this framework is applied to the Orange and Rhine basins. The paper concludes that the framework provides a consistent and comprehensive perspective on transboundary river basin management regimes, and can be used for assessing their capacity to support adaptive management.

  9. Using visualizations to support collaboration and coordination during computer-supported collaborative learning

    NARCIS (Netherlands)

    Janssen, J.J.H.M.

    2008-01-01

    This thesis addresses the topic of computer-supported collaborative learning (CSCL in short). In a CSCL-environment, students work in small groups on complex and challenging tasks. Although the teacher guides this process at a distance, students have to regulate and monitor their own learning

  10. Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems

    Science.gov (United States)

    Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.

    2013-12-01

    server-based system. Open source web technologies and community-based tools are used to facilitate wide dissemination and adaptation by diverse, independent institutions. The new hydrologic learning modules are based on recent developments in hydrologic modeling, data, and resources. The modules are embedded in three regional-scale ecosystems, Coastal Louisiana, Florida Everglades, and Utah Great Salt Lake Basin. These sites provide a wealth of hydrologic concepts and scenarios that can be used in most water resource and hydrology curricula. The study develops several learning modules based on the three hydro-systems covering subjects such as: water-budget analysis, effects of human and natural changes, climate-hydrology teleconnections, and water-resource management scenarios. The new developments include an instructional interface to give critical guidance and support to the learner and an instructor's guide containing adaptation and implementation procedures to assist instructors in adopting and integrating the material into courses and provide a consistent experience. The design of the new hydrologic education developments will be transferable to independent institutions and adaptable both instructionally and technically through a server system capable of supporting additional developments by the educational community.

  11. MRSA model of learning and adaptation: a qualitative study among the general public

    Science.gov (United States)

    2012-01-01

    Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA) infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1) a common model of MRSA learning and adaptation; 2) the self-directed nature of adult learning; 3) the focus on general MRSA information, care and prevention, and antibiotic

  12. MRSA model of learning and adaptation: a qualitative study among the general public

    Directory of Open Access Journals (Sweden)

    Rohde Rodney E

    2012-04-01

    Full Text Available Abstract Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1 a common model of MRSA learning and adaptation; 2 the self-directed nature of adult learning; 3 the focus on general MRSA information, care and

  13. eLearning techniques supporting problem based learning in clinical simulation.

    Science.gov (United States)

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

    2005-08-01

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

  14. GP supervisors' experience in supporting self-regulated learning: a balancing act

    NARCIS (Netherlands)

    Sagasser, M.H.; Kramer, A.W.M.; Weel, C. van; Vleuten, C.P.M. van der

    2015-01-01

    Self-regulated learning is essential for professional development and lifelong learning. As self-regulated learning has many inaccuracies, the need to support self-regulated learning has been recommended. Supervisors can provide such support. In a prior study trainees reported on the variation in

  15. Learners' experiences of learning support in selected Western Cape ...

    African Journals Online (AJOL)

    The learning support assisted in meeting learners' academic, social and emotional needs by addressing barriers to learning, creating conducive learning environments, enhancing learners' self-esteem and improving learners' academic performance. Keywords: academic needs; academic performance; barriers to learning; ...

  16. Supporting Inquiry-based Learning with Google Glass (GPIM)

    NARCIS (Netherlands)

    Suarez, Angel; Ternier, Stefaan; Kalz, Marco; Specht, Marcus

    2015-01-01

    Wearable technology is a new genre of technology that is appearing to enhance learning in context. This manuscript introduces a Google Glass application to support Inquiry-based Learning (IBL). Applying Google Glass to IBL, we aim to transform the learning process into a more seamless, personal and

  17. Social networks as ICT collaborative and supportive learning media ...

    African Journals Online (AJOL)

    ... ICT collaborative and supportive learning media utilisation within the Nigerian educational system. The concept of ICT was concisely explained vis-à-vis the social network concept, theory and collaborative and supportive learning media utilisation. Different types of social network are highlighted among which Facebook, ...

  18. Seamless Support: Technology Enhanced Learning in Open Distance Learning at NWU

    Science.gov (United States)

    Esterhuizen, Hennie

    2015-01-01

    Frantic attempts of investing in technology to demonstrate willingness to educate for the knowledge society may result in failure to address the real requirements. This paper presents the main features of a framework for integrating Technology Enhanced Learning in Open Distance Learning at North-West University, South Africa. Support towards…

  19. Co-operative learning and adaptive instruction in a mathematics curriculum

    NARCIS (Netherlands)

    Terwel, J.; Herfs, P.G.P.; Mertens, E.H.M.; Perrenet, J.Chr.

    1994-01-01

    The AGO 12 to 16 Project (the acronym AGO stands for the Dutch equivalent of 'Adaptive Instruction and Co-operative Learning') seeks to develop and evaluate a mathematics curriculum which is suitable for mixed-ability groups in secondary education. The research questions we will address here are,

  20. Considering Peer Support for Self-Access Learning

    Directory of Open Access Journals (Sweden)

    Craig Manning

    2014-01-01

    Full Text Available This paper briefly examines if and how peer support can be implemented as an appropriate means to improve self-access learning. The potential for further alignment with the higher aims common among self-access learning centers will be examined. Opportunities for increasing interdependence, purpose, and level of challenge to foster student engagement will also be explored. Finally, future directions in self-access learning will be discussed.

  1. Lost in Translation: Adapting a Face-to-Face Course Into an Online Learning Experience.

    Science.gov (United States)

    Kenzig, Melissa J

    2015-09-01

    Online education has grown dramatically over the past decade. Instructors who teach face-to-face courses are being called on to adapt their courses to the online environment. Many instructors do not have sufficient training to be able to effectively move courses to an online format. This commentary discusses the growth of online learning, common challenges faced by instructors adapting courses from face-to-face to online, and best practices for translating face-to-face courses into online learning opportunities. © 2015 Society for Public Health Education.

  2. Relationship between Psychological Hardiness and Social Support with Adaptation: A Study on Individuals with Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    N hasan neghad

    2013-10-01

    Full Text Available Introduction: Psychological hardiness is a personal factor and social support is regarded as an environmental factor that can facilitate adjustment to disease. This study aimed to investigate the relationship between adaptation with psychological hardiness and social support in individuals with Multiple sclerosis (MS. Methods: Seventy two females with MS and 25 males with MSwere selected through randomized sampling from two MS centers. Main variables of the study including adaptation, psychological hardiness, and social supportwere assessed respectively by Adaptation Inventory, Personal Attitudes Survey, and Social Support Questionnaire. Results: Spearman correlation coefficients revealed that there are significant relationships between adaptation and psychological hardiness (p<0.0001, as well as between adaptation and social support (p<0.0001. In addition, Multiple linear Regression showed that psychological hardiness (β= -0.483 and social support (β= -0.240 can explain 35/1% of adaptation variance in individuals with MS. Psychological hardinessproved to have a more important role in adaptation of individuals with MS. Conclusion: The study data demonstrated that personal factors like psychological hardiness and environmental factors such as social support can predict adjustment in individuals with MS. In order to clarify mechanisms of these factors on adaptation in individuals with MS, morelongitudinal and experimental studiesare required. These results are alsoapplicable in designing therapeutic programs for individuals with MS.

  3. Adaptation, postpartum concerns, and learning needs in the first two weeks after caesarean birth.

    Science.gov (United States)

    Weiss, Marianne; Fawcett, Jacqueline; Aber, Cynthia

    2009-11-01

    The purpose of this Roy Adaptation Model-based study was to describe women's physical, emotional, functional and social adaptation; postpartum concerns; and learning needs during the first two weeks following caesarean birth and identify relevant nursing interventions. Studies of caesarean-delivered women indicated a trend toward normalisation of the caesarean birth experience. Escalating caesarean birth rates mandate continued study of contemporary caesarean-delivered women. Mixed methods (qualitative and quantitative) descriptive research design. Nursing students collected data from 233 culturally diverse caesarean-delivered women in urban areas of the Midwestern and Northeastern USA between 2002-2004. The focal stimulus was the planned or unplanned caesarean birth; contextual stimuli were cultural identity and parity. Adaptation was measured by open-ended interview questions, fixed choice questionnaires about postpartum concerns and learning needs and nurse assessment of post-discharge problems. Potential interventions were identified using the Omaha System Intervention Scheme. More positive than negative responses were reported for functional and social adaptation than for physical and emotional adaptation. Women with unplanned caesarean births and primiparous women reported less favourable adaptation than planned caesarean mothers and multiparas. Black women reported lower social adaptation, Hispanic women had more role function concerns and Black and Hispanic women had more learning needs than White women. Post-discharge nursing assessments revealed that actual problems accounted for 40% of identified actual or potential problems or needs. Health teaching was the most commonly recommended postpartum intervention strategy followed by case management, treatment and surveillance interventions. Caesarean-delivered women continue to experience some problems with adapting to childbirth. Recommended intervention strategies reflect the importance of health teaching

  4. The Effects of Reflective Activities on Skill Adaptation in a Work-Related Instrumental Learning Setting

    Science.gov (United States)

    Roessger, Kevin M.

    2014-01-01

    In work-related instrumental learning contexts, the role of reflective activities is unclear. Kolb's experiential learning theory and Mezirow's transformative learning theory predict skill adaptation as an outcome. This prediction was tested by manipulating reflective activities and assessing participants' response and error rates during novel…

  5. Algebraic and adaptive learning in neural control systems

    Science.gov (United States)

    Ferrari, Silvia

    A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

  6. Learning How to Design a Technology Supported Inquiry-Based Learning Environment

    Science.gov (United States)

    Hakverdi-Can, Meral; Sonmez, Duygu

    2012-01-01

    This paper describes a study focusing on pre-service teachers' experience of learning how to design a technology supported inquiry-based learning environment using the Internet. As part of their elective course, pre-service science teachers were asked to develop a WebQuest environment targeting middle school students. A WebQuest is an…

  7. Study on the Correlation between job adaptation obstacle and perceived social support of community nurses in Changchun

    Directory of Open Access Journals (Sweden)

    Meng Wei

    2017-01-01

    Full Text Available Objective: To investigate the present situation of job adaptation and perceived social support of community nurses in Changchun, and to explore the relevance between them, for the purpose of providing the basis for community nursing managers to implement effective human resource management. Methods: A general demographic information questionnaire, job adaptation obstacle scale and perceived social support scale were used to investigate 290 community nurses in Changchun. Results: The score of job adaptation obstacle was 20.85±5.18; the score of perceived social support was 64.25±10.32, the score of support in the family was 20.01±3.58, and the score of the support out of family was 42.57±6.86; the job adaptation obstacle was negatively correlated with the perceived social support, the support in the family, and the support out of family. Conclusion: The job adaptation situation of the nurses in the survey communities was generally poor and the perceived social support was at a moderate level. Therefore, community nursing managers should actively understand the situation of nurse job adaptation, and then take effective measures to improve the community nurses social support, improve the current situation of the poor job adaptation of the community nurses, and prevent loss of nursing talents, for the improvement of the quality of nursing service.

  8. Learning Motivation and Adaptive Video Caption Filtering for EFL Learners Using Handheld Devices

    Science.gov (United States)

    Hsu, Ching-Kun

    2015-01-01

    The aim of this study was to provide adaptive assistance to improve the listening comprehension of eleventh grade students. This study developed a video-based language learning system for handheld devices, using three levels of caption filtering adapted to student needs. Elementary level captioning excluded 220 English sight words (see Section 1…

  9. Adaptive critic learning techniques for engine torque and air-fuel ratio control.

    Science.gov (United States)

    Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

    2008-08-01

    A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

  10. Studying the Effectiveness of an Online Language Learning Platform in China

    Science.gov (United States)

    Baker, Ryan; Wang, Feng; Ma, Zhenjun; Ma, Wei; Zheng, Shiyue

    2018-01-01

    In this paper we evaluate the effectiveness of an adaptive online learning platform, designed to support Chinese students in learning the English language. The adaptive platform is studied in three studies, where the experimental platform is compared to an alternate, non-adaptive platform, with random assignment to conditions (the adaptive…

  11. Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

    Science.gov (United States)

    Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

    2018-06-01

    This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

  12. The effect of adaptive versus static practicing on student learning - evidence from a randomized field experiment

    NARCIS (Netherlands)

    van Klaveren, Chris; Vonk, Sebastiaan; Cornelisz, Ilja

    2017-01-01

    Schools and governments are increasingly investing in adaptive practice software. To date, the evidence whether adaptivity improves learning outcomes is limited and mixed. A large-scale randomized control trial is conducted in Dutch secondary schools to evaluate the effectiveness of an adaptive

  13. Classification of multiple sclerosis lesions using adaptive dictionary learning.

    Science.gov (United States)

    Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

    2015-12-01

    This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods

    NARCIS (Netherlands)

    Verpoorten, Dominique; Poumay, M; Leclercq, D

    2006-01-01

    Please, cite this publication as: Verpoorten, D., Poumay, M., & Leclercq, D. (2006). The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence

  15. Adaptive enhancement of learning protocol in hippocampal cultured networks grown on multielectrode arrays

    Science.gov (United States)

    Pimashkin, Alexey; Gladkov, Arseniy; Mukhina, Irina; Kazantsev, Victor

    2013-01-01

    Learning in neuronal networks can be investigated using dissociated cultures on multielectrode arrays supplied with appropriate closed-loop stimulation. It was shown in previous studies that weakly respondent neurons on the electrodes can be trained to increase their evoked spiking rate within a predefined time window after the stimulus. Such neurons can be associated with weak synaptic connections in nearby culture network. The stimulation leads to the increase in the connectivity and in the response. However, it was not possible to perform the learning protocol for the neurons on electrodes with relatively strong synaptic inputs and responding at higher rates. We proposed an adaptive closed-loop stimulation protocol capable to achieve learning even for the highly respondent electrodes. It means that the culture network can reorganize appropriately its synaptic connectivity to generate a desired response. We introduced an adaptive reinforcement condition accounting for the response variability in control stimulation. It significantly enhanced the learning protocol to a large number of responding electrodes independently on its base response level. We also found that learning effect preserved after 4–6 h after training. PMID:23745105

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

    Science.gov (United States)

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

    2017-10-01

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

  17. Acculturation Strategies, Social Support, and Cross-Cultural Adaptation: A Mediation Analysis

    Science.gov (United States)

    Ng, Ting Kin; Tsang, Kwok Kuen; Lian, Yi

    2013-01-01

    Previous acculturation research has established the influences of acculturation strategies and social support on cross-cultural adaptation. The present study attempted to elaborate these direct associations by proposing that social support and the use of the integration and marginalization strategies might affect psychological adaptation…

  18. The evolutionary basis of human social learning.

    Science.gov (United States)

    Morgan, T J H; Rendell, L E; Ehn, M; Hoppitt, W; Laland, K N

    2012-02-22

    Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.

  19. Facil authentication as an extra support in virtual learning environments to avoid academic fraud

    Directory of Open Access Journals (Sweden)

    Francisco David Guillén Gámez

    2016-01-01

    Full Text Available Currently, both teachers and students are adapting themselves to the new technologies offered by the XXI century. In the case of teachers, this adaptation is greater since there is a need to adapt learning to new technologies, lifestyles and habits. One of the possibilities that information and communication technologies (ICT offer us is to provide learning management systems, with flexible learning, that allows us to manage and evaluate different activities of an e-learning process. Despite the progress made in the field of e-learning, there is a very low number of works that allow through proper mechanisms to a correct identification of students when they do their on-line activities to prevent cheating. Although current learning management systems include tools for user authentication, they only verify the user's identity at the time of login through a username and password, but it does not certify that it is the correct student. Against this trouble, the use of facial authentication software in on-line activities which students have to do, allows us to identify and prevent those students who might cheat. This research project seeks to propose a mechanism or technique to ensure the correct access to the student within a learning platform, that is to say, the student is the one who really is, through a facial recognition software called Smowl.

  20. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being

    Directory of Open Access Journals (Sweden)

    Sindhu Ravindran

    2015-01-01

    Full Text Available A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG dataset through an Improved Adaptive Genetic Algorithm (IAGA and Extreme Learning Machine (ELM. IAGA employs a new scaling technique (called sigma scaling to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.

  1. Using technology to support science inquiry learning

    Directory of Open Access Journals (Sweden)

    P John Williams

    2017-03-01

    Full Text Available This paper presents a case study of a teacher’s experience in implementing an inquiry approach to his teaching over a period of two years with two different classes. His focus was on using a range of information technologies to support student inquiry learning. The study demonstrates the need to consider the characteristics of students when implementing an inquiry approach, and also the influence of the teachers level of understanding and related confidence in such an approach. The case also indicated that a range of technologies can be effective in supporting student inquiry learning.

  2. Towards Contextualized Learning Services

    Science.gov (United States)

    Specht, Marcus

    Personalization of feedback and instruction has often been considered as a key feature in learning support. The adaptations of the instructional process to the individual and its different aspects have been investigated from different research perspectives as learner modelling, intelligent tutoring systems, adaptive hypermedia, adaptive instruction and others. Already in the 1950s first commercial systems for adaptive instruction for trainings of keyboard skills have been developed utilizing adaptive configuration of feedback based on user performance and interaction footprints (Pask 1964). Around adaptive instruction there is a variety of research issues bringing together interdisciplinary research from computer science, engineering, psychology, psychotherapy, cybernetics, system dynamics, instructional design, and empirical research on technology enhanced learning. When classifying best practices of adaptive instruction different parameters of the instructional process have been identified which are adapted to the learner, as: sequence and size of task difficulty, time of feedback, pace of learning speed, reinforcement plan and others these are often referred to the adaptation target. Furthermore Aptitude Treatment Interaction studies explored the effect of adapting instructional parameters to different characteristics of the learner (Tennyson and Christensen 1988) as task performance, personality characteristics, or cognitive abilities, this is information is referred to as adaptation mean.

  3. Mobile Apps to Support and Assess Foreign Language Learning

    Science.gov (United States)

    Berns, Anke; Palomo-Duarte, Manuel; Dodero, Juan Manuel; Ruiz-Ladrón, Juan Miguel; Márquez, Andrea Calderón

    2015-01-01

    In the last two decades there have been many attempts to integrate all kinds of mobile devices and apps to support formal as well as informal learning processes. However, most of the available apps still support mainly individual learning, using mobile devices to deliver content rather than providing learners with the opportunity to interact with…

  4. Constructive, Self-Regulated, Situated, and Collaborative Learning: An Approach for the Acquisition of Adaptive Competence

    Science.gov (United States)

    de Corte, Erik

    2012-01-01

    In today's learning society, education must focus on fostering adaptive competence (AC) defined as the ability to apply knowledge and skills flexibly in different contexts. In this article, four major types of learning are discussed--constructive, self-regulated, situated, and collaborative--in relation to what students must learn in order to…

  5. Adaptation Provisioning with Respect to Learning Styles in a Web-Based Educational System: An Experimental Study

    Science.gov (United States)

    Popescu, E.

    2010-01-01

    Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization criterion called learning style-based adaptive educational systems. The paper presents an innovative approach based on an integrative set of learning preferences that alleviates…

  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. Adaptation and validation of the instrument Clinical Learning Environment and Supervision for medical students in primary health care

    Directory of Open Access Journals (Sweden)

    Eva Öhman

    2016-12-01

    Full Text Available Abstract Background Clinical learning takes place in complex socio-cultural environments that are workplaces for the staff and learning places for the students. In the clinical context, the students learn by active participation and in interaction with the rest of the community at the workplace. Clinical learning occurs outside the university, therefore is it important for both the university and the student that the student is given opportunities to evaluate the clinical placements with an instrument that allows evaluation from many perspectives. The instrument Clinical Learning Environment and Supervision (CLES was originally developed for evaluation of nursing students’ clinical learning environment. The aim of this study was to adapt and validate the CLES instrument to measure medical students’ perceptions of their learning environment in primary health care. Methods In the adaptation process the face validity was tested by an expert panel of primary care physicians, who were also active clinical supervisors. The adapted CLES instrument with 25 items and six background questions was sent electronically to 1,256 medical students from one university. Answers from 394 students were eligible for inclusion. Exploratory factor analysis based on principal component methods followed by oblique rotation was used to confirm the adequate number of factors in the data. Construct validity was assessed by factor analysis. Confirmatory factor analysis was used to confirm the dimensions of CLES instrument. Results The construct validity showed a clearly indicated four-factor model. The cumulative variance explanation was 0.65, and the overall Cronbach’s alpha was 0.95. All items loaded similarly with the dimensions in the non-adapted CLES except for one item that loaded to another dimension. The CLES instrument in its adapted form had high construct validity and high reliability and internal consistency. Conclusion CLES, in its adapted form, appears

  8. PACS infrastructure supporting e-learning

    Energy Technology Data Exchange (ETDEWEB)

    Mildenberger, Peter, E-mail: milden@radiologie.klinik.uni-mainz.de [University Medicine Mainz, Johannes Gutenberg-University Mainz, Langenbeckstr 1, Mainz (Germany); Brueggemann, Kerstin; Roesner, Freya; Koch, Katja; Ahlers, Christopher [University Medicine Mainz, Johannes Gutenberg-University Mainz, Langenbeckstr 1, Mainz (Germany)

    2011-05-15

    Digital imaging is becoming predominant in radiology. This has implications for teaching support, because conventional film-based concepts are now obsolete. The IHE Teaching File and Clinical Study Export (TCE) profile provides an excellent platform to enhance PACS infrastructure with educational functionality. This can be supplemented with dedicated e-learning tools.

  9. PACS infrastructure supporting e-learning

    International Nuclear Information System (INIS)

    Mildenberger, Peter; Brueggemann, Kerstin; Roesner, Freya; Koch, Katja; Ahlers, Christopher

    2011-01-01

    Digital imaging is becoming predominant in radiology. This has implications for teaching support, because conventional film-based concepts are now obsolete. The IHE Teaching File and Clinical Study Export (TCE) profile provides an excellent platform to enhance PACS infrastructure with educational functionality. This can be supplemented with dedicated e-learning tools.

  10. Implementation of Multiple Intelligences Supported Project-Based Learning in EFL/ESL Classrooms

    Science.gov (United States)

    Bas, Gokhan

    2008-01-01

    This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…

  11. Recent Contributions to a Generic Architecture Design that Supports Learning Objects Interoperability

    Science.gov (United States)

    Botsios, Sotirios; Georgiou, Dimitrios A.

    2009-01-01

    Adaptation and personalization services in e-learning environments are considered the turning point of recent research efforts, as the "one-size-fits-all" approach has some important drawbacks, from the educational point of view. Adaptive Educational Hypermedia Systems in World Wide Web became a very active research field and the need of…

  12. Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

    International Nuclear Information System (INIS)

    Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

    2009-01-01

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

  13. Using social media to support small group learning.

    Science.gov (United States)

    Cole, Duncan; Rengasamy, Emma; Batchelor, Shafqat; Pope, Charles; Riley, Stephen; Cunningham, Anne Marie

    2017-11-10

    Medical curricula are increasingly using small group learning and less didactic lecture-based teaching. This creates new challenges and opportunities in how students are best supported with information technology. We explored how university-supported and external social media could support collaborative small group working on our new undergraduate medical curriculum. We made available a curation platform (Scoop.it) and a wiki within our virtual learning environment as part of year 1 Case-Based Learning, and did not discourage the use of other tools such as Facebook. We undertook student surveys to capture perceptions of the tools and information on how they were used, and employed software user metrics to explore the extent to which they were used during the year. Student groups developed a preferred way of working early in the course. Most groups used Facebook to facilitate communication within the group, and to host documents and notes. There were more barriers to using the wiki and curation platform, although some groups did make extensive use of them. Staff engagement was variable, with some tutors reviewing the content posted on the wiki and curation platform in face-to-face sessions, but not outside these times. A small number of staff posted resources and reviewed student posts on the curation platform. Optimum use of these tools depends on sufficient training of both staff and students, and an opportunity to practice using them, with ongoing support. The platforms can all support collaborative learning, and may help develop digital literacy, critical appraisal skills, and awareness of wider health issues in society.

  14. Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

    Science.gov (United States)

    Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

    2015-05-01

    Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

  15. Ambient Learning Displays - Distributed Mixed Reality Information Mash-ups to support Ubiquitous Learning

    NARCIS (Netherlands)

    Börner, Dirk

    2012-01-01

    Börner, D. (2012). Ambient Learning Displays - Distributed Mixed Reality Information Mash-ups to support Ubiquitous Learning. 2012 IEEE Seventh International Conference on Wireless, Mobile and Ubiquitous Technology in Education (pp. 337-338). March, 27-30, 2012, Takamatsu, Japan: IEEE Computer

  16. Strategies for Adapting WebQuests for Students with Learning Disabilities

    Science.gov (United States)

    Skylar, Ashley A.; Higgins, Kyle; Boone, Randall

    2007-01-01

    WebQuests are gaining popularity as teachers explore using the Internet for guided learning activities. A WebQuest involves students working on a task that is broken down into clearly defined steps. Students often work in groups to actively conduct the research. This article suggests a variety of methods for adapting WebQuests for students with…

  17. Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

    Science.gov (United States)

    Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

    2012-01-01

    This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

  18. 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...

  19. Developing the learning physical science curriculum: Adapting a small enrollment, laboratory and discussion based physical science course for large enrollments

    Science.gov (United States)

    Goldberg, Fred; Price, Edward; Robinson, Stephen; Boyd-Harlow, Danielle; McKean, Michael

    2012-06-01

    We report on the adaptation of the small enrollment, lab and discussion based physical science course, Physical Science and Everyday Thinking (PSET), for a large-enrollment, lecture-style setting. Like PSET, the new Learning Physical Science (LEPS) curriculum was designed around specific principles based on research on learning to meet the needs of nonscience students, especially prospective and practicing elementary and middle school teachers. We describe the structure of the two curricula and the adaptation process, including a detailed comparison of similar activities from the two curricula and a case study of a LEPS classroom implementation. In LEPS, short instructor-guided lessons replace lengthier small group activities, and movies, rather than hands-on investigations, provide the evidence used to support and test ideas. LEPS promotes student peer interaction as an important part of sense making via “clicker” questions, rather than small group and whole class discussions typical of PSET. Examples of student dialog indicate that this format is capable of generating substantive student discussion and successfully enacting the design principles. Field-test data show similar student content learning gains with the two curricula. Nevertheless, because of classroom constraints, some important practices of science that were an integral part of PSET were not included in LEPS.

  20. Developing the learning physical science curriculum: Adapting a small enrollment, laboratory and discussion based physical science course for large enrollments

    Directory of Open Access Journals (Sweden)

    Fred Goldberg1

    2012-05-01

    Full Text Available We report on the adaptation of the small enrollment, lab and discussion based physical science course, Physical Science and Everyday Thinking (PSET, for a large-enrollment, lecture-style setting. Like PSET, the new Learning Physical Science (LEPS curriculum was designed around specific principles based on research on learning to meet the needs of nonscience students, especially prospective and practicing elementary and middle school teachers. We describe the structure of the two curricula and the adaptation process, including a detailed comparison of similar activities from the two curricula and a case study of a LEPS classroom implementation. In LEPS, short instructor-guided lessons replace lengthier small group activities, and movies, rather than hands-on investigations, provide the evidence used to support and test ideas. LEPS promotes student peer interaction as an important part of sense making via “clicker” questions, rather than small group and whole class discussions typical of PSET. Examples of student dialog indicate that this format is capable of generating substantive student discussion and successfully enacting the design principles. Field-test data show similar student content learning gains with the two curricula. Nevertheless, because of classroom constraints, some important practices of science that were an integral part of PSET were not included in LEPS.

  1. Adjusted Framework of M-Learning in Blended Learning System for Mathematics Study Field of Junior High School Level VII

    Science.gov (United States)

    Sugiyanta, Lipur; Sukardjo, Moch.

    2018-04-01

    The 2013 curriculum requires teachers to be more productive, creative, and innovative in encouraging students to be more independent by strengthening attitudes, skills and knowledge. Teachers are given the options to create lesson plan according to the environment and conditions of their students. At the junior level, Core Competence (KI) and Basic Competence (KD) have been completely designed. In addition, there had already guidebooks, both for teacher manuals (Master’s Books) and for learners (Student Books). The lesson plan and guidebooks which already exist are intended only for learning in the classroom/in-school. Many alternative classrooms and alternatives learning models opened up using educational technology. The advance of educational technology opened opportunity for combination of class interaction using mobile learning applications. Mobile learning has rapidly evolved in education for the last ten years and many initiatives have been conducted worldwide. However, few of these efforts have produced any lasting outcomes. It is evident that mobile education applications are complex and hence, will not become sustainable. Long-term sustainability remains a risk. Long-term sustainability usually was resulted from continuous adaptation to changing conditions [4]. Frameworks are therefore required to avoid sustainability pitfalls. The implementation should start from simple environment then gradually become complex through adaptation steps. Therefore, our paper developed the framework of mobile learning (m-learning) adaptation for grade 7th (junior high school). The environment setup was blended mobile learning (not full mobile learning) and emphasize on Algebra. The research is done by R&D method (research and development). Results of the framework includes requirements and adaptation steps. The adjusted m-learning framework is designed to be a guidance for teachers to adopt m-learning to support blended learning environments. During mock-up prototype, the

  2. Designing and Developing a Novel Hybrid Adaptive Learning Path Recommendation System (ALPRS) for Gamification Mathematics Geometry Course

    Science.gov (United States)

    Su, Chung-Ho

    2017-01-01

    Since recommendation systems possess the advantage of adaptive recommendation, they have gradually been applied to e-learning systems to recommend subsequent learning content for learners. However, problems exist in current learning recommender systems available to students in that they are often general learning content and unable to offer…

  3. 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.

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

    Science.gov (United States)

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

    2011-06-01

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

  5. Professional Learning Communities Assessment: Adaptation, Internal Validity, and Multidimensional Model Testing in Turkish Context

    Science.gov (United States)

    Dogan, Selçuk; Tatik, R. Samil; Yurtseven, Nihal

    2017-01-01

    The main purpose of this study is to adapt and validate the Professional Learning Communities Assessment Revised (PLCA-R) by Olivier, Hipp, and Huffman within the context of Turkish schools. The instrument was translated and adapted to administer to teachers in Turkey. Internal structure of the Turkish version of PLCA-R was investigated by using…

  6. 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.

  7. Chronic condition self-management support for Aboriginal people: Adapting tools and training.

    Science.gov (United States)

    Battersby, Malcolm; Lawn, Sharon; Kowanko, Inge; Bertossa, Sue; Trowbridge, Coral; Liddicoat, Raylene

    2018-04-22

    Chronic conditions are major health problems for Australian Aboriginal people. Self-management programs can improve health outcomes. However, few health workers are skilled in self-management support and existing programs are not always appropriate in Australian Aboriginal contexts. The goal was to increase the capacity of the Australian health workforce to support Australian Aboriginal people to self-manage their chronic conditions by adapting the Flinders Program of chronic condition self-management support for Australian Aboriginal clients and develop and deliver training for health professionals to implement the program. Feedback from health professionals highlighted that the Flinders Program assessment and care planning tools needed to be adapted to suit Australian Aboriginal contexts. Through consultation with Australian Aboriginal Elders and other experts, the tools were condensed into an illustrated booklet called 'My Health Story'. Associated training courses and resources focusing on cultural safety and effective engagement were developed. A total of 825 health professionals  across Australia was trained and 61 people qualified as accredited trainers in the program, ensuring sustainability. The capacity and skills of the Australian health workforce to engage with and support Australian Aboriginal people to self-manage their chronic health problems significantly increased as a result of this project. The adapted tools and training were popular and appreciated by the health care organisations, health professionals and clients involved. The adapted tools have widespread appeal for cultures that do not have Western models of health care and where there are health literacy challenges. My Health Story has already been used internationally. © 2018 National Rural Health Alliance Ltd.

  8. Learning for transformation of water governance

    NARCIS (Netherlands)

    Blackmore, Chris; Bommel, van Severine; Bruin, de Annemarieke; Vries, de Jasper; Westberg, Lotten; Powell, Neil; Foster, Natalie; Collins, Kevin; Roggero, Pier Paolo; Seddaiu, Giovanna

    2016-01-01

    This paper considers how learning for transformation of water governance in the context of climate change adaptation can be designed for and supported, drawing examples from the international climate change adaptation and water governance project (CADWAGO). The project explicitly set out to design

  9. Automation of information decision support to improve e-learning resources quality

    Directory of Open Access Journals (Sweden)

    A.L. Danchenko

    2013-06-01

    Full Text Available Purpose. In conditions of active development of e-learning the high quality of e-learning resources is very important. Providing the high quality of e-learning resources in situation with mass higher education and rapid obsolescence of information requires the automation of information decision support for improving the quality of e-learning resources by development of decision support system. Methodology. The problem is solved by methods of artificial intelligence. The knowledge base of information structure of decision support system that is based on frame model of knowledge representation and inference production rules are developed. Findings. According to the results of the analysis of life cycle processes and requirements to the e-learning resources quality the information model of the structure of the knowledge base of the decision support system, the inference rules for the automatically generating of recommendations and the software implementation are developed. Practical value. It is established that the basic requirements for quality are performance, validity, reliability and manufacturability. It is shown that the using of a software implementation of decision support system for researched courses gives a growth of the quality according to the complex quality criteria. The information structure of a knowledge base system to support decision-making and rules of inference can be used by methodologists and content developers of learning systems.

  10. Collaborative learning: A next step in the training of peer support providers.

    Science.gov (United States)

    Cronise, Rita

    2016-09-01

    This column explores how peer support provider training is enhanced through collaborative learning. Collaborative learning is an approach that draws upon the "real life" experiences of individual learners and encompasses opportunities to explore varying perspectives and collectively construct solutions that enrich the practice of all participants. This description draws upon published articles and examples of collaborative learning in training and communities of practice of peer support providers. Similar to person-centered practices that enhance the recovery experience of individuals receiving services, collaborative learning enhances the experience of peer support providers as they explore relevant "real world" issues, offer unique contributions, and work together toward improving practice. Three examples of collaborative learning approaches are provided that have resulted in successful collaborative learning opportunities for peer support providers. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  11. Learning deep features with adaptive triplet loss for person reidentification

    Science.gov (United States)

    Li, Zhiqiang; Sang, Nong; Chen, Kezhou; Gao, Changxin; Wang, Ruolin

    2018-03-01

    Person reidentification (re-id) aims to match a specified person across non-overlapping cameras, which remains a very challenging problem. While previous methods mostly focus on feature extraction or metric learning, this paper makes the attempt in jointly learning both the global full-body and local body-parts features of the input persons with a multichannel convolutional neural network (CNN) model, which is trained by an adaptive triplet loss function that serves to minimize the distance between the same person and maximize the distance between different persons. The experimental results show that our approach achieves very promising results on the large-scale Market-1501 and DukeMTMC-reID datasets.

  12. The Role of Digital Libraries to Support of E-learning

    OpenAIRE

    Akbar Majidi

    2012-01-01

    E-learning is the new pattern of teaching and learning process. The main characteristic of e-learning is delivery of content and learning activity within learning management systems (LMS). E-learning for its success requires that access to resources and information services. Digital libraries can offer different resources and information services on the Internet. Therefore, it will be very useful to support e-learning in this article, after expression of definitions of e-learning and ...

  13. Learning Analytics Architecture to Scaffold Learning Experience through Technology-based Methods

    Directory of Open Access Journals (Sweden)

    Jannicke Madeleine Baalsrud Hauge

    2015-02-01

    Full Text Available The challenge of delivering personalized learning experiences is often increased by the size of classrooms and online learning communities. Serious Games (SGs are increasingly recognized for their potential to improve education. However, the issues related to their development and their level of effectiveness can be seriously affected when brought too rapidly into growing online learning communities. Deeper insights into how the students are playing is needed to deliver a comprehensive and intelligent learning framework that facilitates better understanding of learners' knowledge, effective assessment of their progress and continuous evaluation and optimization of the environments in which they learn. This paper discusses current SOTA and aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model (ecosystem and architecture discussed in this paper aims to highlight the key considerations that may advance the current state of learning analytics, adaptive learning and SGs, by leveraging SGs as an suitable medium for gathering data and performing adaptations.

  14. Work Stress Adaptation: Roles of Gender, Social Support and ...

    African Journals Online (AJOL)

    Workers in Nigeria are faced with many stress factors such as work-related, domestic, after job, age or retirement problem to cope with or managed. In view of this, the present study examined the effects of gender, social support and personality (Type A and Type B) on work stress adaptation. Using random and accidental ...

  15. Adaptation of the multidimensional scale of perceived social support ...

    African Journals Online (AJOL)

    Background: The Multidimensional Scale of Perceived Social Support (MSPSS) was developed in the USA. The adequacy of its use in Uganda to guarantee its reliability and validity has not been ascertained. Aim: Thus the aim of the present study was to adapt the MSPSS scale by testing the validity and reliability of the ...

  16. Evaluation of an Adaptive Learning Technology in a First-year Extended Curriculum Programme Physics course

    Directory of Open Access Journals (Sweden)

    Moses Mushe Basitere

    2017-12-01

    Full Text Available Personalised, adaptive online learning platforms that form part of web-based proficiency tests play a major role in the improvement of the quality of learning in physics and assist learners in building proficiency, preparing for tests and using their time more effectively. In this study, the effectiveness of an adaptive learning platform, Wiley Plus ORION, was evaluated using proficiency test scores compared to paper-based test scores in a first-year introductory engineering physics course. Learners’ performance activities on the adaptive learning platform as well as their performance on the proficiency tests and their impact on the paper-based midterm averaged test were investigated using both qualitative and quantitative methods of data collection. A comparison between learners’ performance on the proficiency tests and a paper-based midterm test was done to evaluate whether there was a correlation between their performance on the proficiency tests and the midterm test. Focus group interviews were carried out with three categories of learners to elicit their experiences. Results showed that there was a positive relationship between high-performing learners’ proficiency score in the midterm averaged test and that the proficiency test enhanced learners’ performance in the paper-based midterm averaged test.

  17. A framework for adaptive e-learning for continuum mechanics and structural analysis

    OpenAIRE

    Mosquera Feijoo, Juan Carlos; Plaza Beltrán, Luis Francisco; González Rodrigo, Beatriz

    2015-01-01

    This paper presents a project for providing the students of Structural Engineering with the flexibility to learn outside classroom schedules. The goal is a framework for adaptive E-learning based on a repository of open educational courseware with a set of basic Structural Engineering concepts and fundamentals. These are paramount for students to expand their technical knowledge and skills in structural analysis and design of tall buildings, arch-type structures as well as bridges. Thus, conc...

  18. A field experiment of energy education using integrative learning support system

    International Nuclear Information System (INIS)

    Obayashi, Fumiaki; Yamamoto, Atsumu; Ito, Kyoko; Shimoda, Hiroshi; Yoshikawa, Hidekazu

    2002-01-01

    A new energy learning support system for higher education was the object of this experiment. The aim of this learning support system is to support students within an integrative study environment in which various personal skills and general knowledge on energy related issues are to be developed. The main goals of this learning tool for the students are to simulate their interest and creativity, to enhance awareness, to increase capability of researching on the subject and to improve problem-solving skills on energy related issues. The salient feature of this learning support system is that it is used for group learning by which each learner can develop the ability to reflect on the subject through mutual discussion. Moreover, in order to keep the attention of the students on the topic and provide them with a better assimilation of the curriculum, a personified agent is used as a cooperative associate who assists learners through natural communication, using voice conversation function in Japanese language. Then, the subject experiment has been conducted. Also, means of effective energy education are discussed in this research. As a conclusion, this learning support system is proven to be effective and the use of it for energy education is recommended. (author)

  19. Adaptive Training and Collective Decision Support Based on Man-Machine Interface

    Science.gov (United States)

    2016-03-02

    Based on Man -machine Interface The views, opinions and/or findings contained in this report are those of the author(s) and should not contrued as an...ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 adaptive training, EEG, man -machine interface...non peer-reviewed journals: Final Report: Adaptive Training and Collective Decision Support Based on Man -machine Interface Report Title The existence of

  20. Collaborative Education in Climate Change Sciences and Adaptation through Interactive Learning

    Science.gov (United States)

    Ozbay, G.; Sriharan, S.; Fan, C.

    2014-12-01

    As a result of several funded climate change education grants, collaboration between VSU, DSU, and MSU, was established to provide the innovative and cohesive education and research opportunities to underrepresented groups in the climate related sciences. Prior to offering climate change and adaptation related topics to the students, faculty members of the three collaborating institutions participated at a number of faculty training and preparation workshops for teaching climate change sciences (i.e. AMS Diversity Project Workshop, NCAR Faculty-Student Team on Climate Change, NASA-NICE Program). In order to enhance the teaching and student learning on various issues in the Environmental Sciences Programs, Climatology, Climate Change Sciences and Adaptation or related courses were developed at Delaware State University and its partner institutions (Virginia State University and Morgan State University). These courses were prepared to deliver information on physical basis for the earth's climate system and current climate change instruction modules by AMS and historic climate information (NOAA Climate Services, U.S. and World Weather Data, NCAR and NASA Climate Models). By using Global Seminar as a Model, faculty members worked in teams to engage students in videoconferencing on climate change through Contemporary Global Studies and climate courses including Climate Change and Adaptation Science, Sustainable Agriculture, Introduction to Environmental Sciences, Climatology, and Ecology and Adaptation courses. All climate change courses have extensive hands-on practices and research integrated into the student learning experiences. Some of these students have presented their classroom projects during Earth Day, Student Climate Change Symposium, Undergraduate Summer Symposium, and other national conferences.

  1. Bridging Scientific Reasoning and Conceptual Change through Adaptive Web-Based Learning

    Science.gov (United States)

    She, Hsiao-Ching; Liao, Ya-Wen

    2010-01-01

    This study reports an adaptive digital learning project, Scientific Concept Construction and Reconstruction (SCCR), and examines its effects on 108 8th grade students' scientific reasoning and conceptual change through mixed methods. A one-group pre-, post-, and retention quasi-experimental design was used in the study. All students received tests…

  2. The Adaptation of Contents for the Creation of Foreign Language Learning Exams for Mobile Devices

    Directory of Open Access Journals (Sweden)

    Gimenez López Jose Luis

    2009-07-01

    Full Text Available This article describes the process of adaptation of online digital contents for the realization of foreign language learning tests through mobile devices. Taking into account the need detected in relation to the quick development of mobile technologies, the development and adaptation of existing online exams for mobile devices will be studied. We will do that by considering the possible navigation limits when using multiplatforms, and the aspects related to the formal and technical conditions which the audiovisual contents shown by the device must fulfil. The existing online language learning tests can be adapted to mobile devices through the programming XHTML language. But, the limitations of navigability in relation to contents and the handling of interaction devices available for users to do the tests must also be considered.

  3. Theta synchronization between medial prefrontal cortex and cerebellum is associated with adaptive performance of associative learning behavior

    Science.gov (United States)

    Chen, Hao; Wang, Yi-jie; Yang, Li; Sui, Jian-feng; Hu, Zhi-an; Hu, Bo

    2016-01-01

    Associative learning is thought to require coordinated activities among distributed brain regions. For example, to direct behavior appropriately, the medial prefrontal cortex (mPFC) must encode and maintain sensory information and then interact with the cerebellum during trace eyeblink conditioning (TEBC), a commonly-used associative learning model. However, the mechanisms by which these two distant areas interact remain elusive. By simultaneously recording local field potential (LFP) signals from the mPFC and the cerebellum in guinea pigs undergoing TEBC, we found that theta-frequency (5.0–12.0 Hz) oscillations in the mPFC and the cerebellum became strongly synchronized following presentation of auditory conditioned stimulus. Intriguingly, the conditioned eyeblink response (CR) with adaptive timing occurred preferentially in the trials where mPFC-cerebellum theta coherence was stronger. Moreover, both the mPFC-cerebellum theta coherence and the adaptive CR performance were impaired after the disruption of endogenous orexins in the cerebellum. Finally, association of the mPFC -cerebellum theta coherence with adaptive CR performance was time-limited occurring in the early stage of associative learning. These findings suggest that the mPFC and the cerebellum may act together to contribute to the adaptive performance of associative learning behavior by means of theta synchronization. PMID:26879632

  4. An Ontology to Support the Classification of Learning Material in an Organizational Learning Environment: An Evaluation

    Science.gov (United States)

    Valaski, Joselaine; Reinehr, Sheila; Malucelli, Andreia

    2017-01-01

    Purpose: The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area. Design/methodology/approach: An ontology for recommending learning material was integrated in the organizational learning environment…

  5. Panorama of recommender systems to support learning

    OpenAIRE

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework. The reviewed systems have been classified into 7 clusters according to their c...

  6. Student Support in Open Learning: Sustaining the Process.

    Science.gov (United States)

    Dearnley, Christine

    2003-01-01

    A 2-year study included interviews with 18 and survey of 160 nurses studying through open learning in the United Kingdom. They were challenged by returning to study, requiring time management and technological skills. Professional, academic, and social networks provided important support as life responsibilities and events impinged on learning.…

  7. Technology Support for Discussion Based Learning: From Computer Supported Collaborative Learning to the Future of Massive Open Online Courses

    Science.gov (United States)

    Rosé, Carolyn Penstein; Ferschke, Oliver

    2016-01-01

    This article offers a vision for technology supported collaborative and discussion-based learning at scale. It begins with historical work in the area of tutorial dialogue systems. It traces the history of that area of the field of Artificial Intelligence in Education as it has made an impact on the field of Computer-Supported Collaborative…

  8. Web-Based System for Adaptable Rubrics: Case Study on CAD Assessment

    Science.gov (United States)

    Company, Pedro; Contero, Manuel; Otey, Jeffrey; Camba, Jorge D.; Agost, María-Jesús; Pérez-López, David

    2017-01-01

    This paper describes the implementation and testing of our concept of adaptable rubrics, defined as analytical rubrics that arrange assessment criteria at multiple levels that can be expanded on demand. Because of its adaptable nature, these rubrics cannot be implemented in paper formats, neither are they supported by current Learning Management…

  9. Supporting Shared Resource Usage for a Diverse User Community: the OSG Experience and Lessons Learned

    International Nuclear Information System (INIS)

    Garzoglio, Gabriele; Levshina, Tanya; Sehgal, Chander; Slyz, Marko; Rynge, Mats

    2012-01-01

    The Open Science Grid (OSG) supports a diverse community of new and existing users in adopting and making effective use of the Distributed High Throughput Computing (DHTC) model. The LHC user community has deep local support within the experiments. For other smaller communities and individual users the OSG provides consulting and technical services through the User Support area. We describe these sometimes successful and sometimes not so successful experiences and analyze lessons learned that are helping us improve our services. The services offered include forums to enable shared learning and mutual support, tutorials and documentation for new technology, and troubleshooting of problematic or systemic failure modes. For new communities and users, we bootstrap their use of the distributed high throughput computing technologies and resources available on the OSG by following a phased approach. We first adapt the application and run a small production campaign on a subset of “friendly” sites. Only then do we move the user to run full production campaigns across the many remote sites on the OSG, adding to the community resources up to hundreds of thousands of CPU hours per day. This scaling up generates new challenges – like no determinism in the time to job completion, and diverse errors due to the heterogeneity of the configurations and environments – so some attention is needed to get good results. We cover recent experiences with image simulation for the Large Synoptic Survey Telescope (LSST), small-file large volume data movement for the Dark Energy Survey (DES), civil engineering simulation with the Network for Earthquake Engineering Simulation (NEES), and accelerator modeling with the Electron Ion Collider group at BNL. We will categorize and analyze the use cases and describe how our processes are evolving based on lessons learned.

  10. Reflections on providing sport science support for athletes with learning difficulties.

    Science.gov (United States)

    Hills, Laura; Utley, Andrea

    2010-01-01

    To highlight the benefits and the need for sport science support for athletes with learning difficulties, and to reflect on our experience of working with the GB squad for athletes with learning difficulties. A review of key and relevant literature is presented, followed by a discussion of the sport science support provision and the issues that emerged in working with athletes with learning difficulties. Pre- and post- physiological tests along with evaluations of athletes' potential to benefit from sport psychology support were conducted. The aim of these tests was to provide information for the athletes and the coaches on fitness levels, to use this information to plan future training, and to identify how well the performance could be enhanced. A case study is presented for one athlete, who had competed in distance events. The focus is the psychological support that was provided. It is clear that athletes with learning difficulties require the same type of sports science support as their mainstream peers. However, sport scientists will need to consider ways to extend their practice in order to provide the appropriate level of support.

  11. Biometeorology - a science supporting adaptation strategies

    Science.gov (United States)

    Matzarakis, A.; Cegnar, T.

    2010-09-01

    research activities, identify the needs of the actors and to jointly develop adaptation strategies at local scale. The anticipatory adaptation requires communication activities on the level of the individual tourism actors among themselves and with visitors as well as processes of cooperative learning and joint decision-making in tourism regions. There are well known several examples of using heat budget models for assessing human thermal comfort and developing Heat Watch Warning Systems to prevent adverse effects of heat waves.

  12. Investigating the Impact of Formal Reflective Activities on Skill Adaptation in a Work-Related Instrumental Learning Setting

    Science.gov (United States)

    Roessger, Kevin M.

    2013-01-01

    In work-related, instrumental learning contexts the role of reflective activities is unclear. Kolb's (1985) experiential learning theory and Mezirow's transformative learning theory (2000) predict skill-adaptation as a possible outcome. This prediction was experimentally explored by manipulating reflective activities and assessing participants'…

  13. Children and adolescents with migratory experience at risk in language learning and psychosocial adaptation contexts.

    OpenAIRE

    Figueiredo, Sandra; Silva, Carlos Fernandes da; Monteiro, Sara

    2007-01-01

    A compelling body of evidence shows a strong association between psychological, affective and learning variables, related also with the age and gender factors, which are involved in the language learning development process. Children and adolescents with migratory experience (direct/indirect) can develop behaviours at risk in their academic learning and psychosocial adaptation, according to several stressors as anxiety, low motivation, negative attitudes, within a stressed internal l...

  14. Adaptive Advice in Learning With a Computer-Based Knowledge Management Simulation Game

    NARCIS (Netherlands)

    Leemkuil, Hendrik H.; de Jong, Anthonius J.M.

    2012-01-01

    Despite the long tradition of game-based learning, there are still many unanswered questions regarding the instructional design of educational games. An important issue is the support that learners can be given in a game to enhance their learning. One recommended type of support is “advice,” which

  15. QUALITY ASSURANCE IN RWANDAN HIGHER LEARNING EDUCATION: IS THE SYSTEM ADAPTIVE OR COMPLEX?

    Directory of Open Access Journals (Sweden)

    Nathan Kanuma Taremwa

    2014-01-01

    Full Text Available Developing knowledge infrastructure by massive investments in education and training are taken as a benchmark in facilitating the acceleration and possible increases in skills, capacities and competences of Rwandan people has become apriority issue in the recent years. This notion is relevant to vision 2020 where human resource development and building of a knowledge based economy are fundamental pillars. In the past years, several policy reforms have taken place in education sector. However, the overarching question is if such reforms are becoming adaptive or complex and if such reforms will not compromise the quality of education in higher learning education in Rwanda? The main objective of the study was to investigate the impact of changes in Higher Learning Institutions on the quality of education in Rwanda. This research had three hypotheses, namely; there is an impact of changes in Higher Learning Institutions on quality of education in Rwanda; the current complexity in Rwandan education system is affecting the quality of education in HLIs; Tailoring education system to the regional reforms and implementation strategies is affecting the quality of education in Rwanda. This study was carried out in 10 higher learning institutions (5 public, 5 private and 2 Ministry of Education directorates (HEC and REB. Key informants were the senior management/head of institutions, experienced academic staff, and students. The parameters considered included; the learning methods, assessment styles, workloads, language of instruction, merging of public HLIs, curriculum, and the transformation of some private higher learning institutions into company forms. Main research instruments were questionnaires and interview guides. Both qualitative and quantitative research was collected. Analyses were done using SPSS and excel packages. Major findings indicate that the system is still in transition with indicative gaps. Ample time would therefore be necessary for

  16. Six Characteristics of Nutrition Education Videos That Support Learning and Motivation to Learn

    Science.gov (United States)

    Ramsay, Samantha A.; Holyoke, Laura; Branen, Laurel J.; Fletcher, Janice

    2012-01-01

    Objective: To identify characteristics in nutrition education video vignettes that support learning and motivation to learn about feeding children. Methods: Nine focus group interviews were conducted with child care providers in child care settings from 4 states in the western United States: California, Idaho, Oregon, and Washington. At each focus…

  17. Development of decision support system for employee selection using Adaptive Neuro Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    ‘Azzam Abdullah

    2018-01-01

    Full Text Available The number of children day care is increasing from year to year. Children day care is categorized as service industry that help parents in caring and educate children. This type of service industry plays a substitute for the family at certain hours, usually during work hours. The common problems in this industry is related to the employee performance. Most of employees have a less understanding about the whole job. Some employees only perform a routine task, i.e. feeding, cleaning and putting the child to sleep. The role in educating children is not performed as well as possible. Therefore, the employee selection is an important process to solve a children day care problem. An effective decision support system is required to optimize the employee selection process. Adaptive neuro fuzzy inference system (ANFIS is used to develop the decision support system for employee selection process. The data used to build the system is the historical data of employee selection process in children day care. The data shows the characteristic of job applicant that qualified and not qualified. From that data, the system can perform a learning process and give the right decision. The system is able to provide the right decision with an error of 0,00016249. It means that the decision support system that developed using ANFIS can give the right recommendation for employee selection process.

  18. Observation on the uses of Mobile Phones to Support Informal Learning

    Directory of Open Access Journals (Sweden)

    Mohd Azlishah Othman

    2012-10-01

    Full Text Available This paper explores how a group of undergraduate students in one of the university in South of Malaysian use their mobile phones to perform informal learning activities related to the content of their courses outside the classroom. The paper also addresses the usefulness of informal learning activities to support students’ learning. The study adopts an exploratory case study design and uses two methods of data collection including questionnaires and interviews. Main findings suggest that students performed informal learning activities mostly from office, home, interacting mainly with classmates. It also shows that students were in control of their informal learning activities without tutor or SMEs’ input. However, it was found that students used only a limited number of applications but these were considered useful to their learning. The paper contributes to a discussion of the implications of training and instructional support to help students to take more advantage of mobile phone applications to support informal learning. The conclusion is discussed about the further research in this domain.

  19. Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

    Science.gov (United States)

    Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

    2017-10-01

    Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. A dual-adaptive support-based stereo matching algorithm

    Science.gov (United States)

    Zhang, Yin; Zhang, Yun

    2017-07-01

    Many stereo matching algorithms use fixed color thresholds and a rigid cross skeleton to segment supports (viz., Cross method), which, however, does not work well for different images. To address this issue, this paper proposes a novel dual adaptive support (viz., DAS)-based stereo matching method, which uses both appearance and shape information of a local region to segment supports automatically, and, then, integrates the DAS-based cost aggregation with the absolute difference plus census transform cost, scanline optimization and disparity refinement to develop a stereo matching system. The performance of the DAS method is also evaluated in the Middlebury benchmark and by comparing with the Cross method. The results show that the average error for the DAS method 25.06% lower than that for the Cross method, indicating that the proposed method is more accurate, with fewer parameters and suitable for parallel computing.

  1. Adaptive support ventilation: A translational study evaluating the size of delivered tidal volumes

    NARCIS (Netherlands)

    Veelo, Denise P.; Dongelmans, Dave A.; Binnekade, Jan M.; Paulus, Frederique; Schultz, Marcus J.

    2010-01-01

    Purpose: Adaptive support ventilation (ASV) is a microprocessor-controlled, closed-loop mode of mechanical ventilation that adapts respiratory rates and tidal volumes (V(T)s) based on the Otis least work of breathing formula. We studied calculated V(T)s in a computer simulation model, and V(T)s

  2. Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems.

    Science.gov (United States)

    Grisafi, Andrea; Wilkins, David M; Csányi, Gábor; Ceriotti, Michele

    2018-01-19

    Statistical learning methods show great promise in providing an accurate prediction of materials and molecular properties, while minimizing the need for computationally demanding electronic structure calculations. The accuracy and transferability of these models are increased significantly by encoding into the learning procedure the fundamental symmetries of rotational and permutational invariance of scalar properties. However, the prediction of tensorial properties requires that the model respects the appropriate geometric transformations, rather than invariance, when the reference frame is rotated. We introduce a formalism that extends existing schemes and makes it possible to perform machine learning of tensorial properties of arbitrary rank, and for general molecular geometries. To demonstrate it, we derive a tensor kernel adapted to rotational symmetry, which is the natural generalization of the smooth overlap of atomic positions kernel commonly used for the prediction of scalar properties at the atomic scale. The performance and generality of the approach is demonstrated by learning the instantaneous response to an external electric field of water oligomers of increasing complexity, from the isolated molecule to the condensed phase.

  3. Effectiveness of Adaptive Contextual Learning Model of Integrated Science by Integrating Digital Age Literacy on Grade VIII Students

    Science.gov (United States)

    Asrizal, A.; Amran, A.; Ananda, A.; Festiyed, F.

    2018-04-01

    Educational graduates should have good competencies to compete in the 21st century. Integrated learning is a good way to develop competence of students in this century. Besides that, literacy skills are very important for students to get success in their learning and daily life. For this reason, integrated science learning and literacy skills are important in 2013 curriculum. However, integrated science learning and integration of literacy in learning can’t be implemented well. Solution of this problem is to develop adaptive contextual learning model by integrating digital age literacy. The purpose of the research is to determine the effectiveness of adaptive contextual learning model to improve competence of grade VIII students in junior high school. This research is a part of the research and development or R&D. Research design which used in limited field testing was before and after treatment. The research instruments consist of three parts namely test sheet of learning outcome for assessing knowledge competence, observation sheet for assessing attitudes, and performance sheet for assessing skills of students. Data of student’s competence were analyzed by three kinds of analysis, namely descriptive statistics, normality test and homogeneity test, and paired comparison test. From the data analysis result, it can be stated that the implementation of adaptive contextual learning model of integrated science by integrating digital age literacy is effective to improve the knowledge, attitude, and literacy skills competences of grade VIII students in junior high school at 95% confidence level.

  4. Scripting intercultural computer-supported collaborative learning in higher education

    NARCIS (Netherlands)

    Popov, V.

    2013-01-01

    Introduction of computer-supported collaborative learning (CSCL), specifically in an intercultural learning environment, creates both challenges and benefits. Among the challenges are the coordination of different attitudes, styles of communication, and patterns of behaving. Among the benefits are

  5. Mild-moderate TBI: clinical recommendations to optimize neurobehavioral functioning, learning, and adaptation.

    Science.gov (United States)

    Chen, Anthony J-W; Loya, Fred

    2014-11-01

    Traumatic brain injury (TBI) can result in functional deficits that persist long after acute injury. The authors present a case study of an individual who experienced some of the most common debilitating problems that characterize the chronic phase of mild-to-moderate TBI-difficulties with neurobehavioral functions that manifest via complaints of distractibility, poor memory, disorganization, poor frustration tolerance, and feeling easily overwhelmed. They present a rational strategy for management that addresses important domain-general targets likely to have far-ranging benefits. This integrated, longitudinal, and multifaceted approach first addresses approachable targets and provides an important foundation to enhance the success of other, more specific interventions requiring specialty intervention. The overall approach places an emphasis on accomplishing two major categories of clinical objectives: optimizing current functioning and enhancing learning and adaptation to support improvement of functioning in the long-term for individuals living with brain injury. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  6. A Survey of Technologies Supporting Virtual Project Based Learning

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    2002-01-01

    This paper describes a survey of technologies and to what extent they support virtual project based learning. The paper argues that a survey of learning technologies should be related to concrete learning tasks and processes. Problem oriented project pedagogy (POPP) is discussed, and a framework...... for evaluation is proposed where negotiation of meaning, coordination and resource management are identified as the key concepts in virtual project based learning. Three e-learning systems are selected for the survey, Virtual-U, Lotus Learningspace and Lotus Quickplace, as each system offers different strategies...... for e-learning. The paper concludes that virtual project based learning may benefit from facilities of all these systems....

  7. Social Support Provisions as Differential Predictors of Adaptive Outcomes in Young Adolescents

    Science.gov (United States)

    Warren, Jared S.; Jackson, Yo; Sifers, Sarah K.

    2009-01-01

    Social support provisions were examined in relation to negative life events, adaptive skills, hope, and grade point average in a sample of 103 inner-city youth (ages 11-14). Analyses focused on seven support provisions: social integration, attachment, guidance and information, reliable alliance, reassurance of worth, nurturance, and instrumental…

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

    Science.gov (United States)

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

    2016-09-14

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

  9. A globally convergent MC algorithm with an adaptive learning rate.

    Science.gov (United States)

    Peng, Dezhong; Yi, Zhang; Xiang, Yong; Zhang, Haixian

    2012-02-01

    This brief deals with the problem of minor component analysis (MCA). Artificial neural networks can be exploited to achieve the task of MCA. Recent research works show that convergence of neural networks based MCA algorithms can be guaranteed if the learning rates are less than certain thresholds. However, the computation of these thresholds needs information about the eigenvalues of the autocorrelation matrix of data set, which is unavailable in online extraction of minor component from input data stream. In this correspondence, we introduce an adaptive learning rate into the OJAn MCA algorithm, such that its convergence condition does not depend on any unobtainable information, and can be easily satisfied in practical applications.

  10. Negotiating Service Learning through Community Engagement: Adaptive Leadership, Knowledge, Dialogue and Power

    Science.gov (United States)

    Preece, Julia

    2016-01-01

    This article builds on two recent publications (Preece 2013; 2013a) concerning the application of asset-based community development and adaptive leadership theories when negotiating university service learning placements with community organisations in one South African province. The first publication introduced the concept of 'adaptive…

  11. Japanese English Education and Learning: A History of Adapting Foreign Cultures

    Science.gov (United States)

    Shimizu, Minoru

    2010-01-01

    This essay is a history that relates the Japanese tradition of accepting and adapting aspects of foreign culture, especially as it applies to the learning of foreign languages. In particular, the essay describes the history of English education in Japan by investigating its developments after the Meiji era. The author addresses the issues from the…

  12. Supportive Elements for Learning at a Global IT Company

    DEFF Research Database (Denmark)

    Kolbæk, Ditte

    2016-01-01

    This paper presents a completed research study that connects design, theory and practice. It explores learning in an online community of practice, which reflects upon experiences from facilitating learning situations in the context of work. The study’s aim is to identify supportive elements...... for learning at a global IT company that is classified as ‘big business’ and supports hundreds of communities of practice. This study examines an online community with members from more than 30 countries in Europe, the Middle East and Africa. The members never meet, and yet develop new working practices...... by collaborating online. The study draws on Silvia Gherardi’s (2015) work on working practices and Etienne Wenger’s (1998) theory of communities of practice. The research question is: ‘How can the context support the development of new working practices in communities of practice, when the members only interact...

  13. System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

    Science.gov (United States)

    Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

    2014-05-01

    During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

  14. Seamless Integration of Desktop and Mobile Learning Experience through an Ontology-Based Adaptation Engine: Report of a Pilot-Project

    Science.gov (United States)

    Mercurio, Marco; Torre, Ilaria; Torsani, Simone

    2014-01-01

    The paper describes a module within the distance language learning environment of the Language Centre at the Genoa University which adapts, through an ontology, learning activities to the device in use. Adaptation means not simply resizing a page but also the ability to transform the nature of a task so that it fits the device with the smallest…

  15. Data mining methods application in reflexive adaptation realization in e-learning systems

    Directory of Open Access Journals (Sweden)

    A. S. Bozhday

    2017-01-01

    Full Text Available In recent years, e-learning technologies are rapidly gaining momentum in their evolution. In this regard, issues related to improving the quality of software for virtual educational systems are becoming topical: increasing the period of exploitation of programs, increasing their reliability and flexibility. The above characteristics directly depend on the ability of the software system to adapt to changes in the domain, environment and user characteristics. In some cases, this ability is reduced to the timely optimization of the program’s own interfaces and data structure. At present, several approaches to creating mechanisms for self-optimization of software systems are known, but all of them have an insufficient degree of formalization and, as a consequence, weak universality. The purpose of this work is to develop the basics of the technology of self-optimization of software systems in the structure of e-learning. The proposed technology is based on the formulated and formalized principle of reflexive adaptation of software, applicable to a wide class of software systems and based on the discovery of new knowledge in the behavioral products of the system.To solve this problem, methods of data mining were applied. Data mining allows finding regularities in the functioning of software systems, which may not be obvious at the stage of their development. Finding such regularities and their subsequent analysis will make it possible to reorganize the structure of the system in a more optimal way and without human intervention, which will prolong the life cycle of the software and reduce the costs of its maintenance. Achieving this effect is important for e-learning systems, since they are quite expensive.The main results of the work include: the proposed classification of software adaptation mechanisms, taking into account the latest trends in the IT field in general and in the field of e-learning in particular; Formulation and formalization of

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

    Science.gov (United States)

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

    1997-01-01

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

  17. Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

    Science.gov (United States)

    Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

    2017-02-07

    Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Natural pedagogy as evolutionary adaptation.

    Science.gov (United States)

    Csibra, Gergely; Gergely, György

    2011-04-12

    We propose that the cognitive mechanisms that enable the transmission of cultural knowledge by communication between individuals constitute a system of 'natural pedagogy' in humans, and represent an evolutionary adaptation along the hominin lineage. We discuss three kinds of arguments that support this hypothesis. First, natural pedagogy is likely to be human-specific: while social learning and communication are both widespread in non-human animals, we know of no example of social learning by communication in any other species apart from humans. Second, natural pedagogy is universal: despite the huge variability in child-rearing practices, all human cultures rely on communication to transmit to novices a variety of different types of cultural knowledge, including information about artefact kinds, conventional behaviours, arbitrary referential symbols, cognitively opaque skills and know-how embedded in means-end actions. Third, the data available on early hominin technological culture are more compatible with the assumption that natural pedagogy was an independently selected adaptive cognitive system than considering it as a by-product of some other human-specific adaptation, such as language. By providing a qualitatively new type of social learning mechanism, natural pedagogy is not only the product but also one of the sources of the rich cultural heritage of our species.

  19. Natural pedagogy as evolutionary adaptation

    Science.gov (United States)

    Csibra, Gergely; Gergely, György

    2011-01-01

    We propose that the cognitive mechanisms that enable the transmission of cultural knowledge by communication between individuals constitute a system of ‘natural pedagogy’ in humans, and represent an evolutionary adaptation along the hominin lineage. We discuss three kinds of arguments that support this hypothesis. First, natural pedagogy is likely to be human-specific: while social learning and communication are both widespread in non-human animals, we know of no example of social learning by communication in any other species apart from humans. Second, natural pedagogy is universal: despite the huge variability in child-rearing practices, all human cultures rely on communication to transmit to novices a variety of different types of cultural knowledge, including information about artefact kinds, conventional behaviours, arbitrary referential symbols, cognitively opaque skills and know-how embedded in means-end actions. Third, the data available on early hominin technological culture are more compatible with the assumption that natural pedagogy was an independently selected adaptive cognitive system than considering it as a by-product of some other human-specific adaptation, such as language. By providing a qualitatively new type of social learning mechanism, natural pedagogy is not only the product but also one of the sources of the rich cultural heritage of our species. PMID:21357237

  20. The Impact of Leadership Support for Blended Learning on Teachers and Students

    Science.gov (United States)

    Bodden-White, Michelle Marie

    2015-01-01

    This quantitative study examined the relationship between teachers' perceptions of leadership support for their use of a blended learning approach to teach math in fourth or fifth grade and their use of blended learning. The study also examined teachers' perceptions of leadership support for incorporating blended learning and student engagement.…

  1. Supporting Vocationally Oriented Learning in the High School Years: Rationale, Tasks, Challenges

    Science.gov (United States)

    Halpern, Robert

    2012-01-01

    This article highlights the limitations of our current educational system in terms of vocational learning and highlights the role that vocational learning can play in supporting youth development and improving youth outcomes. It discusses the role that nonschool settings can play in supporting vocational learning and suggests strategies to improve…

  2. Shifting the Balance in First-Year Learning Support: From Staff Instruction to Peer-Learning Primacy

    Science.gov (United States)

    van der Meer, Jacques; Scott, Carole

    2008-01-01

    Effective response to the learning needs of first-year students is a contested issue. In many learning support centres the dominant approach to developing student learning skills is through generic or tailored workshops and/or individual consultations. Although there is a place for these activities, we argue that the balance should be shifted…

  3. Quality Assessment of Adaptive Bitrate Videos using Image Metrics and Machine Learning

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Brunnström, Kjell

    2015-01-01

    Adaptive bitrate (ABR) streaming is widely used for distribution of videos over the internet. In this work, we investigate how well we can predict the quality of such videos using well-known image metrics, information about the bitrate levels, and a relatively simple machine learning method...

  4. Questions for Parents to Ask about School Adaptations. PHP-c91

    Science.gov (United States)

    PACER Center, 2004

    2004-01-01

    A child with a disability who has an Individualized Education Program (IEP) or Section 504 Accommodation Plan may need extra help and support to participate in school. It takes thoughtful planning to choose adaptations, based on a child's disability, to help the child learn or have access to learning. Appropriate accommodations vary with…

  5. Implementation of Evidence-Based Practice From a Learning Perspective.

    Science.gov (United States)

    Nilsen, Per; Neher, Margit; Ellström, Per-Erik; Gardner, Benjamin

    2017-06-01

    For many nurses and other health care practitioners, implementing evidence-based practice (EBP) presents two interlinked challenges: acquisition of EBP skills and adoption of evidence-based interventions and abandonment of ingrained non-evidence-based practices. The purpose of this study to describe two modes of learning and use these as lenses for analyzing the challenges of implementing EBP in health care. The article is theoretical, drawing on learning and habit theory. Adaptive learning involves a gradual shift from slower, deliberate behaviors to faster, smoother, and more efficient behaviors. Developmental learning is conceptualized as a process in the "opposite" direction, whereby more or less automatically enacted behaviors become deliberate and conscious. Achieving a more EBP depends on both adaptive and developmental learning, which involves both forming EBP-conducive habits and breaking clinical practice habits that do not contribute to realizing the goals of EBP. From a learning perspective, EBP will be best supported by means of adaptive learning that yields a habitual practice of EBP such that it becomes natural and instinctive to instigate EBP in appropriate contexts by means of seeking out, critiquing, and integrating research into everyday clinical practice as well as learning new interventions best supported by empirical evidence. However, the context must also support developmental learning that facilitates disruption of existing habits to ascertain that the execution of the EBP process or the use of evidence-based interventions in routine practice is carefully and consciously considered to arrive at the most appropriate response. © 2017 Sigma Theta Tau International.

  6. Quality through E-Learning and Quality for E-Learning

    OpenAIRE

    Vatuiu Teodora; Udrica Mioara; Negrutiu Magdalena

    2013-01-01

    E-learning is a term frequently debated in the lasts years, especially in the academic environment. Computer technology has profoundly transformed society, research and education. It provides support for the development of an educational system continuously adapted to society’s demands and advances in knowledge acquisition. Students can learn, evaluate and communicate their own results in formal or informal settings, universities and other public institutions take part in the development of i...

  7. Sparing of descending axons rescues interneuron plasticity in the lumbar cord to allow adaptive learning after thoracic spinal cord injury

    Directory of Open Access Journals (Sweden)

    Christopher Nelson Hansen

    2016-03-01

    Full Text Available This study evaluated the role of spared axons on structural and behavioral neuroplasticity in the lumbar enlargement after a thoracic spinal cord injury (SCI. Previous work has demonstrated that recovery in the presence of spared axons after an incomplete lesion increases behavioral output after a subsequent complete spinal cord transection (TX. This suggests that spared axons direct adaptive changes in below-level neuronal networks of the lumbar cord. In response to spared fibers, we postulate that lumbar neuron networks support behavioral gains by preventing aberrant plasticity. As such, the present study measured histological and functional changes in the isolated lumbar cord after complete TX or incomplete contusion (SCI. To measure functional plasticity in the lumbar cord, we used an established instrumental learning paradigm. In this paradigm, neural circuits within isolated lumbar segments demonstrate learning by an increase in flexion duration that reduces exposure to a noxious leg shock. We employed this model using a proof-of-principle design to evaluate the role of sparing on lumbar learning and plasticity early (7 days or late (42 days after midthoracic SCI in a rodent model. Early after SCI or TX at 7d, spinal learning was unattainable regardless of whether the animal recovered with or without axonal substrate. Failed learning occurred alongside measures of cell soma atrophy and aberrant dendritic spine expression within interneuron populations responsible for sensorimotor integration and learning. Alternatively, exposure of the lumbar cord to a small amount of spared axons for 6 weeks produced near-normal learning late after SCI. This coincided with greater cell soma volume and fewer aberrant dendritic spines on interneurons. Thus, an opportunity to influence activity-based learning in locomotor networks depends on spared axons limiting maladaptive plasticity. Together, this work identifies a time dependent interaction between

  8. Solar adaptive optics: specificities, lessons learned, and open alternatives

    Science.gov (United States)

    Montilla, I.; Marino, J.; Asensio Ramos, A.; Collados, M.; Montoya, L.; Tallon, M.

    2016-07-01

    the Strehl and the Point Spread Function used in night time adaptive optics but not really suitable to the solar systems, and new control strategies more complex than the ones used in nowadays solar Multi Conjugate Adaptive Optics systems. In this paper we summarize the lessons learned with past and current solar adaptive optics systems and focus on the discussion on the new alternatives to solve present open issues limiting their performance.

  9. Social Networks, Psychosocial Adaptation, and Preventive/Developmental Interventions: The Support Development Workshop.

    Science.gov (United States)

    Todd, David M.

    The Support Development Group is an approach which explores and develops a theory for the relationship between network characteristics and notions of psychosocial adaptation. The approach is based on the assumption that teaching people to view their social world in network terms can be helpful to them. The Support Development Workshop is presented…

  10. Run-Time and Compiler Support for Programming in Adaptive Parallel Environments

    Directory of Open Access Journals (Sweden)

    Guy Edjlali

    1997-01-01

    Full Text Available For better utilization of computing resources, it is important to consider parallel programming environments in which the number of available processors varies at run-time. In this article, we discuss run-time support for data-parallel programming in such an adaptive environment. Executing programs in an adaptive environment requires redistributing data when the number of processors changes, and also requires determining new loop bounds and communication patterns for the new set of processors. We have developed a run-time library to provide this support. We discuss how the run-time library can be used by compilers of high-performance Fortran (HPF-like languages to generate code for an adaptive environment. We present performance results for a Navier-Stokes solver and a multigrid template run on a network of workstations and an IBM SP-2. Our experiments show that if the number of processors is not varied frequently, the cost of data redistribution is not significant compared to the time required for the actual computation. Overall, our work establishes the feasibility of compiling HPF for a network of nondedicated workstations, which are likely to be an important resource for parallel programming in the future.

  11. The experiences of supporting learning in pairs of nursing students in clinical practice.

    Science.gov (United States)

    Holst, Hanna; Ozolins, Lise-Lotte; Brunt, David; Hörberg, Ulrica

    2017-09-01

    The purpose of this study is to describe how supervisors experience supporting nursing students' learning in pairs on a Developing and Learning Care Unit in Sweden. The present study has been carried out with a Reflective Lifeworld Research (RLR) approach founded on phenomenology. A total of 25 lifeworld interviews were conducted with supervisors who had supervised pairs of students. The findings reveal how supervisors support students' learning in pairs through a reflective approach creating learning space in the encounter with patients, students and supervisors. Supervisors experience a movement that resembles balancing between providing support in learning together and individual learning. The findings also highlight the challenge in supporting both the pairs of students and being present in the reality of caring. In conclusion, the learning space has the potential of creating a relative level of independency in the interaction between pairs of students and their supervisor when the supervisor strives towards a reflective approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs

    Science.gov (United States)

    Adamson, David; Dyke, Gregory; Jang, Hyeju; Rosé, Carolyn Penstein

    2014-01-01

    This paper investigates the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called Academically Productive Talk (APT). In contrast to past work on dynamic support for collaborative learning, where agents were used to elevate conceptual depth by leading students through directed lines of…

  13. Adaptation and Retention of a Perceptual-Motor Task in Children: Effects of a Single Bout of Intense Endurance Exercise.

    Science.gov (United States)

    Ferrer-Uris, Blai; Busquets, Albert; Angulo-Barroso, Rosa

    2018-02-01

    We assessed the effect of an acute intense exercise bout on the adaptation and consolidation of a visuomotor adaptation task in children. We also sought to assess if exercise and learning task presentation order could affect task consolidation. Thirty-three children were randomly assigned to one of three groups: (a) exercise before the learning task, (b) exercise after the learning task, and (c) only learning task. Baseline performance was assessed by practicing the learning task in a 0° rotation condition. Afterward, a 60° rotation-adaptation set was applied followed by three rotated retention sets after 1 hr, 24 hr, and 7 days. For the exercise groups, exercise was presented before or after the motor adaptation. Results showed no group differences during the motor adaptation while exercise seemed to enhance motor consolidation. Greater consolidation enhancement was found in participants who exercised before the learning task. Our data support the importance of exercise to improve motor-memory consolidation in children.

  14. EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

    Directory of Open Access Journals (Sweden)

    Suwicha Jirayucharoensak

    2014-01-01

    Full Text Available Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN to discover unknown feature correlation between input signals that is crucial for the learning task. The DLN is implemented with a stacked autoencoder (SAE using hierarchical feature learning approach. Input features of the network are power spectral densities of 32-channel EEG signals from 32 subjects. To alleviate overfitting problem, principal component analysis (PCA is applied to extract the most important components of initial input features. Furthermore, covariate shift adaptation of the principal components is implemented to minimize the nonstationary effect of EEG signals. Experimental results show that the DLN is capable of classifying three different levels of valence and arousal with accuracy of 49.52% and 46.03%, respectively. Principal component based covariate shift adaptation enhances the respective classification accuracy by 5.55% and 6.53%. Moreover, DLN provides better performance compared to SVM and naive Bayes classifiers.

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

    Science.gov (United States)

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

    2003-12-01

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

  16. Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices

    OpenAIRE

    Lim, Suhwan; Bae, Jong-Ho; Eum, Jai-Ho; Lee, Sungtae; Kim, Chul-Heung; Kwon, Dongseok; Park, Byung-Gook; Lee, Jong-Ho

    2017-01-01

    In this paper, we propose a learning rule based on a back-propagation (BP) algorithm that can be applied to a hardware-based deep neural network (HW-DNN) using electronic devices that exhibit discrete and limited conductance characteristics. This adaptive learning rule, which enables forward, backward propagation, as well as weight updates in hardware, is helpful during the implementation of power-efficient and high-speed deep neural networks. In simulations using a three-layer perceptron net...

  17. Peer Pressure and Adaptive Behavior Learning: A Study of Adolescents in Gujrat City

    OpenAIRE

    Asma Yunus; Shahzad Khaver Mushtaq; Sobia Qaiser

    2012-01-01

    The study aims at discovering the influences of Peer Pressure on adaptive behavior learning in the adolescents. For the purpose two scales, Adaptive behavior scale (ABS) and Peer Pressure Scale (PPS) were developed to measure both variables. The Sample of the study was purposive in nature and comprised of late adolescents (n=120) i.e. 60 males and 60 females, from Gujrat city. Cronbach alpha was calculated and found to be significant for Peer Pressure Scale(PPS) and its subscales i.e. Belongi...

  18. A Digital Coach That Provides Affective and Social Learning Support to Low-Literate Learners

    NARCIS (Netherlands)

    Schouten, D.G.M.; Venneker, F.; Bosse, T.; Neerincx, M.; Cremer, A.H.M.

    In this study, we investigate if a digital coach for low-literate learners that provides cognitive learning support based on scaffolding can be improved by adding affective learning support based on motivational interviewing, and social learning support based on small talk. Several knowledge gaps

  19. Game-Based Learning in an OpenSim-Supported Virtual Environment on Perceived Motivational Quality of Learning

    Science.gov (United States)

    Kim, Heesung; Ke, Fengfeng; Paek, Insu

    2017-01-01

    This experimental study was intended to examine whether game-based learning (GBL) that encompasses four particular game characteristics (challenges, a storyline, immediate rewards and the integration of game-play with learning content) in an OpenSimulator-supported virtual reality learning environment can improve perceived motivational quality of…

  20. A CONCEPT OF SOFTWARE SUPPORT OF LEARNING PROGRAMMING LANGUAGE AND TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    V. Kruglyk

    2013-03-01

    Full Text Available A concept of software support of learning programming language and technologies is regarded in the article. Present systems of independent study of subjects, related to programming, are examined. Necessary components of a system of support learning programming languages and technologies, which is oriented on independent study, are considered.

  1. Developing a Matrix Organization to Unify Learning Support Services.

    Science.gov (United States)

    Clarke, John H.; Mansfield, Barry K.

    1988-01-01

    Describes use of matrix management to organize learning support services on a college campus. Claims matrix management, which links support services from academic and student affairs, increases access, improves accountability, and encourages new programs. (Author/ABL)

  2. Integrating Collaborative and Decentralized Models to Support Ubiquitous Learning

    Science.gov (United States)

    Barbosa, Jorge Luis Victória; Barbosa, Débora Nice Ferrari; Rigo, Sandro José; de Oliveira, Jezer Machado; Rabello, Solon Andrade, Jr.

    2014-01-01

    The application of ubiquitous technologies in the improvement of education strategies is called Ubiquitous Learning. This article proposes the integration between two models dedicated to support ubiquitous learning environments, called Global and CoolEdu. CoolEdu is a generic collaboration model for decentralized environments. Global is an…

  3. Adaptive Control Using Fully Online Sequential-Extreme Learning Machine and a Case Study on Engine Air-Fuel Ratio Regulation

    Directory of Open Access Journals (Sweden)

    Pak Kin Wong

    2014-01-01

    Full Text Available Most adaptive neural control schemes are based on stochastic gradient-descent backpropagation (SGBP, which suffers from local minima problem. Although the recently proposed regularized online sequential-extreme learning machine (ReOS-ELM can overcome this issue, it requires a batch of representative initial training data to construct a base model before online learning. The initial data is usually difficult to collect in adaptive control applications. Therefore, this paper proposes an improved version of ReOS-ELM, entitled fully online sequential-extreme learning machine (FOS-ELM. While retaining the advantages of ReOS-ELM, FOS-ELM discards the initial training phase, and hence becomes suitable for adaptive control applications. To demonstrate its effectiveness, FOS-ELM was applied to the adaptive control of engine air-fuel ratio based on a simulated engine model. Besides, controller parameters were also analyzed, in which it is found that large hidden node number with small regularization parameter leads to the best performance. A comparison among FOS-ELM and SGBP was also conducted. The result indicates that FOS-ELM achieves better tracking and convergence performance than SGBP, since FOS-ELM tends to learn the unknown engine model globally whereas SGBP tends to “forget” what it has learnt. This implies that FOS-ELM is more preferable for adaptive control applications.

  4. The Mediating Effect of Intrinsic Motivation to Learn on the Relationship between Student´s Autonomy Support and Vitality and Deep Learning.

    Science.gov (United States)

    Núñez, Juan L; León, Jaime

    2016-07-18

    Self-determination theory has shown that autonomy support in the classroom is associated with an increase of students' intrinsic motivation. Moreover, intrinsic motivation is related with positive outcomes. This study examines the relationships between autonomy support, intrinsic motivation to learn and two motivational consequences, deep learning and vitality. Specifically, the hypotheses were that autonomy support predicts the two types of consequences, and that autonomy support directly and indirectly predicts the vitality and the deep learning through intrinsic motivation to learn. Participants were 276 undergraduate students. The mean age was 21.80 years (SD = 2.94). Structural equation modeling was used to test the relationships between variables and delta method was used to analyze the mediating effect of intrinsic motivation to learn. Results indicated that student perception of autonomy support had a positive effect on deep learning and vitality (p motivation to learn. These findings suggest that teachers are key elements in generating of autonomy support environment to promote intrinsic motivation, deep learning, and vitality in classroom. Educational implications are discussed.

  5. Adaptive Learning in Cartesian Product of Reproducing Kernel Hilbert Spaces

    OpenAIRE

    Yukawa, Masahiro

    2014-01-01

    We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs). The task is estimating/tracking nonlinear functions which are supposed to contain multiple components such as (i) linear and nonlinear components, (ii) high- and low- frequency components etc. In this case, the use of multiple RKHSs permits a compact representation of multicomponent functions. The proposed algorithm is where t...

  6. Adaptive ethnography

    DEFF Research Database (Denmark)

    Berth, Mette

    2005-01-01

    This paper focuses on the use of an adaptive ethnography when studying such phenomena as young people's use of mobile media in a learning perspective. Mobile media such as PDAs and mobile phones have a number of affordances which make them potential tools for learning. However, before we begin to...... formal and informal learning contexts. The paper also proposes several adaptive methodological techniques for studying young people's interaction with mobiles.......This paper focuses on the use of an adaptive ethnography when studying such phenomena as young people's use of mobile media in a learning perspective. Mobile media such as PDAs and mobile phones have a number of affordances which make them potential tools for learning. However, before we begin...... to design and develop educational materials for mobile media platforms we must first understand everyday use and behaviour with a medium such as a mobile phone. The paper outlines the research design for a PhD project on mobile learning which focuses on mobile phones as a way to bridge the gap between...

  7. Adaptive SVM for Data Stream Classification

    Directory of Open Access Journals (Sweden)

    Isah A. Lawal

    2017-07-01

    Full Text Available In this paper, we address the problem of learning an adaptive classifier for the classification of continuous streams of data. We present a solution based on incremental extensions of the Support Vector Machine (SVM learning paradigm that updates an existing SVM whenever new training data are acquired. To ensure that the SVM effectiveness is guaranteed while exploiting the newly gathered data, we introduce an on-line model selection approach in the incremental learning process. We evaluated the proposed method on real world applications including on-line spam email filtering and human action classification from videos. Experimental results show the effectiveness and the potential of the proposed approach.

  8. Application of ICT supported learning in fluid mechanics

    DEFF Research Database (Denmark)

    Brohus, Henrik; Svidt, Kjeld

    2004-01-01

    of tools for knowledge transfer facilitates deep understanding and increases learning efficiency. Air flow is by nature invisible and represents a further challenge in the effort of providing sufficient understanding of typical flow patterns and behaviour of room air flow. An example of visualisation......This paper focuses on the application of ICT, Information & Communication Technology, supported learning in the area of fluid mechanics education. Taking a starting point in a course in Ventilation Technology, including room air flow and contaminant distribution, it explains how ICT may be used...... actively in the learning environment to increase efficiency in the learning process. The paper comprises past experiences and lessons learnt as well as prospect for future development in the area. A model is presented that describes a high efficiency learning environment where ICT plays an important role...

  9. Learning in Educational Computer Games for Novices: The Impact of Support Provision Types on Virtual Presence, Cognitive Load, and Learning Outcomes

    Directory of Open Access Journals (Sweden)

    Claudia Schrader

    2012-06-01

    Full Text Available Embedding support devices in educational computer games has been asserted to positively affect learning outcomes. However, there is only limited direct empirical evidence on which design variations of support provision influence learning. In order to better understand the impact of support design on novices’ learning, the current study investigates how support devices and their type of provision (intrinsic vs. extrinsic determine games’ effectiveness on learning outcomes. This effectiveness is also related to how the design-type of provision influences learners’ virtual presence and cognitive load. Compared to an educational adventure game without additional support, the results indicate that the game equipped with support devices enhances learning outcomes, although no differences in cognitive load were found. A variation in the design of provision shows no effect. In order to gain a more thorough understanding of support devices and their design for games, additional learner characteristics (e.g., interest should be considered in future research.

  10. Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-20

    Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

  11. Support vector machine incremental learning triggered by wrongly predicted samples

    Science.gov (United States)

    Tang, Ting-long; Guan, Qiu; Wu, Yi-rong

    2018-05-01

    According to the classic Karush-Kuhn-Tucker (KKT) theorem, at every step of incremental support vector machine (SVM) learning, the newly adding sample which violates the KKT conditions will be a new support vector (SV) and migrate the old samples between SV set and non-support vector (NSV) set, and at the same time the learning model should be updated based on the SVs. However, it is not exactly clear at this moment that which of the old samples would change between SVs and NSVs. Additionally, the learning model will be unnecessarily updated, which will not greatly increase its accuracy but decrease the training speed. Therefore, how to choose the new SVs from old sets during the incremental stages and when to process incremental steps will greatly influence the accuracy and efficiency of incremental SVM learning. In this work, a new algorithm is proposed to select candidate SVs and use the wrongly predicted sample to trigger the incremental processing simultaneously. Experimental results show that the proposed algorithm can achieve good performance with high efficiency, high speed and good accuracy.

  12. Sustained Professional Development on Cooperative Learning: Impact on Six Teachers' Practices and Students' Learning.

    Science.gov (United States)

    Goodyear, Victoria A

    2017-03-01

    It has been argued, extensively and internationally, that sustained school-based continuous professional development (CPD) has the potential to overcome some of the shortcomings of traditional one-off CPD programs. Yet, the evidence base on more effective or less effective forms of CPD is contradictory. The mechanisms by which sustained support should be offered are unclear, and the impacts on teachers' and students' learning are complex and difficult to track. The purpose of this study was to examine the impact of a sustained school-based, tailored, and supported CPD program on teachers' practices and students' learning. Data are reported from 6 case studies of individual teachers engaged in a yearlong CPD program focused on cooperative learning. The CPD program involved participatory action research and frequent interaction/support from a boundary spanner (researcher/facilitator). Data were gathered from 29 video-recorded lessons, 108 interviews, and 35 field journal entries. (a) Individualized (external) support, (b) departmental (internal) support, and (c) sustained support impacted teachers' practices of cooperative learning. The teachers adapted their practices of cooperative learning in response to their students' learning needs. Teachers began to develop a level of pedagogical fluency, and in doing so, teachers advanced students' learning. Because this study demonstrates impact, it contributes to international literature on effective CPD. The key contribution is the detailed evidence about how and why CPD supported 6 individual teachers to learn-differently-and the complexity of the learning support required to engage in ongoing curriculum development to positively impact student learning.

  13. Cooperative Learning, Responsibility, Ambiguity, Controversy and Support in Motivating Students

    Directory of Open Access Journals (Sweden)

    Ronald Brecke, PhD

    2007-08-01

    Full Text Available This paper argues that student motivation is nurtured more by intrinsic rather than extrinsic rewards. Rather than relying on grades alone to stimulate students, this paper explores how engendering a natural critical learning environment can give students a sense of ownership in their own learning and lead to their commitment to that learning. We examine uses of cooperative learning, shared responsibility, ambiguity, controversy and support in student motivation.

  14. Cooperative Learning, Responsibility, Ambiguity, Controversy and Support in Motivating Students

    Directory of Open Access Journals (Sweden)

    Ronald Brecke

    2007-01-01

    Full Text Available This paper argues that student motivation is nurtured more by intrinsic rather than extrinsic rewards. Rather than relying on grades alone to stimulate students, this paper explores how engendering a natural critical learning environment can give students a sense of ownership in their own learning and lead to their commitment to that learning. We examine uses of cooperative learning, shared responsibility, ambiguity, controversy and support in student motivation.

  15. Elements of Social Learning Supporting Transformative Change

    African Journals Online (AJOL)

    sound, ontologically congruent methodology to support their social-learning ..... role in strengthening democratisation of the decision-making of the participants. ... powers of the contextual social structures and cultural systems (Lindley, 2014). ... participatory practice in integrated water resource management in South Africa.

  16. Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach.

    Science.gov (United States)

    Chen, Jinying; Jagannatha, Abhyuday N; Fodeh, Samah J; Yu, Hong

    2017-10-31

    Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation-that is, creating lay definitions for these terms. Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target

  17. The Effects of Mobile-Computer-Supported Collaborative Learning: Meta-Analysis and Critical Synthesis

    Science.gov (United States)

    Sung, Yao-Ting; Yang, Je-Ming; Lee, Han-Yueh

    2017-01-01

    One of the trends in collaborative learning is using mobile devices for supporting the process and products of collaboration, which has been forming the field of mobile-computer-supported collaborative learning (mCSCL). Although mobile devices have become valuable collaborative learning tools, evaluative evidence for their substantial…

  18. Integrated Decision Support for Global Environmental Change Adaptation

    Science.gov (United States)

    Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

    2011-12-01

    Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

  19. A Digital Coach That Provides Affective and Social Learning Support to Low-Literate Learners

    Science.gov (United States)

    Schouten, Dylan G. M.; Venneker, Fleur; Bosse, Tibor; Neerincx, Mark A.; Cremers, Anita H. M.

    2018-01-01

    In this study, we investigate if a digital coach for low-literate learners that provides cognitive learning support based on scaffolding can be improved by adding affective learning support based on motivational interviewing, and social learning support based on small talk. Several knowledge gaps are identified: motivational interviewing and small…

  20. A Case Study on Learning Difficulties and Corresponding Supports for Learning in cMOOCs

    Science.gov (United States)

    Li, Shuang; Tang, Qi; Zhang, Yanxia

    2016-01-01

    cMOOCs, which are based on connectivist learning theory, bring challenges for learners as well as opportunities for self-inquiry. Previous studies have shown that learners in cMOOCs may have difficulties learning, but these studies do not provide any in-depth, empirical explorations of student difficulties or support strategies. This paper…

  1. Regulation of Emotions in Socially Challenging Learning Situations: An Instrument to Measure the Adaptive and Social Nature of the Regulation Process

    Science.gov (United States)

    Jarvenoja, Hanna; Volet, Simone; Jarvela, Sanna

    2013-01-01

    Self-regulated learning (SRL) research has conventionally relied on measures, which treat SRL as an aptitude. To study self-regulation and motivation in learning contexts as an ongoing adaptive process, situation-specific methods are needed in addition to static measures. This article presents an "Adaptive Instrument for Regulation of Emotions"…

  2. Automatic, Global and Dynamic Student Modeling in a Ubiquitous Learning Environment

    Directory of Open Access Journals (Sweden)

    Sabine Graf

    2009-03-01

    Full Text Available Ubiquitous learning allows students to learn at any time and any place. Adaptivity plays an important role in ubiquitous learning, aiming at providing students with adaptive and personalized learning material, activities, and information at the right place and the right time. However, for providing rich adaptivity, the student model needs to be able to gather a variety of information about the students. In this paper, an automatic, global, and dynamic student modeling approach is introduced, which aims at identifying and frequently updating information about students’ progress, learning styles, interests and knowledge level, problem solving abilities, preferences for using the system, social connectivity, and current location. This information is gathered in an automatic way, using students’ behavior and actions in different learning situations provided by different components/services of the ubiquitous learning environment. By providing a comprehensive student model, students can be supported by rich adaptivity in every component/service of the learning environment. Furthermore, the information in the student model can help in giving teachers a better understanding about the students’ learning process.

  3. Applications of Support Vector Machine (SVM) Learning in Cancer Genomics

    OpenAIRE

    HUANG, SHUJUN; CAI, NIANGUANG; PACHECO, PEDRO PENZUTI; NARANDES, SHAVIRA; WANG, YANG; XU, WAYNE

    2017-01-01

    Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better ...

  4. Online discussion compensates for suboptimal timing of supportive information presentation in a digitally supported learning environment

    NARCIS (Netherlands)

    Noroozi, O.; Busstra, M.C.; Mulder, M.; Biemans, H.J.A.; Tobi, H.; Geelen, A.; Veer, van 't P.; Chizari, M.

    2012-01-01

    This study used a sequential set-up to investigate the consecutive effects of timing of supportive information presentation (information before vs. information during the learning task clusters) in interactive digital learning materials (IDLMs) and type of collaboration (personal discussion vs.

  5. Comparison of the Psychological Characteristics of Adaptation in Orphan Students of Initial Learning Stage to Adaptation Potential in Students Brought up in Families

    Directory of Open Access Journals (Sweden)

    Zamorueva V.V.,

    2014-08-01

    Full Text Available We present a study of psychological characteristics of preadult orphans, their psychological adaptation to the conditions of learning in high school compared to the norm population (students living in family. We assumed that the level of adaptation of the orphan students is significantly smaller than in other students, because of their special life circumstances (maternal deprivation, living in residential care institutions, sometimes bad heredity, lack of life skills in everyday issues, personal problems. The results of the survey of 49 orphan students (26 girls and 23 boys and 49 first-year students brought up by parents (28 girls and 21 boys, confirmed this hypothesis and allow us to tell that orphan students need special psychological help in the learning process in high school to grow at a personal and professional level.

  6. Perceived support among Iranian mothers of children with learning disability.

    Science.gov (United States)

    Kermanshahi, Sima Mohammad Khan; Vanaki, Zohreh; Ahmadi, Fazlollah; Azadfalah, Parviz

    2009-01-01

    This qualitative phenomenological study explores the lived experiences of perceived support by Iranian mothers who have children with learning disability. Twelve open interviews with six mothers of learning-disabled children (7-12 years of age) were audiotape-recorded with participants' consent. The interviews were transcribed and data were analyzed using Van Manen methodology. Two major themes emerged from 138 thematic sentences. The mothers'experiences could be interpreted as a sense of being in the light or being in the shade of support, with variations for different participants. The results indicate a need for more specialized and individually adjusted support for mothers in Iran.

  7. Linear hypergeneralization of learned dynamics across movement speeds reveals anisotropic, gain-encoding primitives for motor adaptation.

    Science.gov (United States)

    Joiner, Wilsaan M; Ajayi, Obafunso; Sing, Gary C; Smith, Maurice A

    2011-01-01

    The ability to generalize learned motor actions to new contexts is a key feature of the motor system. For example, the ability to ride a bicycle or swing a racket is often first developed at lower speeds and later applied to faster velocities. A number of previous studies have examined the generalization of motor adaptation across movement directions and found that the learned adaptation decays in a pattern consistent with the existence of motor primitives that display narrow Gaussian tuning. However, few studies have examined the generalization of motor adaptation across movement speeds. Following adaptation to linear velocity-dependent dynamics during point-to-point reaching arm movements at one speed, we tested the ability of subjects to transfer this adaptation to short-duration higher-speed movements aimed at the same target. We found near-perfect linear extrapolation of the trained adaptation with respect to both the magnitude and the time course of the velocity profiles associated with the high-speed movements: a 69% increase in movement speed corresponded to a 74% extrapolation of the trained adaptation. The close match between the increase in movement speed and the corresponding increase in adaptation beyond what was trained indicates linear hypergeneralization. Computational modeling shows that this pattern of linear hypergeneralization across movement speeds is not compatible with previous models of adaptation in which motor primitives display isotropic Gaussian tuning of motor output around their preferred velocities. Instead, we show that this generalization pattern indicates that the primitives involved in the adaptation to viscous dynamics display anisotropic tuning in velocity space and encode the gain between motor output and motion state rather than motor output itself.

  8. A sequential model to link contextual risk, perception and public support for flood adaptation policy.

    Science.gov (United States)

    Shao, Wanyun; Xian, Siyuan; Lin, Ning; Small, Mitchell J

    2017-10-01

    The economic damage from coastal flooding has dramatically increased over the past several decades, owing to rapid development in shoreline areas and possible effects of climate change. To respond to these trends, it is imperative for policy makers to understand individuals' support for flood adaptation policy. Using original survey data for all coastal counties of the United States Gulf Coast merged with contextual data on flood risk, this study investigates coastal residents' support for two adaptation policy measures: incentives for relocation and funding for educational programs on emergency planning and evacuation. Specifically, this study explores the interactive relationships among contextual flood risks, perceived flood risks and policy support for flood adaptation, with the effects of social-demographic variables being controlled. Age, gender, race and partisanship are found to significantly affect individuals' policy support for both adaptation measures. The contextual flooding risks, indicated by distance from the coast, maximum wind speed and peak height of storm surge associated with the last hurricane landfall, and percentage of high-risk flood zone per county, are shown to impact one's perceptions of risk, which in turn influence one's support for both policy measures. The key finding -risk perception mediates the impact of contextual risk conditions on public support for flood management policies - highlights the need to ensure that the public is well informed by the latest scientific, engineering and economic knowledge. To achieve this, more information on current and future flood risks and options available for mitigation as well as risk communication tools are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Body dysmorphic concerns, social adaptation, and motivation for psychotherapeutic support in dermatological outpatients.

    Science.gov (United States)

    Ritter, Viktoria; Fluhr, Joachim W; Schliemann-Willers, Sibylle; Elsner, Peter; Strauß, Bernhard; Stangier, Ulrich

    2016-09-01

    Dermatologists are increasingly confronted with patients affected by body dysmorphic disorder (BDD). BDD is characterized by excessive preoccupation with one or more perceived defect(s) or flaw(s) in physical appearance which are not observable or appear slight to others. So far, there have been only few studies examining the prevalence of BDD in dermatological outpatients. In addition, the need for psychotherapeutic support in dermatological outpatients with body dysmorphic concerns has not yet been systematically examined. The objective of the present study was therefore to investigate the frequency of body dysmorphic concerns as well as social adaptation and the need for psychotherapeutic support in the aforementioned patient group. A total of 252 dermatological outpatients seen at a German university hospital were consecutively enrolled, and examined using the Dysmorphic Concerns Questionnaire, the Social Adaptation Self-Evaluation Scale, and the German version of the University of Rhode Island Change Assessment Scale. 7.9 % of all outpatients (unselected sample) showed positive test results, suggesting clinically relevant body dysmorphic concerns. Patients with clinically relevant body dysmorphic concerns exhibited poor social adaptation. Contrary to expectations, these patients revealed a high motivation for change, indicating the necessity for psychotherapeutic support. Our findings confirm previous prevalence rates of BDD in dermatological outpatients, and highlight the need for providing psychotherapeutic support to dermatological patients. © 2016 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.

  10. Successful Implementation of a Computer-Supported Collaborative Learning System in Teaching E-Commerce

    Science.gov (United States)

    Ngai, E. W. T.; Lam, S. S.; Poon, J. K. L.

    2013-01-01

    This paper describes the successful application of a computer-supported collaborative learning system in teaching e-commerce. The authors created a teaching and learning environment for 39 local secondary schools to introduce e-commerce using a computer-supported collaborative learning system. This system is designed to equip students with…

  11. Internal and External Factors Affecting Teachers' Adoption of Formative Assessment to Support Learning

    Science.gov (United States)

    Izci, Kemal

    2016-01-01

    Assessment forms an important part of instruction. Assessment that aims to support learning is known as formative assessment and it contributes student's learning gain and motivation. However, teachers rarely use assessment formatively to aid their students' learning. Thus reviewing the factors that limit or support teachers' practices of…

  12. Older adults learn less, but still reduce metabolic cost, during motor adaptation

    Science.gov (United States)

    Huang, Helen J.

    2013-01-01

    The ability to learn new movements and dynamics is important for maintaining independence with advancing age. Age-related sensorimotor changes and increased muscle coactivation likely alter the trial-and-error-based process of adapting to new movement demands (motor adaptation). Here, we asked, to what extent is motor adaptation to novel dynamics maintained in older adults (≥65 yr)? We hypothesized that older adults would adapt to the novel dynamics less well than young adults. Because older adults often use muscle coactivation, we expected older adults to use greater muscle coactivation during motor adaptation than young adults. Nevertheless, we predicted that older adults would reduce muscle activity and metabolic cost with motor adaptation, similar to young adults. Seated older (n = 11, 73.8 ± 5.6 yr) and young (n = 15, 23.8 ± 4.7 yr) adults made targeted reaching movements while grasping a robotic arm. We measured their metabolic rate continuously via expired gas analysis. A force field was used to add novel dynamics. Older adults had greater movement deviations and compensated for just 65% of the novel dynamics compared with 84% in young adults. As expected, older adults used greater muscle coactivation than young adults. Last, older adults reduced muscle activity with motor adaptation and had consistent reductions in metabolic cost later during motor adaptation, similar to young adults. These results suggest that despite increased muscle coactivation, older adults can adapt to the novel dynamics, albeit less accurately. These results also suggest that reductions in metabolic cost may be a fundamental feature of motor adaptation. PMID:24133222

  13. The relationships of social support, uncertainty, self-efficacy, and commitment to prenatal psychosocial adaptation.

    Science.gov (United States)

    Hui Choi, W H; Lee, G L; Chan, Celia H Y; Cheung, Ray Y H; Lee, Irene L Y; Chan, Cecilia L W

    2012-12-01

    To report a study of the relations of prenatal psychosocial adaptation, social support, demographic and obstetric characteristics, uncertainty, information-seeking behaviour, motherhood normalization, self-efficacy, and commitment to pregnancy. Prenatal psychosocial assessment is recommended to identify psychosocial risk factors early to prevent psychiatric morbidities of mothers and children. However, knowledge on psychosocial adaptation and its explanatory variables is inconclusive. This study was non-experimental, with a cross-sectional, correlational, prospective design. The study investigated Hong Kong Chinese women during late pregnancy. Convenience sampling methods were used, with 550 women recruited from the low-risk clinics of three public hospitals. Data was collected between January-April 2007. A self-reported questionnaire was used, consisting of a number of measurements derived from an integrated framework of the Life Transition Theory and Theory of Uncertainty in Illness. Explanatory variables of psychosocial adaptation were identified using a structural equation modelling programme. The four explanatory variables of the psychosocial adaptation were social support, uncertainty, self-efficacy, and commitment to pregnancy. In the established model, which had good fit indices, greater psychosocial adaptation was associated with higher social support, higher self-efficacy, higher commitment to pregnancy, and lower uncertainty. The findings give clinicians and midwives guidance in the aspects to focus on when providing psychosocial assessment in routine prenatal screening. Since there are insufficient reliable screening tools to assist that assessment, midwives should receive adequate training, and effective screening instruments have to be identified. The explanatory role of uncertainty found in this study should encourage inquiries into the relationship between uncertainty and psychosocial adaptation in pregnancy. © 2012 Blackwell Publishing Ltd.

  14. A Lecture Supporting System Based on Real-Time Learning Analytics

    Science.gov (United States)

    Shimada, Atsushi; Konomi, Shin'ichi

    2017-01-01

    A new lecture supporting system based on real-time learning analytics is proposed. Our target is on-site classrooms where teachers give their lectures, and a lot of students listen to teachers' explanation, conduct exercises etc. We utilize not only an e-Learning system, but also an e-Book system to collect real-time learning activities during the…

  15. Using tablets to support self-regulated learning in a longitudinal integrated clerkship

    Directory of Open Access Journals (Sweden)

    Dylan Archbold Hufty Alegría

    2014-03-01

    Full Text Available Introduction: The need to train physicians committed to learning throughout their careers has prompted medical schools to encourage the development and practice of self-regulated learning by students. Longitudinal integrated clerkships (LICs require students to exercise self-regulated learning skills. As mobile tools, tablets can potentially support self-regulation among LIC students. Methods: We provided 15 LIC students with tablet computers with access to the electronic health record (EHR, to track their patient cohort, and a multiplatform online notebook, to support documentation and retrieval of self-identified clinical learning issues. Students received a 1-hour workshop on the relevant features of the tablet and online notebook. Two focus groups with the students were used to evaluate the program, one early and one late in the year and were coded by two raters. Results: Students used the tablet to support their self-regulated learning in ways that were unique to their learning styles and increased access to resources and utilization of down-time. Students who used the tablet to self-monitor and target learning demonstrated the utility of tablets as learning tools. Conclusions: LICs are environments rich in opportunity for self-regulated learning. Tablets can enhance students’ ability to develop and employ self-regulatory skills in a clinical context.

  16. Using tablets to support self-regulated learning in a longitudinal integrated clerkship.

    Science.gov (United States)

    Alegría, Dylan Archbold Hufty; Boscardin, Christy; Poncelet, Ann; Mayfield, Chandler; Wamsley, Maria

    2014-01-01

    The need to train physicians committed to learning throughout their careers has prompted medical schools to encourage the development and practice of self-regulated learning by students. Longitudinal integrated clerkships (LICs) require students to exercise self-regulated learning skills. As mobile tools, tablets can potentially support self-regulation among LIC students. We provided 15 LIC students with tablet computers with access to the electronic health record (EHR), to track their patient cohort, and a multiplatform online notebook, to support documentation and retrieval of self-identified clinical learning issues. Students received a 1-hour workshop on the relevant features of the tablet and online notebook. Two focus groups with the students were used to evaluate the program, one early and one late in the year and were coded by two raters. Students used the tablet to support their self-regulated learning in ways that were unique to their learning styles and increased access to resources and utilization of down-time. Students who used the tablet to self-monitor and target learning demonstrated the utility of tablets as learning tools. LICs are environments rich in opportunity for self-regulated learning. Tablets can enhance students' ability to develop and employ self-regulatory skills in a clinical context.

  17. Using tablets to support self-regulated learning in a longitudinal integrated clerkship

    Science.gov (United States)

    Alegría, Dylan Archbold Hufty; Boscardin, Christy; Poncelet, Ann; Mayfield, Chandler; Wamsley, Maria

    2014-01-01

    Introduction The need to train physicians committed to learning throughout their careers has prompted medical schools to encourage the development and practice of self-regulated learning by students. Longitudinal integrated clerkships (LICs) require students to exercise self-regulated learning skills. As mobile tools, tablets can potentially support self-regulation among LIC students. Methods We provided 15 LIC students with tablet computers with access to the electronic health record (EHR), to track their patient cohort, and a multiplatform online notebook, to support documentation and retrieval of self-identified clinical learning issues. Students received a 1-hour workshop on the relevant features of the tablet and online notebook. Two focus groups with the students were used to evaluate the program, one early and one late in the year and were coded by two raters. Results Students used the tablet to support their self-regulated learning in ways that were unique to their learning styles and increased access to resources and utilization of down-time. Students who used the tablet to self-monitor and target learning demonstrated the utility of tablets as learning tools. Conclusions LICs are environments rich in opportunity for self-regulated learning. Tablets can enhance students’ ability to develop and employ self-regulatory skills in a clinical context. PMID:24646438

  18. Metacognitive components in smart learning environment

    Science.gov (United States)

    Sumadyo, M.; Santoso, H. B.; Sensuse, D. I.

    2018-03-01

    Metacognitive ability in digital-based learning process helps students in achieving learning goals. So that digital-based learning environment should make the metacognitive component as a facility that must be equipped. Smart Learning Environment is the concept of a learning environment that certainly has more advanced components than just a digital learning environment. This study examines the metacognitive component of the smart learning environment to support the learning process. A review of the metacognitive literature was conducted to examine the components involved in metacognitive learning strategies. Review is also conducted on the results of study smart learning environment, ranging from design to context in building smart learning. Metacognitive learning strategies certainly require the support of adaptable, responsive and personalize learning environments in accordance with the principles of smart learning. The current study proposed the role of metacognitive component in smart learning environment, which is useful as the basis of research in building environment in smart learning.

  19. An Adaptive Geometry Game for Handheld Devices

    Directory of Open Access Journals (Sweden)

    Harri Ketamo

    2003-01-01

    Full Text Available The development of adaptive learning systems is only in the very beginning. In fact, the concept of adaptive learning systems range from different user interfaces to behaviour adaptive systems as well as from the place and time independent systems to terminal independent systems. When approaching the concept of adaptive learning materials, we must first have conceptual models of the behaviour of different learners within digital environments.The aim of this study was to develop a geometry learning game that adapts to user’s behaviour. The learners in this study were six years old Finnish pre-school pupils. The adaptive system was very limited and the observed behaviour was defined as very simple. However, the software developed achieves good learning results among the tested pupils. The study shows that the learning effect is very promising with this kind of handheld platform and simple adaptation system. This study gives good visions of what can be achieved with more complex behaviour adaptive systems in the field of eLearning.

  20. Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

    Science.gov (United States)

    Piastra, Marco

    2013-05-01

    Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. e-Learning in Advanced Life Support-What factors influence assessment outcome?

    Science.gov (United States)

    Thorne, C J; Lockey, A S; Kimani, P K; Bullock, I; Hampshire, S; Begum-Ali, S; Perkins, G D

    2017-05-01

    To establish variables which are associated with favourable Advanced Life Support (ALS) course assessment outcomes, maximising learning effect. Between 1 January 2013 and 30 June 2014, 8218 individuals participated in a Resuscitation Council (UK) e-learning Advanced Life Support (e-ALS) course. Participants completed 5-8h of online e-learning prior to attending a one day face-to-face course. e-Learning access data were collected through the Learning Management System (LMS). All participants were assessed by a multiple choice questionnaire (MCQ) before and after the face-to-face aspect alongside a practical cardiac arrest simulation (CAS-Test). Participant demographics and assessment outcomes were analysed. The mean post e-learning MCQ score was 83.7 (SD 7.3) and the mean post-course MCQ score was 87.7 (SD 7.9). The first attempt CAS-Test pass rate was 84.6% and overall pass rate 96.6%. Participants with previous ALS experience, ILS experience, or who were a core member of the resuscitation team performed better in the post-course MCQ, CAS-Test and overall assessment. Median time spent on the e-learning was 5.2h (IQR 3.7-7.1). There was a large range in the degree of access to e-learning content. Increased time spent accessing e-learning had no effect on the overall result (OR 0.98, P=0.367) on simulated learning outcome. Clinical experience through membership of cardiac arrest teams and previous ILS or ALS training were independent predictors of performance on the ALS course whilst time spent accessing e-learning materials did not affect course outcomes. This supports the blended approach to e-ALS which allows participants to tailor their e-learning experience to their specific needs. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. The Potential of a Mobile Group Blog to Support Cultural Learning among Overseas Students

    Science.gov (United States)

    Shao, Yinjuan; Crook, Charles

    2015-01-01

    We explored the use of mobile social software, in the form of a mobile group blog, to assist cultural learning. The potential of using this technology for cultural adaptation among overseas students was examined as those students adapted to the everyday life of studying abroad. Two pilot studies and a successful field study of a mobile group blog…

  3. Collaborative Multimedia Learning: Influence of a Social Regulatory Support on Learning Performance and on Collaboration

    Science.gov (United States)

    Acuña, Santiago Roger; López-Aymes, Gabriela

    2016-01-01

    This paper analyzes the effects of a support aimed at favoring the social regulatory processes in a computer-supported collaborative learning (CSCL) environment, specifically in a comprehension task of a multimedia text about Psychology of Communication. This support, named RIDE (Saab, van Joolingen, & van Hout-Wolters, 2007; 2012), consists…

  4. Theory-based Support for Mobile Language Learning: Noticing and Recording

    Directory of Open Access Journals (Sweden)

    Agnes Kukulska-Hulme

    2009-04-01

    Full Text Available This paper considers the issue of 'noticing' in second language acquisition, and argues for the potential of handheld devices to: (i support language learners in noticing and recording noticed features 'on the spot', to help them develop their second language system; (ii help language teachers better understand the specific difficulties of individuals or those from a particular language background; and (iii facilitate data collection by applied linguistics researchers, which can be fed back into educational applications for language learning. We consider: theoretical perspectives drawn from the second language acquisition literature, relating these to the practice of writing language learning diaries; and the potential for learner modelling to facilitate recording and prompting noticing in mobile assisted language learning contexts. We then offer guidelines for developers of mobile language learning solutions to support the development of language awareness in learners.

  5. Anatomy of Student Models in Adaptive Learning Systems: A Systematic Literature Review of Individual Differences from 2001 to 2013

    Science.gov (United States)

    Nakic, Jelena; Granic, Andrina; Glavinic, Vlado

    2015-01-01

    This study brings an evidence-based review of user individual characteristics employed as sources of adaptation in recent adaptive learning systems. Twenty-two user individual characteristics were explored in a systematically designed search procedure, while 17 of them were identified as sources of adaptation in final selection. The content…

  6. Agent Based Framework Architecture for Supporting Content Adaptation for Mobile Government

    Directory of Open Access Journals (Sweden)

    Hasan Omar Al-Sakran

    2013-01-01

    Full Text Available Rapid spread of smart mobile technology that supports internet access is transforming the way governments provide services to their citizens. Mobile devices have different capabilities based on the manufacturers and models. This paper proposes a new framework for adapting the content of M-government services using mobile agent technology. The framework is based on a mediation architecture that uses multiple mobile agents and XML as semi-structure mediation language. The flexibility of the mediation and XML provide an adaptive environment to stream data based on the capabilities of the device sending the query to the system.

  7. The Personal Digital Library (PDL)-based e-learning: Using the PDL as an e-learning support tool

    Science.gov (United States)

    Deng, Xiaozhao; Ruan, Jianhai

    The paper describes a support tool for learners engaged in e-learning, the Personal Digital Library (PDL). The characteristics and functionality of the PDL are presented. Suggested steps for constructing and managing a PDL are outlined and discussed briefly. The authors believe that the PDL as a support tool of e-learning will be important and essential in the future.

  8. Supporting Case-Based Learning in Information Security with Web-Based Technology

    Science.gov (United States)

    He, Wu; Yuan, Xiaohong; Yang, Li

    2013-01-01

    Case-based learning has been widely used in many disciplines. As an effective pedagogical method, case-based learning is also being used to support teaching and learning in the domain of information security. In this paper, we demonstrate case-based learning in information security by sharing our experiences in using a case study to teach security…

  9. Action Learning--A Process Which Supports Organisational Change Initiatives

    Science.gov (United States)

    Joyce, Pauline

    2012-01-01

    This paper reflects on how action learning sets (ALSs) were used to support organisational change initiatives. It sets the scene with contextualising the inclusion of change projects in a masters programme. Action learning is understood to be a dynamic process where a team meets regularly to help individual members address issues through a highly…

  10. Leveraging open-source technology and adapting open eLearning content to improve the knowledge and motivation of Ghana’s rural nurses

    Directory of Open Access Journals (Sweden)

    Lisa Mwaikambo

    2016-03-01

    Full Text Available Access to training opportunities is strongly correlated with health workers’ motivation because it enables health workers to take on more challenging duties. Mobile technology can be leveraged for professional development support by providing access to open education resources. Community Health Nurses (CHNs in Ghana are the frontline health workers of the Ghana Health Service (GHS and play a vital role in extending maternal and child health care to rural communities. However, as the lowest credentialed nurses, they are at the bottom of the GHS hierarchy. CHNs have limited opportunities for career advancement and report challenges with isolation and lack of resources. Leveraging open-source technology platforms and open eLearning content, the Care Community Hub (CCH project sought to address these barriers in CHN motivation by developing and deploying a mobile application (app, CHN on the Go, to CHNs in five rural districts. The app supports CHNs through tools for continuous learning, diagnostic decision-making, and improved nurse-supervisor interactions. This paper focuses on the adaptation and use of the open eLearning content to address CHNs’ motivation challenges and, ultimately, improve their knowledge and job performance as a result of having access to open education resources.

  11. Learning to adapt: Organisational adaptation to climate change impacts

    NARCIS (Netherlands)

    Berkhout, F.G.H.; Hertin, J.; Gann, D.M.

    2006-01-01

    Analysis of human adaptation to climate change should be based on realistic models of adaptive behaviour at the level of organisations and individuals. The paper sets out a framework for analysing adaptation to the direct and indirect impacts of climate change in business organisations with new

  12. Clinical quality needs complex adaptive systems and machine learning.

    Science.gov (United States)

    Marsland, Stephen; Buchan, Iain

    2004-01-01

    The vast increase in clinical data has the potential to bring about large improvements in clinical quality and other aspects of healthcare delivery. However, such benefits do not come without cost. The analysis of such large datasets, particularly where the data may have to be merged from several sources and may be noisy and incomplete, is a challenging task. Furthermore, the introduction of clinical changes is a cyclical task, meaning that the processes under examination operate in an environment that is not static. We suggest that traditional methods of analysis are unsuitable for the task, and identify complexity theory and machine learning as areas that have the potential to facilitate the examination of clinical quality. By its nature the field of complex adaptive systems deals with environments that change because of the interactions that have occurred in the past. We draw parallels between health informatics and bioinformatics, which has already started to successfully use machine learning methods.

  13. Adaptive structured dictionary learning for image fusion based on group-sparse-representation

    Science.gov (United States)

    Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

    2018-04-01

    Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

  14. Teaching Case: Adapting the Access Northwind Database to Support a Database Course

    Science.gov (United States)

    Dyer, John N.; Rogers, Camille

    2015-01-01

    A common problem encountered when teaching database courses is that few large illustrative databases exist to support teaching and learning. Most database textbooks have small "toy" databases that are chapter objective specific, and thus do not support application over the complete domain of design, implementation and management concepts…

  15. Collaborative Working e-Learning Environments Supported by Rule-Based e-Tutor

    Directory of Open Access Journals (Sweden)

    Salaheddin Odeh

    2007-10-01

    Full Text Available Collaborative working environments for distance education sets a goal of convenience and an adaptation into our technologically advanced societies. To achieve this revolutionary new way of learning, environments must allow the different participants to communicate and coordinate with each other in a productive manner. Productivity and efficiency is obtained through synchronized communication between the different coordinating partners, which means that multiple users can execute an experiment simultaneously. Within this process, coordination can be accomplished by voice communication and chat tools. In recent times, multi-user environments have been successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat text tools, and multi-player games. Thus, understanding the ideas and the techniques behind these systems can be of great significance regarding the contribution of newer ideas to collaborative working e-learning environments. However, many problems still exist in distance learning and tele-education, such as not finding the proper assistance while performing the remote experiment. Therefore, the students become overwhelmed and the experiment will fail. In this paper, we are going to discuss a solution that enables students to obtain an automated help by either a human tutor or a rule-based e-tutor (embedded rule-based system for the purpose of student support in complex remote experimentative environments. The technical implementation of the system can be realized by using the powerful Microsoft .NET, which offers a complete integrated developmental environment (IDE with a wide collection of products and technologies. Once the system is developed, groups of students are independently able to coordinate and to execute the experiment at any time and from any place, organizing the work between them positively.

  16. Navigation Support and Social Visualization for Personalized E-Learning

    Science.gov (United States)

    Hsiao, I-Han

    2012-01-01

    A large number of educational resources is now made available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produced at least two problems: how to help students to find the most appropriate resources and how to engage them into using these resources and benefit from them.…

  17. The added value of a gaming context and intelligent adaptation for a mobile application for vocabulary learning

    NARCIS (Netherlands)

    Sandberg, J.; Maris, M.; Hoogendoorn, P.

    2014-01-01

    Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The

  18. Internal and External Regulation to Support Knowledge Construction and Convergence in Computer Supported Collaborative Learning (CSCL)

    Science.gov (United States)

    Romero, Margarida; Lambropoulos, Niki

    2011-01-01

    Computer Supported Collaborative Learning (CSCL) activities aim to promote collaborative knowledge construction and convergence. During the CSCL activity, the students should regulate their learning activity, at the individual and collective level. This implies an organisation cost related to the coordination of the activity with the team-mates…

  19. Predicting Career Adaptability through Self-Esteem and Social Support: A Research on Young Adults

    Science.gov (United States)

    Ataç, Lale Oral; Dirik, Deniz; Tetik, Hilmiye Türesin

    2018-01-01

    The purpose of this study is to investigate the relationship between career adaptability and self-esteem, and analyze the moderating role of social support in this relationship on a sample of 313 young adults. The results of the study confirm that career adaptability is significantly predicted by self-esteem. Moreover, findings suggest that (1)…

  20. Robot Competence Development by Constructive Learning

    Science.gov (United States)

    Meng, Q.; Lee, M. H.; Hinde, C. J.

    This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system’s adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use.

  1. Promoting parenting to support reintegrating military families: after deployment, adaptive parenting tools.

    Science.gov (United States)

    Gewirtz, Abigail H; Pinna, Keri L M; Hanson, Sheila K; Brockberg, Dustin

    2014-02-01

    The high operational tempo of the current conflicts and the unprecedented reliance on National Guard and Reserve forces highlights the need for services to promote reintegration efforts for those transitioning back to civilian family life. Despite evidence that parenting has significant influence on children's functioning, and that parenting may be impaired during stressful family transitions, there is a dearth of empirically supported psychological interventions tailored for military families reintegrating after deployment. This article reports on the modification of an empirically supported parenting intervention for families in which a parent has deployed to war. A theoretical rationale for addressing parenting during reintegration after deployment is discussed. We describe the intervention, After Deployment, Adaptive Parenting Tools (ADAPT), and report early feasibility and acceptability data from a randomized controlled effectiveness trial of ADAPT, a 14-week group-based, Web-enhanced parenting training program. Among the first 42 families assigned to the intervention group, participation rates were high, and equal among mothers and fathers. Satisfaction was high across all 14 sessions. Implications for psychological services to military families dealing with the deployment process are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Kathy Buckner

    1999-12-01

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

  3. Special Education in General Education Classrooms: Cooperative Teaching Using Supportive Learning Activities.

    Science.gov (United States)

    Johnson, Robin R.; And Others

    1995-01-01

    Supportive learning activities were implemented in a multiple-baseline time series design across four fifth-grade classrooms to evaluate the effects of a cooperative teaching alternative (supportive learning) on teaching behavior, the behavior and grades of general and special education students, and the opinions of general education teachers.…

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

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2017-01-01

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

  5. Deep learning aided decision support for pulmonary nodules diagnosing: a review.

    Science.gov (United States)

    Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

    2018-04-01

    Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

  6. Towards an intelligent environment for distance learning

    Directory of Open Access Journals (Sweden)

    Rafael Morales

    2009-12-01

    Full Text Available Mainstream distance learning nowadays is heavily influenced by traditional educational approaches that produceshomogenised learning scenarios for all learners through learning management systems. Any differentiation betweenlearners and personalisation of their learning scenarios is left to the teacher, who gets minimum support from the system inthis respect. This way, the truly digital native, the computer, is left out of the move, unable to better support the teachinglearning processes because it is not provided with the means to transform into knowledge all the information that it storesand manages. I believe learning management systems should care for supporting adaptation and personalisation of bothindividual learning and the formation of communities of learning. Open learner modelling and intelligent collaborativelearning environments are proposed as a means to care. The proposal is complemented with a general architecture for anintelligent environment for distance learning and an educational model based on the principles of self-management,creativity, significance and participation.

  7. A care improvement program acting as a powerful learning environment to support nursing students learning facilitation competencies.

    Science.gov (United States)

    Jukema, Jan S; Harps-Timmerman, Annelies; Stoopendaal, Annemiek; Smits, Carolien H M

    2015-11-01

    Change management is an important area of training in undergraduate nursing education. Successful change management in healthcare aimed at improving practices requires facilitation skills that support teams in attaining the desired change. Developing facilitation skills in nursing students requires formal educational support. A Dutch Regional Care Improvement Program based on a nationwide format of change management in healthcare was designed to act as a Powerful Learning Environment for nursing students developing competencies in facilitating change. This article has two aims: to provide comprehensive insight into the program components and to describe students' learning experiences in developing their facilitation skills. This Dutch Regional Care Improvement Program considers three aspects of a Powerful Learning Environment: self-regulated learning; problem-based learning; and complex, realistic and challenging learning tasks. These three aspects were operationalised in five distinct areas of facilitation: increasing awareness of the need for change; leadership and project management; relationship building and communication; importance of the local context; and ongoing monitoring and evaluation. Over a period of 18 months, 42 nursing students, supported by trained lecturer-coaches, took part in nine improvement teams in our Regional Care Improvement Program, executing activities in all five areas of facilitation. Based on the students' experiences, we propose refinements to various components of this program, aimed at strengthenin the learning environment. There is a need for further detailed empirical research to study the impact this kind of learning environment has on students developing facilitation competencies in healthcare improvement. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. The Link between Age, Career Goals, and Adaptive Development for Work-Related Learning among Local Government Employees

    Science.gov (United States)

    Tones, Megan; Pillay, Hitendra; Kelly, Kathy

    2011-01-01

    More recently, lifespan development psychology models of adaptive development have been applied to the workforce to investigate ageing worker and lifespan issues. The current study uses the Learning and Development Survey (LDS) to investigate employee selection and engagement of learning and development goals and opportunities and constraints for…

  9. Supporting learning experiences beyond the school context

    NARCIS (Netherlands)

    Rusman, Ellen

    2015-01-01

    In this workshop you’ll become familiar with two examples of how technology can support learning experiences that go beyond, but still connect to, the school context. The first example, called Elena, is for primary schools. The second example, called weSPOT, is for secondary schools. The Elena

  10. Doctoral learning: a case for a cohort model of supervision and support

    Directory of Open Access Journals (Sweden)

    Naydene de Lange

    2011-01-01

    Full Text Available We document the efforts of the faculty of education of a large research-oriented university in supporting doctoral learning. The development of a space for doctoral learning is in line with the need to develop a community of researchers in South Africa. We describe the historical origins of this cohort model of doctoral supervision and support, draw on literature around doctoral learning, and analyse a cohort of doctoral students' evaluation of the seminarsoverthree years. The findings indicate that the model has great value in developing scholarship and reflective practice in candidates, in providing support and supervision, and in sustaining students towards the completion of their doctorates.

  11. Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

    Science.gov (United States)

    Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

    2018-01-01

    Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  12. 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.)

  13. Experimenting on how to create a sustainable gamified learning design that supports adult students when learning through designing learning games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2014-01-01

    digital learning games (small games) in cross‐disciplinary subject matters. The experiment has focused on creating a game‐based learning design that enables the students to implement the learning goals into their games, and on making the game design process motivating and engaging. Another focus......This paper presents and discusses the first iteration of a design‐based research experiment focusing on how to create an overall gamified learning design (big Game) facilitating the learning process for adult students by letting them be their own learning designers through designing their own...... of the study has been to create a sustainable learning design that supports the learning game design process and gives teachers the ability to evaluate whether the students have been successful in learning their subject matter through this learning game design process. The findings are that this initial...

  14. A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2017-11-01

    Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

  15. An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition

    Directory of Open Access Journals (Sweden)

    Ming Liu

    2017-09-01

    Full Text Available Algorithms for locomotion mode recognition (LMR based on surface electromyography and mechanical sensors have recently been developed and could be used for the neural control of powered prosthetic legs. However, the variations in input signals, caused by physical changes at the sensor interface and human physiological changes, may threaten the reliability of these algorithms. This study aimed to investigate the effectiveness of applying adaptive pattern classifiers for LMR. Three adaptive classifiers, i.e., entropy-based adaptation (EBA, LearnIng From Testing data (LIFT, and Transductive Support Vector Machine (TSVM, were compared and offline evaluated using data collected from two able-bodied subjects and one transfemoral amputee. The offline analysis indicated that the adaptive classifier could effectively maintain or restore the performance of the LMR algorithm when gradual signal variations occurred. EBA and LIFT were recommended because of their better performance and higher computational efficiency. Finally, the EBA was implemented for real-time human-in-the-loop prosthesis control. The online evaluation showed that the applied EBA effectively adapted to changes in input signals across sessions and yielded more reliable prosthesis control over time, compared with the LMR without adaptation. The developed novel adaptive strategy may further enhance the reliability of neurally-controlled prosthetic legs.

  16. A Knowledge Comparison Environment for Supporting Meaningful Learning of E-Book Users

    Directory of Open Access Journals (Sweden)

    Jingyun Wang

    2016-05-01

    Full Text Available In this paper, we present an ontology-based visualization support system which can provide a meaningful learning environment to help e-book learners to effectively construct their knowledge frameworks. In this personalized visualization support system, learners are encouraged to actively locate new knowledge in their own knowledge framework and check the logical consistency of their ideas for clearing up misunderstandings; on the other hand, instructors will be able to decide the group distribution for collaborative learning activities based on the knowledge structure of learners. For facilitating those visualization supports, a method to semi-automatically construct a course-centered ontology to describe the required information in a map structure is presented. To automatically manipulate this course-centered ontology to provide visualization learning supports, a prototype system is designed and developed.

  17. An Ecological Approach to Understanding Assessment for Learning in Support of Student Writing Achievement

    Directory of Open Access Journals (Sweden)

    Bronwen Cowie

    2018-02-01

    Full Text Available In this paper, we report on a project conducted in a New Zealand primary school that aimed to enhance the writing achievement of primary school boys who were achieving just below the national standard for their age or level through the use of peer feedback and information and communication technologies (ICTs. The project involved a teacher collaborative inquiry approach where all seven teachers in the school and the school principal participated to achieve the project aim. We adopt an ecological approach as a lens to offer a holistic and comprehensive view of how peer assessment and use of ICTs can be facilitated to improve writing achievement. Data were collected through teacher interviews and written reflections of practice and student learning, teacher analysis of student work, team meeting notes, classroom observations, and student focus group interviews. Findings from the thematic analysis of textual data illustrate the potential of adopting an ecological approach to consider how teacher classroom practices are shaped by the school, community, and wider policy context. At the classroom level, our ecological analysis highlighted a productive synergy between commonplace writing pedagogy strategies and assessment for learning (AfL practices as part of teacher orchestration of an ensemble of interdependent routines, tools, and activities. Diversity, redundancy, and local adaptations of resources to provide multiple pathways and opportunities—social and material and digital—emerged as important in fostering peer assessment and ICT use in support of writing achievement. Importantly, these practices were made explicit and taken up across the school and in the parent community because of whole staff involvement in the project. The wider policy context allowed for and supported teachers developing more effective pedagogy to impact student learning outcomes. We propose that an ecological orientation offers the field a productive insight into the

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

    Science.gov (United States)

    So, Hyo-Jeong; Bonk, Curtis J.

    2010-01-01

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

  19. Hand gestures support word learning in patients with hippocampal amnesia.

    Science.gov (United States)

    Hilverman, Caitlin; Cook, Susan Wagner; Duff, Melissa C

    2018-06-01

    Co-speech hand gesture facilitates learning and memory, yet the cognitive and neural mechanisms supporting this remain unclear. One possibility is that motor information in gesture may engage procedural memory representations. Alternatively, iconic information from gesture may contribute to declarative memory representations mediated by the hippocampus. To investigate these alternatives, we examined gesture's effects on word learning in patients with hippocampal damage and declarative memory impairment, with intact procedural memory, and in healthy and in brain-damaged comparison groups. Participants learned novel label-object pairings while producing gesture, observing gesture, or observing without gesture. After a delay, recall and object identification were assessed. Unsurprisingly, amnesic patients were unable to recall the labels at test. However, they correctly identified objects at above chance levels, but only if they produced a gesture at encoding. Comparison groups performed well above chance at both recall and object identification regardless of gesture. These findings suggest that gesture production may support word learning by engaging nondeclarative (procedural) memory. © 2018 Wiley Periodicals, Inc.

  20. CLOUD EDUCATIONAL RESOURCES FOR PHYSICS LEARNING RESEARCHES SUPPORT

    Directory of Open Access Journals (Sweden)

    Oleksandr V. Merzlykin

    2015-10-01

    Full Text Available The definition of cloud educational resource is given in paper. Its program and information components are characterized. The virtualization as the technological ground of transforming from traditional electronic educational resources to cloud ones is reviewed. Such levels of virtualization are described: data storage device virtualization (Data as Service, hardware virtualization (Hardware as Service, computer virtualization (Infrastructure as Service, software system virtualization (Platform as Service, «desktop» virtualization (Desktop as Service, software user interface virtualization (Software as Service. Possibilities of designing the cloud educational resources system for physics learning researches support taking into account standards of learning objects metadata (accessing via OAI-PMH protocol and standards of learning tools interoperability (LTI are shown. The example of integration cloud educational resources into Moodle learning management system with use of OAI-PMH and LTI is given.