Sample records for learning progression framework

  1. Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework

    Directory of Open Access Journals (Sweden)

    Robert L. Mayes


    Full Text Available Quantitative reasoning is a complex concept with many definitions and a diverse account in the literature. The purpose of this article is to establish a working definition of quantitative reasoning within the context of science, construct a quantitative reasoning framework, and summarize research on key components in that framework. Context underlies all quantitative reasoning; for this review, environmental science serves as the context.In the framework, we identify four components of quantitative reasoning: the quantification act, quantitative literacy, quantitative interpretation of a model, and quantitative modeling. Within each of these components, the framework provides elements that comprise the four components. The quantification act includes the elements of variable identification, communication, context, and variation. Quantitative literacy includes the elements of numeracy, measurement, proportional reasoning, and basic probability/statistics. Quantitative interpretation includes the elements of representations, science diagrams, statistics and probability, and logarithmic scales. Quantitative modeling includes the elements of logic, problem solving, modeling, and inference. A brief comparison of the quantitative reasoning framework with the AAC&U Quantitative Literacy VALUE rubric is presented, demonstrating a mapping of the components and illustrating differences in structure. The framework serves as a precursor for a quantitative reasoning learning progression which is currently under development.

  2. Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework. (United States)

    El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher


    Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

  3. Formal Learning Sequences and Progression in the Studio: A Framework for Digital Design Education

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    Pontus Wärnestål


    Full Text Available This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a implements a theory of formal learning sequences as a user-centered design process in the studio; and (b describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.

  4. Integration of Culturally Relevant Pedagogy Into the Science Learning Progression Framework (United States)

    Bernardo, Cyntra

    This study integrated elements of culturally relevant pedagogy into a science learning progression framework, with the goal of enhancing teachers' cultural knowledge and thereby creating better teaching practices in an urban public high school science classroom. The study was conducted using teachers, an administrator, a science coach, and students involved in science courses in public high school. Through a qualitative intrinsic case study, data were collected and analyzed using traditional methods. Data from primary participants (educators) were analyzed through identification of big ideas, open coding, and themes. Through this process, patterns and emergent ideas were reported. Outcomes of this study demonstrated that educators lack knowledge about research-based academic frameworks and multicultural education strategies, but benefit through institutionally-based professional development. Students from diverse cultures responded positively to culturally-based instruction. Their progress was further manifested in better communication and discourse with their teacher and peers, and increased academic outcomes. This study has postulated and provided an exemplar for science teachers to expand and improve multicultural knowledge, ultimately transferring these skills to their pedagogical practice.

  5. Framework for pedagogical learning analytics


    Heilala, Ville


    Learning analytics is an emergent technological practice and a multidisciplinary scientific discipline, which goal is to facilitate effective learning and knowledge of learning. In this design science research, I combine knowledge discovery process, a concept of pedagogical knowledge, ethics of learning analytics and microservice architecture. The result is a framework for pedagogical learning analytics. The framework is applied and evaluated in the context of agency analytics. The framework ...

  6. A Conceptual Framework for Ambient Learning Displays

    NARCIS (Netherlands)

    Börner, Dirk; Kalz, Marco; Specht, Marcus


    Börner, D., Kalz, M., & Specht, M. (2010, 29 November-3 December). A Conceptual Framework for Ambient Learning Displays. Poster presented at the Work-in-Progress Poster and Invited Young Researcher Symposium of the 18th International Conference on Computers in Education, Putrajaya, Malaysia:

  7. A Conceptual Framework for Ambient Learning Displays

    NARCIS (Netherlands)

    Börner, Dirk; Kalz, Marco; Specht, Marcus


    Börner, D., Kalz, M., & Specht, M. (2010). A Conceptual Framework for Ambient Learning Displays. In B. Chang, T. Hirashima, & H. Ogata (Eds.), Joint Proceedings of the Work-in-Progress Poster and Invited Young Researcher Symposium for the 18th International Conference on Computers in Education (pp.

  8. Progressive Education Standards: A Neuroscience Framework (United States)

    O'Grady, Patty


    This paper proposes a coherent and unique set of 12 standards, adopting a neuroscience framework for biologically based on school reform. This model of educational principles and practices aligns with the long-standing principles and practices of the Progressive Education Movement in the United States and the emerging principles of neuroscience.…

  9. A Learning Progression for Elementary Students' Functional Thinking (United States)

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


    In this article we advance characterizations of and supports for elementary students' progress in generalizing and representing functional relationships as part of a comprehensive approach to early algebra. Our learning progressions approach to early algebra research involves the coordination of a curricular framework and progression, an…

  10. An Organizational Learning Framework for Patient Safety. (United States)

    Edwards, Marc T

    Despite concerted effort to improve quality and safety, high reliability remains a distant goal. Although this likely reflects the challenge of organizational change, persistent controversy over basic issues suggests that weaknesses in conceptual models may contribute. The essence of operational improvement is organizational learning. This article presents a framework for identifying leverage points for improvement based on organizational learning theory and applies it to an analysis of current practice and controversy. Organizations learn from others, from defects, from measurement, and from mindfulness. These learning modes correspond with contemporary themes of collaboration, no blame for human error, accountability for performance, and managing the unexpected. The collaborative model has dominated improvement efforts. Greater attention to the underdeveloped modes of organizational learning may foster more rapid progress in patient safety by increasing organizational capabilities, strengthening a culture of safety, and fixing more of the process problems that contribute to patient harm.

  11. ENGAGE: A Game Based Learning and Problem Solving Framework (United States)


    Gamification Summit 2012  Mensa Colloquium 2012.2: Social and Video Games  Seattle Science Festival  TED Salon Vancouver : http...From - To) 6/1/2012 – 6/30/2012 4. TITLE AND SUBTITLE ENGAGE: A Game Based Learning and Problem Solving Framework 5a. CONTRACT NUMBER N/A 5b...Popović ENGAGE: A Game Based Learning and Problem Solving Framework (Task 1 Month 4) Progress, Status and Management Report Monthly Progress

  12. An e-Learning Theoretical Framework (United States)

    Aparicio, Manuela; Bacao, Fernando; Oliveira, Tiago


    E-learning systems have witnessed a usage and research increase in the past decade. This article presents the e-learning concepts ecosystem. It summarizes the various scopes on e-learning studies. Here we propose an e-learning theoretical framework. This theory framework is based upon three principal dimensions: users, technology, and services…

  13. Learning Progressions as Tools for Assessment and Learning (United States)

    Shepard, Lorrie A.


    This article addresses the teaching and learning side of the learning progressions literature, calling out for measurement specialists the knowledge most needed when collaborating with subject-matter experts in the development of learning progressions. Learning progressions are one of the strongest instantiations of principles from "Knowing…

  14. Learning frameworks as an alternative to repositories

    DEFF Research Database (Denmark)

    Dalsgaard, Christian


    This paper presents the concept of ‘learning frameworks’. The purpose of the paper is to discuss and question collections of digital learning objects in large repositories and to argue for large learning frameworks which organise a number of thematically related digital learning materials. Whereas...... a learning object repository contains all kinds of materials, a learning framework consists of an organisation of materials related to a common theme. Further, a repository consists of single, self-contained objects, whereas a learning framework is an open-ended environment which presents a number...

  15. Evaluation of Learning Materials: A Holistic Framework (United States)

    Bundsgaard, Jeppe; Hansen, Thomas Illum


    This paper presents a holistic framework for evaluating learning materials and designs for learning. A holistic evaluation comprises investigations of the potential learning potential, the actualised learning potential, and the actual learning. Each aspect is explained and exemplified through theoretical models and definitions. (Contains 3 figures…

  16. E-learning process maturity level: a conceptual framework (United States)

    Rahmah, A.; Santoso, H. B.; Hasibuan, Z. A.


    ICT advancement is a sure thing with the impact influencing many domains, including learning in both formal and informal situations. It leads to a new mindset that we should not only utilize the given ICT to support the learning process, but also improve it gradually involving a lot of factors. These phenomenon is called e-learning process evolution. Accordingly, this study attempts to explore maturity level concept to provide the improvement direction gradually and progression monitoring for the individual e-learning process. Extensive literature review, observation, and forming constructs are conducted to develop a conceptual framework for e-learning process maturity level. The conceptual framework consists of learner, e-learning process, continuous improvement, evolution of e-learning process, technology, and learning objectives. Whilst, evolution of e-learning process depicted as current versus expected conditions of e-learning process maturity level. The study concludes that from the e-learning process maturity level conceptual framework, it may guide the evolution roadmap for e-learning process, accelerate the evolution, and decrease the negative impact of ICT. The conceptual framework will be verified and tested in the future study.

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


    Yata, Chikahiko; Hamamoto, Kengo; Oguri, Takenori


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

  18. Analyzing Learning in Professional Learning Communities: A Conceptual Framework (United States)

    Van Lare, Michelle D.; Brazer, S. David


    The purpose of this article is to build a conceptual framework that informs current understanding of how professional learning communities (PLCs) function in conjunction with organizational learning. The combination of sociocultural learning theories and organizational learning theories presents a more complete picture of PLC processes that has…

  19. A Conceptual Framework for Competencies Assessment. In-Progress Reflection No. 4 on "Current and Critical Issues in the Curriculum and Learning" (United States)

    Roegiers, Xavier


    There can be no denying the influence of competencies on the development of the school and its curricula. It is increasingly the case that, to enrol in a socio-economic fabric, whether locally or globally, learners--male or female--must learn to place their knowledge and know-how at the service of action: they must be able to deal with complex…

  20. Collaborative Learning Framework in Business Management Systems

    Directory of Open Access Journals (Sweden)

    Vladimir GRIGORE


    Full Text Available This paper presents a solution based on collaboration with experts and practitioner from university and ERP companies involved in process learning by training and learning by working. The solution uses CPI test to establish proper team for framework modules: Real-Time Chat Room, Discussion Forum, E-mail Support and Learning through Training. We define novice, practitioner and expert competence level based on CORONET train methodology. ERP companies have own roles for mentoring services to knowledge workers and evaluate the performance of learning process with teachers’ cooperation in learning by teaching and learning by working module.

  1. Intercultural Historical Learning: A Conceptual Framework (United States)

    Nordgren, Kenneth; Johansson, Maria


    This paper outlines a conceptual framework in order to systematically discuss the meaning of intercultural learning in history education and how it could be advanced. We do so by bringing together theories of historical consciousness, intercultural competence and postcolonial thinking. By combining these theories into one framework, we identify…

  2. A Design Framework for Personal Learning Environments

    NARCIS (Netherlands)

    Rahimi, E.


    The purpose of our research was to develop a PLE (personal learning environment) design framework for workplace settings. By doing such, the research has answered this research question, how should a technology-based personal learning environment be designed, aiming at supporting learners to gain

  3. Astrobiology Learning Progressions: Linking Astrobiology Concepts with the 3D Learning Paradigm of NGSS (United States)

    Scalice, D.; Davis, H. B.; Leach, D.; Chambers, N.


    The Next Generation Science Standards (NGSS) introduce a Framework for teaching and learning with three interconnected "dimensions:" Disciplinary Core Ideas (DCI's), Cross-cutting Concepts (CCC's), and Science and Engineering Practices (SEP's). This "3D" Framework outlines progressions of learning from K-12 based on the DCI's, detailing which parts of a concept should be taught at each grade band. We used these discipline-based progressions to synthesize interdisciplinary progressions for core concepts in astrobiology, such as the origins of life, what makes a world habitable, biosignatures, and searching for life on other worlds. The final product is an organizing tool for lesson plans, learning media, and other educational materials in astrobiology, as well as a fundamental resource in astrobiology education that serves both educators and scientists as they plan and carry out their programs for learners.

  4. Framework of Strategic Learning: The PDCA Cycle

    Directory of Open Access Journals (Sweden)

    Michał Pietrzak


    Full Text Available Nowadays, strategic planning has to be permanent process and organizational learning should support it. Researchers in theories of organizational learning attempt to understand processes, which lead to changes in organizational knowledge, as well as the effects of learning on organizational performance. In traditional approach, the strategy is viewed as one shot event. However, in contemporary turbulent environment this could not be still valid. There is a need of elastic strategic management, which employs organizational learning process. The crucial element of such process is information acquisition, which allows refining the initial version of strategic plan. In this article authors discuss the PDCA cycle as a framework of strategic learning process, including both single-loop and double loop learning. Authors proposed the ideas for further research in area of organizational learning and strategic management.

  5. Expanding the frontiers of national qualifications frameworks through lifelong learning (United States)

    Owusu-Agyeman, Yaw


    The adoption of a national qualifications framework (NQF) by some governments in all world regions has shown some success in the area of formal learning. However, while NQFs continue to enhance formal learning in many countries, the same cannot be said for the recognition, validation and accreditation (RVA) of non-formal and informal learning. Focusing on competency-based technical and vocational education and training (TVET) within its NQF, Ghana introduced the National Technical and Vocational Education and Training Qualifications Framework (NTVETQF) as a sub-framework in 2012. In the wake of the NTVETQF's limited success, the author of this article reasons that a lifelong learning approach could enhance its effectiveness considerably. Comparing national and international policies, he argues that the NTVETQF should be able to properly address the issues of progression from informal and non-formal to formal modes of lifelong learning within the country's broad context of education. In addition, the study conceptualises the integration of lifelong learning within a broad NQF in four key domains: (1) individual; (2) institutional; (3) industry; and (4) state. The author concludes that, for the NTVETQF to achieve its goal of facilitating access to further education and training while also promoting lifelong learning for all (including workers in the informal economy), effective integration of all modes of lifelong learning is required. Although this entails some challenges, such as recognition of prior learning and validation of all modes of learning, it will help to widen access to education as well as providing individuals with a pathway for achieving their educational aspirations.

  6. Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research (United States)

    Miranda, Paula; Isaias, Pedro; Costa, Carlos J.; Pifano, Sara


    Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0's critical success factors and its empirical validation.…

  7. A Multimodal Interaction Framework for Blended Learning

    DEFF Research Database (Denmark)

    Vidakis, Nikolaos; Kalafatis, Konstantinos; Triantafyllidis, Georgios


    Humans interact with each other by utilizing the five basic senses as input modalities, whereas sounds, gestures, facial expressions etc. are utilized as output modalities. Multimodal interaction is also used between humans and their surrounding environment, although enhanced with further senses ...... framework enabling deployment of a vast variety of modalities, tailored appropriately for use in blended learning environment....

  8. A Data Protection Framework for Learning Analytics (United States)

    Cormack, Andrew


    Most studies on the use of digital student data adopt an ethical framework derived from human-subject research, based on the informed consent of the experimental subject. However, consent gives universities little guidance on using learning analytics as a routine part of educational provision: which purposes are legitimate and which analyses…

  9. Exploring the Climate Literacy Development Utilizing a Learning Progressions Approach (United States)

    Drewes, A.; Breslyn, W.; McGinnis, J. R.; Hestness, E.; Mouza, C.


    Climate change encompasses a broad and complex set of concepts that is often challenging for students and educators. Using a learning progressions framework, in this exploratory study we report our efforts to identify, describe, and organize the development of learners' understanding of climate change in an empirically supported learning progression (LP). The learning progression framework is a well suited analytical tool for investigating how student thinking develops over time (Duschl et al., 2007). Our primary research question is "How do learners progress over time from an initial to a more sophisticated understanding of climate change?"We followed a development process that involved drafting a hypothetical learning progression based on the science education research literature, consensus documents such as the Next Generation Science Standards and the Atlas of Science Literacy. Additionally, we conducted expert reviews with both climate scientists and educational researchers on the content and pedagogical expectations. Data are then collected from learners, which are used to modify the hypothetical learning progression based on how well it describes actual student learning. In this current analysis, we present findings from written assessments (N=294) and in-depth interviews (n=27) with middle school students in which we examine their understanding of the role of human activity, the greenhouse effect as the mechanism of climate change, local and global impacts, and strategies for the adaptation and mitigation of climate change. The culmination of our research is a proposed, empirically supported LP for climate change. Our LP is framed by consideration of four primary constructs: Human Activity, Mechanism, Impacts, and Mitigation and Adaptation. The conditional LP provides a solid foundation for continued research as well as providing urgently needed guidance to the education community on climate change education (for curriculum, instruction, and assessment

  10. Learning to learn in the European Reference Framework for lifelong learning

    NARCIS (Netherlands)

    Pirrie, Anne; Thoutenhoofd, Ernst D.


    This article explores the construction of learning to learn that is implicit in the document Key Competences for Lifelong LearningEuropean Reference Framework and related education policy from the European Commission. The authors argue that the hallmark of learning to learn is the development of a

  11. A Learning Activity Design Framework for Supporting Mobile Learning

    Directory of Open Access Journals (Sweden)

    Jalal Nouri


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

  12. Elementary Students' Generalization and Representation of Functional Relationships: A Learning Progressions Approach (United States)

    Stephens, Ana; Fonger, Nicole L.; Blanton, Maria; Knuth, Eric


    In this paper, we describe our learning progressions approach to early algebra research that involves the coordination of a curricular framework, an instructional sequence, written assessments, and levels of sophistication describing the development of students' thinking. We focus in particular on what we have learning through this approach about…

  13. Collaborative learning framework for online stakeholder engagement. (United States)

    Khodyakov, Dmitry; Savitsky, Terrance D; Dalal, Siddhartha


    Public and stakeholder engagement can improve the quality of both research and policy decision making. However, such engagement poses significant methodological challenges in terms of collecting and analysing input from large, diverse groups. To explain how online approaches can facilitate iterative stakeholder engagement, to describe how input from large and diverse stakeholder groups can be analysed and to propose a collaborative learning framework (CLF) to interpret stakeholder engagement results. We use 'A National Conversation on Reducing the Burden of Suicide in the United States' as a case study of online stakeholder engagement and employ a Bayesian data modelling approach to develop a CLF. Our data modelling results identified six distinct stakeholder clusters that varied in the degree of individual articulation and group agreement and exhibited one of the three learning styles: learning towards consensus, learning by contrast and groupthink. Learning by contrast was the most common, or dominant, learning style in this study. Study results were used to develop a CLF, which helps explore multitude of stakeholder perspectives; identifies clusters of participants with similar shifts in beliefs; offers an empirically derived indicator of engagement quality; and helps determine the dominant learning style. The ability to detect learning by contrast helps illustrate differences in stakeholder perspectives, which may help policymakers, including Patient-Centered Outcomes Research Institute, make better decisions by soliciting and incorporating input from patients, caregivers, health-care providers and researchers. Study results have important implications for soliciting and incorporating input from stakeholders with different interests and perspectives. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

  14. A Teaching - Learning Framework for MEMS Education

    International Nuclear Information System (INIS)

    Sheeparamatti, B G; Angadi, S A; Sheeparamatti, R B; Kadadevaramath, J S


    Micro-Electro-Mechanical Systems (MEMS) technology has been identified as one of the most promising technologies in the 21st century. MEMS technology has opened up a wide array of unforeseen applications. Hence it is necessary to train the technocrats of tomorrow in this emerging field to meet the industrial/societal demands. The drive behind fostering of MEMS technology is the reduction in the cost, size, weight, and power consumption of the sensors, actuators, and associated electronics. MEMS is a multidisciplinary engineering and basic science area which includes electrical engineering, mechanical engineering, material science and biomedical engineering. Hence MEMS education needs a special approach to prepare the technocrats for a career in MEMS. The modern education methodology using computer based training systems (CBTS) with embedded modeling and simulation tools will help in this direction. The availability of computer based learning resources such as MATLAB, ANSYS/Multiphysics and rapid prototyping tools have contributed to proposition of an efficient teaching-learning framework for MEMS education presented in this paper. This paper proposes a conceptual framework for teaching/learning MEMS in the current technical education scenario

  15. SQL Collaborative Learning Framework Based on SOA (United States)

    Armiati, S.; Awangga, RM


    The research is focused on designing collaborative learning-oriented framework fulfilment service in teaching SQL Oracle 10g. Framework built a foundation of academic fulfilment service performed by a layer of the working unit in collaboration with Program Studi Manajemen Informatika. In the design phase defined what form of collaboration models and information technology proposed for Program Studi Manajemen Informatika by using a framework of collaboration inspired by the stages of modelling a Service Oriented Architecture (SOA). Stages begin with analyzing subsystems, this activity is used to determine subsystem involved and reliance as well as workflow between the subsystems. After the service can be identified, the second phase is designing the component specifications, which details the components that are implemented in the service to include the data, rules, services, profiles can be configured, and variations. The third stage is to allocate service, set the service to the subsystems that have been identified, and its components. Implementation framework contributes to the teaching guides and application architecture that can be used as a landing realize an increase in service by applying information technology.

  16. A Framework for Mobile Learning for Enhancing Learning in Higher Education (United States)

    Barreh, Kadar Abdillahi; Abas, Zoraini Wati


    As mobile learning becomes increasingly pervasive, many higher education institutions have initiated a number of mobile learning initiatives to support their traditional learning modes. This study proposes a framework for mobile learning for enhancing learning in higher education. This framework for mobile learning is based on research conducted…

  17. Framework for robot skill learning using reinforcement learning (United States)

    Wei, Yingzi; Zhao, Mingyang


    Robot acquiring skill is a process similar to human skill learning. Reinforcement learning (RL) is an on-line actor critic method for a robot to develop its skill. The reinforcement function has become the critical component for its effect of evaluating the action and guiding the learning process. We present an augmented reward function that provides a new way for RL controller to incorporate prior knowledge and experience into the RL controller. Also, the difference form of augmented reward function is considered carefully. The additional reward beyond conventional reward will provide more heuristic information for RL. In this paper, we present a strategy for the task of complex skill learning. Automatic robot shaping policy is to dissolve the complex skill into a hierarchical learning process. The new form of value function is introduced to attain smooth motion switching swiftly. We present a formal, but practical, framework for robot skill learning and also illustrate with an example the utility of method for learning skilled robot control on line.

  18. Learning to cooperate is essential for progress in physics (United States)

    Dickau, Jonathan J.


    At the 10th Frontiers of Fundamental Physics symposium, Gerard't Hooft stated that, for some of the advances we hope to see in Physics during the future, there must be a great deal of cooperation between physicists from different disciplines, as well as mathematicians, programmers, technologists, and others. This requires us to evolve a new mindset; however, as so much of our past progress has come out of a fiercely competitive process - especially since a critical review of our ideas about reality remains essential to making clear progress and checking our progress. We must also address the fact that some frameworks appear incompatible, as with relativity and quantum mechanics, whose unification remains distant despite years of attempts to find a quantum gravity theory. I explore the idea that playful exploration, using both left-brained and right-brained approaches to learning, allows us to resolve conflicting ideas by taking advantage of innate human developmental and learning strategies and brain structure. It may thus foster the kind of interdisciplinary cooperation we are hoping to see.

  19. A process for developing and revising a learning progression on sea level rise using learners' explanations (United States)

    McDonald, Robert Christopher

    The purpose of this study was to explore the process of developing a learning progression (LP) on constructing explanations about sea level rise. I used a learning progressions theoretical framework informed by the situated cognition learning theory. During this exploration, I explicitly described my decision-making process as I developed and revised a hypothetical learning progression. Correspondingly, my research question was: What is a process by which a hypothetical learning progression on sea level rise is developed into an empirical learning progression using learners' explanations? To answer this question, I used a qualitative descriptive single case study with multiple embedded cases (Yin, 2014) that employed analytic induction (Denzin, 1970) to analyze data collected on middle school learners (grades 6-8). Data sources included written artifacts, classroom observations, and semi-structured interviews. Additionally, I kept a researcher journal to track my thinking about the learning progression throughout the research study. Using analytic induction to analyze collected data, I developed eight analytic concepts: participant explanation structures varied widely, global warming and ice melt cause sea level rise, participants held alternative conceptions about sea level rise, participants learned about thermal expansion as a fundamental aspect of sea level rise, participants learned to incorporate authentic scientific data, participants' mental models of the ocean varied widely, sea ice melt contributes to sea level rise, and participants held vague and alternative conceptions about how pollution impacts the ocean. I started with a hypothetical learning progression, gathered empirical data via various sources (especially semi-structured interviews), revised the hypothetical learning progression in response to those data, and ended with an empirical learning progression comprising six levels of learner thinking. As a result of developing an empirically based LP

  20. The ICCE Framework: Framing Learning Experiences Afforded by Games (United States)

    Foster, Aroutis; Shah, Mamta


    There is a need for game-based learning frameworks that provide a lens for understanding learning experiences afforded in digital games. These frameworks should aim to facilitate game analyses, identification of learning opportunities, and support for learner experiences. This article uses the inquiry, communication, construction, and expression…

  1. Framework for Designing Context-Aware Learning Systems (United States)

    Tortorella, Richard A. W.; Kinshuk; Chen, Nian-Shing


    Today people learn in many diverse locations and contexts, beyond the confines of classical brick and mortar classrooms. This trend is ever increasing, progressing hand-in-hand with the progress of technology. Context-aware learning systems are systems which adapt to the learner's context, providing tailored learning for a particular learning…

  2. First Nations, Metis and Inuit Education Policy Framework: Progress Report, 2008 (United States)

    Alberta Education, 2008


    This progress report describes the work currently underway toward improving the success of First Nations, Metis and Inuit (FNMI) students in Alberta. It provides an update on the progress made since the release of the Framework in 2002 and the 2004 Progress Report up to December 31, 2007. Since the release of the Framework, a new Ministry of…

  3. Optimizing microstimulation using a reinforcement learning framework. (United States)

    Brockmeier, Austin J; Choi, John S; Distasio, Marcello M; Francis, Joseph T; Príncipe, José C


    The ability to provide sensory feedback is desired to enhance the functionality of neuroprosthetics. Somatosensory feedback provides closed-loop control to the motor system, which is lacking in feedforward neuroprosthetics. In the case of existing somatosensory function, a template of the natural response can be used as a template of desired response elicited by electrical microstimulation. In the case of no initial training data, microstimulation parameters that produce responses close to the template must be selected in an online manner. We propose using reinforcement learning as a framework to balance the exploration of the parameter space and the continued selection of promising parameters for further stimulation. This approach avoids an explicit model of the neural response from stimulation. We explore a preliminary architecture--treating the task as a k-armed bandit--using offline data recorded for natural touch and thalamic microstimulation, and we examine the methods efficiency in exploring the parameter space while concentrating on promising parameter forms. The best matching stimulation parameters, from k = 68 different forms, are selected by the reinforcement learning algorithm consistently after 334 realizations.

  4. Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research


    Paula Miranda; Pedro Isaias; Carlos J Costa; Sara Pifano


    Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0’s critical success factors and its empirical validation. Methodology: The framework is the result of an extensive literature review and its empirical substantiation derives from semi-structured inte...

  5. A Framework for Narration and Learning in Educational Multimedia

    DEFF Research Database (Denmark)

    Mosegaard, Jesper; Bennedsen, Jens


    In this article we describe a multimedia adventure game framework for a learning environment to support the teaching and learning of introductory programming. In the framework we have conceptualized two important aspects of such an environment: narration and learning topics. We describe...... the interplay between these aspects and how the framework utilizes this to adapt the learning process to the individual student. The motivation for the separation is to help the teacher balance the two main driving forces of an edutainment product: entertainment and learning. It is the responsibility...... of the teacher to define the range of stories and topics using the framework. The framework provides a complete learning environment where the teacher merely needs to define the content....

  6. Workplace learning and career progression: qualitative perspectives of UK dietitians. (United States)

    Boocock, R C; O'Rourke, R K


    Post-graduate education and continuous professional development (CPD) within dietetics lack clearly defined pathways. The current literature primarily focuses on new graduate perceptions of workplace learning (WPL). The present study raises issues of how CPD is sustained throughout a National Health Service (NHS) career, how informal learning might be made more visible and whether the workplace withholds learning opportunities. Qualified dietitians participated in focus groups (n = 32) and a nominal group technique (n = 24). Data from audio recordings were transcribed and triangulated. Thematic analysis took an interpretative approach. One size for WPL for dietetics and, likely, other allied health professionals (AHPs) did not meet the learning needs of everyone. The informal implicit learning affordances often went unrecognised. A greater emphasis on teaching, picking up on the strong preference for discussion with others voiced in the present study, may improve recognition of all WPL opportunities. Better scaffolding or guided support of entry level dietitians may ease the transition from study to workplace and challenge any perception of 'clipped wings'. Where development and career progression proves difficult for experienced dietitians, mentoring or stepping outside the NHS may revitalise by providing new communities of practice. WPL cannot be understood as a unitary concept. Dietitians engage with WPL differently across their careers. Future visions of WPL, especially explicit post-graduate career and education frameworks, must accommodate these differences to retain the highest calibre dietitians. The implications of a period of learning 'maintenance' rather than CPD among experienced dietitians offers a topic for further research, particularly as the workforce ages. © 2018 The British Dietetic Association Ltd.

  7. Research on machine learning framework based on random forest algorithm (United States)

    Ren, Qiong; Cheng, Hui; Han, Hai


    With the continuous development of machine learning, industry and academia have released a lot of machine learning frameworks based on distributed computing platform, and have been widely used. However, the existing framework of machine learning is limited by the limitations of machine learning algorithm itself, such as the choice of parameters and the interference of noises, the high using threshold and so on. This paper introduces the research background of machine learning framework, and combined with the commonly used random forest algorithm in machine learning classification algorithm, puts forward the research objectives and content, proposes an improved adaptive random forest algorithm (referred to as ARF), and on the basis of ARF, designs and implements the machine learning framework.

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

    DEFF Research Database (Denmark)

    Gynther, Karsten


    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...

  9. An Argument for Formative Assessment with Science Learning Progressions (United States)

    Alonzo, Alicia C.


    Learning progressions--particularly as defined and operationalized in science education--have significant potential to inform teachers' formative assessment practices. In this overview article, I lay out an argument for this potential, starting from definitions for "formative assessment practices" and "learning progressions"…

  10. BlueSky Cloud Framework: An E-Learning Framework Embracing Cloud Computing (United States)

    Dong, Bo; Zheng, Qinghua; Qiao, Mu; Shu, Jian; Yang, Jie

    Currently, E-Learning has grown into a widely accepted way of learning. With the huge growth of users, services, education contents and resources, E-Learning systems are facing challenges of optimizing resource allocations, dealing with dynamic concurrency demands, handling rapid storage growth requirements and cost controlling. In this paper, an E-Learning framework based on cloud computing is presented, namely BlueSky cloud framework. Particularly, the architecture and core components of BlueSky cloud framework are introduced. In BlueSky cloud framework, physical machines are virtualized, and allocated on demand for E-Learning systems. Moreover, BlueSky cloud framework combines with traditional middleware functions (such as load balancing and data caching) to serve for E-Learning systems as a general architecture. It delivers reliable, scalable and cost-efficient services to E-Learning systems, and E-Learning organizations can establish systems through these services in a simple way. BlueSky cloud framework solves the challenges faced by E-Learning, and improves the performance, availability and scalability of E-Learning systems.

  11. The learning progression of diagnostic sialendoscopy

    Directory of Open Access Journals (Sweden)

    José Higino Steck


    Full Text Available ABSTRACT INTRODUCTION: Sialendoscopy is becoming the gold standard procedure for diagnosis and treatment of Salivary Gland Inflammatory Diseases. OBJECTIVE: To evaluate the learning progression of a single surgeon to implement and perform diagnostic sialendoscopy: to estimate how many procedures were necessary to achieve better results; if it was higher rate of complications in the beginning. METHODS: Retrospective analysis involving 113 consecutive sialendoscopies performed from 2010 to 2013. According to a descriptive analysis of the factors related to surgeon's experience, the casuistic was divided into two groups: group (A comprising the first 50 exams, and group (B the last 63. Groups were then compared concerning demographic and peri-operative aspects. RESULTS: In Group A, failure to catheterize papilla were 22% versus 3% in B (p = 0.001. Failure to complete examination was 30% in group A versus 6% in B (p = 0.001, and necessity to repeat exams was 22% in group A versus 10% in B (p = 0.058. The complication rates were 18% in group A, and 10% in B (p = 0.149. Operative time was slightly shorter in group B (56 versus 41 min, p = 0.045. CONCLUSION: We found better outcomes after the first 50 diagnostic sialendoscopies. Complication rates were statistically the same between early and late groups of experience with sialendoscopy.

  12. A survey on the progress with implementation of the radiography profession's career progression framework in UK radiotherapy centres

    International Nuclear Information System (INIS)

    James, Sarah; Beardmore, Charlotte; Dumbleton, Claire


    Aim: The purpose of the survey was to benchmark the progress with implementing the radiography profession's career progression framework within radiotherapy centres across the United Kingdom (UK). Methods: A survey questionnaire was constructed using the Survey Monkey™ tool to assess implementation of the career progression framework of the Society and College of Radiographers. Once constructed, an on line link to the survey questionnaire was emailed to all radiotherapy centre managers in the UK (N = 67) who were invited to provide one response per centre. The survey comprised twenty nine questions which were grouped into nine sections. Key results: The workforce profile indicates that increases in assistant, advanced and consultant level practitioners are required to meet National Radiotherapy Advisory Group recommendations with only a small number of centres having fully implemented the career progression framework. The overall vacancy level across the therapeutic radiography workforce was 4.6% at the time of the survey. Conclusions: and Recommendations: The survey has highlighted some progress with implementation of the career progression framework across the UK since its launch in 2000. However the current level of implementation demonstrated is disappointing considering it is a key recommendation within the NRAG Report 2007 with respect to England. It is recommended that all centres undertake a multi-professional workforce review to embed the career progression framework within their service in order to meet the workforce challenge associated with the required anticipated large growth in radiotherapy capacity.

  13. Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

    Directory of Open Access Journals (Sweden)

    Paula Miranda


    Full Text Available Aim/Purpose: As e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background: This paper outlines a framework of e-Learning 3.0’s critical success factors and its empirical validation. Methodology: The framework is the result of an extensive literature review and its empirical substantiation derives from semi-structured interviews with e-Learning experts. Contribution: The viewpoints of the experts enable the confirmation and the refinement of the original framework and serve as a foundation for the prospective implementation of e-Learning 3.0. Findings: The analysis of the interviews demonstrates that e-Learning 3.0 remains in its early stages with a reticent dissemination. Nonetheless, the interviewees invoked factors related to technology, content and stakeholders as being critical for the success of this new phase of e-Learning. Recommendations for Practitioners: Practitioners can use the framework as a guide for promoting and implementing effective e-Learning 3.0 initiatives. Recommendation for Researchers: As a new phenomenon with uncharted potential, e-Learning 3.0 should be placed at the centre of educational research. Impact on Society: The understanding of what drives the success of e-Learning 3.0 is fundamental for its implementation and for the progress of online education in this new stage of its evolution. Future Research: Future research ventures can include the design of quantitative and self-administered data collection instruments that can provide further insight into the elements of the framework.

  14. An Analytic Framework to Support E.Learning Strategy Development (United States)

    Marshall, Stephen J.


    Purpose: The purpose of this paper is to discuss and demonstrate the relevance of a new conceptual framework for leading and managing the development of learning and teaching to e.learning strategy development. Design/methodology/approach: After reviewing and discussing the research literature on e.learning in higher education institutions from…

  15. Games and Simulations in Online Learning: Research and Development Frameworks (United States)

    Gibson, David; Aldrich, Clark; Prensky, Marc


    Games and Simulations in Online Learning: Research and Development Frameworks examines the potential of games and simulations in online learning, and how the future could look as developers learn to use the emerging capabilities of the Semantic Web. It presents a general understanding of how the Semantic Web will impact education and how games and…

  16. A Personalized e-Learning Framework (United States)

    Alhawiti, Mohammed M.; Abdelhamid, Yasser


    With the advent of web based learning and content management tools, e-learning has become a matured learning paradigm, and changed the trend of instructional design from instructor centric learning paradigm to learner centric approach, and evolved from "one instructional design for many learners" to "one design for one learner"…

  17. Progressive image denoising through hybrid graph Laplacian regularization: a unified framework. (United States)

    Liu, Xianming; Zhai, Deming; Zhao, Debin; Zhai, Guangtao; Gao, Wen


    Recovering images from corrupted observations is necessary for many real-world applications. In this paper, we propose a unified framework to perform progressive image recovery based on hybrid graph Laplacian regularized regression. We first construct a multiscale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned, which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space. In this procedure, the intrinsic manifold structure is explicitly considered using both measured and unmeasured samples, and the nonlocal self-similarity property is utilized as a fruitful resource for abstracting a priori knowledge of the images. On the other hand, between two successive scales, the proposed model is extended to a projected high-dimensional feature space through explicit kernel mapping to describe the interscale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. In this way, the proposed algorithm gradually recovers more and more image details and edges, which could not been recovered in previous scale. We test our algorithm on one typical image recovery task: impulse noise removal. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art algorithms.

  18. Evaluation Framework for Dependable Mobile Learning Scenarios (United States)

    Bensassi, Manel; Laroussi, Mona


    The goal of the dependability analysis is to predict inconsistencies and to reveal ambiguities and incompleteness in the designed learning scenario. Evaluation, in traditional learning design, is generally planned after the execution of the scenario. In mobile learning, this stage becomes too difficult and expensive to apply due to the complexity…

  19. Proposing a Framework for Mobile Applications in Disaster Health Learning. (United States)

    Liu, Alexander G; Altman, Brian A; Schor, Kenneth; Strauss-Riggs, Kandra; Thomas, Tracy N; Sager, Catherine; Leander-Griffith, Michelle; Harp, Victoria


    Mobile applications, or apps, have gained widespread use with the advent of modern smartphone technologies. Previous research has been conducted in the use of mobile devices for learning. However, there is decidedly less research into the use of mobile apps for health learning (eg, patient self-monitoring, medical student learning). This deficiency in research on using apps in a learning context is especially severe in the disaster health field. The objectives of this article were to provide an overview of the current state of disaster health apps being used for learning, to situate the use of apps in a health learning context, and to adapt a learning framework for the use of mobile apps in the disaster health field. A systematic literature review was conducted by using the PRISMA checklist, and peer-reviewed articles found through the PubMed and CINAHL databases were examined. This resulted in 107 nonduplicative articles, which underwent a 3-phase review, culminating in a final selection of 17 articles. While several learning models were identified, none were sufficient as an app learning framework for the field. Therefore, we propose a learning framework to inform the use of mobile apps in disaster health learning. (Disaster Med Public Health Preparedness. 2017;11:487-495).

  20. A Conceptual Framework for Evolving, Recommender Online Learning Systems (United States)

    Peiris, K. Dharini Amitha; Gallupe, R. Brent


    A comprehensive conceptual framework is developed and described for evolving recommender-driven online learning systems (ROLS). This framework describes how such systems can support students, course authors, course instructors, systems administrators, and policy makers in developing and using these ROLS. The design science information systems…

  1. A DBR Framework for Designing Mobile Virtual Reality Learning Environments (United States)

    Cochrane, Thomas Donald; Cook, Stuart; Aiello, Stephen; Christie, Duncan; Sinfield, David; Steagall, Marcus; Aguayo, Claudio


    This paper proposes a design based research (DBR) framework for designing mobile virtual reality learning environments. The application of the framework is illustrated by two design-based research projects that aim to develop more authentic educational experiences and learner-centred pedagogies in higher education. The projects highlight the first…

  2. Designing for Learning and Play - The Smiley Model as Framework

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke


    digital games. The Smiley Model inspired and provided a scaffold or a heuristic for the overall gamified learning design –- as well as for the students’ learning game design processes when creating small games turning the learning situation into an engaging experience. The audience for the experiments......This paper presents a framework for designing engaging learning experiences in games – the Smiley Model. In this Design-Based Research project, student-game-designers were learning inside a gamified learning design - while designing and implementing learning goals from curriculum into the small...... was adult upper secondary general students as well as 7th grade primary school students. The intention with this article is to inspire future learning designers that would like to experiment with integrating learning and play....

  3. Quantitative Reasoning in Environmental Science: A Learning Progression (United States)

    Mayes, Robert Lee; Forrester, Jennifer Harris; Christus, Jennifer Schuttlefield; Peterson, Franziska Isabel; Bonilla, Rachel; Yestness, Nissa


    The ability of middle and high school students to reason quantitatively within the context of environmental science was investigated. A quantitative reasoning (QR) learning progression was created with three progress variables: quantification act, quantitative interpretation, and quantitative modeling. An iterative research design was used as it…

  4. Lerot: An Online Learning to Rank Framework

    NARCIS (Netherlands)

    Schuth, A.; Hofmann, K.; Whiteson, S.; de Rijke, M.


    Online learning to rank methods for IR allow retrieval systems to optimize their own performance directly from interactions with users via click feedback. In the software package Lerot, presented in this paper, we have bundled all ingredients needed for experimenting with online learning to rank for

  5. Orchestration in Learning Technology Research: Evaluation of a Conceptual Framework (United States)

    Prieto, Luis P.; Dimitriadis, Yannis; Asensio-Pérez, Juan I.; Looi, Chee-Kit


    The term "orchestrating learning" is being used increasingly often, referring to the coordination activities performed while applying learning technologies to authentic settings. However, there is little consensus about how this notion should be conceptualised, and what aspects it entails. In this paper, a conceptual framework for…

  6. Is "Learning without Limits" a Framework of Values? (United States)

    Booth, Tony


    In this article the author connects his own work with Brian Simon's writing on IQ (intelligence quotient) testing and selection and with the Learning without Limits project. He discusses the significance he gives to a values framework in the development of education and asks whether "Learning without Limits," in part, stands for a…

  7. A framework for studying teacher learning by design

    NARCIS (Netherlands)

    Voogt, Joke; McKenney, Susan; Janssen, Fred; Berry, Amanda; Kicken, Wendy; Coenders, Fer


    Voogt, J., McKenney, S., Janssen, F., Berry, A., Kicken, W., & Coenders, F. (2012, 2-6 July). A framework for studying teacher learning by design. Paper presentation at the Teachers as Designers of Technology Enhanced Learning pre-conference workshop in conjunction with the ISLS annual meeting,

  8. Expanding the Frontiers of National Qualifications Frameworks through Lifelong Learning (United States)

    Owusu-Agyeman, Yaw


    The adoption of a national qualifications framework (NQF) by some governments in all world regions has shown some success in the area of formal learning. However, while NQFs continue to enhance "formal" learning in many countries, the same cannot be said for the recognition, validation and accreditation (RVA) of "non-formal"…

  9. Evaluating QR Code Case Studies Using a Mobile Learning Framework (United States)

    Rikala, Jenni


    The aim of this study was to evaluate the feasibility of Quick Response (QR) codes and mobile devices in the context of Finnish basic education. The feasibility was analyzed through a mobile learning framework, which includes the core characteristics of mobile learning. The study is part of a larger research where the aim is to develop a…

  10. A Conceptual Framework for Mentoring in a Learning Organization (United States)

    Klinge, Carolyn M.


    The purpose of this article is to provide a conceptual framework for mentoring as an added component of a learning organization in the context of adult learning and development theories. Mentoring is traditionally a process in which an experienced person (the mentor) guides another person (the mentee or protégé) in the development of her or his…

  11. Emergent frameworks of research teaching and learning in a cohort ...

    African Journals Online (AJOL)

    ... frameworks for doctoral pedagogies –“democratic teaching/learning participation”, “structured scaffolding”, “Ubuntu” and “serendipity”– as useful explanatory shaping influences which underpin and frame the model promoting a contextually relevant and appropriate doctoral research teaching and learning pedagogy.

  12. Orchestration Framework for Learning Activities in Augmented Reality Environments


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


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

  13. Social innovation education: towards a framework for learning design


    Alden Rivers, Bethany; Armellini, Alejandro; Maxwell, Rachel; Allen, Sue; Durkin, Chris


    Purpose—This paper proposes a theoretical framework to support the embedding of social innovation education in existing academic programmes.\\ud Design/methodology/approach—By adopting Conole et al.’s (2004) methodological approach to reviewing, mapping and modelling learning theory, this study addresses four research questions: 1) How can social innovation education be defined? 2) Which learning theories best support social innovation education? 3) How do such learning theories relate to exis...

  14. Learning Resources Organization Using Ontological Framework (United States)

    Gavrilova, Tatiana; Gorovoy, Vladimir; Petrashen, Elena

    The paper describes the ontological approach to the knowledge structuring for the e-learning portal design as it turns out to be efficient and relevant to current domain conditions. It is primarily based on the visual ontology-based description of the content of the learning materials and this helps to provide productive and personalized access to these materials. The experience of ontology developing for Knowledge Engineering coursetersburg State University is discussed and “OntolingeWiki” tool for creating ontology-based e-learning portals is described.

  15. A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs (United States)

    Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry


    This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

  16. Learning by Doing: the Progressive Novella Project. (United States)

    Conroy, Michael G.


    States that the Progressive Novella Project for high school students involves the collaborative writing of a 35-50 page novella. Explains that prior to the actual writing process, students are educated in the basic elements of fiction writing. Describes the division of labor into groups. Comments that the results of the project are invariably…

  17. Effective social justice advocacy: a theory-of-change framework for assessing progress. (United States)

    Klugman, Barbara


    This article offers a theory-of-change framework for social justice advocacy. It describes broad outcome categories against which activists, donors and evaluators can assess progress (or lack thereof) in an ongoing manner: changes in organisational capacity, base of support, alliances, data and analysis from a social justice perspective, problem definition and potential policy options, visibility, public norms, and population level impacts. Using these for evaluation enables activists and donors to learn from and rethink their strategies as the political context and/or actors change over time. The paper presents a case study comparing factors that facilitated reproductive rights policy wins during the transition from apartheid to democracy in South Africa and factors that undermined their implementation in the post-apartheid period. It argues that after legal and policy victories had been won, failure to maintain strong organizations and continually rethink strategies contributed to the loss of government focus on and resources for implementation of new policies. By implication, evaluating effectiveness only by an actual policy change does not allow for ongoing learning to ensure appropriate strategies. It also fails to recognise that a policy win can be overturned and needs vigilant monitoring and advocacy for implementation. This means that funding and organising advocacy should seldom be undertaken as a short-term proposition. It also suggests that the building and maintenance of organisational and leadership capacity is as important as any other of the outcome categories in enabling success. Copyright © 2011 Foundation Review. Published by Elsevier Ltd. All rights reserved.

  18. Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper (United States)

    Luo, Gang


    For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022

  19. E-Learning dengan Menggunakan COI Framework

    Directory of Open Access Journals (Sweden)

    Lydiawati Kosasih


    Full Text Available This study discusses some considerations in education to achieve a good quality of learning by utilizing technological advances such as E-Learning. This study uses a model of Community of Inquiry (COI as a comparative study to improve the quality of E-Learning program. Implementation of COI model in discussionforum on BiNusMaya through E-Learning is able to improve the quality of a discussion as improvement of knowledge management. This study aims to provide a proposal to the Department of Information Systems Bina Nusantara University in enhancing the effectiveness of the use of discussion forums on BiNusMaya (ELearning. By presenting the survey results related to the Binusmaya current condition,s such constraints and development expectations of both the lecturers and students for Binusmaya can be described. In addition, theapplication of CoI model is presented in a learning process especially when meeting outside of class (without face-to-face. The results of this study is expected to be the basis for developing a COI model design and implementation plan in Management Information Systems course, that may improve the quality of the use of discussion forums as part of the knowledge management process in future study.

  20. Innovation, Learning and Institutional Frameworks in Natural ...

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

    This project is concerned with how Latin American countries can take ... to innovation, industrial growth, technological progress, environmental ... Policymakers, corporate managers and decision-makers will be formally involved throughout project ... In partnership with UNESCO's Organization for Women in Science for the ...

  1. Binational Learning Communities: A Work in Progress (United States)

    Gross, Joan


    The author, having directed, taught and evaluated five study-abroad programmes in three different countries, created her own programme based on the pros and cons she had observed. In December 2013, she completed a pilot run of a binational learning community focused on food, culture and social justice in Ecuador and Oregon, and here she shares…

  2. Early Learning Foundations. Indiana's Early Learning Development Framework Aligned to the Indiana Academic Standards, 2014 (United States)

    Indiana Department of Education, 2015


    The "Foundations" (English/language arts, mathematics, social emotional skills, approaches to play and learning, science, social studies, creative arts, and physical health and growth) are Indiana's early learning development framework and are aligned to the 2014 Indiana Academic Standards. This framework provides core elements that…

  3. Unraveling networked learning initiatives: an analytic framework

    NARCIS (Netherlands)

    Rusman, Ellen; Prinsen, Fleur; Vermeulen, Marjan


    Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences

  4. Learning Physical Domains: Toward a Theoretical Framework. (United States)


    advanced ids o the iaime doinain in containing more information, especially perceptual " ’It. iho lI b1 rwt... tI hat. psychboigists by no means...Acquisitions Dr Kenneth D Forbus 4833 Rugby Avenue University of Illinois Dr Robert Glaser Bethesda, MD 20014 Department of Computer Science Learning

  5. A Framework for Narration and Learning in Educational Multimedia

    DEFF Research Database (Denmark)

    Mosegaard, Jesper; Bennedsen, Jens


    In this article we describe a multimedia adventure game framework for a learningenvironment to support the teaching and learning of introductory programming. In theframework we have conceptualized two important aspects of such an environment: narrationand learning topics. We describe the interplay...... between these aspects and how the frameworkutilizes this to adapt the learning process to the individual student. The motivation for theseparation is to help the teacher balance the two main driving forces of an edutainmentproduct: entertainment and learning. It is the responsibility of the teacher...

  6. Developing a Learning Progression for Curriculum, Instruction, and Student Learning: An Example from Mathematics Education (United States)

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


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

  7. A framework for designing and improving learning environments fostering creativity

    Directory of Open Access Journals (Sweden)

    Norio Ishii

    Full Text Available This paper proposes a framework for designing and improving learning environment for creativity in engineering. The framework consists of the following three components: instructional design based on knowledge from psychology, development of systems for supporting creative activities, and objective evaluation of learning results related to creativity. Based on that framework, we design and practice course based in the programation of a robot at a Japan University in the 2004 academic year. As a result, we confirm the following two advantages of our framework: learners' idea generation skills were improved and their meta-cognitive activities were also activated. In the 2005 academic year, we improve the course based on 2004 results. As a result, we confirm that the number of uploads of activity data from students have increased in the 2005 course, students' reflection sheets have become more detailed, and their volume of information have also increased.

  8. Theoretical frameworks for the learning of geometrical reasoning


    Jones, Keith


    With the growth in interest in geometrical ideas it is important to be clear about the nature of geometrical reasoning and how it develops. This paper provides an overview of three theoretical frameworks for the learning of geometrical reasoning: the van Hiele model of thinking in geometry, Fischbein’s theory of figural concepts, and Duval’s cognitive model of geometrical reasoning. Each of these frameworks provides theoretical resources to support research into the development of geometrical...

  9. Modeling Geomagnetic Variations using a Machine Learning Framework (United States)

    Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.


    We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

  10. A Framework for Mobile Learning for the enhancement of Learning in Higher Education

    Directory of Open Access Journals (Sweden)

    Kadar Abdillahi Barreh


    Full Text Available As mobile learning becomes increasingly pervasive, many higher education institutions have embarked on a number of mobile learning initiatives to support their traditional learning modes. This study proposes a framework for mobile learning for the enhancement of learning in higher education. This framework for mobile learning is based on the research conducted on the second year course entitled “Internet Technology,” taught to second year students in the Department of Mathematics and Computer Science at the University of Djibouti. While the entire gamut of mobile technologies and academic applications needs to be considered, special emphasis and focus is provided to Short Message Services (SMS and popular social network sites such as Facebook, which is widely used for recreation. This paper highlights how mobile learning using SMS and Facebook can be designed to enhance student learning in order to help achieve learning outcomes.

  11. A Framework for Measuring the Progress in Exoskeleton Skills in People with Complete Spinal Cord Injury. (United States)

    van Dijsseldonk, Rosanne B; Rijken, Hennie; van Nes, Ilse J W; van de Meent, Henk; Keijsers, Noel L W


    For safe application of exoskeletons in people with spinal cord injury at home or in the community, it is required to have completed an exoskeleton training in which users learn to perform basic and advanced skills. So far, a framework to test exoskeleton skills is lacking. The aim of this study was to develop and test the hierarchy and reliability of a framework for measuring the progress in the ability to perform basic and advanced skills. Twelve participants with paraplegia were given twenty-four training sessions in 8 weeks with the Rewalk-exoskeleton. During the 2nd, 4th, and 6th training week the Intermediate-skills-test was performed consisting of 27 skills, measured in an hierarchical order of difficulty, until two skills were not achieved. When participants could walk independently, the Final-skills-test, consisting of 20 skills, was performed in the last training session. Each skill was performed at least two times with a maximum of three attempts. As a reliability measure the consistency was used, which was the number of skills performed the same in the first two attempts relative to the total number. Ten participants completed the training program. Their number of achieved intermediate skills was significantly different between the measurements X F 2 (2) = 12.36, p = 0.001. Post-hoc analysis revealed a significant increase in the median achieved intermediate skills from 4 [1-7] at the first to 10.5 [5-26] at the third Intermediate-skills-test. The rate of participants who achieved the intermediate skills decreased and the coefficient of reproducibility was 0.98. Eight participants met the criteria to perform the Final-skills-test. Their median number of successfully performed final skills was 16.5 [13-20] and 17 [14-19] skills in the first and second time. The overall consistency of >70% was achieved in the Intermediate-skills-test (73%) and the Final-skills-test (81%). Eight out of twelve participants experienced skin damage during the training, in

  12. Translating Learning into Numbers: A Generic Framework for Learning Analytics (United States)

    Greller, Wolfgang; Drachsler, Hendrik


    With the increase in available educational data, it is expected that Learning Analytics will become a powerful means to inform and support learners, teachers and their institutions in better understanding and predicting personal learning needs and performance. However, the processes and requirements behind the beneficial application of Learning…

  13. 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


    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.

  14. An analytical quality framework for learning cities and regions (United States)

    Preisinger-Kleine, Randolph


    There is broad agreement that innovation, knowledge and learning have become the main source of wealth, employment and economic development of cities, regions and nations. Over the past two decades, the number of European cities and regions which label themselves as "learning city" or "learning region" has constantly grown. However, there are also pitfalls and constraints which not only hinder them in unlocking their full potential, but also significantly narrow their effects and their wider impact on society. Most prominently, learning cities and regions manifest serious difficulties in rendering transparent the surplus value they generate, which is vital for attracting investment into lifelong learning. While evaluation and quality management are still perceived as being a bureaucratic necessity rather than a lesson one could learn from or an investment in the future, it is also true that without evaluation and quality assurance local networks do not have the means to examine their strengths and weaknesses. In order to design strategies to maximise the strengths and effectively address the weaknesses it is necessary to understand the factors that contribute to success and those that pose challenges. This article proposes an analytical quality framework which is generic and can be used to promote a culture of quality in learning cities and regions. The proposed framework builds on the findings and results of the R3L+ project, part-funded by the European Commission under the Grundtvig (adult education) strand of the Lifelong Learning programme 2007-2013.

  15. A Conceptual Framework for Web-Based Learning Design (United States)

    Alomyan, Hesham


    The purpose of this paper is to provide a coherent framework to present the relationship between individual differences and web-based learning. Two individual difference factors have been identified for investigation within the present paper: Cognitive style and prior knowledge. The importance of individual differences is reviewed and previous…

  16. Developing an Evaluation Framework of Quality Indicators for Learning Analytics

    NARCIS (Netherlands)

    Scheffel, Maren; Drachsler, Hendrik; Specht, Marcus


    This paper presents results from the continuous process of developing an evaluation framework of quality indicators for learning analytics (LA). Building on a previous study, a group concept mapping approach that uses multidimensional scaling and hierarchical clustering, the study presented here

  17. Mapping of Supply Chain Learning: A Framework for SMEs (United States)

    Thakkar, Jitesh; Kanda, Arun; Deshmukh, S. G.


    Purpose: The aim of this paper is to propose a mapping framework for evaluating supply chain learning potential for the context of small- to medium-sized enterprises (SMEs). Design/methodology/approach: The extracts of recently completed case based research for ten manufacturing SME units and facts reported in the previous research are utilized…

  18. A Road Map for Learning Progressions Research in Geography (United States)

    Huynh, Niem Tu; Solem, Michael; Bednarz, Sarah Witham


    This article provides an overview of learning progressions (LP) and assesses the potential of this line of research to improve geography education. It presents the merits and limitations of three of the most common approaches used to conduct LP research and draws on one approach to propose a first draft of a LP on map reading and interpretation.…

  19. Software framework for automatic learning of telescope operation (United States)

    Rodríguez, Jose A.; Molgó, Jordi; Guerra, Dailos


    The "Gran Telescopio de Canarias" (GTC) is an optical-infrared 10-meter segmented mirror telescope at the ORM observatory in Canary Islands (Spain). The GTC Control System (GCS) is a distributed object and component oriented system based on RT-CORBA and it is responsible for the operation of the telescope, including its instrumentation. The current development state of GCS is mature and fully operational. On the one hand telescope users as PI's implement the sequences of observing modes of future scientific instruments that will be installed in the telescope and operators, in turn, design their own sequences for maintenance. On the other hand engineers develop new components that provide new functionality required by the system. This great work effort is possible to minimize so that costs are reduced, especially if one considers that software maintenance is the most expensive phase of the software life cycle. Could we design a system that allows the progressive assimilation of sequences of operation and maintenance of the telescope, through an automatic self-programming system, so that it can evolve from one Component oriented organization to a Service oriented organization? One possible way to achieve this is to use mechanisms of learning and knowledge consolidation to reduce to the minimum expression the effort to transform the specifications of the different telescope users to the operational deployments. This article proposes a framework for solving this problem based on the combination of the following tools: data mining, self-Adaptive software, code generation, refactoring based on metrics, Hierarchical Agglomerative Clustering and Service Oriented Architectures.

  20. Personalized Age Progression with Bi-Level Aging Dictionary Learning. (United States)

    Shu, Xiangbo; Tang, Jinhui; Li, Zechao; Lai, Hanjiang; Zhang, Liyan; Yan, Shuicheng


    Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a personalized way. Basically, for each age group, we learn an aging dictionary to reveal its aging characteristics (e.g., wrinkles), where the dictionary bases corresponding to the same index yet from two neighboring aging dictionaries form a particular aging pattern cross these two age groups, and a linear combination of all these patterns expresses a particular personalized aging process. Moreover, two factors are taken into consideration in the dictionary learning process. First, beyond the aging dictionaries, each person may have extra personalized facial characteristics, e.g., mole, which are invariant in the aging process. Second, it is challenging or even impossible to collect faces of all age groups for a particular person, yet much easier and more practical to get face pairs from neighboring age groups. To this end, we propose a novel Bi-level Dictionary Learning based Personalized Age Progression (BDL-PAP) method. Here, bi-level dictionary learning is formulated to learn the aging dictionaries based on face pairs from neighboring age groups. Extensive experiments well demonstrate the advantages of the proposed BDL-PAP over other state-of-the-arts in term of personalized age progression, as well as the performance gain for cross-age face verification by synthesizing aging faces.

  1. Informing a Learning Progression in Genetics: Which Should Be Taught First, Mendelian Inheritance or the Central Dogma of Molecular Biology? (United States)

    Duncan, Ravit Golan; Castro-Faix, Moraima; Choi, Jinnie


    The Framework for Science Education and the Next Generation Science Standards in the USA emphasize learning progressions (LPs) that support conceptual coherence and the gradual building of knowledge over time. In the domain of genetics there are two independently developed alternative LPs. In essence, the difference between the two progressions…

  2. Towards a Framework to Improve the Quality of Teaching and Learning: Consciousness and Validation in Computer Engineering Science, UCT (United States)

    Lévano, Marcos; Albornoz, Andrea


    This paper aims to propose a framework to improve the quality in teaching and learning in order to develop good practices to train professionals in the career of computer engineering science. To demonstrate the progress and achievements, our work is based on two principles for the formation of professionals, one based on the model of learning…

  3. ‘Living' theory: a pedagogical framework for process support in networked learning

    Directory of Open Access Journals (Sweden)

    Philipa Levy


    Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.

  4. Overcoming complexities: Damage detection using dictionary learning framework (United States)

    Alguri, K. Supreet; Melville, Joseph; Deemer, Chris; Harley, Joel B.


    For in situ damage detection, guided wave structural health monitoring systems have been widely researched due to their ability to evaluate large areas and their ability detect many types of damage. These systems often evaluate structural health by recording initial baseline measurements from a pristine (i.e., undamaged) test structure and then comparing later measurements with that baseline. Yet, it is not always feasible to have a pristine baseline. As an alternative, substituting the baseline with data from a surrogate (nearly identical and pristine) structure is a logical option. While effective in some circumstance, surrogate data is often still a poor substitute for pristine baseline measurements due to minor differences between the structures. To overcome this challenge, we present a dictionary learning framework to adapt surrogate baseline data to better represent an undamaged test structure. We compare the performance of our framework with two other surrogate-based damage detection strategies: (1) using raw surrogate data for comparison and (2) using sparse wavenumber analysis, a precursor to our framework for improving the surrogate data. We apply our framework to guided wave data from two 108 mm by 108 mm aluminum plates. With 20 measurements, we show that our dictionary learning framework achieves a 98% accuracy, raw surrogate data achieves a 92% accuracy, and sparse wavenumber analysis achieves a 57% accuracy.

  5. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

    Directory of Open Access Journals (Sweden)

    Karim El-Laithy


    Full Text Available An integration of both the Hebbian-based and reinforcement learning (RL rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

  6. Conceptualizing Debates in Learning and Educational Research: Toward a Complex Systems Conceptual Framework of Learning (United States)

    Jacobson, Michael J.; Kapur, Manu; Reimann, Peter


    This article proposes a conceptual framework of learning based on perspectives and methodologies being employed in the study of complex physical and social systems to inform educational research. We argue that the contexts in which learning occurs are complex systems with elements or agents at different levels--including neuronal, cognitive,…

  7. A Framework for (Tele-) Monitoring of the Rehabilitation Progress in Stroke Patients (United States)

    David, V.; Haller, M.; Kotzian, S.; Hofmann, M.; Schlossarek, S.; Eichholzer, K.; Winkler, M.; Frohner, M.; Reichel, M.; Mayr, W.; Rafolt, D.


    Background Preservation of mobility in conjunction with an independent life style is one of the major goals of rehabilitation after stroke. Objectives The Rehab@Home framework shall support the continuation of rehabilitation at home. Methods The framework consists of instrumented insoles, connected wirelessly to a 3G ready tablet PC, a server, and a web-interface for medical experts. The rehabilitation progress is estimated via automated analysis of movement data from standardized assessment tests which are designed according to the needs of stroke patients and executed via the tablet PC application. Results The Rehab@Home framework’s implementation is finished and ready for the field trial (at five patients’ homes). Initial testing of the automated evaluation of the standardized mobility tests shows reproducible results. Conclusions Therefore it is assumed that the Rehab@Home framework is applicable as monitoring tool for the gait rehabilitation progress in stroke patients. PMID:26767068

  8. A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles. (United States)

    Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng


    In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

  9. A blended learning framework for curriculum design and professional development

    Directory of Open Access Journals (Sweden)

    Negin Mirriahi


    Full Text Available The need for flexibility in learning and the affordances of technology provided the impetus for the rise of blended learning (BL globally across higher education institutions. However, the adoption of BL practices continues at a low pace due to academics’ low digital fluency, various views and BL definitions, and limited standards-based tools to guide academic practice. To address these issues, this paper introduces a BL framework, based on one definition and with criteria and standards of practice to support the evaluation and advancement of BL in higher education. The framework is theoretically underpinned by the extant literature and supported by focus group discussions. The evidence supporting the criteria and standards are discussed with suggestions for how they can be used to guide course design, academic practice, and professional development.

  10. Psychological theory and pedagogical effectiveness: the learning promotion potential framework. (United States)

    Tomlinson, Peter


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

  11. A Machine Learning Framework for Plan Payment Risk Adjustment. (United States)

    Rose, Sherri


    To introduce cross-validation and a nonparametric machine learning framework for plan payment risk adjustment and then assess whether they have the potential to improve risk adjustment. 2011-2012 Truven MarketScan database. We compare the performance of multiple statistical approaches within a broad machine learning framework for estimation of risk adjustment formulas. Total annual expenditure was predicted using age, sex, geography, inpatient diagnoses, and hierarchical condition category variables. The methods included regression, penalized regression, decision trees, neural networks, and an ensemble super learner, all in concert with screening algorithms that reduce the set of variables considered. The performance of these methods was compared based on cross-validated R 2 . Our results indicate that a simplified risk adjustment formula selected via this nonparametric framework maintains much of the efficiency of a traditional larger formula. The ensemble approach also outperformed classical regression and all other algorithms studied. The implementation of cross-validated machine learning techniques provides novel insight into risk adjustment estimation, possibly allowing for a simplified formula, thereby reducing incentives for increased coding intensity as well as the ability of insurers to "game" the system with aggressive diagnostic upcoding. © Health Research and Educational Trust.

  12. The CABES (Clare Adult Basic Education Service) Framework as a Tool for Teaching and Learning (United States)

    Greene, Moira


    This article describes a Framework that can be used to help bridge the gap between theory and practice in adult learning. The Framework promotes practice informed by three strands important to adult literacy work: social theories of literacy, social-constructivist learning theory and principles of adult learning. The Framework shows how five key…


    Directory of Open Access Journals (Sweden)

    Mike Levy


    Full Text Available This paper seeks to improve approaches to the learning and teaching of culture using new technologies by relating the key qualities and dimensions of the culture concept to elements within a pedagogical framework. In Part One, five facets of the culture concept are developed: culture as elemental; culture as relative; culture as group membership; culture as contested; and culture as individual (variable and multiple. Each perspective aims to provide a focus for thinking about culture, and thereby to provide a valid and useful point of departure for thinking about the practice of culture learning and teaching with new technologies. The referenced literature draws from a broad range of disciplines and definitions of culture. In Part Two, five projects are chosen to represent relevant technologies currently in use for culture learning: e-mail, chat, a discussion forum and a Web-based project. Each project is used to illustrate facets of the culture concept discussed in Part One with a view to identifying key elements within a pedagogical framework that can help us respond effectively to the challenge of culture learning and teaching utilising new technologies. Thus the goal is to align fundamental qualities of the culture concept with specific pedagogical designs, tasks and technologies.

  14. A Conceptual Framework for Educational Design at Modular Level to Promote Transfer of Learning (United States)

    Botma, Yvonne; Van Rensburg, G. H.; Coetzee, I. M.; Heyns, T.


    Students bridge the theory-practice gap when they apply in practice what they have learned in class. A conceptual framework was developed that can serve as foundation to design for learning transfer at modular level. The framework is based on an adopted and adapted systemic model of transfer of learning, existing learning theories, constructive…

  15. Driver. D530.2 – Tools for the Lessons Learned Framework

    NARCIS (Netherlands)

    Schaik, M.G. van; et al


    In this deliverable D530.2 “Tools for the Lessons Learned Framework” the overall lessons learned framework will be clarified based on the delivery D53.1 “Lessons Learned Framework Concept” and aligned with the deliverable D52.1 “Harmonized competence framework”. The Tools for the Lessons Learned

  16. [Progress on metaplasticity and its role in learning and memory]. (United States)

    Wang, Shao-Li; Lu, Wei


    Long-term potentiation (LTP) and long-term depression (LTD) are two major forms of synaptic plasticity that are widely considered as important cellular models of learning and memory. Metaplasticity is defined as the plasticity of synaptic plasticity and thus is an advanced form of plasticity. The history of synaptic activity can affect the subsequent synaptic plasticity induction. Therefore, it is important to study metaplasticity to explore new mechanisms underlying various brain functions including learning and memory. Since the concept of metaplasticity was proposed, it has aroused widespread concerns and attracted numerous researchers to dig more details on this topic. These new-found experimental phenomena and cellular mechanisms have established the basis of theoretical studies on metaplasticity. In recent years, researchers have found that metaplasticity can not only affect the synaptic plasticity, but also regulate the neural network to encode specific content and enhance the learning and memory. These findings have greatly enriched our knowledge on plasticity and opened a new route to study the mechanism of learning and memory. In this review, we discuss the recent progress on metaplasticity on following three aspects: (1) the molecular mechanisms of metaplasticity; (2) the role of metaplasticity in learning and memory; and (3) the outlook of future study on metaplasticity.

  17. Active Self-Paced Learning for Cost-Effective and Progressive Face Identification. (United States)

    Lin, Liang; Wang, Keze; Meng, Deyu; Zuo, Wangmeng; Zhang, Lei


    This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into training under weak expert recertification. We first initialize the classifier using a few annotated samples for each individual, and extract image features using the convolutional neural nets. Then, a number of candidates are selected from the unannotated samples for classifier updating, in which we apply the current classifiers ranking the samples by the prediction confidence. In particular, our approach utilizes the high-confidence and low-confidence samples in the self-paced and the active user-query way, respectively. The neural nets are later fine-tuned based on the updated classifiers. Such heuristic implementation is formulated as solving a concise active SPL optimization problem, which also advances the SPL development by supplementing a rational dynamic curriculum constraint. The new model finely accords with the "instructor-student-collaborative" learning mode in human education. The advantages of this proposed framework are two-folds: i) The required number of annotated samples is significantly decreased while the comparable performance is guaranteed. A dramatic reduction of user effort is also achieved over other state-of-the-art active learning techniques. ii) The mixture of SPL and AL effectively improves not only the classifier accuracy compared to existing AL/SPL methods but also the robustness against noisy data. We evaluate our framework on two challenging datasets, which include hundreds of persons under diverse conditions, and demonstrate very promising results. Please find the code of this project at:

  18. Progress of the patients with diabetes mellitus who were managed with the staged diabetes management framework


    Zanetti, Maria Lúcia; Otero, Liudmila Miyar; Peres, Denise Siqueira; Santos, Manoel Antônio dos; Guimarães, Fernanda Pontin de Mattos; Freitas, Maria Cristina Foss


    OBJECTIVE: To describe the progress of patients with diabetes mellitus seen by health care team members who followed the Staged Diabetes Management framework. METHODS: This descriptive, prospective, and longitudinal study was conducted in a period of 12 months. The sample consisted of 54 patients with diabetes mellitus. Data were collected in three occasions through interviews: P0 - at beginning of the study; P6 - in six months; and, P12 - at the end of the study. RESULTS: There was an increa...

  19. Yield curve and Recession Forecasting in a Machine Learning Framework


    Theophilos Papadimitriou; Periklis Gogas; Maria Matthaiou; Efthymia Chrysanthidou


    In this paper, we investigate the forecasting ability of the yield curve in terms of the U.S. real GDP cycle. More specifically, within a Machine Learning (ML) framework, we use data from a variety of short (treasury bills) and long term interest rates (bonds) for the period from 1976:Q3 to 2011:Q4 in conjunction with the real GDP for the same period, to create a model that can successfully forecast output fluctuations (inflation and output gaps) around its long-run trend. We focus our attent...

  20. Supporting Collective Inquiry: A Technology Framework for Distributed Learning (United States)

    Tissenbaum, Michael

    This design-based study describes the implementation and evaluation of a technology framework to support smart classrooms and Distributed Technology Enhanced Learning (DTEL) called SAIL Smart Space (S3). S3 is an open-source technology framework designed to support students engaged in inquiry investigations as a knowledge community. To evaluate the effectiveness of S3 as a generalizable technology framework, a curriculum named PLACE (Physics Learning Across Contexts and Environments) was developed to support two grade-11 physics classes (n = 22; n = 23) engaged in a multi-context inquiry curriculum based on the Knowledge Community and Inquiry (KCI) pedagogical model. This dissertation outlines three initial design studies that established a set of design principles for DTEL curricula, and related technology infrastructures. These principles guided the development of PLACE, a twelve-week inquiry curriculum in which students drew upon their community-generated knowledge base as a source of evidence for solving ill-structured physics problems based on the physics of Hollywood movies. During the culminating smart classroom activity, the S3 framework played a central role in orchestrating student activities, including managing the flow of materials and students using real-time data mining and intelligent agents that responded to emergent class patterns. S3 supported students' construction of knowledge through the use individual, collective and collaborative scripts and technologies, including tablets and interactive large-format displays. Aggregate and real-time ambient visualizations helped the teacher act as a wondering facilitator, supporting students in their inquiry where needed. A teacher orchestration tablet gave the teacher some control over the flow of the scripted activities, and alerted him to critical moments for intervention. Analysis focuses on S3's effectiveness in supporting students' inquiry across multiple learning contexts and scales of time, and in

  1. Learn, see, practice, prove, do, maintain: an evidence-based pedagogical framework for procedural skill training in medicine. (United States)

    Sawyer, Taylor; White, Marjorie; Zaveri, Pavan; Chang, Todd; Ades, Anne; French, Heather; Anderson, JoDee; Auerbach, Marc; Johnston, Lindsay; Kessler, David


    Acquisition of competency in procedural skills is a fundamental goal of medical training. In this Perspective, the authors propose an evidence-based pedagogical framework for procedural skill training. The framework was developed based on a review of the literature using a critical synthesis approach and builds on earlier models of procedural skill training in medicine. The authors begin by describing the fundamentals of procedural skill development. Then, a six-step pedagogical framework for procedural skills training is presented: Learn, See, Practice, Prove, Do, and Maintain. In this framework, procedural skill training begins with the learner acquiring requisite cognitive knowledge through didactic education (Learn) and observation of the procedure (See). The learner then progresses to the stage of psychomotor skill acquisition and is allowed to deliberately practice the procedure on a simulator (Practice). Simulation-based mastery learning is employed to allow the trainee to prove competency prior to performing the procedure on a patient (Prove). Once competency is demonstrated on a simulator, the trainee is allowed to perform the procedure on patients with direct supervision, until he or she can be entrusted to perform the procedure independently (Do). Maintenance of the skill is ensured through continued clinical practice, supplemented by simulation-based training as needed (Maintain). Evidence in support of each component of the framework is presented. Implementation of the proposed framework presents a paradigm shift in procedural skill training. However, the authors believe that adoption of the framework will improve procedural skill training and patient safety.

  2. Improved Student Reasoning About Carbon-Transforming Processes Through Inquiry-Based Learning Activities Derived from an Empirically Validated Learning Progression (United States)

    JW, Schramm; Jin, H.; Keeling, EG; Johnson, M.; Shin, HJ


    This paper reports on our use of a fine-grained learning progression to assess secondary students' reasoning through carbon-transforming processes (photosynthesis, respiration, biosynthesis). Based on previous studies, we developed a learning progression with four progress variables: explaining mass changes, explaining energy transformations, explaining subsystems, and explaining large-scale systems. For this study, we developed a 2-week teaching module integrating these progress variables. Students were assessed before and after instruction, with the learning progression framework driving data analysis. Our work revealed significant overall learning gains for all students, with the mean post-test person proficiency estimates higher by 0.6 logits than the pre-test proficiency estimates. Further, instructional effects were statistically similar across all grades included in the study (7th-12th) with students in the lowest third of initial proficiency evidencing the largest learning gains. Students showed significant gains in explaining the processes of photosynthesis and respiration and in explaining transformations of mass and energy, areas where prior research has shown that student misconceptions are prevalent. Student gains on items about large-scale systems were higher than with other variables (although absolute proficiency was still lower). Gains across each of the biological processes tested were similar, despite the different levels of emphasis each had in the teaching unit. Together, these results indicate that students can benefit from instruction addressing these processes more explicitly. This requires pedagogical design quite different from that usually practiced with students at this level.

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

    Directory of Open Access Journals (Sweden)

    Tian Li


    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.

  4. When Playing Meets Learning: Methodological Framework for Designing Educational Games (United States)

    Linek, Stephanie B.; Schwarz, Daniel; Bopp, Matthias; Albert, Dietrich

    Game-based learning builds upon the idea of using the motivational potential of video games in the educational context. Thus, the design of educational games has to address optimizing enjoyment as well as optimizing learning. Within the EC-project ELEKTRA a methodological framework for the conceptual design of educational games was developed. Thereby state-of-the-art psycho-pedagogical approaches were combined with insights of media-psychology as well as with best-practice game design. This science-based interdisciplinary approach was enriched by enclosed empirical research to answer open questions on educational game-design. Additionally, several evaluation-cycles were implemented to achieve further improvements. The psycho-pedagogical core of the methodology can be summarized by the ELEKTRA's 4Ms: Macroadaptivity, Microadaptivity, Metacognition, and Motivation. The conceptual framework is structured in eight phases which have several interconnections and feedback-cycles that enable a close interdisciplinary collaboration between game design, pedagogy, cognitive science and media psychology.

  5. Architectural frameworks: defining the structures for implementing learning health systems. (United States)

    Lessard, Lysanne; Michalowski, Wojtek; Fung-Kee-Fung, Michael; Jones, Lori; Grudniewicz, Agnes


    The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment. We present an architectural framework for LHSs that incorporates five dimensions-goals, scientific, social, technical, and ethical-commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making. In this paper, we outline

  6. Empirical Refinements of a Molecular Genetics Learning Progression: The Molecular Constructs (United States)

    Todd, Amber; Kenyon, Lisa


    This article describes revisions to four of the eight constructs of the Duncan molecular genetics learning progression [Duncan, Rogat, & Yarden, (2009)]. As learning progressions remain hypothetical models until validated by multiple rounds of empirical studies, these revisions are an important step toward validating the progression. Our…

  7. Pedagogy framework design in social networked-based learning: Focus on children with learning difficulties

    Directory of Open Access Journals (Sweden)

    Samira Sadat Sajadi


    Full Text Available This paper presents an investigation on the theory of constructivism applicable for learners with learning difficulties, specifically learners with Attention Deficit Hyperactivity Disorder (ADHD. The primary objective of this paper is to determine whether a constructivist technology enhanced learning pedagogy could be used to help ADHD learners cope with their educational needs within a social-media learning environment. Preliminary work is stated here, in which we are seeking evidence to determine the viability of a constructivist approach for learners with ADHD. The novelty of this research lies in the proposals to support ADHD learners to overcome their weaknesses with appropriate pedagogically sound interventions. As a result, a framework has been designed to illuminate areas in which constructivist pedagogies require to address the limitations of ADHD learners. An analytical framework addressing the suitability of a constructivist learning for ADHD is developed from a combination of literature and expert advice from those involved in the education of learners with ADHD. This analytical framework is married to a new model of pedagogy, which the authors have derived from literature analysis. Future work will expand this model to develop a constructivist social network-based learning and eventually test it in specialist schools with ADHD learners.

  8. The Belem Framework for Action: Harnessing the Power and Potential of Adult Learning and Education for a Viable Future (United States)

    Adult Learning, 2012


    This article presents the Belem Framework for Action. This framework focuses on harnessing the power and potential of adult learning and education for a viable future. This framework begins with a preamble on adult education and towards lifelong learning.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin


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

  10. Systemic assessment framework of a learning organization's competitive positioning

    Directory of Open Access Journals (Sweden)

    Wissam EL Hachem


    Full Text Available Purpose: The purpose of this paper is to devise an innovative feasible, replicable and comprehensive assessment framework of a learning organization's competitive positioning. Design/methodology/approach: The three characteristics listed above are approached as follows. Feasible refers to being easy and not in need of much resources (time, personnel,.... This is done through early elimination of non-important variables. Replicable is having a well structured methodology based on scientific proven methods. Following this methodology would result in good results that can be explained if needed and replicated if deemed necessary. Comprehensive translates into a holistic set of indices that measure performance as well as organizational learning. Findings and Originality/value: The three attributes (feasible, replicable and comprehensive have become crucial for ensuring any kind of added value for such a methodology that hopes to tackle the modern dynamic business environment and gaining a sustainable competitive advantage. Research limitations/implications: Such a methodology would require several full contextual applications to be able to set its final design. It entails thorough internal revision of a company's structure. Therefore a great deal of transparency and self-transcendence from the individual involved is a pre-requisite for any chance of success. Originality/value: It offers a systematic way to assess a company's performance/competitive positioning while accounting for the crucial attribute of organizational learning in its makeup.

  11. Assessment of Intralaminar Progressive Damage and Failure Analysis Using an Efficient Evaluation Framework (United States)

    Hyder, Imran; Schaefer, Joseph; Justusson, Brian; Wanthal, Steve; Leone, Frank; Rose, Cheryl


    Reducing the timeline for development and certification for composite structures has been a long standing objective of the aerospace industry. This timeline can be further exacerbated when attempting to integrate new fiber-reinforced composite materials due to the large number of testing required at every level of design. computational progressive damage and failure analysis (PDFA) attempts to mitigate this effect; however, new PDFA methods have been slow to be adopted in industry since material model evaluation techniques have not been fully defined. This study presents an efficient evaluation framework which uses a piecewise verification and validation (V&V) approach for PDFA methods. Specifically, the framework is applied to evaluate PDFA research codes within the context of intralaminar damage. Methods are incrementally taken through various V&V exercises specifically tailored to study PDFA intralaminar damage modeling capability. Finally, methods are evaluated against a defined set of success criteria to highlight successes and limitations.

  12. A framework for prospectively defining progression rules for internal pilot studies monitoring recruitment. (United States)

    Hampson, Lisa V; Williamson, Paula R; Wilby, Martin J; Jaki, Thomas


    Just over half of publicly funded trials recruit their target sample size within the planned study duration. When recruitment targets are missed, the funder of a trial is faced with the decision of either committing further resources to the study or risk that a worthwhile treatment effect may be missed by an underpowered final analysis. To avoid this challenging situation, when there is insufficient prior evidence to support predicted recruitment rates, funders now require feasibility assessments to be performed in the early stages of trials. Progression criteria are usually specified and agreed with the funder ahead of time. To date, however, the progression rules used are typically ad hoc. In addition, rules routinely permit adaptations to recruitment strategies but do not stipulate criteria for evaluating their effectiveness. In this paper, we develop a framework for planning and designing internal pilot studies which permit a trial to be stopped early if recruitment is disappointing or to continue to full recruitment if enrolment during the feasibility phase is adequate. This framework enables a progression rule to be pre-specified and agreed upon prior to starting a trial. The novel two-stage designs stipulate that if neither of these situations arises, adaptations to recruitment should be made and subsequently evaluated to establish whether they have been successful. We derive optimal progression rules for internal pilot studies which minimise the expected trial overrun and maintain a high probability of completing the study when the recruitment rate is adequate. The advantages of this procedure are illustrated using a real trial example.

  13. A Machine LearningFramework to Forecast Wave Conditions (United States)

    Zhang, Y.; James, S. C.; O'Donncha, F.


    Recently, significant effort has been undertaken to quantify and extract wave energy because it is renewable, environmental friendly, abundant, and often close to population centers. However, a major challenge is the ability to accurately and quickly predict energy production, especially across a 48-hour cycle. Accurate forecasting of wave conditions is a challenging undertaking that typically involves solving the spectral action-balance equation on a discretized grid with high spatial resolution. The nature of the computations typically demands high-performance computing infrastructure. Using a case-study site at Monterey Bay, California, a machine learning framework was trained to replicate numerically simulated wave conditions at a fraction of the typical computational cost. Specifically, the physics-based Simulating WAves Nearshore (SWAN) model, driven by measured wave conditions, nowcast ocean currents, and wind data, was used to generate training data for machine learning algorithms. The model was run between April 1st, 2013 and May 31st, 2017 generating forecasts at three-hour intervals yielding 11,078 distinct model outputs. SWAN-generated fields of 3,104 wave heights and a characteristic period could be replicated through simple matrix multiplications using the mapping matrices from machine learning algorithms. In fact, wave-height RMSEs from the machine learning algorithms (9 cm) were less than those for the SWAN model-verification exercise where those simulations were compared to buoy wave data within the model domain (>40 cm). The validated machine learning approach, which acts as an accurate surrogate for the SWAN model, can now be used to perform real-time forecasts of wave conditions for the next 48 hours using available forecasted boundary wave conditions, ocean currents, and winds. This solution has obvious applications to wave-energy generation as accurate wave conditions can be forecasted with over a three-order-of-magnitude reduction in

  14. A Driver Behavior Learning Framework for Enhancing Traffic Simulation

    Directory of Open Access Journals (Sweden)

    Ramona Maria Paven


    Full Text Available Traffic simulation provides an essential support for developing intelligent transportation systems. It allows affordable validation of such systems using a large variety of scenarios that involves massive data input. However, realistic traffic models are hard to be implemented especially for microscopic traffic simulation. One of the hardest problems in this context is to model the behavior of drivers, due the complexity of human nature. The work presented in this paper proposes a framework for learning driver behavior based on a Hidden Markov Model technique. Moreover, we propose also a practical method to inject this behavior in a traffic model used by the SUMO traffic simulator. To demonstrate the effectiveness of this method we present a case study involving real traffic collected from Timisoara city area.

  15. Social Support System in Learning Network for lifelong learners: A Conceptual framework

    NARCIS (Netherlands)

    Nadeem, Danish; Stoyanov, Slavi; Koper, Rob


    Nadeem, D., Stoyanov, S., & Koper, R. (2009). Social support system in learning network for lifelong learners: A Conceptual framework [Special issue]. International Journal of Continuing Engineering Education and Life-Long Learning, 19(4/5/6), 337-351.

  16. Determinants of E-learning Acceptance among Agricultural Extension Agents in Malaysia: A Conceptual Framework


    Mangir, Safaie; Othman, Zakirah; Udin, Zulkifli Mohamed


    The objective of this paper is to develop a framework on e-learning acceptance among agricultural extension agents in Malaysian agricultural sector. E-learning is viewed as a solution in response to the increasing need for learning and training. This paper will review past literatures for the relevant factors that influence behavioral intention for e-learning acceptance as well as the relevant behavioral theories that provide the foundation for developing research framework to illustrate the ...

  17. A Framework for Learning Analytics Using Commodity Wearable Devices. (United States)

    Lu, Yu; Zhang, Sen; Zhang, Zhiqiang; Xiao, Wendong; Yu, Shengquan


    We advocate for and introduce LEARNSense, a framework for learning analytics using commodity wearable devices to capture learner's physical actions and accordingly infer learner context (e.g., student activities and engagement status in class). Our work is motivated by the observations that: (a) the fine-grained individual-specific learner actions are crucial to understand learners and their context information; (b) sensor data available on the latest wearable devices (e.g., wrist-worn and eye wear devices) can effectively recognize learner actions and help to infer learner context information; (c) the commodity wearable devices that are widely available on the market can provide a hassle-free and non-intrusive solution. Following the above observations and under the proposed framework, we design and implement a sensor-based learner context collector running on the wearable devices. The latest data mining and sensor data processing techniques are employed to detect different types of learner actions and context information. Furthermore, we detail all of the above efforts by offering a novel and exemplary use case: it successfully provides the accurate detection of student actions and infers the student engagement states in class. The specifically designed learner context collector has been implemented on the commodity wrist-worn device. Based on the collected and inferred learner information, the novel intervention and incentivizing feedback are introduced into the system service. Finally, a comprehensive evaluation with the real-world experiments, surveys and interviews demonstrates the effectiveness and impact of the proposed framework and this use case. The F1 score for the student action classification tasks achieve 0.9, and the system can effectively differentiate the defined three learner states. Finally, the survey results show that the learners are satisfied with the use of our system (mean score of 3.7 with a standard deviation of 0.55).

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

    Directory of Open Access Journals (Sweden)

    Benjamin L. Wiggins


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

  19. IAEA Mission Sees Significant Progress in Georgia’s Regulatory Framework, Challenges Ahead

    International Nuclear Information System (INIS)


    An International Atomic Energy Agency (IAEA) team of experts said Georgia has made significant progress in strengthening its regulatory framework for nuclear and radiation safety. The team also pointed to challenges ahead as Georgia seeks to achieve further progress. The Integrated Regulatory Review Service (IRRS) team concluded a 10-day mission on 28 February to assess the regulatory safety framework in Georgia. The mission was conducted at the request of the Government and hosted by the Agency of Nuclear and Radiation Safety (ANRS), which is responsible for regulatory oversight in the country. IRRS missions are designed to strengthen the effectiveness of the national safety regulatory infrastructure, while recognizing the responsibility of each State to ensure nuclear and radiation safety. Georgia uses radioactive sources in medicine and industry and operates radioactive waste management facilities. It has decommissioned its only research reactor and has no nuclear power plants. In recent years, the Government and ANRS, with assistance from the IAEA, introduced new safety regulations and increased the number of regulatory inspections.

  20. A Learning Framework for Control-Oriented Modeling of Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.; Vishnu, Abhinav; Vrabie, Draguna L.


    Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.

  1. Teaching and Learning Numerical Analysis and Optimization: A Didactic Framework and Applications of Inquiry-Based Learning (United States)

    Lappas, Pantelis Z.; Kritikos, Manolis N.


    The main objective of this paper is to propose a didactic framework for teaching Applied Mathematics in higher education. After describing the structure of the framework, several applications of inquiry-based learning in teaching numerical analysis and optimization are provided to illustrate the potential of the proposed framework. The framework…

  2. A Pedagogical Framework for Mobile Learning: Categorizing Educational Applications of Mobile Technologies into Four Types

    Directory of Open Access Journals (Sweden)

    Yeonjeong Park


    Full Text Available Instructional designers and educators recognize the potential of mobile technologies as a learning tool for students and have incorporated them into the distance learning environment. However, little research has been done to categorize the numerous examples of mobile learning in the context of distance education, and few instructional design guidelines based on a solid theoretical framework for mobile learning exist. In this paper I compare mobile learning (m-learning with electronic learning (e-learning and ubiquitous learning (u-learning and describe the technological attributes and pedagogical affordances of mobile learning presented in previous studies. I modify transactional distance (TD theory and adopt it as a relevant theoretical framework for mobile learning in distance education. Furthermore, I attempt to position previous studies into four types of mobile learning: 1 high transactional distance socialized m-learning, 2 high transactional distance individualized m-learning, 3 low transactional distance socialized m-learning, and 4 low transactional distance individualized m-learning. As a result, this paper can be used by instructional designers of open and distance learning to learn about the concepts of mobile learning and how mobile technologies can be incorporated into their teaching and learning more effectively.

  3. One lens missing? Clarifying the clinical microsystem framework with learning theories. (United States)

    Norman, Ann-Charlott; Fritzen, Lena; Fridh, Marianne Lindblad


    The clinical microsystem (CMS) approach is widely used and is perceived as helpful in practice but, we ask the question: "Is its learning potential sufficiently utilized?" To scrutinize aspects of learning within the CMS framework and to clarify the learning aspects the framework includes and thereby support the framework with the enhanced learning perspective that becomes visible. Literature on the CMS framework was systematically searched and selected using inclusion criteria. An analytical tool was constructed in the form of a theoretical lens that was used to clarify learning aspects that are associated with the framework. The analysis revealed 3 learning aspects: (1) The CMS framework describes individual and social learning but not how to adapt learning strategies for purposes of change. (2) The metaphorical language of how to reach a holistic health care system for each patient has developed over time but can still be improved by naming social interactions to transcend organizational boundaries. (3) Power structures are recognized but not as a characteristic that restricts learning due to asymmetric communication. The "lens" perspective reveals new meanings to learning that enhance our understanding of health care as a social system and provides new practical learning strategies.

  4. Radioactive waste management in Canada: progress and challenges 15 years after the policy framework

    International Nuclear Information System (INIS)

    McCauley, D.


    wastes produced by other producers of these forms of waste. Initiatives are underway that should define options for these wastes. Other issues are associated with optimizing long-term waste management options. These issues include the optimization of management solutions for historic wastes and the identification of management solutions for very low-level radioactive wastes that will result from future decommissioning activity. Canada has made much progress in the area of radioactive waste management since the elaboration of the Policy Framework. At the 2009 Third Review Meeting of the Joint Convention on the Safety of Spent Fuel Management and on the Safety of Radioactive Waste Management the International Atomic Energy Agency highlighted Canada's 'substantial progress made in the radioactive waste and spent fuel management since the last review meeting'. It noted that Canada had made good progress in the implementation of the waste management programme and the programme is ongoing. Given recent progress, Canada will enter the Fourth Review Meeting in 2012 in an even stronger position as long-term waste management initiatives begun after the elaboration of the Policy Framework fifteen years ago, begin to mature. (author)

  5. Organizational learning for sustainable development: Correlation with the national culture dimensions framework

    Directory of Open Access Journals (Sweden)

    Jovanović Violeta


    Full Text Available Knowledge has become a key resource and the driver of economic progress. The distribution of welfare in the world demonstrates that the richest countries are the ones that have the knowledge, not natural resources. Creating a knowledge-based society is the foundation for sustainable development. Key factors influencing the creation of a knowledge-based economy are investments in education, research and development and application of new technologies. Nevertheless, culture, attitudes and values that affect people’s commitment to continuous improvement and learning, can also play an important role in creating a knowledge society for sustainable development. In this paper authors are making an attempt to identify the basic values of employees in several Serbian companies by means of factor analysis approach, with special emphasis on the national cultural dimensions framework and its utility.

  6. Analytics to Literacies: The Development of a Learning Analytics Framework for Multiliteracies Assessment

    Directory of Open Access Journals (Sweden)

    Shane Dawson


    Full Text Available The rapid advances in information and communication technologies, coupled with increased access to information and the formation of global communities, have resulted in interest among researchers and academics to revise educational practice to move beyond traditional ‘literacy’ skills towards an enhanced set of “multiliteracies” or “new media literacies”. Measuring the literacy of a population, in the light of its linkage to individual and community wealth and wellbeing, is essential to determining the impact of compulsory education. The opportunity now is to develop tools to assess individual and societal attainment of these new literacies. Drawing on the work of Jenkins and colleagues (2006 and notions of a participatory culture, this paper proposes a conceptual framework for how learning analytics can assist in measuring individual achievement of multiliteracies and how this evaluative process can be scaled to provide an institutional perspective of the educational progress in fostering these fundamental skills.

  7. Teachers' Knowing How to Use Technology: Exploring a Conceptual Framework for Purposeful Learning Activity (United States)

    Fisher, Tony; Denning, Tim; Higgins, Chris; Loveless, Avril


    This article describes a project to apply and validate a conceptual framework of clusters of purposeful learning activity involving ICT tools. The framework, which is based in a socio-cultural perspective, is described as "DECK", and comprises the following major categories of the use of digital technologies to support learning:…

  8. Linking a Learning Progression for Natural Selection to Teachers' Enactment of Formative Assessment (United States)

    Furtak, Erin Marie


    Learning progressions, or representations of how student ideas develop in a domain, hold promise as tools to support teachers' formative assessment practices. The ideas represented in a learning progression might help teachers to identify and make inferences about evidence collected of student thinking, necessary precursors to modifying…

  9. The Framework of Intervention Engine Based on Learning Analytics (United States)

    Sahin, Muhittin; Yurdugül, Halil


    Learning analytics primarily deals with the optimization of learning environments and the ultimate goal of learning analytics is to improve learning and teaching efficiency. Studies on learning analytics seem to have been made in the form of adaptation engine and intervention engine. Adaptation engine studies are quite widespread, but intervention…

  10. The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement (United States)

    Bodily, Robert; Nyland, Rob; Wiley, David


    The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the…

  11. Recent Progress in Metal-Organic Frameworks and Their Derived Nanostructures for Energy and Environmental Applications. (United States)

    Xie, Zhiqiang; Xu, Wangwang; Cui, Xiaodan; Wang, Ying


    Metal-organic frameworks (MOFs), as a very promising category of porous materials, have attracted increasing interest from research communities due to their extremely high surface areas, diverse nanostructures, and unique properties. In recent years, there is a growing body of evidence to indicate that MOFs can function as ideal templates to prepare various nanostructured materials for energy and environmental cleaning applications. Recent progress in the design and synthesis of MOFs and MOF-derived nanomaterials for particular applications in lithium-ion batteries, sodium-ion batteries, supercapacitors, dye-sensitized solar cells, and heavy-metal-ion detection and removal is reviewed herein. In addition, the remaining major challenges in the above fields are discussed and some perspectives for future research efforts in the development of MOFs are also provided. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Disposal Systems Evaluation Framework (DSEF) Version 1.0 - Progress Report

    Energy Technology Data Exchange (ETDEWEB)

    Sutton, Mark [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Blink, James A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fratoni, Massimiliano [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Greenberg, Harris R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Halsey, William G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wolery, Thomas J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)


    The Disposal Systems Evaluation Framework (DSEF) is being developed at Lawrence Livermore National Laboratory to formalize the development and documentation of repository conceptual design options for each waste form and environment combination. This report summarizes current status and plans for the remainder of FY11 and for FY12. This progress report defines the architecture and interface parameters of the DSEF Excel workbook, which contains worksheets that link to each other to provide input and document output from external codes such that concise comparisons between fuel cycles, disposal environments, repository designs and engineered barrier system materials can be performed. Collaborations between other Used Fuel Disposition Campaign work packages and US Department of Energy / Nuclear Energy campaigns are clearly identified. File naming and configuration management is recommended to allow automated abstraction of data from multiple DSEF runs.

  13. Framework for Conducting Empirical Observations of Learning Processes. (United States)

    Fischer, Hans Ernst; von Aufschnaiter, Stephan


    Reviews four hypotheses about learning: Comenius's transmission-reception theory, information processing theory, Gestalt theory, and Piagetian theory. Uses the categories preunderstanding, conceptual change, and learning processes to classify and assess investigations on learning processes. (PR)

  14. A Framework for Building an Interactive Satellite TV Based M-Learning Environment

    Directory of Open Access Journals (Sweden)

    Ghassan Issa


    Full Text Available This paper presents a description of an interactive satellite TV based mobile learning (STV-ML framework, in which a satellite TV station is used as an integral part of a comprehensive interactive mobile learning (M-Learning environment. The proposed framework assists in building a reliable, efficient, and cost-effective environment to meet the growing demands of M-Learning all over the world, especially in developing countries. It utilizes recent advances in satellite reception, broadcasting technologies, and interactive TV to facilitate the delivery of gigantic learning materials. This paper also proposed a simple and flexible three-phase implementation methodology which includes construction of earth station, expansion of broadcasting channels, and developing true user interactivity. The proposed framework and implementation methodology ensure the construction of a true, reliable, and cost effective M-Learning system that can be used efficiently and effectively by a wide range of users and educational institutions to deliver ubiquitous learning.

  15. Visual Hybrid Development Learning System (VHDLS) framework for children with autism. (United States)

    Banire, Bilikis; Jomhari, Nazean; Ahmad, Rodina


    The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework.

  16. A Framework of Metacognitive Scaffolding in Learning Authoring System through Facebook (United States)

    Jumaat, Nurul Farhana; Tasir, Zaidatun


    Scaffolding refers to a guidance that helps students during their learning sessions whereby it makes learning easier for them. This study aims to develop a framework of metacognitive scaffolding (MS) to guide students in learning Authoring System through Facebook. Thirty-seven master degree students who were enrolled in Authoring System course…

  17. e-Learning for Expanding Distance Education in Tertiary Level in Bangladesh: Problems and Progress (United States)

    Al-Masum, Md. Abdullah; Chowdhury, Saiful Islam


    E-learning has broadly become an important enabler to promote distance education (DE) and lifelong learning in most of the developed countries, but in Bangladesh it is still a new successful progressive system for the learning communities. Distance education is thought to be introduced as an effective way of educating people of all sections in…

  18. A Framework for (Tele-) Monitoring of the Rehabilitation Progress in Stroke Patients: eHealth 2015 Special Issue. (United States)

    Jagos, H; David, V; Haller, M; Kotzian, S; Hofmann, M; Schlossarek, S; Eichholzer, K; Winkler, M; Frohner, M; Reichel, M; Mayr, W; Rafolt, D


    Preservation of mobility in conjunction with an independent life style is one of the major goals of rehabilitation after stroke. The Rehab@Home framework shall support the continuation of rehabilitation at home. The framework consists of instrumented insoles, connected wirelessly to a 3G ready tablet PC, a server, and a web-interface for medical experts. The rehabilitation progress is estimated via automated analysis of movement data from standardized assessment tests which are designed according to the needs of stroke patients and executed via the tablet PC application. The Rehab@Home framework's implementation is finished and ready for the field trial (at five patients' homes). Initial testing of the automated evaluation of the standardized mobility tests shows reproducible results. Therefore it is assumed that the Rehab@Home framework is applicable as monitoring tool for the gait rehabilitation progress in stroke patients.

  19. A framework for exploring integrated learning systems for the governance and management of public protected areas. (United States)

    Nkhata, Bimo Abraham; Breen, Charles


    This article discusses how the concept of integrated learning systems provides a useful means of exploring the functional linkages between the governance and management of public protected areas. It presents a conceptual framework of an integrated learning system that explicitly incorporates learning processes in governance and management subsystems. The framework is premised on the assumption that an understanding of an integrated learning system is essential if we are to successfully promote learning across multiple scales as a fundamental component of adaptability in the governance and management of protected areas. The framework is used to illustrate real-world situations that reflect the nature and substance of the linkages between governance and management. Drawing on lessons from North America and Africa, the article demonstrates that the establishment and maintenance of an integrated learning system take place in a complex context which links elements of governance learning and management learning subsystems. The degree to which the two subsystems are coupled influences the performance of an integrated learning system and ultimately adaptability. Such performance is largely determined by how integrated learning processes allow for the systematic testing of societal assumptions (beliefs, values, and public interest) to enable society and protected area agencies to adapt and learn in the face of social and ecological change. It is argued that an integrated perspective provides a potentially useful framework for explaining and improving shared understanding around which the concept of adaptability is structured and implemented.

  20. Real World Learning: toward a differentiated framework for outdoor learning for sustainability

    Directory of Open Access Journals (Sweden)

    Lewis Winks


    Full Text Available The Real World Learning network (RWLn set out in 2011 to explore elements which contribute to a ‘deep and meaningful’ outdoor education experience. Following three years of work, the RWLn developed the ‘Hand Model’, a learning model designed to support educators in the development of Outdoor Learning for Sustainability (OLfS. Since its launch in early 2014, the model has been used for planning, delivering and reflecting upon OLfS experiences. Making use of the comments made in Činčera’s (2015 Real World Learning: a critical analysis which highlights inconsistencies existent within the model’s internal logic, this paper considers the perceived contradiction between emancipatory and instrumental approaches to learning. Beginning with a comprehensive introduction to the Hand model, this paper goes on to discuss the theoretical divide which the model spans between a goal-led, knowledge based approach promoted by the model’s focus upon understanding and values, and a pluralistic and exploratory approach typified by aspects of educational empowerment and experience. In response to this and augmented by examples, a differentiated conceptual framework is presented to facilitate a pragmatic application of the model from a practice perspective, making use of what has been termed a ‘blended approach’, whilst acknowledging degrees of inconsistency and dissonance from a theoretical perspective. Additionally, the model is viewed from a context perspective where questions are asked regarding the appropriateness of particular approaches depending upon the setting in which learning takes place. It is hoped that by moving beyond theoretically entrenched positions a mediated middle ground for the model’s application may be established.

  1. A Learning and Interaction design framework, from a study on formulating principles for the design of engaging music learning games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke; Ørngreen, Rikke


    Based on a preliminary action research study investigating the design of digital music games and years of experiences from interaction design processes of learning resources, this extended abstract presents a framework that mixes designs for learning principles and game design with a process view...... using a simple interaction design lifecycle. Though the first outset was to design engaging music games, the resulting framework has a more generic character....

  2. Knowledge. Progression and the Understanding of Workplace Learning

    DEFF Research Database (Denmark)

    Laursen, Erik


    The book explores new ways of thinking about learning at work, and the understanding of its role and purpose.......The book explores new ways of thinking about learning at work, and the understanding of its role and purpose....

  3. A Conceptual Framework over Contextual Analysis of Concept Learning within Human-Machine Interplays

    DEFF Research Database (Denmark)

    Badie, Farshad


    This research provides a contextual description concerning existential and structural analysis of ‘Relations’ between human beings and machines. Subsequently, it will focus on conceptual and epistemological analysis of (i) my own semantics-based framework [for human meaning construction] and of (ii......) a well-structured machine concept learning framework. Accordingly, I will, semantically and epistemologically, focus on linking those two frameworks for logical analysis of concept learning in the context of human-machine interrelationships. It will be demonstrated that the proposed framework provides...

  4. Constructing an Overarching Framework for Learning--Connecting the Dots (United States)

    Amey, Marilyn J.


    This chapter highlights a variety of ways researchers use learning theories with respect to different stakeholder groups. The chapter brings together common themes across these areas and proposes ways to use these ideas for future research on learning.

  5. An Analytical Quality Framework for Learning Cities and Regions (United States)

    Preisinger-Kleine, Randolph


    There is broad agreement that innovation, knowledge and learning have become the main source of wealth, employment and economic development of cities, regions and nations. Over the past two decades, the number of European cities and regions which label themselves as "learning city" or "learning region" has constantly grown.…

  6. Multi-Agent Framework for Virtual Learning Spaces. (United States)

    Sheremetov, Leonid; Nunez, Gustavo


    Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

  7. An Evolutionary Machine Learning Framework for Big Data Sequence Mining (United States)

    Kamath, Uday Krishna


    Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…

  8. The 4C framework for making reasonable adjustments for people with learning disabilities. (United States)

    Marsden, Daniel; Giles, Rachel


    Background People with learning disabilities experience significant inequalities in accessing healthcare. Legal frameworks, such as the Equality Act 2010, are intended to reduce such disparities in care, and require organisations to make 'reasonable adjustments' for people with disabilities, including learning disabilities. However, reasonable adjustments are often not clearly defined or adequately implemented in clinical practice. Aim To examine and synthesise the challenges in caring for people with learning disabilities to develop a framework for making reasonable adjustments for people with learning disabilities in hospital. This framework would assist ward staff in identifying and managing the challenges of delivering person-centred, safe and effective healthcare to people with learning disabilities in this setting. Method Fourth-generation evaluation, collaborative thematic analysis, reflection and a secondary analysis were used to develop a framework for making reasonable adjustments in the hospital setting. The authors attended ward manager and matron group meetings to collect their claims, concerns and issues, then conducted a collaborative thematic analysis with the group members to identify the main themes. Findings Four main themes were identified from the ward manager and matron group meetings: communication, choice-making, collaboration and coordination. These were used to develop the 4C framework for making reasonable adjustments for people with learning disabilities in hospital. Discussion The 4C framework has provided a basis for delivering person-centred care for people with learning disabilities. It has been used to inform training needs analyses, develop audit tools to review delivery of care that is adjusted appropriately to the individual patient; and to develop competencies for learning disability champions. The most significant benefit of the 4C framework has been in helping to evaluate and resolve practice-based scenarios. Conclusion Use of


    Directory of Open Access Journals (Sweden)

    Arjen Deij


    Full Text Available The paper reveals the international prospects of developing and spreading the qualifications frameworks across the globe. It introduces the key terms and concepts related to the given issue, and examines both the benefits and challenges of qualifications frameworks implementation. The author looks into the origins and causes of the worldwide interest in qualifications framework application, and gives the overview of related recent publications and their conclusions to reinforce the provided argumentation.

  10. Learning modalities in artificial intelligence systems: a framework and review

    Energy Technology Data Exchange (ETDEWEB)

    Araya, A A


    Intelligent systems should possess two fundamental capabilities: problem solving and learning. Problem solving capabilities allow an intelligent system to cope with problems in a given domain. Learning capabilities make possible for an intelligent system to improve the solution to the problems within its current reach or to cope with new problems. This paper examines research in artificial intelligence from the perspective of learning with the purpose of: 1) developing and understanding of the problem of learning from the AI point of view, and II) characterizing the current state of the art on learning in AI. 35 references.

  11. A Design Framework for Enhancing Engagement in Student-Centered Learning: Own It, Learn It, and Share It (United States)

    Lee, Eunbae; Hannafin, Michael J.


    Student-centered learning (SCL) identifies students as the owners of their learning. While SCL is increasingly discussed in K-12 and higher education, researchers and practitioners lack current and comprehensive framework to design, develop, and implement SCL. We examine the implications of theory and research-based evidence to inform those who…

  12. An Integrated Framework Of Web 2.0 Technology And A Collaborative Learning

    Directory of Open Access Journals (Sweden)

    Mohamed Madar


    Full Text Available Abstract This paper contributes to the suitability of web 2.0 technology in implementing collaborative learning and proposes an integrated framework of Web 2.0 tools and collaborative learning activities. This paper is also identifying the mismatch between adopting web 2.0 technologies and the delivery of the curriculum on the cloud or via the Internet. It is found that Web 2.0 and a collaborative learning are two platforms to be easily synchronized due to their common attributes that enable their complementariness. This paper argues that integrated framework of Web 2.0 and CL allow users exploit teachinglearning materials maximally and at the same upsurges learners understanding in the subject knowledge. Suitable of Web 2.0 in implementing curriculum was also encouraged since the proposed framework consists of both components of Web 2.0 functions and activities of collaborative learning environment. Pedagogically there has been a mismatch between E-learning technologies and mode of delivery for instance E-learning platforms are widely used to increase content accessibility only while now this framework introduces that Web 2.0 technology of E-learning can also be used to create share knowledge among users. The proposed framework if efficiently exploited will also allow users at all levels create personalized learning environment which suits perspective teachinglearning styles of the users. Apart from academic achievement or enhancements of the teaching and learning processes the proposed framework also would help learners develop generic skills which are very important in the workplaces. As a result of this fast and independent learning technically depend on technology based pedagogy and in this case this proposed model has two dimensions which are very crucial to the enrichment of students learning activities.

  13. Progress towards and barriers to implementation of a risk framework for US federal wildland fire policy and decision making (United States)

    David C. Calkin; Mark A. Finney; Alan A. Ager; Matthew P. Thompson; Krista M. Gebert


    In this paper we review progress towards the implementation of a riskmanagement framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical methods to measure...

  14. A Theoretical Framework for the Studio as a Learning Environment (United States)

    Brandt, Carol B.; Cennamo, Katherine; Douglas, Sarah; Vernon, Mitzi; McGrath, Margarita; Reimer, Yolanda


    In this article we describe a holistic, ecological framework that takes into account the surface structures and pedagogical approaches in the studio and how these elements are connected to the construction of design knowledge: epistemology. In our development of this framework, we came to understand how disciplinary underpinnings and academic…

  15. The digital Dalton Plan: Progressive education as integral part of web-based learning environments

    Directory of Open Access Journals (Sweden)

    Georg Weichhart


    Full Text Available e-Learning systems increasingly support learning management and self-organized learning processes. Since the latter have been studied in the field of progressive education extensively, it is worthwhile to consider them for developing digital learning environments to support self-regulated learning processes. In this paper we aim at transforming one of the most prominent and sustainable approaches to self-organized learning, the “Dalton Plan” as proposed by Helen Parkhurst. Its assignment structure supports learners when managing their learning tasks, thus triggering self-organized acquisition of knowledge, and its feedback graphs enable transparent learning processes. Since e-learning environments have become common use, rather than creating another system, we propose a modular approach that can be used for extending existing e-learning environments. In order to design a respective component, we interviewed experts in self-organized e-learning. Their input facilitated integrating the Dalton Plan with existing features of e-learning environments. After representing each interview in concept maps, we were able to aggregate them for deriving e-learning requirements conform to the Dalton Plan instruments. In the course of implementing them, particular attention had to be paid to the asynchrony of interaction during runtime. Java Server Faces technology enable the Dalton Plan component to be migrated into existing web 2.0 e-learning platforms. The result was evaluated based on the acquired concept maps, as they also captured the transformation process of the Dalton Plan to e-learning features. The findings encourage embodying further progressive education approaches in this way, since the structured (concept mapping of the Dalton Plan to e-learning features turned out to be accurate. The experts were able to recognize the potential of the approach both in terms of structuring the knowledge acquisition process, and in terms of developing

  16. A systemic framework for managing e-learning adoption in campus universities: individual strategies in context

    Directory of Open Access Journals (Sweden)

    Carol Russell


    Full Text Available There are hopes that new learning technologies will help to transform university learning and teaching into a more engaging experience for twenty-first-century students. But since 2000 the changes in campus university teaching have been more limited than expected. I have drawn on ideas from organisational change management research to investigate why this is happening in one particular campus university context. My study examines the strategies of individual lecturers for adopting e-learning within their disciplinary, departmental and university work environments to develop a conceptual framework for analysing university learning and teaching as a complex adaptive system. This conceptual framework links the processes through which university teaching changes, the resulting forms of learning activity and the learning technologies used – all within the organisational context of the university. The framework suggests that systemic transformation of a university's learning and teaching requires coordinated change across activities that have traditionally been managed separately in campus universities. Without such coordination, established ways of organising learning and teaching will reassert themselves, as support staff and lecturers seek to optimise their own work locally. The conceptual framework could inform strategies for realising the full benefits of new learning technologies in other campus universities.

  17. Grounding theories of W(e)Learn: a framework for online interprofessional education. (United States)

    Casimiro, Lynn; MacDonald, Colla J; Thompson, Terrie Lynn; Stodel, Emma J


    Interprofessional care (IPC) is a prerequisite for enhanced communication between healthcare team members, improved quality of care, and better outcomes for patients. A move to an IPC model requires changing the learning experiences of healthcare providers during and after their qualification program. With the rapid growth of online and blended approaches to learning, an educational framework that explains how to construct quality learning events to provide IPC is pressing. Such a framework would offer a quality standard to help educators design, develop, deliver, and evaluate online interprofessional education (IPE) programs. IPE is an extremely delicate process due to issues related to knowledge, status, power, accountability, personality traits, and culture that surround IPC. In this paper, a review of the pertinent literature that would inform the development of such a framework is presented. The review covers IPC, IPE, learning theories, and eLearning in healthcare.

  18. D.3.3 PLOT Persuasive Learning Design Framework

    DEFF Research Database (Denmark)

    Gram-Hansen, Sandra Burri


    In this third and final deliverable of WP3: Persuasive Learning Designs, the theoretical cross field between persuasion and learning and the practical analysis of the technological learning tools and products which are currently related to the PLOT project, namely the GLOMaker and the 3ET tool......, are linked together as persuasive learning designs are defined and exemplified through the four e-PLOT cases. Based on the literary study of D.3.1 as well as the subsequent discussions and reflections regarding the theoretical foundation and practical application of persuasive learning technologies......-PLOT work cases. In conclusion, the report presents a number of suggestions regarding the improvement of the two learning tools, which from a theoretical perspective will enhance the persuasive potential, and which can be taken into consideration in WP4 and 5....

  19. The Inquiry, Communication, Construction and Expression (ICCE) Framework for Understanding Learning Experiences in Games (United States)

    Shah, Mamta; Foster, Aroutis


    There is a paucity of research frameworks that focus on aiding game selection and use, analyzing the game as a holistic system, and studying learner experiences in games. There is a need for frameworks that provide a lens for understanding learning experiences afforded in digital games and facilitating knowledge construction and motivation to…

  20. Framework for the Development of OER-Based Learning Materials in ODL Environment (United States)

    Teng, Khor Ean; Hung, Chung Sheng


    This paper describes the framework for the development of OER-based learning materials "TCC121/05 Programming Fundamentals with Java" for ODL learners in Wawasan Open University (WOU) using three main development phases mainly: creation, evaluation and production phases. The proposed framework has further been tested on ODL learners to…

  1. A Conceptual Framework for Error Remediation with Multiple External Representations Applied to Learning Objects (United States)

    Leite, Maici Duarte; Marczal, Diego; Pimentel, Andrey Ricardo; Direne, Alexandre Ibrahim


    This paper presents the application of some concepts of Intelligent Tutoring Systems (ITS) to elaborate a conceptual framework that uses the remediation of errors with Multiple External Representations (MERs) in Learning Objects (LO). To this is demonstrated a development of LO for teaching the Pythagorean Theorem through this framework. This…

  2. Evaluation Framework EFI for Measuring the Impact of Learning, Education and Training

    NARCIS (Netherlands)

    Stracke, Christian M.


    This article introduces the Evaluation Framework EFI for the Impact Measurement of learning, education and training: The Evaluation Framework for Impact Measurement was developed for specifying the evaluation phase and its objectives and tasks within the IDEAL Reference Model for the introduction

  3. Learning in Physics by Doing Laboratory Work: Towards a New Conceptual Framework (United States)

    Danielsson, Anna Teresia; Linder, Cedric


    Drawing on a study that explores university students' experiences of doing laboratory work in physics, this article outlines a proposed conceptual framework for extending the exploration of the gendered experience of learning. In this framework situated cognition and post-structural gender theory are merged together. By drawing on data that aim at…

  4. Factors Influencing the Use of Learning Management System in Saudi Arabian Higher Education: A Theoretical Framework (United States)

    Asiri, Mohammed J. Sherbib; Mahmud, Rosnaini bt; Bakar, Kamariah Abu; Ayub, Ahmad Fauzi bin Mohd


    The purpose of this paper is to present the theoretical framework underlying a research on factors that influence utilization of the Jusur Learning Management System (Jusur LMS) in Saudi Arabian public universities. Development of the theoretical framework was done based on library research approach. Initially, the existing literature relevant to…

  5. An Experience-Based Learning Framework: Activities for the Initial Development of Sustainability Competencies (United States)

    Caniglia, Guido; John, Beatrice; Kohler, Martin; Bellina, Leonie; Wiek, Arnim; Rojas, Christopher; Laubichler, Manfred D.; Lang, Daniel


    Purpose: This paper aims to present an experience-based learning framework that provides a bottom-up, student-centered entrance point for the development of systems thinking, normative and collaborative competencies in sustainability. Design/methodology/approach: The framework combines mental mapping with exploratory walking. It interweaves…

  6. The extraction and integration framework: a two-process account of statistical learning. (United States)

    Thiessen, Erik D; Kronstein, Alexandra T; Hufnagle, Daniel G


    The term statistical learning in infancy research originally referred to sensitivity to transitional probabilities. Subsequent research has demonstrated that statistical learning contributes to infant development in a wide array of domains. The range of statistical learning phenomena necessitates a broader view of the processes underlying statistical learning. Learners are sensitive to a much wider range of statistical information than the conditional relations indexed by transitional probabilities, including distributional and cue-based statistics. We propose a novel framework that unifies learning about all of these kinds of statistical structure. From our perspective, learning about conditional relations outputs discrete representations (such as words). Integration across these discrete representations yields sensitivity to cues and distributional information. To achieve sensitivity to all of these kinds of statistical structure, our framework combines processes that extract segments of the input with processes that compare across these extracted items. In this framework, the items extracted from the input serve as exemplars in long-term memory. The similarity structure of those exemplars in long-term memory leads to the discovery of cues and categorical structure, which guides subsequent extraction. The extraction and integration framework provides a way to explain sensitivity to both conditional statistical structure (such as transitional probabilities) and distributional statistical structure (such as item frequency and variability), and also a framework for thinking about how these different aspects of statistical learning influence each other. 2013 APA, all rights reserved

  7. Adjusted Framework of M-Learning in Blended Learning System for Mathematics Study Field of Junior High School Level VII (United States)

    Sugiyanta, Lipur; Sukardjo, Moch.


    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

  8. Towards a Learning Society: A Framework for Research. (United States)

    Schuller, Tom


    This research framework has three levels: (1) societal (individual, household/family, work organization, regional/national/international); (2) disciplinary approach (social anthropology, sociology, industrial relations, economics, politics); and (3) time (historical/diachronic, life course, routines). (SK)

  9. A Framework for Sustainable Mobile Learning in Schools (United States)

    Ng, Wan; Nicholas, Howard


    While there are studies that have looked at the implementation of mobile learning in educational institutions, particularly the identification of issues encountered, few studies have explored holistically the elements that sustain mobile learning. This study dissects the findings of a longitudinal study of a secondary school adopting a personal…

  10. An Analytical framework of social learning facilitated by participatory methods

    NARCIS (Netherlands)

    Scholz, G.; Dewulf, A.; Pahl-Wostl, C.


    Social learning among different stakeholders is often a goal in problem solving contexts such as environmental management. Participatory methods (e.g., group model-building and role playing games) are frequently assumed to stimulate social learning. Yet understanding if and why this assumption is

  11. Learning with animation as a framework for educational excellence

    DEFF Research Database (Denmark)

    Gjedde, Lisa

    and the refinement of the expression. For some of the learners this type of learning environment, did present potentials for the experience of accomplishment, success and excellence, which they had rarely enjoyed in other types of learning environments. The notion of excellence will be reconsidered in relation...

  12. Comprehensive Framework for Evaluating e-Learning Systems: Using BSC Framework (United States)

    Momeni, Mansor; Jamporazmey, Mona; Mehrafrouz, Mohsen; Bahadori, Fatemeh


    The development of information and communication technology (ICT) is changing the way in which people work, communicate and learn. Recently developing and implementing e-learning solutions have increased dramatically. According to heavily investing in this area, it is essential to evaluate its different aspects and understand measures, which…

  13. Teachers' and Researchers' Beliefs of Learning and the use of Learning Progressions (United States)

    Clapp, Francis Neely

    In the last decade, science education reform in the United States has emphasized the exploration of cognitive learning pathways, which are theories on how a person learns a particular science subject matter. These theories are based, in part, by Piagetian developmental theory. One such model, called Learning Progressions (LP), has become prominent within science education reform. Science education researchers design LPs which in turn are used by science educators to sequence their curricula. The new national science standards released in April 2013 (Next Generation Science Standards) are, in part, grounded in the LP model. Understanding how teachers apply and use LPs, therefore, is valuable because professional development programs are likely to use this model, given the federal attention LP have received in science education reform. I sought to identify the beliefs and discourse that both LP developers and intended LP implementers have around student learning, teaching, and learning progressions. However, studies measuring beliefs or perspectives of LP-focused projects are absent in published works. A qualitative research is therefore warranted to explore this rather uncharted research area. Research questions were examined through the use of an instrumental case study. A case study approach was selected over other methodologies, as the research problem is, in part, bound within a clearly identifiable case (a professional development experience centering on a single LP model). One of the broadest definitions of a case study is noted by Becker (1968), who stated that goals of case studies are "to arrive at a comprehensive understanding of the groups under study" and to develop "general theoretical statements about regularities in social structure and process." (p.233). Based on Merriam (1985) the general consensus in the case study literature is that the assumptions underlying this method are common to naturalistic inquiry with research conducted primarily in the

  14. Architectural Design and the Learning Environment: A Framework for School Design Research (United States)

    Gislason, Neil


    This article develops a theoretical framework for studying how instructional space, teaching and learning are related in practice. It is argued that a school's physical design can contribute to the quality of the learning environment, but several non-architectural factors also determine how well a given facility serves as a setting for teaching…

  15. Implementation of a Framework for Collaborative Social Networks in E-Learning (United States)

    Maglajlic, Seid


    This paper describes the implementation of a framework for the construction and utilization of social networks in ELearning. These social networks aim to enhance collaboration between all E-Learning participants (i.e. both traineeto-trainee and trainee-to-tutor communication are targeted). E-Learning systems that include a so-called "social…

  16. Students' "Uses and Gratification Expectancy" Conceptual Framework in Relation to E-Learning Resources (United States)

    Mondi, Makingu; Woods, Peter; Rafi, Ahmad


    This paper presents the systematic development of a "Uses and Gratification Expectancy" (UGE) conceptual framework which is able to predict students' "Perceived e-Learning Experience." It is argued that students' UGE as regards e-learning resources cannot be implicitly or explicitly explored without first examining underlying communication…

  17. The Social Outcomes of Older Adult Learning in Taiwan: Evaluation Framework and Indicators (United States)

    Lin, Li-Hui


    The purpose of this study is to explore the social outcomes of older adult learning in Taiwan. In light of our society's aging population structure, the task of establishing evaluation framework and indicators for the social outcomes of learning (SOL) as applied to older adults is urgent. In order to construct evaluation indicators for older adult…

  18. A Framework for Research on E-Learning Assimilation in SMEs: A Strategic Perspective (United States)

    Raymond, Louis; Uwizeyemungu, Sylvestre; Bergeron, Francois; Gauvin, Stephane


    Purpose: This study aims to propose an integrative conceptual framework of e-learning adoption and assimilation that is adapted to the specific context of small to medium-sized enterprises (SMEs). Design/methodology/approach: The literature on the state of e-learning usage in SMEs and on the IT adoption and assimilation factors that can be…

  19. Developing a Framework for Social Technologies in Learning via Design-Based Research (United States)

    Parmaxi, Antigoni; Zaphiris, Panayiotis


    This paper reports on the use of design-based research (DBR) for the development of a framework that grounds the use of social technologies in learning. The paper focuses on three studies which step on the learning theory of constructionism. Constructionism assumes that knowledge is better gained when students find this knowledge for themselves…

  20. A Conceptual Framework for the Cultural Integration of Cooperative Learning: A Thai Primary Mathematics Education Perspective (United States)

    Park, Ji Yong; Nuntrakune, Tippawan


    The Thailand education reform adopted cooperative learning to improve the quality of education. However, it has been reported that the introduction and maintenance of cooperative learning has been difficult and uncertain because of the cultural differences. The study proposed a conceptual framework developed based on making a connection between…

  1. Teacher Competencies for the Implementation of Collaborative Learning in the Classroom: A Framework and Research Review (United States)

    Kaendler, Celia; Wiedmann, Michael; Rummel, Nikol; Spada, Hans


    This article describes teacher competencies for implementing collaborative learning in the classroom. Research has shown that the effectiveness of collaborative learning largely depends on the quality of student interaction. We therefore focus on what a "teacher" can do to foster student interaction. First, we present a framework that…

  2. Children Learning to Use Technologies through Play: A Digital Play Framework (United States)

    Bird, Jo; Edwards, Susan


    Digital technologies are increasingly acknowledged as an important aspect of early childhood education. A significant problem for early childhood education has been how to understand the pedagogical use of technologies in a sector that values play-based learning. This paper presents a new framework to understand how children learn to use…

  3. A Framework for Developing Self-Directed Technology Use for Language Learning (United States)

    Lai, Chun


    Critical to maximizing the potential of technology for learning is enhancing language learners' self-directed use of technology for learning purposes. This study aimed to enhance our understanding of the determinants of self-directed technology use through the construction of a structural equation modelling (SEM) framework of factors and…

  4. Intergenerational Learning at a Nature Center: Families Using Prior Experiences and Participation Frameworks to Understand Raptors (United States)

    Zimmerman, Heather Toomey; McClain, Lucy Richardson


    Using a sociocultural framework to approach intergenerational learning, this inquiry examines learning processes used by families during visits to one nature center. Data were collected from videotaped observations of families participating in an environmental education program and a follow-up task to draw the habitat of raptors. Based on a…

  5. A reference model and technical framework for mobile social software for learning

    NARCIS (Netherlands)

    De Jong, Tim; Specht, Marcus; Koper, Rob


    De Jong,T., Specht, M., & Koper, R. (2008). A reference model and technical framework for mobile social software for learning. In I. A. Sánchez & P. Isaías (Eds.), Proceedings of the IADIS Mobile Learning Conference 2008 (pp. 206-210). April, 11-13, 2008, Carvoeiro, Portugal.

  6. The knowledge-learning-instruction framework: bridging the science-practice chasm to enhance robust student learning. (United States)

    Koedinger, Kenneth R; Corbett, Albert T; Perfetti, Charles


    Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. Copyright © 2012 Cognitive Science Society, Inc.

  7. Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning (United States)

    Koh, Jansen


    Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. PMID:27446767

  8. A framework for interactive learning in emerging technologies


    Rens L.J. Vandeberg; Ellen H.M. Moors


    Innovation is an interactive learning process which is of special interest for emerging technologies in which complex complementary knowledge from heterogeneous stakeholders is combined. In the emerging phase of technology development a lot of knowledge is tacit and can only be transferred face-to-face. At the same time a shared vision between stakeholders is being formed that acts as a driver for innovation. Although the importance of interactive learning is widely acknowledged, an adequate ...

  9. A learning progression based teaching module on the causes of seasons

    International Nuclear Information System (INIS)

    Galano, S.


    In this paper, we report about designing and validating a teaching learning module based on a learning progression and focused on the causes of seasons. An initial learning progression about the Celestial Motion big idea —causes of seasons, lunar and solar eclipse and Moon phases— was developed and validated. Existing curricula, research studies on alternative conceptions about these phenomena, and students’ answers to an open questionnaire were the starting point to develop initial learning progressions; then, a two-tier multiple-choice questionnaire was designed to validate and improve it. The questionnaire was submitted to about 300 secondary-school students whose answers were used to revise the hypothesized learning progressions. This improved version of the learning progression was used to design a module focused on the causes of seasons in which students were engaged in quantitative measurements with a photovoltaic panel to explain changes of the Sun rays’ flow on the Earth’s surface over the year. The efficacy of our module in improving students’ understanding of the phenomenon of the seasons was tested using our questionnaire as pre- and post-test.

  10. Continuing professional development for teachers in South Africa and social learning systems: conflicting conceptual frameworks of learning

    Directory of Open Access Journals (Sweden)

    G.M. Steyn


    Full Text Available To transform education in this country, South African teachers need to be appropriately equipped to meet the evolving challenges and needs of the country. The national policy framework for teacher education and development is an attempt to address the need for suitably qualified teachers in South Africa. Its aim is to improve the quality of education by focusing on the professional development of teachers. This article attempts to address the following research problem: Does continuing professional development for teachers (CPDT, as stipulated by the national policy framework, have the potential to contribute to the development of teachers as proposed by social learning systems? The answer to this question has the potential to inform and influence the policy and its implementation. The answer also describes how conceptual frameworks for learning in Wenger’s social learning systems conflict with effective professional development (PD programmes and CPDT.

  11. Progress Check Module; Basic Electricity and Electronics Individualized Learning System. Progress Check Booklet. (United States)

    Bureau of Naval Personnel, Washington, DC.

    The Progress Check Booklet is designed to be used by the student working in the programed course to determine if he has mastered the concepts in the course booklets on: electrical current; voltage; resistance; measuring current and voltage in series circuits; relationships of current, voltage, and resistance; parellel circuits; combination…

  12. Students' Knowledge Progression: Sustainable Learning in Higher Education (United States)

    Rovio-Johansson, Airi


    The purpose of this phenomenographic study is to examine students' knowledge progression in a three-year Bachelor program in Business Administration. Theoretical sampling was used to select nine students from a group of 200 university students admitted to the program. The students were interviewed on three occasions: Year 1, after their Management…

  13. Making Learning Personally Meaningful: A New Framework for Relevance Research (United States)

    Priniski, Stacy J.; Hecht, Cameron A.; Harackiewicz, Judith M.


    Personal relevance goes by many names in the motivation literature, stemming from a number of theoretical frameworks. Currently these lines of research are being conducted in parallel with little synthesis across them, perhaps because there is no unifying definition of the relevance construct within which this research can be situated. In this…

  14. The Midwifery Services Framework: Lessons learned from the initial stages of implementation in six countries. (United States)

    Garg, Shantanu; Moyo, Nester T; Nove, Andrea; Bokosi, Martha


    In 2015, the International Confederation of Midwives (ICM) launched the Midwifery Services Framework (MSF): an evidence-based tool to guide countries through the process of improving their sexual, reproductive, maternal and newborn health services through strengthening and developing the midwifery workforce. The MSF is aligned with key global architecture for sexual, reproductive, maternal and newborn health and human resources for health. This third in a series of three papers describes the experience of starting to implement the MSF in the first six countries that requested ICM support to adopt the tool, and the lessons learned during these early stages of implementation. The early adopting countries selected a variety of priority work areas, but nearly all highlighted the importance of improving the attractiveness of midwifery as a career so as to improve attraction and retention, and several saw the need for improvements to midwifery regulation, pre-service education, availability and/or accessibility of midwives. Key lessons from the early stages of implementation include the need to ensure a broad range of stakeholder involvement from the outset and the need for an in-country lead organisation to maintain the momentum of implementation even when there are changes in political leadership, security concerns or other barriers to progress. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. A framework to develop a clinical learning culture in health facilities: ideas from the literature. (United States)

    Henderson, A; Briggs, J; Schoonbeek, S; Paterson, K


    Internationally, there is an increase in demand to educate nurses within the clinical practice environment. Clinical practice settings that encourage teaching and learning during episodes of care delivery can be powerful in educating both the existing nursing workforce and nursing students. This paper presents a framework, informed by the literature, that identifies the key factors that are needed to encourage the interactions fundamental to learning in clinical practice. Learning occurs when nurses demonstrate good practice, share their knowledge through conversations and discussions, and also provide feedback to learners, such as students and novices. These types of interactions occur when positive leadership practices encourage trust and openness between staff; when the management team provides sessions for staff to learn how to interact with learners, and also when partnerships provide support and guidance around learning in the workplace. APPLICATION OF CONCEPTS: This framework presents how the concepts of leadership, management and partnership interact to create and sustain learning environments. The feedback from proposed measurement tools can provide valuable information about the positive and negative aspects of these concepts in the clinical learning environment. Analysis of the subscales can assist in identifying appropriate recommended strategies outlined in the framework to guide nurses in improving the recognized deficits in the relationship between the concepts. Leadership, management and partnerships are pivotal for the creation and maintenance of positive learning environments. Diagnostic measurement tools can provide specific information about weaknesses across these areas. This knowledge can guide future initiatives. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

  16. D.3.2 PLOT Persuasive Learning Design Framework

    DEFF Research Database (Denmark)

    Gram-Hansen, Sandra Burri; Schärfe, Henrik; Winther-Nielsen, Nicolai


    of the technological learning tools and products which are currently related to the PLOT project, namely the GLOMaker and the 3ET tool, and a selection of GLOs and learning exercises. The primary focus of the analysis is to explore how the theoretical perspectives presented in D.3.1 are represented in these tools...... as an: ‚Internal report for project use containing an empirically-based assessment of existing systems and their potential in terms of learning and persuasion. This will be used as a discussion document by the consortium.‛ To meet the requirements of this deliverable, this documents presents analysis......, in particular the notions of persuasive design and constructive alignment. Whilst the report provides a persuasive design perspective on the technologies related to Euro PLOT, it must be stressed that if the document is to function as a basis for further discussion within the consortium, the partners...

  17. The e-Learning Conceptual Framework Project. Leaflet


    Sangrà Morer, Albert


    Aquest projecte es basa en la hipòtesi que en l'actualitat no existeix un concepte únic d'e-learning -acceptat per la majoria de la comunitat científica o, és més, pels professionals. Per tant, l'objectiu és contribuir a la consolidació i l'especificació del concepte d'e-learning tant des del punt de vista científic com des del punt de vista del camp de l'activitat educativa. This project is based on the hypothesis that currently there is no single concept of e-learning -accepted by the ma...

  18. Beyond Effectiveness: A Pragmatic Evaluation Framework for Learning and Continuous Quality Improvement of e-Learning Interventions in Healthcare. (United States)

    Dafalla, Tarig Dafalla Mohamed; Kushniruk, Andre W; Borycki, Elizabeth M


    A pragmatic evaluation framework for evaluating the usability and usefulness of an e-learning intervention for a patient clinical information scheduling system is presented in this paper. The framework was conceptualized based on two different but related concepts (usability and usefulness) and selection of appropriate and valid methods of data collection and analysis that included: (1) Low-Cost Rapid Usability Engineering (LCRUE), (2) Cognitive Task Analysis (CTA), (3) Heuristic Evaluation (HE) criteria for web-based learning, and (4) Software Usability Measurement Inventory (SUMI). The results of the analysis showed some areas where usability that were related to General Interface Usability (GIU), instructional design and content was problematic; some of which might account for the poorly rated aspects of usability when subjectively measured. This paper shows that using a pragmatic framework can be a useful way, not only for measuring the usability and usefulness, but also for providing a practical objective evidences for learning and continuous quality improvement of e-learning systems. The findings should be of interest to educators, developers, designers, researchers, and usability practitioners involved in the development of e-learning systems in healthcare. This framework could be an appropriate method for assessing the usability, usefulness and safety of health information systems both in the laboratory and in the clinical context.

  19. Work in Progress : Learner-Centered Online Learning Facility

    NARCIS (Netherlands)

    Pantic, M.; Zwitserloot, R.; De Weerdt, M.M.


    This paper describes a novel, learner-centered technology for authoring web lectures. Besides seamless integration of video and audio feeds, Microsoft PowerPoint slides, and web-pages, the proposed Online Learning Facility (OLF) also facilitates online interactive testing and review of covered

  20. Teaching and Learning: Using Digital Tools for Progressive Assessment

    DEFF Research Database (Denmark)

    Kastbjerg, Rita B.; Petersson, Eva; Lewis Brooks, Anthony


      Non-biased assessment becomes a reality when Information and Communication Technology (ICT) is implemented as a pedagogical tool to augment teacher practice and student learning. This paper details a study that was undertaken at a secondary school in Lithuania involving four educators and 200...... in education to address future augmented teacher - students' liaisons....

  1. SDL: Saliency-Based Dictionary Learning Framework for Image Similarity. (United States)

    Sarkar, Rituparna; Acton, Scott T


    In image classification, obtaining adequate data to learn a robust classifier has often proven to be difficult in several scenarios. Classification of histological tissue images for health care analysis is a notable application in this context due to the necessity of surgery, biopsy or autopsy. To adequately exploit limited training data in classification, we propose a saliency guided dictionary learning method and subsequently an image similarity technique for histo-pathological image classification. Salient object detection from images aids in the identification of discriminative image features. We leverage the saliency values for the local image regions to learn a dictionary and respective sparse codes for an image, such that the more salient features are reconstructed with smaller error. The dictionary learned from an image gives a compact representation of the image itself and is capable of representing images with similar content, with comparable sparse codes. We employ this idea to design a similarity measure between a pair of images, where local image features of one image, are encoded with the dictionary learned from the other and vice versa. To effectively utilize the learned dictionary, we take into account the contribution of each dictionary atom in the sparse codes to generate a global image representation for image comparison. The efficacy of the proposed method was evaluated using three tissue data sets that consist of mammalian kidney, lung and spleen tissue, breast cancer, and colon cancer tissue images. From the experiments, we observe that our methods outperform the state of the art with an increase of 14.2% in the average classification accuracy over all data sets.

  2. Development and validation of a learning progression for change of seasons, solar and lunar eclipses, and moon phases (United States)

    Testa, Italo; Galano, Silvia; Leccia, Silvio; Puddu, Emanuella


    In this paper, we report about the development and validation of a learning progression about the Celestial Motion big idea. Existing curricula, research studies on alternative conceptions about these phenomena, and students' answers to an open questionnaire were the starting point to develop initial learning progressions about change of seasons, solar and lunar eclipses, and Moon phases; then, a two-tier multiple choice questionnaire was designed to validate and improve them. The questionnaire was submitted to about 300 secondary students of different school levels (14 to 18 years old). Item response analysis and curve integral method were used to revise the hypothesized learning progressions. Findings support that spatial reasoning is a key cognitive factor for building an explanatory framework for the Celestial Motion big idea, but also suggest that causal reasoning based on physics mechanisms underlying the phenomena, as light flux laws or energy transfers, may significantly impact a students' understanding. As an implication of the study, we propose that the teaching of the three discussed astronomy phenomena should follow a single teaching-learning path along the following sequence: (i) emphasize from the beginning the geometrical aspects of the Sun-Moon-Earth system motion; (ii) clarify consequences of the motion of the Sun-Moon-Earth system, as the changing solar radiation flow on the surface of Earth during the revolution around the Sun; (iii) help students moving between different reference systems (Earth and space observer's perspective) to understand how Earth's rotation and revolution can change the appearance of the Sun and Moon. Instructional and methodological implications are also briefly discussed.

  3. An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing. (United States)

    Wu, Zujian; Pang, Wei; Coghill, George M


    Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

  4. The POL Model: Using a Social Constructivist Framework to Develop Blended and Online Learning

    DEFF Research Database (Denmark)

    Dalsgaard, Christian; Godsk, Mikkel


    The paper presents a model for developing blended and online learning based on a given curriculum and typical learning objectives for university courses. The model consists of a three-step-process in which the instructor formulates product-oriented tasks, develops and structures the learning...... materials and tools, outlines a schedule, and supports the students' learning activity in developing a product. The model is based on our experiences with transforming traditional lecture-based lessons into problem-based blended and online learning using a social constructivist approach and a standard...... virtual learning environment (VLE). Our initial experiments indicate that our model is useful to develop blended and online modules and, furthermore, it seems fruitful to use a social constructivist framework and orienting learning activities towards the development of products....

  5. Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts (United States)

    Hamid, R.; Pabunga, D. B.


    The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.

  6. Meta-learning framework applied in bioinformatics inference system design. (United States)

    Arredondo, Tomás; Ormazábal, Wladimir


    This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.

  7. Learner Analysis Framework for Globalized E-Learning (United States)

    Saxena, Mamta


    The digital shift to technology-mediated modes of instructional delivery and the increased global connectivity has led to the rise in globalized e-learning programs. Educational institutions face multiple challenges as they seek to design effective, engaging and culturally competent instruction for an increasingly diverse learner population. The…

  8. 360 Degree Feedback: An Integrative Framework for Learning and Assessment (United States)

    Tee, Ding Ding; Ahmed, Pervaiz K.


    Feedback is widely acknowledged as the crux of a learning process. Multiplicities of research studies have been advanced to address the common "cri de coeur" of teachers and students for a constructive and effective feedback mechanism in the current higher educational settings. Nevertheless, existing pedagogical approaches in feedback…

  9. University and Flipped Learning TIC & DIL Project: Framework and Design (United States)

    Pinnelli, Stefania; Fiorucci, Andrea


    The flipped classroom approach (FC) is for the educational world a chance of recovery and improvement of pedagogical student-centered model and collaborative teaching methods aimed at optimizing the time resource and to promote personalization and self-learning in a perspective of autonomy. The paper moving from a pedagogical reflection on…

  10. A Human Capabilities Framework for Evaluating Student Learning (United States)

    Walker, Melanie


    This paper proposes a human capabilities approach for evaluating student learning and the social and pedagogical arrangements that support equality in capabilities for all students. It outlines the focus on valuable beings and doings in the capability approach developed by Amartya Sen, and Martha Nussbaum's capabilities focus on human flourishing.…

  11. Digital game elements, user experience and learning : A conceptual framework

    NARCIS (Netherlands)

    A. Alexiou (Andreas); M.C. Schippers (Michaéla)


    textabstractThe primary aim of this paper is to identify and theoretically validate the relationships between core game design elements and mechanics, user motivation and engagement and consequently learning. Additionally, it tries to highlight the moderating role of player personality traits on

  12. Social Capital Framework in the Adoption of E-Learning (United States)

    Barton, Siew Mee


    This is a study of the influence of social and cultural factors on the adoption of e-learning in higher education in Malaysia, Indonesia, Turkey, Singapore and Australia. Particular attention in each case was given to factors relating to social capital, attitudes and patterns of behavior in leadership, entrepreneurialism, and teaching and to…

  13. An Instructional Strategy Framework for Online Learning Environments. (United States)

    Johnson, Scott D.; Aragon, Steven R.

    The rapid growth of Web-based instruction has raised many questions about the quality of online courses. It appears that many online courses are simply modeled after traditional forms of instruction instead of incorporating a design that takes advantage of the unique capabilities of Web-based learning environments. This paper describes a research…

  14. Interactive Digital Textbooks and Engagement: A Learning Strategies Framework (United States)

    Bikowski, Dawn; Casal, J. Elliott


    This mixed-methods study explored non-native English speaking students' learning processes and engagement as they used a customized interactive digital textbook housed on a mobile device. Think aloud protocols, surveys of anticipated and actual engagement with the digital textbook, reflective journals, and member checking constituted data…

  15. A Fuzzy Logic Framework for Integrating Multiple Learned Models

    Energy Technology Data Exchange (ETDEWEB)

    Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)


    The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

  16. Professional Learning Design Framework: Supporting Technology Integration in Alberta (United States)

    van Thiel, Lydia


    Researchers around the world are interested in knowing how to support teachers in developing both their technology skills and their understanding of how educational technologies can provide opportunity to engage all learners at their skill and interest level in learning activities that were not possible without technology. The solution involves…

  17. D.3.1 PLOT Persuasive Learning Design Framework

    DEFF Research Database (Denmark)

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


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

  18. A theoretical framework for measuring the quality of student learning ...

    African Journals Online (AJOL)

    The most important principles of outcomes-based education is that planning, teaching and assessment should focus on helping learners to achieve significant outcomes to high standards. This cannot be achieved without having suitable ways to describe desired learning outcomes and the quality of students' ...

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

    Directory of Open Access Journals (Sweden)

    Mirjana Rittmeyer


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

  20. Selectivity in associative learning: A cognitive stage framework for blocking and cue competition phenomena

    Directory of Open Access Journals (Sweden)

    Yannick eBoddez


    Full Text Available Blocking is the most important phenomenon in the history of associative learning theory: For over 40 years, blocking has inspired a whole generation of learning models. Blocking is part of a family of effects that are typically termed cue competition effects. Common amongst all cue competition effects is that a cue-outcome relation is poorly learned or poorly expressed because the cue is trained in the presence of an alternative predictor or cause of the outcome. We provide an overview of the cognitive processes involved in cue competition effects in humans and propose a stage framework that brings these processes together. The framework contends that the behavioral display of cue competition is cognitively construed following three stages that include (1 an encoding stage, (2 a retention stage, and (3 a performance stage. We argue that the stage framework supports a comprehensive understanding of cue competition effects.

  1. A Framework for Collaborative Networked Learning in Higher Education: Design & Analysis

    Directory of Open Access Journals (Sweden)

    Ghassan F. Issa


    Full Text Available This paper presents a comprehensive framework for building collaborative learning networks within higher educational institutions. This framework focuses on systems design and implementation issues in addition to a complete set of evaluation, and analysis tools. The objective of this project is to improve the standards of higher education in Jordan through the implementation of transparent, collaborative, innovative, and modern quality educational programs. The framework highlights the major steps required to plan, design, and implement collaborative learning systems. Several issues are discussed such as unification of courses and program of studies, using appropriate learning management system, software design development using Agile methodology, infrastructure design, access issues, proprietary data storage, and social network analysis (SNA techniques.

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

    Directory of Open Access Journals (Sweden)

    Marija Cubric


    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.

  3. Investigation into Mobile Learning Framework in Cloud Computing Platform


    Wei, Guo; Joan, Lu


    Abstract—Cloud computing infrastructure is increasingly\\ud used for distributed applications. Mobile learning\\ud applications deployed in the cloud are a new research\\ud direction. The applications require specific development\\ud approaches for effective and reliable communication. This\\ud paper proposes an interdisciplinary approach for design and\\ud development of mobile applications in the cloud. The\\ud approach includes front service toolkit and backend service\\ud toolkit. The front servi...

  4. A deep learning framework for causal shape transformation. (United States)

    Lore, Kin Gwn; Stoecklein, Daniel; Davies, Michael; Ganapathysubramanian, Baskar; Sarkar, Soumik


    Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the dependencies typically lie in the latent domain which may not be suitable for applications involving the prediction of a step-wise transformation sequence that is dependent on the previous states only in the visible domain with a known terminal state. We propose a hybrid architecture of convolution neural networks (CNN) and stacked autoencoders (SAE) to learn a sequence of causal actions that nonlinearly transform an input visual pattern or distribution into a target visual pattern or distribution with the same support and demonstrated its practicality in a real-world engineering problem involving the physics of fluids. We solved a high-dimensional one-to-many inverse mapping problem concerning microfluidic flow sculpting, where the use of deep learning methods as an inverse map is very seldom explored. This work serves as a fruitful use-case to applied scientists and engineers in how deep learning can be beneficial as a solution for high-dimensional physical problems, and potentially opening doors to impactful advance in fields such as material sciences and medical biology where multistep topological transformations is a key element. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Towards a Framework for Learning in the OSMA Serious Game Engine

    Directory of Open Access Journals (Sweden)

    Tanguy Coenen


    Full Text Available Online multiplayer serious games offer a way to support learning in a gaming paradigm that is familiar to many players and has proven its effectiveness in providing sustainably enjoyable gameplay. We aim to decrease development cost for these games by providing a modular game design framework and a component-based technical architecture. The technical architecture and the game design framework will be implemented and iteratively refined through two proofs of concept.

  6. Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework


    Varun Mithal; Guruprasad Nayak; Ankush Khandelwal; Vipin Kumar; Ramakrishna Nemani; Nikunj C. Oza


    This paper presents an application of a novel machine-learning framework on MODIS (moderate-resolution imaging spectroradiometer) data to map burned areas over tropical forests of South America and South-east Asia. The RAPT (RAre Class Prediction in the absence of True labels) framework is able to build data adaptive classification models using noisy training labels. It is particularly suitable when expert annotated training samples are difficult to obtain as in the case of wild fires in the ...


    Directory of Open Access Journals (Sweden)

    Vladimir Tatochenko


    Full Text Available The article is devoted to theoretical substantiation of modern methodical system of Mathematics teaching of poor progressing secondary school pupils. A systematic approach to the study of psycho-pedagogical determinants of poor progress of pupils in math was implemented. The dynamic of interfunctional relationship of structure of educational and informative sphere of poor progressing pupils in mathematics was disclosed and scientific understanding of this process was expanded. The introduction in the educational process of didactic methodical and psychologically balanced methodical control system and correction of poor progressing students’ in Maths improves quality indicators of their permanent knowledge and skills. It allows you to discover the fullness, depth and durability of learning at different stages and levels of education, it contributes to correction, management and partly self-management learning process of poor progressing students in Mathematics, excites them to an active mental activity promotes the development of a conscious attitude to their systematic academic work. The essence of “poor progress” phenomena is observed as well as “educational retardation” of school students during teaching mathematics. Target orientation, the resource potential of the real educational process of poor progressing pupils in Mathematics are determined. Contradictions are singled out and pedagogical conditions of results control of learning outcomes of comprehensive school pupils are proved. An attempt to consider the academic failure of schoolchildren in Mathematics in connection with the main categories of didactics – the content and the learning process was made. Certain shortcomings of teaching and learning activities of students in the study of Mathematics are highlighted as poor progressing elements and gaps. The process and content, enriched with the use of NIT, ensuring the formation of key competencies of lagging behind and

  8. A Framework for Re-thinking Learning in Science from Recent Cognitive Science Perspectives (United States)

    Tytler, Russell; Prain, Vaughan


    Recent accounts by cognitive scientists of factors affecting cognition imply the need to reconsider current dominant conceptual theories about science learning. These new accounts emphasize the role of context, embodied practices, and narrative-based representation rather than learners' cognitive constructs. In this paper we analyse data from a longitudinal study of primary school children's learning to outline a framework based on these contemporary accounts and to delineate key points of difference from conceptual change perspectives. The findings suggest this framework provides strong theoretical and practical insights into how children learn and the key role of representational negotiation in this learning. We argue that the nature and process of conceptual change can be re-interpreted in terms of the development of students' representational resources.

  9. Dynamically analyzing cell interactions in biological environments using multiagent social learning framework. (United States)

    Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong


    Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

  10. Tunneling on the Yucca Mountain Project: Progress and lessons learned

    International Nuclear Information System (INIS)

    Hansmire, W.H.; Rogers, D.J.; Wightman, W.D.


    The Yucca Mountain Site Characterization Project is the US's effort to confirm the technical acceptability of Yucca Mountain as a repository for high-level nuclear waste. A key part of the site characterization project is the construction of a 7.8-km-long, 7.6-m-diameter tunnel for in-depth geologic and other scientific investigations. The work is governed in varying degrees by the special requirements for nuclear quality assurance, which imposes uncommon and often stringent limitations on the materials which can be used in construction, the tunneling methods and procedures used, and record-keeping for many activities. This paper presents the current status of what has been learned, how construction has adapted to meet the requirements, and how the requirements were interpreted in a mitigating way to meet the legal obligations, yet build the tunnel as rapidly as possible. With regard to design methodologies and the realities of tunnel construction, ground support with a shielded Tunnel Boring Machine is discussed. Notable lessons learned include the need for broad design analyses for a wide variety of conditions and how construction procedures affect ground support

  11. An Instructional Design Framework to Improve Student Learning in a First-Year Engineering Class

    Directory of Open Access Journals (Sweden)

    Kumar Yelamarthi


    Full Text Available Increasingly, numerous universities have identified benefits of flipped learning environments and have been encouraging instructors to adapt such methodologies in their respective classrooms, at a time when departments are facing significant budget constraints. This article proposes an instructional design framework utilized to strategically enhance traditional flipped methodologies in a first-year engineering course, by using low-cost technology aids and proven pedagogical techniques to enhance student learning. Implemented in a first-year engineering course, this modified flipped model demonstrated an improved student awareness of essential engineering concepts and improved academic performance through collaborative and active learning activities, including flipped learning methodologies, without the need for expensive, formal active learning spaces. These findings have been validated through two studies and have shown similar results confirming that student learning is improved by the implementation of multi-pedagogical strategies in-formed by the use of an instructional design in a traditional classroom setting.

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


    Torregrosa García, Blas


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

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


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


    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...

  14. Mature women and the New Zealand qualifications framework. realising the potential of recognising prior learning


    Kamp, Annelies


    Against a backtground of 'second-wave' lifelong learning in Aotearoa New Zealand a new framework for post-compulsory national qualfications was introduced. The restulting competency-based system was argued to present a number of benefits for mature women including flexibility in curriculum and delivery and portability across educational sectors. Competency-based education was to include provision for recognition of prior skills and knowledge gained in formal learning environments and the work...

  15. An Evaluation Quality Framework for Analysing School-Based Learning (SBL) to Work-Based Learning (WBL) Transition Module

    International Nuclear Information System (INIS)

    Alseddiqi, M; Mishra, R; Pislaru, C


    The paper presents the results from a quality framework to measure the effectiveness of a new engineering course entitled 'school-based learning (SBL) to work-based learning (WBL) transition module' in the Technical and Vocational Education (TVE) system in Bahrain. The framework is an extended version of existing information quality frameworks with respect to pedagogical and technological contexts. It incorporates specific pedagogical and technological dimensions as per the Bahrain modern industry requirements. Users' views questionnaire on the effectiveness of the new transition module was distributed to various stakeholders including TVE teachers and students. The aim was to receive critical information in diagnosing, monitoring and evaluating different views and perceptions about the effectiveness of the new module. The analysis categorised the quality dimensions by their relative importance. This was carried out using the principal component analysis available in SPSS. The analysis clearly identified the most important quality dimensions integrated in the new module for SBL-to-WBL transition. It was also apparent that the new module contains workplace proficiencies, prepares TVE students for work placement, provides effective teaching and learning methodologies, integrates innovative technology in the process of learning, meets modern industrial needs, and presents a cooperative learning environment for TVE students. From the principal component analysis finding, to calculate the percentage of relative importance of each factor and its quality dimensions, was significant. The percentage comparison would justify the most important factor as well as the most important quality dimensions. Also, the new, re-arranged quality dimensions from the finding with an extended number of factors tended to improve the extended version of the quality information framework to a revised quality framework.

  16. A pedagogical design pattern framework for sharing experiences and enhancing communities of practice within online and blended learning

    DEFF Research Database (Denmark)

    May, Michael; Neutszky-Wulff, Chresteria; Rosthøj, Susanne


    for teachers at the University of Copenhagen a new and simpler pedagogical design pattern framework was developed for interfaculty sharing of experiences and enhancing communities of practice in relation to online and blended learning across the university. The framework of pedagogical design patterns were...... applied to describe the learning design in four online and blended learning courses within different academic disciplines: Classical Greek, Biostatistics, Environmental Management in Europe, and Climate Change Impacts, Adaptation and Mitigation. Future perspectives for using the framework for developing...... new E-learning patterns for online and blended learning courses are discussed....

  17. Common Mobile Learning Characteristics--An Analysis of Mobile Learning Models and Frameworks (United States)

    Imtinan, Umera; Chang, Vanessa; Issa, Tomayess


    Mobile learning offers learning opportunities to learners without the limitations of time and space. Mobile learning has introduced a number of flexible options to the learners across disciplines and at different educational levels. However, designing mobile learning content is an equally challenging task for the instructional designers.…

  18. Implementing Peer Learning in Clinical Education: A Framework to Address Challenges In the "Real World". (United States)

    Tai, Joanna Hong Meng; Canny, Benedict J; Haines, Terry P; Molloy, Elizabeth K


    Phenomenon: Peer learning has many benefits and can assist students in gaining the educational skills required in future years when they become teachers themselves. Peer learning may be particularly useful in clinical learning environments, where students report feeling marginalized, overwhelmed, and unsupported. Educational interventions often fail in the workplace environment, as they are often conceived in the "ideal" rather than the complex, messy real world. This work sought to explore barriers and facilitators to implementing peer learning activities in a clinical curriculum. Previous peer learning research results and a matrix of empirically derived peer learning activities were presented to local clinical education experts to generate discussion around the realities of implementing such activities. Potential barriers and limitations of and strategies for implementing peer learning in clinical education were the focus of the individual interviews. Thematic analysis of the data identified three key considerations for real-world implementation of peer learning: culture, epistemic authority, and the primacy of patient-centered care. Strategies for peer learning implementation were also developed from themes within the data, focusing on developing a culture of safety in which peer learning could be undertaken, engaging both educators and students, and establishing expectations for the use of peer learning. Insights: This study identified considerations and strategies for the implementation of peer learning activities, which took into account both educator and student roles. Reported challenges were reflective of those identified within the literature. The resultant framework may aid others in anticipating implementation challenges. Further work is required to test the framework's application in other contexts and its effect on learner outcomes.

  19. SAFE: A Sentiment Analysis Framework for E-Learning

    Directory of Open Access Journals (Sweden)

    Francesco Colace


    Full Text Available The spread of social networks allows sharing opinions on different aspects of life and daily millions of messages appear on the web. This textual information can be a rich source of data for opinion mining and sentiment analysis: the computational study of opinions, sentiments and emotions expressed in a text. Its main aim is the identification of the agreement or disagreement statements that deal with positive or negative feelings in comments or reviews. In this paper, we investigate the adoption, in the field of the e-learning, of a probabilistic approach based on the Latent Dirichlet Allocation (LDA as Sentiment grabber. By this approach, for a set of documents belonging to a same knowledge domain, a graph, the Mixed Graph of Terms, can be automatically extracted. The paper shows how this graph contains a set of weighted word pairs, which are discriminative for sentiment classification. In this way, the system can detect the feeling of students on some topics and teacher can better tune his/her teaching approach. In fact, the proposed method has been tested on datasets coming from e-learning platforms. A preliminary experimental campaign shows how the proposed approach is effective and satisfactory.

  20. Framework for e-learning assessment in dental education: a global model for the future. (United States)

    Arevalo, Carolina R; Bayne, Stephen C; Beeley, Josie A; Brayshaw, Christine J; Cox, Margaret J; Donaldson, Nora H; Elson, Bruce S; Grayden, Sharon K; Hatzipanagos, Stylianos; Johnson, Lynn A; Reynolds, Patricia A; Schönwetter, Dieter J


    The framework presented in this article demonstrates strategies for a global approach to e-curricula in dental education by considering a collection of outcome assessment tools. By combining the outcomes for overall assessment, a global model for a pilot project that applies e-assessment tools to virtual learning environments (VLE), including haptics, is presented. Assessment strategies from two projects, HapTEL (Haptics in Technology Enhanced Learning) and UDENTE (Universal Dental E-learning), act as case-user studies that have helped develop the proposed global framework. They incorporate additional assessment tools and include evaluations from questionnaires and stakeholders' focus groups. These measure each of the factors affecting the classical teaching/learning theory framework as defined by Entwistle in a standardized manner. A mathematical combinatorial approach is proposed to join these results together as a global assessment. With the use of haptic-based simulation learning, exercises for tooth preparation assessing enamel and dentine were compared to plastic teeth in manikins. Equivalence for student performance for haptic versus traditional preparation methods was established, thus establishing the validity of the haptic solution for performing these exercises. Further data collected from HapTEL are still being analyzed, and pilots are being conducted to validate the proposed test measures. Initial results have been encouraging, but clearly the need persists to develop additional e-assessment methods for new learning domains.

  1. Evidence-based Frameworks for Teaching and Learning in Classical Singing Training: A Systematic Review. (United States)

    Crocco, Laura; Madill, Catherine J; McCabe, Patricia


    The study systematically reviews evidence-based frameworks for teaching and learning of classical singing training. This is a systematic review. A systematic literature search of 15 electronic databases following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines was conducted. Eligibility criteria included type of publication, participant characteristics, intervention, and report of outcomes. Quality rating scales were applied to support assessment of the included literature. Data analysis was conducted using meta-aggregation. Nine papers met the inclusion criteria. No complete evidence-based teaching and learning framework was found. Thematic content analysis showed that studies either (1) identified teaching practices in one-to-one lessons, (2) identified student learning strategies in one-to-one lessons or personal practice sessions, and (3) implemented a tool to enhance one specific area of teaching and learning in lessons. The included studies showed that research in music education is not always specific to musical genre or instrumental group, with four of the nine studies including participant teachers and students of classical voice training only. The overall methodological quality ratings were low. Research in classical singing training has not yet developed an evidence-based framework for classical singing training. This review has found that introductory information on teaching and learning practices has been provided, and tools have been suggested for use in the evaluation of the teaching-learning process. High-quality methodological research designs are needed. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  2. How Multi-Levels of Individual and Team Learning Interact in a Public Healthcare Organisation: A Conceptual Framework (United States)

    Doyle, Louise; Kelliher, Felicity; Harrington, Denis


    The aim of this paper is to review the relevant literature on organisational learning and offer a preliminary conceptual framework as a basis to explore how the multi-levels of individual learning and team learning interact in a public healthcare organisation. The organisational learning literature highlights a need for further understanding of…

  3. Learners- Perceptions of Mobile Devices for Learning in Higher Education - Towards a Mobile Learning Pedagogical Framework


    Conradie; P.W.; Lombard; A.; Moller; M.


    The dramatic effect of information technology on society is undeniable. In education, it is evident in the use of terms like active learning, blended learning, electronic learning and mobile learning (ubiquitous learning). This study explores the perceptions of 54 learners in a higher education institution regarding the use of mobile devices in a third year module. Using semi-structured interviews, it was found that mobile devices had a positive impact on learner motivati...

  4. Applying Item Response Theory methods to design a learning progression-based science assessment (United States)

    Chen, Jing

    Learning progressions are used to describe how students' understanding of a topic progresses over time and to classify the progress of students into steps or levels. This study applies Item Response Theory (IRT) based methods to investigate how to design learning progression-based science assessments. The research questions of this study are: (1) how to use items in different formats to classify students into levels on the learning progression, (2) how to design a test to give good information about students' progress through the learning progression of a particular construct and (3) what characteristics of test items support their use for assessing students' levels. Data used for this study were collected from 1500 elementary and secondary school students during 2009--2010. The written assessment was developed in several formats such as the Constructed Response (CR) items, Ordered Multiple Choice (OMC) and Multiple True or False (MTF) items. The followings are the main findings from this study. The OMC, MTF and CR items might measure different components of the construct. A single construct explained most of the variance in students' performances. However, additional dimensions in terms of item format can explain certain amount of the variance in student performance. So additional dimensions need to be considered when we want to capture the differences in students' performances on different types of items targeting the understanding of the same underlying progression. Items in each item format need to be improved in certain ways to classify students more accurately into the learning progression levels. This study establishes some general steps that can be followed to design other learning progression-based tests as well. For example, first, the boundaries between levels on the IRT scale can be defined by using the means of the item thresholds across a set of good items. Second, items in multiple formats can be selected to achieve the information criterion at all

  5. Conceptual Framework: Development of Interactive Reading Malay Language Learning System (I-ReaMaLLS

    Directory of Open Access Journals (Sweden)

    Ismail Nurulisma


    Full Text Available Reading is very important to access knowledge. Reading skills starts during preschool level no matter of the types of languages. At present, there are many preschool children who are still unable to recognize letters or even words. This leads to the difficulties in reading. Therefore, there is a need of intervention in reading to overcome such problems. Thus, technologies were adapted in enhancing learning skills, especially in learning to read among the preschool children. Phonological is one of the factors to be considered to ensure a smooth of transition into reading. Phonological concept enables the first learner to easily learn reading such to learn reading Malay language. The medium of learning to read Malay language can be assisted via the supportive of multimedia technology to enhance the preschool children learning. Thus, an interactive system is proposed via a development of interactive reading Malay language learning system, which is called as I-ReaMaLLS. As a part of the development of I-ReaMaLLS, this paper focus on the development of conceptual framework in developing interactive reading Malay language learning system (I-ReaMaLLS. I-ReaMaLLS is voice based system that facilitates the preschool learner in learning reading Malay language. The conceptual framework of developing I-ReaMaLLS is conceptualized based on the initial study conducted via methods of literature review and observation with the preschool children, aged 5 – 6 years. As the result of the initial study, research objectives have been affirmed that finally contributes to the design of conceptual framework for the development of I-ReaMaLLS.

  6. Learning health equity frameworks within a community of scholars. (United States)

    Alexander, Kamila A; Dovydaitis, Tiffany; Beacham, Barbara; Bohinski, Julia M; Brawner, Bridgette M; Clements, Carla P; Everett, Janine S; Gomes, Melissa M; Harner, Holly; McDonald, Catherine C; Pinkston, Esther; Sommers, Marilyn S


    Scholars in nursing science have long espoused the concept of health equity without specifically using the term or dialoguing about the social determinants of health and social justice. This article describes the development, implementation, and evaluation of a doctoral and postdoctoral seminar collective entitled "Health Equity: Conceptual, Linguistic, Methodological, and Ethical Issues." The course enabled scholars-in-training to consider the construct and its nuances and frame a personal philosophy of health equity. An example of how a group of emerging scholars can engage in the important, but difficult, discourse related to health equity is provided. The collective provided a forum for debate, intellectual growth, and increased insight for students and faculty. The lessons learned by all participants have the potential to enrich doctoral and postdoctoral scientific training in nursing science and may serve as a model for other research training programs in the health sciences. Copyright 2011, SLACK Incorporated.

  7. Emotional learning within the framework of nursing education. (United States)

    Christiansen, Bjørg; Jensen, Karen


    Nursing requires a certain degree of emotional investment as well as the capacity to align one's emotions to the norms and values of the profession. The article is based on a qualitative study among nursing students in Norway. It discusses how peer learning in connection with sessions involving role-play may contribute to developing these qualities in future professionals. As researchers, we acquired access to a particular communication course for the third year nursing students at Oslo University College. The study combines two methodological approaches: observation and focus group interviews. The findings illustrate how students, by commenting on each others' experiences and performance, may be able to help each other to develop a richer repertoire in how to express themselves and to adapt their behavior to the needs of those being cared for.

  8. Progress of Grid technology in Argentina: Lessons learned from EELA

    International Nuclear Information System (INIS)

    Dova, M. T.; Grunfeld, C.; Monticelli, F.; Tripiana, M.; Veiga, A.; Ambrosi, V.; Barbieri, A.; Diaz, J.; Luengo, M.; Macia, M.; Molinari, L.; Veonosa, P.; Zabaljauregui, M.


    The EELA project aimed to create a collaboration network between Europe and Latin American for training in Grid technologies and the deployment of a pilot Grid infrastructure for e-science applications. Grid computing has emerged as an important new field, and its development in Argentina is particularly important for a number of reasons, such as that Argentina has recently joined the ATLAS collaboration at CERN and the increasing interest in future biomedical applications. The potential of GRID technology is well known, however, its adoption is not a trivial task as it requires significant investment in several areas. In this paper, the achievements and progress in Argentina through close collaboration with EELA are presented. Among these are the deployment of a Grid Certification Authority infrastructure that is a crucial component in the activities of the e-Science community in the country; the deployment, integration and validation of a small local EELA node; installation and running of an analysis ATLAS application on the EELA infrastructure. The experience gained in participating in EELA dissemination events also allowed us to actively promote the GRID and training for its use different target audiences in Argentina and in LA. (Author)

  9. A deep learning and novelty detection framework for rapid phenotyping in high-content screening (United States)

    Sommer, Christoph; Hoefler, Rudolf; Samwer, Matthias; Gerlich, Daniel W.


    Supervised machine learning is a powerful and widely used method for analyzing high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence on a priori knowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations with CellCognition Explorer, a generic novelty detection and deep learning framework. Application to several large-scale screening data sets on nuclear and mitotic cell morphologies demonstrates that CellCognition Explorer enables discovery of rare phenotypes without user training, which has broad implications for improved assay development in high-content screening. PMID:28954863

  10. Using apps for learning across the curriculum a literacy-based framework and guide

    CERN Document Server

    Beach, Richard


    How can apps be used to foster learning with literacy across the curriculum? This book offers both a theoretical framework for considering app affordances and practical ways to use apps to build students' disciplinary literacies and to foster a wide range of literacy practices.Using Apps for Learning Across the Curriculumpresents a wide range of different apps and also assesses their value features methods for and apps related to planning instruction and assessing student learning identifies favorite apps whose affordances are most likely to foster certain disciplinary literacies includes reso

  11. Mobile technologies in progress of teaching and learning: teaching mobility?

    Directory of Open Access Journals (Sweden)

    Osmar Hélio Alves Araújo


    Full Text Available The article is a survey of basic education teachers in the municipality of Iguatu/CE and aimed to verify if teachers use mobile technology in the classroom as an educational resource, as well as investigate to what extent the professional qualifications of these professionals drives an authentic, autonomous teaching action before the harvest of mobile technologies. The subjects are teachers who work in elementary school. Methodologically, constitutes in a field research, with retaining the qualitative approach, aiming to enhance the school in contemporary times is addressed by changes brought to the company by the technological revolution, especially the proliferation of mobile technologies, which are driving changes in processes teaching and learning. We used semi structured and reflective interview as a technique for data collection. They have as the theoretical studies of Alarcão (2001, Freire (1987, 1992, 2001, Libâneo (2001, 2002, 2005, 2011, Nóvoa (2009, Tardif (2001 UNESCO (2013, Veen and Vrakking (2009. The results of the research showed that teachers, for the most part, do not use the apparatus of mobile technologies in pedagogical practice, and point to the picture of insufficient professional qualification for a teaching practice in the context of safe and educationally effectively technologies. However, this split ends, so in need of a continuous training process that deepens also in reality and knowledge that teachers have. As regard as pillars the changes that the current social context has experienced, among which we highlight the technological changes that proliferate dramatically.

  12. The verification of DRAGON: progress and lessons learned

    International Nuclear Information System (INIS)

    Marleau, G.


    The general requirements for the verification of the legacy code DRAGON are somewhat different from those used for new codes. For example, the absence of a design manual for DRAGON makes it difficult to confirm that the each part of the code performs as required since these requirements are not explicitly spelled out for most of the DRAGON modules. In fact, this conformance of the code can only be assessed, in most cases, by making sure that the contents of the DRAGON data structures, which correspond to the output generated by a module of the code, contains the adequate information. It is also possible in some cases to use the self-verification options in DRAGON to perform additional verification or to evaluate, using an independent software, the performance of specific functions in the code. Here, we will describe the global verification process that was considered in order to bring DRAGON to an industry standard tool-set (IST) status. We will also discuss some of the lessons we learned in performing this verification and present some of the modification to DRAGON that were implemented as a consequence of this verification. (author)

  13. Robotic Motion Learning Framework to Promote Social Engagement

    Directory of Open Access Journals (Sweden)

    Rachael Burns


    Full Text Available Imitation is a powerful component of communication between people, and it poses an important implication in improving the quality of interaction in the field of human–robot interaction (HRI. This paper discusses a novel framework designed to improve human–robot interaction through robotic imitation of a participant’s gestures. In our experiment, a humanoid robotic agent socializes with and plays games with a participant. For the experimental group, the robot additionally imitates one of the participant’s novel gestures during a play session. We hypothesize that the robot’s use of imitation will increase the participant’s openness towards engaging with the robot. Experimental results from a user study of 12 subjects show that post-imitation, experimental subjects displayed a more positive emotional state, had higher instances of mood contagion towards the robot, and interpreted the robot to have a higher level of autonomy than their control group counterparts did. These results point to an increased participant interest in engagement fueled by personalized imitation during interaction.

  14. Leveraging Competency Framework to Improve Teaching and Learning: A Methodological Approach (United States)

    Shankararaman, Venky; Ducrot, Joelle


    A number of engineering education programs have defined learning outcomes and course-level competencies, and conducted assessments at the program level to determine areas for continuous improvement. However, many of these programs have not implemented a comprehensive competency framework to support the actual delivery and assessment of an…

  15. A conceptual framework to identify spatial implications of new ways of learning in higher education

    NARCIS (Netherlands)

    Geert Dewulf; Theo van der Voordt; Ronald Beckers


    Purpose – The purpose of this paper is to explore the spatial implications of new learning theories and the use of information and communication technologies (ICT) in higher education. Design/methodology/approach – Based on a review of the literature, a theoretical framework has been developed

  16. A conceptual framework to identify spatial implications of new ways of learning in higher education

    NARCIS (Netherlands)

    Beckers, R; van der Voordt, Theo; Dewulf, G


    Purpose - The purpose of this paper is to explore the spatial implications of new learning theories and the use of Information and Communication Technologies (ICT) in higher education.
    Design/methodology/approach - Based on a review of literature, a theoretical framework has been developed that

  17. A conceptual framework to identify spatial implications of new ways of learning in higher education

    NARCIS (Netherlands)

    Beckers, Ronald; van der Voordt, Theo; Dewulf, Geert P.M.R.


    Purpose – The purpose of this paper is to explore the spatial implications of new learning theories and the use of information and communication technologies (ICT) in higher education. Design/methodology/approach – Based on a review of the literature, a theoretical framework has been developed that

  18. Press Play for Learning: A Framework to Guide Serious Computer Game Use in the Classroom (United States)

    Southgate, Erica; Budd, Janene; Smith, Shamus


    Computer gaming is a global phenomenon and there has been rapid growth in "serious" games for learning. An emergent body of evidence demonstrates how serious games can be used in primary and secondary school classrooms. Despite the popularity of serious games and their pedagogical potential, there are few specialised frameworks to guide…

  19. Disciplinary Literacies and Learning to Read for Understanding: A Conceptual Framework for Disciplinary Literacy (United States)

    Goldman, Susan R.; Britt, M. Anne; Brown, Willard; Cribb, Gayle; George, MariAnne; Greenleaf, Cynthia; Lee, Carol D.; Shanahan, Cynthia


    This article presents a framework and methodology for designing learning goals targeted at what students need to know and be able to do in order to attain high levels of literacy and achievement in three disciplinary areas--literature, science, and history. For each discipline, a team of researchers, teachers, and specialists in that discipline…

  20. A framework for understanding outcomes of mutual learning situations in IT projects

    DEFF Research Database (Denmark)

    Hansen, Magnus Rotvit Perlt


    How do we analyse and understand design decisions derived from mutual learning (ML) situations and how may practitioners take advantage of these in IT projects? In the following we present a framework of design decisions inferred from ML situations that occurred between end-users and stakeholders...

  1. Applying the Kirkpatrick Model: Evaluating an "Interaction for Learning Framework" Curriculum Intervention (United States)

    Paull, Megan; Whitsed, Craig; Girardi, Antonia


    Global perspectives and interpersonal and intercultural communication competencies are viewed as a priority within higher education. For management educators, globalisation, student mobility and widening pathways present numerous challenges, but afford opportunities for curriculum innovation. The "Interaction for Learning Framework"…

  2. Interrogating "Belonging" in Belonging, Being and Becoming: The Early Years Learning Framework for Australia (United States)

    Sumsion, Jennifer; Wong, Sandie


    In this article, the authors interrogate the use of "belonging" in "Belonging, Being and Becoming: the Early Years Learning Framework for Australia" (EYLF), Australia's first national curriculum for early childhood education and care settings and, from the authors' interrogation, possibilities are offered for thinking about and…

  3. A basic framework for integrating social and collaborative applications into learning environments

    NARCIS (Netherlands)

    Moghnieh, Ayman; Blat, Josep


    Moghnieh, A., & Blat, J. (2009). A basic framework for integrating social and collaborative applications into learning environments. Proceedings of the first conference on Research, Reflection, and Innovations in Integrating ICT in Education: Vol. 2 (pp. 1057-1061). April, 22-24, 2009, Lisbon,

  4. Promoting Student Learning and Productive Persistence in Developmental Mathematics: Research Frameworks Informing the Carnegie Pathways (United States)

    Edwards, Ann R.; Beattie, Rachel L.


    This paper focuses on two research-based frameworks that inform the design of instruction and promote student success in accelerated, developmental mathematics pathways. These are Learning Opportunities--productive struggle on challenging and relevant tasks, deliberate practice, and explicit connections, and Productive Persistence--promoting…

  5. Conceptual Frameworks in Didactics--Learning and Teaching: Trends, Evolutions and Comparative Challenges (United States)

    Ligozat, Florence; Almqvist, Jonas


    This special issue of the "European Educational Research Journal" presents a series of research papers reflecting the trends and evolutions in conceptual frameworks that took place within the EERA 27 "Didactics--Learning and Teaching" network during its first ten years of existence. Most conceptual tools used in this field were…

  6. An Instructional Design Framework to Improve Student Learning in a First-Year Engineering Class (United States)

    Yelamarthi, Kumar; Drake, Eron; Prewett, Matthew


    Increasingly, numerous universities have identified benefits of flipped learning environments and have been encouraging instructors to adapt such methodologies in their respective classrooms, at a time when departments are facing significant budget constraints. This article proposes an instructional design framework utilized to strategically…

  7. Proverbs as Theoretical Frameworks for Lifelong Learning in Indigenous African Education (United States)

    Avoseh, Mejai B. M.


    Every aspect of a community's life and values in indigenous Africa provide the theoretical framework for education. The holistic worldview of the traditional system places a strong emphasis on the centrality of the human element and orature in the symmetrical relationship between life and learning. This article focuses on proverbs and the words…

  8. A Framework for Evaluating and Enhancing Alignment in Self-Regulated Learning Research (United States)

    Dent, Amy L.; Hoyle, Rick H.


    We discuss the articles of this special issue with reference to an important yet previously only implicit dimension of study quality: alignment across the theoretical and methodological decisions that collectively define an approach to self-regulated learning. Integrating and extending work by leaders in the field, we propose a framework for…

  9. Developing Policy Instruments for Education in the EU: The European Qualifications Framework for Lifelong Learning (United States)

    Elken, Mari


    The European Qualifications Framework (EQF) for lifelong learning has been characterized as a policy instrument with a number of contested ideas, raising questions about the process through which such instruments are developed at European level. The introduction of the EQF is in this article examined through variations of neo-institutional theory:…

  10. Application of Resource Description Framework to Personalise Learning: Systematic Review and Methodology (United States)

    Jevsikova, Tatjana; Berniukevicius, Andrius; Kurilovas, Eugenijus


    The paper is aimed to present a methodology of learning personalisation based on applying Resource Description Framework (RDF) standard model. Research results are two-fold: first, the results of systematic literature review on Linked Data, RDF "subject-predicate-object" triples, and Web Ontology Language (OWL) application in education…

  11. Simulation-Based E-Learning Framework for Entrepreneurship Education and Training

    Directory of Open Access Journals (Sweden)

    Constanţa-Nicoleta Bodea


    Full Text Available The paper proposes an e-Learning framework in entrepreneurship. The framework has three main components, for identification the business opportunities, for developing business scenarios and for risk analysis. A common database assures the components integration. The main components of this framework are already available; the main challenging for those interested in using them is to design an integrated flow of activities, adapted with their curricula and other educational settings. The originality of the approach is that the framework is domain independent and uses advanced IT technologies, such as recommendation algorithms, agent-based simulations and extended graphical support. Using this e-learning framework, the students can learn how to choose relevant characteristics/aspects for a type of business and how important is each of them according specific criteria; how to set realistic values for different characteristics/aspects of the business, how a business scenario can be changed in order to fit better to the business context and how to assess/evaluate business scenarios.

  12. Prognosis research strategy (PROGRESS) 1: A framework for researching clinical outcomes

    NARCIS (Netherlands)

    H. Hemingway; P. Croft (Peter); P. Perel (Pablo); J. Hayden (Jill); D. Abrams; A. Timmis (Adam); A. Briggs (Andrew); R. Udumyan (Ruzan); K.G.M. Moons (Karel); E.W. Steyerberg (Ewout); I. Roberts (Ian); S. Schroter (Sara); D.G. Altman (Douglas); R.D. Riley (Richard); N. Brunner; A. Hingorani (Aroon); P.A. Kyzas (Panayiotis); N. Malats (Núria); G. Peat; W. Sauerbrei (Willi); D.A.W.M. van der Windt (Daniëlle)


    textabstractUnderstanding and improving the prognosis of a disease or health condition is a priority in clinical research and practice. In this article, the authors introduce a framework of four interrelated themes in prognosis research, describe the importance of the first of these themes

  13. Active-constructive-interactive: a conceptual framework for differentiating learning activities. (United States)

    Chi, Michelene T H


    Active, constructive, and interactive are terms that are commonly used in the cognitive and learning sciences. They describe activities that can be undertaken by learners. However, the literature is actually not explicit about how these terms can be defined; whether they are distinct; and whether they refer to overt manifestations, learning processes, or learning outcomes. Thus, a framework is provided here that offers a way to differentiate active, constructive, and interactive in terms of observable overt activities and underlying learning processes. The framework generates a testable hypothesis for learning: that interactive activities are most likely to be better than constructive activities, which in turn might be better than active activities, which are better than being passive. Studies from the literature are cited to provide evidence in support of this hypothesis. Moreover, postulating underlying learning processes allows us to interpret evidence in the literature more accurately. Specifying distinct overt activities for active, constructive, and interactive also offers suggestions for how learning activities can be coded and how each kind of activity might be elicited. Copyright © 2009 Cognitive Science Society, Inc.

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

    Directory of Open Access Journals (Sweden)

    KimMarie McGoldrick


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

  15. e-Learning for expanding distance education in tertiary level in Bangladesh: Problems and progress

    Directory of Open Access Journals (Sweden)

    Md. Abdullah Al-Masum


    Full Text Available E-learning has broadly become an important enabler to promote distance education (DE and lifelong learning in most of the developed countries, but in Bangladesh it is still a new successful progressive system for the learning communities. Distance education is thought to be introduced as an effective way of educating people of all sections in Bangladesh. Bangladesh Open University (BOU, the only distance education provider in Bangladesh, has been trying to adopt the use of various e-learning materials for its distance delivery. This paper has tried to describe the current progress of quality e-learning for expanding distance education, identifying the major problems of e-learning in distance education at tertiary level in Bangladesh, with special reference to BOU, and finally to put forward some valuable recommendations for solving the problems. The study is based on both primary and secondary sources. It is observed from the research that e-learning is going to ensure its bright prospect as an alternative mode of education at the tertiary level in Bangladesh. There are several problems that are identified and can be mitigated and solved through Information and Communication Technology (ICT development, greater acceptance by learners, and much research in this sector in Bangladesh to face globalization.   DOI: 10.18870/hlrc.v3i4.171

  16. Development of a Learning Progression for the Formation of the Solar System (United States)

    Plummer, Julia D.; Palma, Christopher; Flarend, Alice; Rubin, KeriAnn; Ong, Yann Shiou; Botzer, Brandon; McDonald, Scott; Furman, Tanya


    This study describes the process of defining a hypothetical learning progression (LP) for astronomy around the big idea of "Solar System formation." At the most sophisticated level, students can explain how the formation process led to the current Solar System by considering how the planets formed from the collapse of a rotating cloud of…

  17. Investigating a Learning Progression for Energy Ideas from Upper Elementary through High School (United States)

    Herrmann-Abell, Cari F.; DeBoer, George E.


    This study tests a hypothesized learning progression for the concept of energy. It looks at 14 specific ideas under the categories of (i) Energy Forms and Transformations; (ii) Energy Transfer; (iii) Energy Dissipation and Degradation; and (iv) Energy Conservation. It then examines students' growth of understanding within each of these ideas at…

  18. Academic and social integration and study progress in problem based learning

    NARCIS (Netherlands)

    S.E. Severiens (Sabine); H.G. Schmidt (Henk)


    textabstractThe present study explores the effects of problem-based learning (PBL) on social and academic integration and study progress. Three hundred and five first-year students from three different psychology curricula completed a questionnaire on social and academic integration. Effects of a

  19. Teachers' Use of Learning Progression-Based Formative Assessment in Water Instruction (United States)

    Covitt, Beth A.; Gunckel, Kristin L.; Caplan, Bess; Syswerda, Sara


    While learning progressions (LPs) hold promise as instructional tools, researchers are still in the early stages of understanding how teachers use LPs in formative assessment practices. We report on a study that assessed teachers' proficiency in using a LP for student ideas about hydrologic systems. Research questions were: (a) what were teachers'…

  20. New Data, Old Tensions: Big Data, Personalized Learning, and the Challenges of Progressive Education (United States)

    Dishon, Gideon


    Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

  1. Progression in Physical Education Teachers' Career-Long Professional Learning: Conceptual and Practical Concerns (United States)

    Armour, Kathleen; Makopoulou, Kyriaki; Chambers, Fiona


    This paper considers the issue of learning "progression" in pedagogy for physical education (PE) teachers in their career-long professional development (CPD). This issue arose from an analysis of findings from three research projects in which the authors were involved. The projects were undertaken in different national contexts (Ireland,…

  2. Developing a Domain Theory Defining and Exemplifying a Learning Theory of Progressive Attainments (United States)

    Bunderson, C. Victor


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

  3. Brain Substrates of Learning and Retention in Mild Cognitive Impairment Diagnosis and Progression to Alzheimer's Disease (United States)

    Chang, Yu-Ling; Bondi, Mark W.; Fennema-Notestine, Christine; McEvoy, Linda K.; Hagler, Donald J., Jr.; Jacobson, Mark W.; Dale, Anders M.


    Understanding the underlying qualitative features of memory deficits in mild cognitive impairment (MCI) can provide critical information for early detection of Alzheimer's disease (AD). This study sought to investigate the utility of both learning and retention measures in (a) the diagnosis of MCI, (b) predicting progression to AD, and (c)…

  4. Towards a common theory for learning from reward, affect, and motivation: The SIMON framework

    Directory of Open Access Journals (Sweden)

    Christopher R Madan


    Full Text Available While the effects of reward, affect, and motivation on learning have each developed into their own fields of research, they largely have been investigated in isolation. As all three of these constructs are highly related, and use similar experimental procedures, an important advance in research would be to consider the interplay between these constructs. Here we first define each of the three constructs, and then discuss how they may influence each other within a common framework. Finally, we delineate several sources of evidence supporting the framework. By considering the constructs of reward, affect, and motivation within a single framework, we can develop a better understanding of the processes involved in learning and how they interplay, and work towards a comprehensive theory that encompasses reward, affect, and motivation.

  5. Toward a common theory for learning from reward, affect, and motivation: the SIMON framework. (United States)

    Madan, Christopher R


    While the effects of reward, affect, and motivation on learning have each developed into their own fields of research, they largely have been investigated in isolation. As all three of these constructs are highly related, and use similar experimental procedures, an important advance in research would be to consider the interplay between these constructs. Here we first define each of the three constructs, and then discuss how they may influence each other within a common framework. Finally, we delineate several sources of evidence supporting the framework. By considering the constructs of reward, affect, and motivation within a single framework, we can develop a better understanding of the processes involved in learning and how they interplay, and work toward a comprehensive theory that encompasses reward, affect, and motivation.

  6. Homelessness Outcome Reporting Normative Framework: Systems-Level Evaluation of Progress in Ending Homelessness (United States)

    Austen, Tyrone; Pauly, Bernie


    Homelessness is a serious and growing issue. Evaluations of systemic-level changes are needed to determine progress in reducing or ending homelessness. The report card methodology is one means of systems-level assessment. Rather than solely establishing an enumeration, homelessness report cards can capture pertinent information about structural…

  7. Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach. (United States)

    Kagawa, Rina; Kawazoe, Yoshimasa; Ida, Yusuke; Shinohara, Emiko; Tanaka, Katsuya; Imai, Takeshi; Ohe, Kazuhiko


    Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users' objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

  8. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa

    The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....

  9. Unpacking Virtual and Intercultural Spaces: A Presentation of a Conceptual Framework to Investigate the Connection between Technology and Intercultural Learning

    DEFF Research Database (Denmark)

    Pedersen, Rikke; Jørgensen, Mette; Harrison, Roger

    This paper presents a framework for the development of research within the emerging areas of internationalisation and technology that connect to build potential learning spaces within intercultural and global settings.......This paper presents a framework for the development of research within the emerging areas of internationalisation and technology that connect to build potential learning spaces within intercultural and global settings....

  10. An Alienation-Based Framework for Student Experience in Higher Education: New Interpretations of Past Observations in Student Learning Theory (United States)

    Barnhardt, Bradford; Ginns, Paul


    This article orients a recently proposed alienation-based framework for student learning theory (SLT) to the empirical basis of the approaches to learning perspective. The proposed framework makes new macro-level interpretations of an established micro-level theory, across three levels of interpretation: (1) a context-free psychological state…

  11. Framework for Educational Robotics: A Multiphase Approach to Enhance User Learning in a Competitive Arena (United States)

    Lye, Ngit Chan; Wong, Kok Wai; Chiou, Andrew


    Educational robotics involves using robots as an educational tool to provide a long term, and progressive learning activity, to cater to different age group. The current concern is that, using robots in education should not be an instance of a one-off project for the sole purpose of participating in a competitive event. Instead, it should be a…

  12. Collaboration in E-Learning: A Study Using the Flexible E-Learning Framework (United States)

    Vandenhouten, C.; Gallagher-Lepak, S.; Reilly, J.; Ralston-Berg, P.


    E-Learning remains a new frontier for many faculty. When compared to the traditional classroom, E- Learning requires the talents of many team members from a variety of departments as well as the use of different teaching and learning strategies. Pedagogy as well as team configurations must change when moving to the online environment. As a result,…

  13. A leadership framework to support the use of e-learning resources. (United States)

    McCutcheon, Karen


    Recognition needs to be given to emerging postgraduate nursing students' status of 'consumer', and the challenge for nurse education is to remain relevant and competitive in a consumer-led market. An e-learning model has been suggested as a competitive and contemporary way forward for student consumers, but successful introduction of this requires leadership and strong organisational management systems. This article applies the NHS leadership framework to nurse education in relation to implementation of e-learning and describes and interprets each element for application in higher education settings. By applying a leadership framework that acknowledges the skills and abilities of staff and encourages the formation of collaborative partnerships in the wider university community, educators can begin to develop skills and confidence in teaching using e-learning resources.

  14. A mathematical framework for virtual IMRT QA using machine learning. (United States)

    Valdes, G; Scheuermann, R; Hung, C Y; Olszanski, A; Bellerive, M; Solberg, T D


    It is common practice to perform patient-specific pretreatment verifications to the clinical delivery of IMRT. This process can be time-consuming and not altogether instructive due to the myriad sources that may produce a failing result. The purpose of this study was to develop an algorithm capable of predicting IMRT QA passing rates a priori. From all treatment, 498 IMRT plans sites were planned in eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam Linacs. 3%/3 mm local dose/distance-to-agreement (DTA) was recorded using a commercial 2D diode array. Each plan was characterized by 78 metrics that describe different aspects of their complexity that could lead to disagreements between the calculated and measured dose. A Poisson regression with Lasso regularization was trained to learn the relation between the plan characteristics and each passing rate. Passing rates 3%/3 mm local dose/DTA can be predicted with an error smaller than 3% for all plans analyzed. The most important metrics to describe the passing rates were determined to be the MU factor (MU per Gy), small aperture score, irregularity factor, and fraction of the plan delivered at the corners of a 40 × 40 cm field. The higher the value of these metrics, the worse the passing rates. The Virtual QA process predicts IMRT passing rates with a high likelihood, allows the detection of failures due to setup errors, and it is sensitive enough to detect small differences between matched Linacs.

  15. Validating Proposed Learning Progressions on Force and Motion Using the Force Concept Inventory: Findings from Singapore Secondary Schools (United States)

    Fulmer, Gavin W.


    This study examines the validity of 2 proposed learning progressions on the force concept when tested using items from the Force Concept Inventory (FCI). This is the first study to compare students' performance with respect to learning progressions both for force and motion and for Newton's third law in parallel. It is also among the first studies…

  16. Development and Validation of a Learning Progression for Change of Seasons, Solar and Lunar Eclipses, and Moon Phases (United States)

    Testa, Italo; Galano, Silvia; Leccia, Silvio; Puddu, Emanuella


    In this paper, we report about the development and validation of a learning progression about the Celestial Motion big idea. Existing curricula, research studies on alternative conceptions about these phenomena, and students' answers to an open questionnaire were the starting point to develop initial learning progressions about change of seasons,…

  17. The Climate Change Education Evidence Base: Lessons Learned from NOAA's Monitoring and Evaluation Framework Implementation (United States)

    Baek, J.


    Federal science mission agencies are under increased pressure to ensure that their STEM education investments accomplish several objectives, including the identification and use of evidence-based approaches. Climate change education and climate literacy programs fall under these broader STEM initiatives. This paper is designed as a primer for climate change education evaluators and researchers to understand the policy context on the use of evidence. Recent initiatives, that include the National Science Foundation (NSF), the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), point to a need for shared goals and measurements amongst the climate change education community. The Tri-agency Climate Change Education (CCE) collaboration, which includes NSF, NASA, and NOAA, developed the Tri-Agency Climate Change Education Common Evaluation Framework Initiative Stakeholder Statement (2012). An excerpt: From the perspective of the tri-agency collaboration, and its individual agency members, the goal of the common framework is not to build a required evaluation scheme or a set of new requirements for our funded climate change education initiatives. Rather, the collaboration would be strengthened by the development of a framework that includes tools, instruments, and/or documentation to: ● Help the agencies see and articulate the relationships between the individual pieces of the tri-agency CCE portfolio; ● Guide the agencies in reporting on the progress, lessons learned, and impacts of the collaboration between the three agencies in developing a coordinated portfolio of climate education initiatives; and ● Help the individual projects, as part of this broader portfolio, understand where they fit into a larger picture. The accomplishments of this initiative to date have been based on the collaborative nature of evaluators the climate change education community within the tri-agency portfolio. While this

  18. A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning. (United States)

    Windridge, David; Felsberg, Michael; Shaukat, Affan


    Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

  19. Defining a risk-informed framework for whole-of-government lessons learned: A Canadian perspective. (United States)

    Friesen, Shaye K; Kelsey, Shelley; Legere, J A Jim

    Lessons learned play an important role in emergency management (EM) and organizational agility. Virtually all aspects of EM can derive benefit from a lessons learned program. From major security events to exercises, exploiting and applying lessons learned and "best practices" is critical to organizational resilience and adaptiveness. A robust lessons learned process and methodology provides an evidence base with which to inform decisions, guide plans, strengthen mitigation strategies, and assist in developing tools for operations. The Canadian Safety and Security Program recently supported a project to define a comprehensive framework that would allow public safety and security partners to regularly share event response best practices, and prioritize recommendations originating from after action reviews. This framework consists of several inter-locking elements: a comprehensive literature review/environmental scan of international programs; a survey to collect data from end users and management; the development of a taxonomy for organizing and structuring information; a risk-informed methodology for selecting, prioritizing, and following through on recommendations; and standardized templates and tools for tracking recommendations and ensuring implementation. This article discusses the efforts of the project team, which provided "best practice" advice and analytical support to ensure that a systematic approach to lessons learned was taken by the federal community to improve prevention, preparedness, and response activities. It posits an approach by which one might design a systematic process for information sharing and event response coordination-an approach that will assist federal departments to institutionalize a cross-government lessons learned program.

  20. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection. (United States)

    Zeng, Xueqiang; Luo, Gang


    Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

  1. Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept


    Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.


    There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to studen...

  2. Learning from instructional explanations: effects of prompts based on the active-constructive-interactive framework. (United States)

    Roelle, Julian; Müller, Claudia; Roelle, Detlev; Berthold, Kirsten


    Although instructional explanations are commonly provided when learners are introduced to new content, they often fail because they are not integrated into effective learning activities. The recently introduced active-constructive-interactive framework posits an effectiveness hierarchy in which interactive learning activities are at the top; these are then followed by constructive and active learning activities, respectively. Against this background, we combined instructional explanations with different types of prompts that were designed to elicit these learning activities and tested the central predictions of the active-constructive-interactive framework. In Experiment 1, N = 83 students were randomly assigned to one of four combinations of instructional explanations and prompts. To test the active learning hypothesis, the learners received either (1) complete explanations and engaging prompts designed to elicit active activities or (2) explanations that were reduced by inferences and inference prompts designed to engage learners in constructing the withheld information. Furthermore, in order to explore how interactive learning activities can be elicited, we gave the learners who had difficulties in constructing the prompted inferences adapted remedial explanations with either (3) unspecific engaging prompts or (4) revision prompts. In support of the active learning hypothesis, we found that the learners who received reduced explanations and inference prompts outperformed the learners who received complete explanations and engaging prompts. Moreover, revision prompts were more effective in eliciting interactive learning activities than engaging prompts. In Experiment 2, N = 40 students were randomly assigned to either (1) a reduced explanations and inference prompts or (2) a reduced explanations and inference prompts plus adapted remedial explanations and revision prompts condition. In support of the constructive learning hypothesis, the learners who received

  3. Improved Discriminability of Spatiotemporal Neural Patterns in Rat Motor Cortical Areas as Directional Choice Learning Progresses

    Directory of Open Access Journals (Sweden)

    Hongwei eMao


    Full Text Available Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2-3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats’ behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.

  4. An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation (United States)

    Zhang, Zhou; Pasolli, Edoardo; Crawford, Melba M.; Tilton, James C.


    Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

  5. Progress report for FACETS (Framework Application for Core-Edge Transport Simulations): C.S. SAP

    Energy Technology Data Exchange (ETDEWEB)

    Epperly, T W


    The mission of the Computer Science Scientific Application Partnership (C.S. SAP) at LLNL is to develop and apply leading-edge scientific component technology to FACETS software. Contributions from LLNL's fusion energy program staff towards the underlying physics modules are described in a separate report. FACETS uses component technology to combine selectively multiple physics and solver software modules written in different languages by different institutions together in an tightly-integrated, parallel computing framework for Tokamak reactor modeling. In the past fiscal year, the C.S. SAP has focused on two primary tasks: applying Babel to connect UEDGE into the FACETS framework through UEDGE's existing Python interface and developing a next generation componentization strategy for UEDGE which avoids the use of Python. The FACETS project uses Babel to solve its language interoperability challenges. Specific accomplishments for the year include: (1) Refined SIDL interfaces for UEDGE to meet satisfy the standard interfaces required by FACETS for all physics modules. This required consensus building between framework and UEDGE developers. (2) Wrote prototype C++ driver for UEDGE to demonstrate how UEDGE can be called from C++ using Babel. (3) Supported the FACETS project by adding new features to Babel such as release number tagging, porting to new machines, and adding new configuration options. Babel modifications were delivered to FACETS by testing and publishing development snapshots in the projects software repository. (4) Assisted Tech-X Corporation in testing and debugging of a high level build system for the complete FACETS tool chain--the complete list of third-party software libraries that FACETS depends on directly or indirectly (e.g., MPI, HDF5, PACT, etc.). (5) Designed and implemented a new approach to wrapping UEDGE as a FACETS component without requiring Python. To get simulation results as soon as possible, our initial connection from the

  6. Progress report for FACETS (Framework Application for Core-Edge Transport Simulations): C.S. SAP

    International Nuclear Information System (INIS)

    Epperly, T.W.


    The mission of the Computer Science Scientific Application Partnership (C.S. SAP) at LLNL is to develop and apply leading-edge scientific component technology to FACETS software. Contributions from LLNL's fusion energy program staff towards the underlying physics modules are described in a separate report. FACETS uses component technology to combine selectively multiple physics and solver software modules written in different languages by different institutions together in an tightly-integrated, parallel computing framework for Tokamak reactor modeling. In the past fiscal year, the C.S. SAP has focused on two primary tasks: applying Babel to connect UEDGE into the FACETS framework through UEDGE's existing Python interface and developing a next generation componentization strategy for UEDGE which avoids the use of Python. The FACETS project uses Babel to solve its language interoperability challenges. Specific accomplishments for the year include: (1) Refined SIDL interfaces for UEDGE to meet satisfy the standard interfaces required by FACETS for all physics modules. This required consensus building between framework and UEDGE developers. (2) Wrote prototype C++ driver for UEDGE to demonstrate how UEDGE can be called from C++ using Babel. (3) Supported the FACETS project by adding new features to Babel such as release number tagging, porting to new machines, and adding new configuration options. Babel modifications were delivered to FACETS by testing and publishing development snapshots in the projects software repository. (4) Assisted Tech-X Corporation in testing and debugging of a high level build system for the complete FACETS tool chain--the complete list of third-party software libraries that FACETS depends on directly or indirectly (e.g., MPI, HDF5, PACT, etc.). (5) Designed and implemented a new approach to wrapping UEDGE as a FACETS component without requiring Python. To get simulation results as soon as possible, our initial connection from the FACETS

  7. A web-based e-learning framework for public perception and acceptance on nuclear energy

    International Nuclear Information System (INIS)

    Zhou Yangping; Yoshikawa, Hidekazu; Liu Jingquan; Ouyang, Jun; Lu Daogang


    Now, public acceptance plays a central role in the nuclear energy. Public concerns on safety and sustainability of nuclear energy, ground nuclear power in many countries and territories to a stop or even a downfall. In this study, an e-learning framework by using Internet, is proposed for public education in order to boost public perception on nuclear energy, which will certainly affect public acceptance toward it. This study aims at investigating public perception and acceptance on nuclear energy in a continuous and accurate manner. In addition, this e-learning framework can promote public perception on nuclear energy by using teaching material with a graphical hierarchy about knowledge of nuclear energy. This web-based e-learning framework mainly consists of two components: (1) an e-learning support module which continuously investigates public perception and acceptance toward nuclear energy and teaches public knowledge about nuclear energy; (2) an updating module which may improve the education materials by analyzing the effect of education or proving the materials submitted by the visitors through Wiki pages. Advantages and future work of this study are also generally described. (author)

  8. Praxis and reflexivity for interprofessional education: towards an inclusive theoretical framework for learning. (United States)

    Hutchings, Maggie; Scammell, Janet; Quinney, Anne


    While there is growing evidence of theoretical perspectives adopted in interprofessional education, learning theories tend to foreground the individual, focusing on psycho-social aspects of individual differences and professional identity to the detriment of considering social-structural factors at work in social practices. Conversely socially situated practice is criticised for being context-specific, making it difficult to draw generalisable conclusions for improving interprofessional education. This article builds on a theoretical framework derived from earlier research, drawing on the dynamics of Dewey's experiential learning theory and Archer's critical realist social theory, to make a case for a meta-theoretical framework enabling social-constructivist and situated learning theories to be interlinked and integrated through praxis and reflexivity. Our current analysis is grounded in an interprofessional curriculum initiative mediated by a virtual community peopled by health and social care users. Student perceptions, captured through quantitative and qualitative data, suggest three major disruptive themes, creating opportunities for congruence and disjuncture and generating a model of zones of interlinked praxis associated with professional differences and identity, pedagogic strategies and technology-mediated approaches. This model contributes to a framework for understanding the complexity of interprofessional learning and offers bridges between individual and structural factors for engaging with the enablements and constraints at work in communities of practice and networks for interprofessional education.

  9. Image Classification, Deep Learning and Convolutional Neural Networks : A Comparative Study of Machine Learning Frameworks


    Airola, Rasmus; Hager, Kristoffer


    The use of machine learning and specifically neural networks is a growing trend in software development, and has grown immensely in the last couple of years in the light of an increasing need to handle big data and large information flows. Machine learning has a broad area of application, such as human-computer interaction, predicting stock prices, real-time translation, and self driving vehicles. Large companies such as Microsoft and Google have already implemented machine learning in some o...

  10. A machine learning-based framework to identify type 2 diabetes through electronic health records. (United States)

    Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You


    To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature

  11. Tracking Progress in Improving Diagnosis: A Framework for Defining Undesirable Diagnostic Events. (United States)

    Olson, Andrew P J; Graber, Mark L; Singh, Hardeep


    Diagnostic error is a prevalent, harmful, and costly phenomenon. Multiple national health care and governmental organizations have recently identified the need to improve diagnostic safety as a high priority. A major barrier, however, is the lack of standardized, reliable methods for measuring diagnostic safety. Given the absence of reliable and valid measures for diagnostic errors, we need methods to help establish some type of baseline diagnostic performance across health systems, as well as to enable researchers and health systems to determine the impact of interventions for improving the diagnostic process. Multiple approaches have been suggested but none widely adopted. We propose a new framework for identifying "undesirable diagnostic events" (UDEs) that health systems, professional organizations, and researchers could further define and develop to enable standardized measurement and reporting related to diagnostic safety. We propose an outline for UDEs that identifies both conditions prone to diagnostic error and the contexts of care in which these errors are likely to occur. Refinement and adoption of this framework across health systems can facilitate standardized measurement and reporting of diagnostic safety.

  12. Controlling misses and false alarms in a machine learning framework for predicting uniformity of printed pages (United States)

    Nguyen, Minh Q.; Allebach, Jan P.


    In our previous work1 , we presented a block-based technique to analyze printed page uniformity both visually and metrically. The features learned from the models were then employed in a Support Vector Machine (SVM) framework to classify the pages into one of the two categories of acceptable and unacceptable quality. In this paper, we introduce a set of tools for machine learning in the assessment of printed page uniformity. This work is primarily targeted to the printing industry, specifically the ubiquitous laser, electrophotographic printer. We use features that are well-correlated with the rankings of expert observers to develop a novel machine learning framework that allows one to achieve the minimum "false alarm" rate, subject to a chosen "miss" rate. Surprisingly, most of the research that has been conducted on machine learning does not consider this framework. During the process of developing a new product, test engineers will print hundreds of test pages, which can be scanned and then analyzed by an autonomous algorithm. Among these pages, most may be of acceptable quality. The objective is to find the ones that are not. These will provide critically important information to systems designers, regarding issues that need to be addressed in improving the printer design. A "miss" is defined to be a page that is not of acceptable quality to an expert observer that the prediction algorithm declares to be a "pass". Misses are a serious problem, since they represent problems that will not be seen by the systems designers. On the other hand, "false alarms" correspond to pages that an expert observer would declare to be of acceptable quality, but which are flagged by the prediction algorithm as "fails". In a typical printer testing and development scenario, such pages would be examined by an expert, and found to be of acceptable quality after all. "False alarm" pages result in extra pages to be examined by expert observers, which increases labor cost. But "false

  13. The Role Of The Integrated, Thematic Project To Learning Progress Of The Child In The Early Period

    Directory of Open Access Journals (Sweden)

    Aida Cornelia Stoian


    Full Text Available In this study, we have proposed to present you the results of an empirical research in order to identify the positive aspects of the integrated, thematic project in learning progress of children in preschool. Using the observation method, we analyzed children's results regarding the objectives in the respect to the objectives in the grid. Children's progress in learning represents the confirmation and affirmation of the role of this integrated, thematic project in supporting the early learning child.

  14. The Community of Inquiry Framework Meets the SOLO Taxonomy: A Process-Product Model of Online Learning (United States)

    Shea, Peter; Gozza-Cohen, Mary; Uzuner, Sedef; Mehta, Ruchi; Valtcheva, Anna Valentinova; Hayes, Suzanne; Vickers, Jason


    This paper presents both a conceptual and empirical investigation of teaching and learning in online courses. Employing both the Community of Inquiry framework (CoI) and the Structure of Observed Learning Outcomes (SOLO) taxonomy, two complete online courses were examined for the quality of both collaborative learning processes and learning…

  15. A Proposed Framework between Internal, External and Pedagogy Dimensions in Adoption of Interactive Multimedia e-Learning (United States)

    Lahwal, Fathia; Al-Ajlan, Ajlan S.; Amain, Mohamad


    This study focuses on interactive multimedia e-learning aims to improve our understanding about the dynamics of e-learning. The objective is to critical evaluate and better understand the interrelationships in the proposed framework between internal, external and the pedagogy dimensions in adoption of interactive multimedia and e-learning. It…

  16. Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept. (United States)

    Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E


    There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning.

  17. Formal Framework to improve the reliability of concurrent and collaborative learning games

    Directory of Open Access Journals (Sweden)



    Full Text Available Multi-player learning games are complex software applications resulting from a costly and complex engineering process, and involving multiple stakeholders (domain experts, teachers, game designers, programmers, testers, etc.. Moreover, they are dynamic systems that evolve over time and implement complex interactions between objects and players. Usually, once a learning game is developed, testing activities are conducted by humans who explore the possible executions of the game’s scenario to detect bugs. The complexity and the dynamic nature of multiplayer learning games enforces the complexity of testing activities. Indeed, it is impracticable to explore manually all possible executions due to their huge number. Moreover, the test cannot verify some properties on multi-player and collaborative scenarios, such as paths leading to deadlock between learners or prevent learners to meet all objectives and win the game. This type of properties should be verified at the design stage. We propose a framework enabling a formal modeling of game scenarios and an associated automatic verification of learning game’s scenario at the design stage of the development process.We use Symmetric Petri nets as a modeling language and choose to verify properties by means of model checkers. This paper discusses the possibilities offered by this framework to verify learning game’s properties before the programming stage.

  18. Russian law: the legal framework for foreign investment in the Russian petroleum industry - problems and progress

    International Nuclear Information System (INIS)

    Barmin, A.; Doeh, D.


    Recent developments in Russian law relating to foreign investment in the petroleum industry are reviewed. The central piece of legislation regulating foreign investment is the Law on Foreign Investments of 1991. Its significance is that it is opened up to foreign investment that had been a closed society but it did not set out how and or what conditions investors' rights were to be acquired and exercised. The main problems that have had to be dealt with include: determining which government authorities (federal, republic, regional etc.) have the power to grant petroleum exploration and production rights; determining the methods by which these rights may be obtained and on what terms; determining export rights; establishing the basis for taxation; establishing the general framework for foreign investment in Russia. The extent to which these issues have been resolved is discussed and remaining areas of concern considered. (UK)

  19. Aligning interprofessional education collaborative sub-competencies to a progression of learning. (United States)

    Patel Gunaldo, Tina; Brisolara, Kari Fitzmorris; Davis, Alison H; Moore, Robert


    In the United States, the Interprofessional Education Collaborative (IPEC) developed four core competencies for interprofessional collaborative practice. Even though the IPEC competencies and respective sub-competencies were not created in a hierarchal manner, one might reflect upon a logical progression of learning as well as learners accruing skills allowing them to master one level of learning and building on the aggregate of skills before advancing to the next level. The Louisiana State University Health-New Orleans Center for Interprofessional Education and Collaborative Practice (CIPECP) determined the need to align the sub-competencies with the level of behavioural expectations in order to simplify the process of developing an interprofessional education experience targeted to specific learning levels. In order to determine the most effective alignment, CIPECP discussions revolved around current programmatic expectations across the institution. Faculty recognised the need to align sub-competencies with student learning objectives. Simultaneously, a progression of learning existing within each of the four IPEC domains was noted. Ultimately, the faculty and staff team agreed upon categorising the sub-competencies in a hierarchical manner for the four domains into either a "basic, intermediate, or advanced" level of competency.

  20. Video copy protection and detection framework (VPD) for e-learning systems (United States)

    ZandI, Babak; Doustarmoghaddam, Danial; Pour, Mahsa R.


    This Article reviews and compares the copyright issues related to the digital video files, which can be categorized as contended based and Digital watermarking copy Detection. Then we describe how to protect a digital video by using a special Video data hiding method and algorithm. We also discuss how to detect the copy right of the file, Based on expounding Direction of the technology of the video copy detection, and Combining with the own research results, brings forward a new video protection and copy detection approach in terms of plagiarism and e-learning systems using the video data hiding technology. Finally we introduce a framework for Video protection and detection in e-learning systems (VPD Framework).

  1. 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


    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{}.

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

    KAUST Repository

    Li, Yu


    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{}.

  3. Tools and Frameworks for Big Learning in Scala: Leveraging the Language for High Productivity and Performance


    Miller, Heather; Haller, Philipp; Odersky, Martin


    Implementing machine learning algorithms for large data, such as the Web graph and social networks, is challenging. Even though much research has focused on making sequential algorithms more scalable, their running times continue to be prohibitively long. Meanwhile, parallelization remains a formidable challenge for this class of problems, despite frameworks like MapReduce which hide much of the associated complexity. We present three ongoing efforts within our team, previously presented at v...

  4. Toward a common theory for learning from reward, affect, and motivation: the SIMON framework


    Madan, Christopher R.


    While the effects of reward, affect, and motivation on learning have each developed into their own fields of research, they largely have been investigated in isolation. As all three of these constructs are highly related, and use similar experimental procedures, an important advance in research would be to consider the interplay between these constructs. Here we first define each of the three constructs, and then discuss how they may influence each other within a common framework. Finally, we...

  5. DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters


    Kim, Hanjoo; Park, Jaehong; Jang, Jaehee; Yoon, Sungroh


    The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU-based acceleration provide a mainstream solution to this computational challenge. In this paper, we propose DeepSpark, a distributed and parallel deep learning framework that exploits Apache Spark on commodity clusters. To support parallel operation...

  6. A Framework for Culturally Relevant Online Learning: Lessons from Alaska's Tribal Health Workers. (United States)

    Cueva, Katie; Cueva, Melany; Revels, Laura; Lanier, Anne P; Dignan, Mark; Viswanath, K; Fung, Teresa T; Geller, Alan C


    Culturally relevant health promotion is an opportunity to reduce health inequities in diseases with modifiable risks, such as cancer. Alaska Native people bear a disproportionate cancer burden, and Alaska's rural tribal health workers consequently requested cancer education accessible online. In response, the Alaska Native Tribal Health Consortium cancer education team sought to create a framework for culturally relevant online learning to inform the creation of distance-delivered cancer education. Guided by the principles of community-based participatory action research and grounded in empowerment theory, the project team conducted a focus group with 10 Alaska Native education experts, 12 culturally diverse key informant interviews, a key stakeholder survey of 62 Alaska Native tribal health workers and their instructors/supervisors, and a literature review on distance-delivered education with Alaska Native or American Indian people. Qualitative findings were analyzed in Atlas.ti, with common themes presented in this article as a framework for culturally relevant online education. This proposed framework includes four principles: collaborative development, interactive content delivery, contextualizing learning, and creating connection. As an Alaskan tribal health worker shared "we're all in this together. All about conversations, relationships. Always learn from you/with you, together what we know and understand from the center of our experience, our ways of knowing, being, caring." The proposed framework has been applied to support cancer education and promote cancer control with Alaska Native people and has motivated health behavior change to reduce cancer risk. This framework may be adaptable to other populations to guide effective and culturally relevant online interventions.

  7. Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

    Directory of Open Access Journals (Sweden)

    Nicolas Frémaux


    Full Text Available Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD learning of Doya (2000 to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

  8. Roles and Domains to Teach in Online Learning Environments: Educational ICT Competency Framework for University Teachers (United States)

    Guasch, Teresa; Alvarez, Ibis; Espasa, Anna

    This chapter is aimed at presenting an integrated framework of the educational information and communications technology (ICT) competencies that university teachers should have to teach in an online learning environment. Teaching through ICT in higher education involves performing three main roles - pedagogical, socialist, and design/planning - and also two cross-cutting domains that arise from the online environment: technological and managerial. This framework as well as the competencies for university teachers associated with it were validated at a European level by a dual process of net-based focus groups of teachers and teacher trainers in each of the participating countries in a European Project (Elene-TLC) and an online Delphi method involving 78 experts from 14 universities of ten European countries. The competency framework and the examples provided in the chapter are the basis for designing innovative professional development activities in online university environments.

  9. SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications.

    Directory of Open Access Journals (Sweden)

    Ahmad Karim

    Full Text Available Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS, disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

  10. SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications. (United States)

    Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram


    Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

  11. SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications (United States)

    Karim, Ahmad; Salleh, Rosli; Khan, Muhammad Khurram


    Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks’ back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps’ detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies. PMID:26978523

  12. Recent Progress in Asymmetric Catalysis and Chromatographic Separation by Chiral Metal–Organic Frameworks

    Directory of Open Access Journals (Sweden)

    Suchandra Bhattacharjee


    Full Text Available Metal–organic frameworks (MOFs, as a new class of porous solid materials, have emerged and their study has established itself very quickly into a productive research field. This short review recaps the recent advancement of chiral MOFs. Here, we present simple, well-ordered instances to classify the mode of synthesis of chiral MOFs, and later demonstrate the potential applications of chiral MOFs in heterogeneous asymmetric catalysis and enantioselective separation. The asymmetric catalysis sections are subdivided based on the types of reactions that have been successfully carried out recently by chiral MOFs. In the part on enantioselective separation, we present the potentiality of chiral MOFs as a stationary phase for high-performance liquid chromatography (HPLC and high-resolution gas chromatography (GC by considering fruitful examples from current research work. We anticipate that this review will provide interest to researchers to design new homochiral MOFs with even greater complexity and effort to execute their potential functions in several fields, such as asymmetric catalysis, enantiomer separation, and chiral recognition.

  13. Progress in the migration towards the real-time framework MARTe at the FTU tokamak

    International Nuclear Information System (INIS)

    Boncagni, L.; Sadeghi, Y.; Vitelli, R.; Centioli, C.; Sinibaldi, S.; Vitale, V.; Zaccarian, L.; Zamborlini, G.


    Keeping in mind the proposed FAST experiment and aiming to meet basic requirements such as a modular and distributed architecture, where different control subsystems can be easily integrated at different times, and can operate either independently or in cooperation with other subsystems, at the end of last year we planned to upgrade the architecture of the FTU real-time system, improving in such a way its flexibility and modularity. We decided to adopt an available packages to reach our goal: MARTe. We report on the state of the art of the MARTe migration process, the difficulties dealt with, the benefits and advantages achieved, the progress made from our last report and, in particular, we describe the integration of the ODIN equilibrium reconstruction system in the real-time environment. The ODIN algorithm was already coded in previous works, but its integration in the real-time system has never been carried out at FTU. We illustrate how the MARTe architecture and the RTNet level allows for a first level of parallelization, distributing the data and/or time among nodes.

  14. Progress in the migration towards the real-time framework MARTe at the FTU tokamak

    Energy Technology Data Exchange (ETDEWEB)

    Boncagni, L., E-mail: [Associazione EURATOM-ENEA sulla Fusione, C.R. ENEA Frascati, Rome (Italy); Sadeghi, Y.; Vitelli, R. [Dipartimento di Informatica, Sistemi e Produzione, Universita di Roma, Tor Vergata, Rome (Italy); Centioli, C. [Associazione EURATOM-ENEA sulla Fusione, C.R. ENEA Frascati, Rome (Italy); Sinibaldi, S. [Dipartimento di Informatica, Sistemi e Produzione, Universita di Roma, Tor Vergata, Rome (Italy); Vitale, V. [Associazione EURATOM-ENEA sulla Fusione, C.R. ENEA Frascati, Rome (Italy); Zaccarian, L. [Dipartimento di Informatica, Sistemi e Produzione, Universita di Roma, Tor Vergata, Rome (Italy); Zamborlini, G. [Facolta di Ingegneria, Universita di Roma La Sapienza, Rome (Italy)


    Keeping in mind the proposed FAST experiment and aiming to meet basic requirements such as a modular and distributed architecture, where different control subsystems can be easily integrated at different times, and can operate either independently or in cooperation with other subsystems, at the end of last year we planned to upgrade the architecture of the FTU real-time system, improving in such a way its flexibility and modularity. We decided to adopt an available packages to reach our goal: MARTe. We report on the state of the art of the MARTe migration process, the difficulties dealt with, the benefits and advantages achieved, the progress made from our last report and, in particular, we describe the integration of the ODIN equilibrium reconstruction system in the real-time environment. The ODIN algorithm was already coded in previous works, but its integration in the real-time system has never been carried out at FTU. We illustrate how the MARTe architecture and the RTNet level allows for a first level of parallelization, distributing the data and/or time among nodes.

  15. From machine learning to deep learning: progress in machine intelligence for rational drug discovery. (United States)

    Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao


    Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. PEDLA: predicting enhancers with a deep learning-based algorithmic framework. (United States)

    Liu, Feng; Li, Hao; Ren, Chao; Bo, Xiaochen; Shu, Wenjie


    Transcriptional enhancers are non-coding segments of DNA that play a central role in the spatiotemporal regulation of gene expression programs. However, systematically and precisely predicting enhancers remain a major challenge. Although existing methods have achieved some success in enhancer prediction, they still suffer from many issues. We developed a deep learning-based algorithmic framework named PEDLA (, which can directly learn an enhancer predictor from massively heterogeneous data and generalize in ways that are mostly consistent across various cell types/tissues. We first trained PEDLA with 1,114-dimensional heterogeneous features in H1 cells, and demonstrated that PEDLA framework integrates diverse heterogeneous features and gives state-of-the-art performance relative to five existing methods for enhancer prediction. We further extended PEDLA to iteratively learn from 22 training cell types/tissues. Our results showed that PEDLA manifested superior performance consistency in both training and independent test sets. On average, PEDLA achieved 95.0% accuracy and a 96.8% geometric mean (GM) of sensitivity and specificity across 22 training cell types/tissues, as well as 95.7% accuracy and a 96.8% GM across 20 independent test cell types/tissues. Together, our work illustrates the power of harnessing state-of-the-art deep learning techniques to consistently identify regulatory elements at a genome-wide scale from massively heterogeneous data across diverse cell types/tissues.

  17. A Symbiotic Framework for coupling Machine Learning and Geosciences in Prediction and Predictability (United States)

    Ravela, S.


    In this presentation we review the two directions of a symbiotic relationship between machine learning and the geosciences in relation to prediction and predictability. In the first direction, we develop ensemble, information theoretic and manifold learning framework to adaptively improve state and parameter estimates in nonlinear high-dimensional non-Gaussian problems, showing in particular that tractable variational approaches can be produced. We demonstrate these applications in the context of autonomous mapping of environmental coherent structures and other idealized problems. In the reverse direction, we show that data assimilation, particularly probabilistic approaches for filtering and smoothing offer a novel and useful way to train neural networks, and serve as a better basis than gradient based approaches when we must quantify uncertainty in association with nonlinear, chaotic processes. In many inference problems in geosciences we seek to build reduced models to characterize local sensitivies, adjoints or other mechanisms that propagate innovations and errors. Here, the particular use of neural approaches for such propagation trained using ensemble data assimilation provides a novel framework. Through these two examples of inference problems in the earth sciences, we show that not only is learning useful to broaden existing methodology, but in reverse, geophysical methodology can be used to influence paradigms in learning.

  18. Research Notes ~ Second Language Acquisition Theories as a Framework for Creating Distance Learning Courses

    Directory of Open Access Journals (Sweden)

    Eileen N. Ariza


    Full Text Available Moore and Kearsley (1996 maintain distance educators should provide for three types of interaction: a learner-content; b learner-instructor; and c learner-learner. According to interactionist second language acquisition (SLA theories that reflect Krashen’s theory (1994 that comprehensible input is critical for second language acquisition, interaction can enhance second language acquisition and fluency. Effective output is necessary as well. We reviewed the research on distance learning for second language learners and concluded that SLA theories can, and should, be the framework that drives the development of courses for students seeking to learn languages by distance technology. This article delineates issues to consider in support of combining SLA theories and research literature as a guide in creating distance language learning courses.

  19. Picasso: A Modular Framework for Visualizing the Learning Process of Neural Network Image Classifiers

    Directory of Open Access Journals (Sweden)

    Ryan Henderson


    Full Text Available Picasso is a free open-source (Eclipse Public License web application written in Python for rendering standard visualizations useful for analyzing convolutional neural networks. Picasso ships with occlusion maps and saliency maps, two visualizations which help reveal issues that evaluation metrics like loss and accuracy might hide: for example, learning a proxy classification task. Picasso works with the Tensorflow deep learning framework, and Keras (when the model can be loaded into the Tensorflow backend. Picasso can be used with minimal configuration by deep learning researchers and engineers alike across various neural network architectures. Adding new visualizations is simple: the user can specify their visualization code and HTML template separately from the application code.

  20. Threat driven modeling framework using petri nets for e-learning system. (United States)

    Khamparia, Aditya; Pandey, Babita


    Vulnerabilities at various levels are main cause of security risks in e-learning system. This paper presents a modified threat driven modeling framework, to identify the threats after risk assessment which requires mitigation and how to mitigate those threats. To model those threat mitigations aspects oriented stochastic petri nets are used. This paper included security metrics based on vulnerabilities present in e-learning system. The Common Vulnerability Scoring System designed to provide a normalized method for rating vulnerabilities which will be used as basis in metric definitions and calculations. A case study has been also proposed which shows the need and feasibility of using aspect oriented stochastic petri net models for threat modeling which improves reliability, consistency and robustness of the e-learning system.

  1. Research progress in machine learning methods for gene-gene interaction detection. (United States)

    Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu


    Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

  2. Progressive practice promotes motor learning and repeated transient increases in corticospinal excitability across multiple days

    DEFF Research Database (Denmark)

    Christiansen, Lasse; Madsen, Mads Alexander Just; Bojsen-Møller, Emil


    Background: A session of motor skill learning is accompanied by transient increases in corticospinal excitability (CSE), which are thought to reflect acute changes in neuronal connectivity associated with improvements in sensorimotor performance. Factors influencing changes in excitability...... and motor skill with continued practice remain however to be elucidated. Objective/Hypothesis: Here we investigate the hypothesis that progressive motor practice during consecutive days can induce repeated transient increases in corticospinal excitability and promote motor skill learning. Methods: Changes...... in motor performance and CSE were assessed during 4 consecutive days of skill learning and 8 days after the last practice session. CSE was assessed as area under recruitment curves (RC) using transcranial magnetic stimulation (TMS). Two groups of participants (n = 12) practiced a visuomotor tracking...

  3. Learning progressions from a sociocultural perspective: response to "co-constructing cultural landscapes for disciplinary learning in and out of school: the next generation science standards and learning progressions in action" (United States)

    Tytler, Russell


    This article discusses a case for a different, socio-cultural way of looking at learning progressions as treated in the next generation science standards (NGSS) as described by Ralph Cordova and Phyllis Balcerzak's paper "Co-constructing cultural landscapes for disciplinary learning in and out of school: the next generation science standards and learning progressions in action". The paper is interesting for a number of reasons, and in this response I will identify different aspects of the paper and link the points made to my own research, and that of colleagues, as complementary perspectives. First, the way that the science curriculum is conceived as an expanding experience that moves from the classroom into the community, across subjects, and across time, links to theoretical positions on disciplinary literacies and notions of learning as apprenticeship into the discursive tools, or `habits of mind' as the authors put it, that underpin disciplinary practice. Second, the formulation of progression through widening communities of practice is a strong feature of the paper, and shows how children take on the role of scientists through this expanding exposure. I will link this approach to some of our own work with school—community science partnerships, drawing on the construct of boundary crossing to tease out relations between school science and professional practice. Third, the demonstration of the expansion of the children's view of what scientists do is well documented in the paper, illustrated by Figure 13 for instance. However I will, in this response, try to draw out and respond to what the paper is saying about the nature of progression; what the progression consists of, over what temporal or spatial dimensions it progresses, and how it can productively frame curriculum processes.

  4. A new unified framework for the early detection of the progression to diabetic retinopathy from fundus images. (United States)

    Leontidis, Georgios


    Human retina is a diverse and important tissue, vastly studied for various retinal and other diseases. Diabetic retinopathy (DR), a leading cause of blindness, is one of them. This work proposes a novel and complete framework for the accurate and robust extraction and analysis of a series of retinal vascular geometric features. It focuses on studying the registered bifurcations in successive years of progression from diabetes (no DR) to DR, in order to identify the vascular alterations. Retinal fundus images are utilised, and multiple experimental designs are employed. The framework includes various steps, such as image registration and segmentation, extraction of features, statistical analysis and classification models. Linear mixed models are utilised for making the statistical inferences, alongside the elastic-net logistic regression, boruta algorithm, and regularised random forests for the feature selection and classification phases, in order to evaluate the discriminative potential of the investigated features and also build classification models. A number of geometric features, such as the central retinal artery and vein equivalents, are found to differ significantly across the experiments and also have good discriminative potential. The classification systems yield promising results with the area under the curve values ranging from 0.821 to 0.968, across the four different investigated combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Conceptual Elements: A Detailed Framework to Support and Assess Student Learning of Biology Core Concepts (United States)

    Cary, Tawnya; Branchaw, Janet


    The Vision and Change in Undergraduate Biology Education: Call to Action report has inspired and supported a nationwide movement to restructure undergraduate biology curricula to address overarching disciplinary concepts and competencies. The report outlines the concepts and competencies generally but does not provide a detailed framework to guide the development of the learning outcomes, instructional materials, and assessment instruments needed to create a reformed biology curriculum. In this essay, we present a detailed Vision and Change core concept framework that articulates key components that transcend subdisciplines and scales for each overarching biological concept, the Conceptual Elements (CE) Framework. The CE Framework was developed using a grassroots approach of iterative revision and incorporates feedback from more than 60 biologists and undergraduate biology educators from across the United States. The final validation step resulted in strong national consensus, with greater than 92% of responders agreeing that each core concept list was ready for use by the biological sciences community, as determined by scientific accuracy and completeness. In addition, we describe in detail how educators and departments can use the CE Framework to guide and document reformation of individual courses as well as entire curricula. PMID:28450444

  6. Interactive Learning in SME-University Collaborations: A Conceptual Framework for Facilitating Interaction

    DEFF Research Database (Denmark)

    Filip, Diane


    . The facilitation process focuses on interactive learning and is divided into phases, which makes it easier for SMEs to progressive engage in innovation projects with researchers. In-depth interviews with the facilitators of the programme were conducted and focused on barriers to collaboration, human interaction......, and lessons learned. From the facilitators’ perspective, a conceptual model capturing the main actor’s activities in each phase paralleled with an illustration of the narrowed gap from the human interaction is presented in the paper. The main findings addressed the issues of human-based and system......-based barriers. One of the lessons learned is the importance of human interaction of narrowing the perceived gap by mitigating the human-based barriers, and to some extent also system-based barriers. The case presented in this paper has managerial and innovation policy implications....

  7. Why Do Chinese College Students Learn ESP: An Analysis of Language Learning Motivations within SDT Framework (United States)

    Liu, Liangxing


    This study mainly investigates the motivational characteristics of Chinese college students learning English for Specific Purposes (ESP). By critically examining and comparing Gardner's (1985) Integrative-Instrumental model and the Self-determination Theory (SDT) by Deci and Ryan(1985), the researcher finds out that the latter one is more…

  8. A pedagogical design pattern framework for sharing experiences and enhancing communities of practice within online and blended learning

    Directory of Open Access Journals (Sweden)

    Chresteria Neutszky-Wulff


    Full Text Available ”Design patterns” were originally proposed in architecture and later in software engineering as a methodology to sketch and share solutions to recurring design problems. In recent years ”pedagogical design patterns” have been introduced as a way to sketch and share good practices in teaching and learning; specifically in the context of technology-enhanced learning (e-learning. Several attempts have been made to establish a framework for describing and sharing such e-learning patterns, but so far they have had limited success. At a series of workshops in a competence-development project for teachers at the University of Copenhagen a new and simpler pedagogical design pattern framework was developed for interfaculty sharing of experiences and enhancing communities of practice in relation to online and blended learning across the university. In this study, the new pedagogical design pattern framework is applied to describe the learning design in four online and blended learning courses within different academic disciplines: Classical Greek, Biostatistics, Environmental Management in Europe, and Climate Change Impacts, Adaptation and Mitigation. Future perspectives for using the framework for developing new E-learning patterns for online and blended learning courses are discussed.

  9. A decision analysis framework for stakeholder involvement and learning in groundwater management (United States)

    Karjalainen, T. P.; Rossi, P. M.; Ala-aho, P.; Eskelinen, R.; Reinikainen, K.; Kløve, B.; Pulido-Velazquez, M.; Yang, H.


    Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision-making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of the MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assessed their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context and the critical issues for the further process.

  10. A Competence-Based Science Learning Framework Illustrated through the Study of Natural Hazards and Disaster Risk Reduction (United States)

    Oyao, Sheila G.; Holbrook, Jack; Rannikmäe, Miia; Pagunsan, Marmon M.


    This article proposes a competence-based learning framework for science teaching, applied to the study of "big ideas", in this case to the study of natural hazards and disaster risk reduction (NH&DRR). The framework focuses on new visions of competence, placing emphasis on nurturing connectedness and behavioral actions toward…

  11. Analytics4Action Evaluation Framework: A Review of Evidence-Based Learning Analytics Interventions at the Open University UK (United States)

    Rienties, Bart; Boroowa, Avinash; Cross, Simon; Kubiak, Chris; Mayles, Kevin; Murphy, Sam


    There is an urgent need to develop an evidence-based framework for learning analytics whereby stakeholders can manage, evaluate, and make decisions about which types of interventions work well and under which conditions. In this article, we will work towards developing a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is…

  12. An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels

    Directory of Open Access Journals (Sweden)

    Gang Zhang


    Full Text Available Objective. This study aims to establish a model to analyze clinical experience of TCM veteran doctors. We propose an ensemble learning based framework to analyze clinical records with ICD-10 labels information for effective diagnosis and acupoints recommendation. Methods. We propose an ensemble learning framework for the analysis task. A set of base learners composed of decision tree (DT and support vector machine (SVM are trained by bootstrapping the training dataset. The base learners are sorted by accuracy and diversity through nondominated sort (NDS algorithm and combined through a deep ensemble learning strategy. Results. We evaluate the proposed method with comparison to two currently successful methods on a clinical diagnosis dataset with manually labeled ICD-10 information. ICD-10 label annotation and acupoints recommendation are evaluated for three methods. The proposed method achieves an accuracy rate of 88.2%  ±  2.8% measured by zero-one loss for the first evaluation session and 79.6%  ±  3.6% measured by Hamming loss, which are superior to the other two methods. Conclusion. The proposed ensemble model can effectively model the implied knowledge and experience in historic clinical data records. The computational cost of training a set of base learners is relatively low.

  13. An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

    Directory of Open Access Journals (Sweden)

    Guanqiu Qi


    Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.

  14. Machine learning & artificial intelligence in the quantum domain: a review of recent progress. (United States)

    Dunjko, Vedran; Briegel, Hans J


    Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and



    Vickerstaff, Rebecca


    Engineering Education experiences turbulent changes, both from government pressures and from industry demands on readdressing the requirements of graduate capability. Despite vast amounts of engineering literature discussing ‘change’ within the field, engineering curricula still maintains its predominant pedagogic model of dissemination to students as it did in previous decades. Technology Enhanced Learning in education has created new and flexible options in the delivery and assessmen...

  16. Introduction of blended learning in a master program: Developing an integrative mixed method evaluation framework. (United States)

    Chmiel, Aviva S; Shaha, Maya; Schneider, Daniel K


    The aim of this research is to develop a comprehensive evaluation framework involving all actors in a higher education blended learning (BL) program. BL evaluation usually either focuses on students, faculty, technological or institutional aspects. Currently, no validated comprehensive monitoring tool exists that can support introduction and further implementation of BL in a higher education context. Starting from established evaluation principles and standards, concepts that were to be evaluated were firstly identified and grouped. In a second step, related BL evaluation tools referring to students, faculty and institutional level were selected. This allowed setting up and implementing an evaluation framework to monitor the introduction of BL during two succeeding recurrences of the program. The results of the evaluation allowed documenting strengths and weaknesses of the BL format in a comprehensive way, involving all actors. It has led to improvements at program, faculty and course level. The evaluation process and the reporting of the results proved to be demanding in time and personal resources. The evaluation framework allows measuring the most significant dimensions influencing the success of a BL implementation at program level. However, this comprehensive evaluation is resource intensive. Further steps will be to refine the framework towards a sustainable and transferable BL monitoring tool that finds a balance between comprehensiveness and efficiency. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. A program wide framework for evaluating data driven teaching and learning - earth analytics approaches, results and lessons learned (United States)

    Wasser, L. A.; Gold, A. U.


    There is a deluge of earth systems data available to address cutting edge science problems yet specific skills are required to work with these data. The Earth analytics education program, a core component of Earth Lab at the University of Colorado - Boulder - is building a data intensive program that provides training in realms including 1) interdisciplinary communication and collaboration 2) earth science domain knowledge including geospatial science and remote sensing and 3) reproducible, open science workflows ("earth analytics"). The earth analytics program includes an undergraduate internship, undergraduate and graduate level courses and a professional certificate / degree program. All programs share the goals of preparing a STEM workforce for successful earth analytics driven careers. We are developing an program-wide evaluation framework that assesses the effectiveness of data intensive instruction combined with domain science learning to better understand and improve data-intensive teaching approaches using blends of online, in situ, asynchronous and synchronous learning. We are using targeted online search engine optimization (SEO) to increase visibility and in turn program reach. Finally our design targets longitudinal program impacts on participant career tracts over time.. Here we present results from evaluation of both an interdisciplinary undergrad / graduate level earth analytics course and and undergraduate internship. Early results suggest that a blended approach to learning and teaching that includes both synchronous in-person teaching and active classroom hands-on learning combined with asynchronous learning in the form of online materials lead to student success. Further we will present our model for longitudinal tracking of participant's career focus overtime to better understand long-term program impacts. We also demonstrate the impact of SEO optimization on online content reach and program visibility.

  18. A semi-supervised learning framework for biomedical event extraction based on hidden topics. (United States)

    Zhou, Deyu; Zhong, Dayou


    Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, due to the lack of explicit structure, literature in life science, one of the most important sources of this information, prevents computer-based systems from accessing. Therefore, biomedical event extraction, automatically acquiring knowledge of molecular events in research articles, has attracted community-wide efforts recently. Most approaches are based on statistical models, requiring large-scale annotated corpora to precisely estimate models' parameters. However, it is usually difficult to obtain in practice. Therefore, employing un-annotated data based on semi-supervised learning for biomedical event extraction is a feasible solution and attracts more interests. In this paper, a semi-supervised learning framework based on hidden topics for biomedical event extraction is presented. In this framework, sentences in the un-annotated corpus are elaborately and automatically assigned with event annotations based on their distances to these sentences in the annotated corpus. More specifically, not only the structures of the sentences, but also the hidden topics embedded in the sentences are used for describing the distance. The sentences and newly assigned event annotations, together with the annotated corpus, are employed for training. Experiments were conducted on the multi-level event extraction corpus, a golden standard corpus. Experimental results show that more than 2.2% improvement on F-score on biomedical event extraction is achieved by the proposed framework when compared to the state-of-the-art approach. The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely

  19. Using Rasch models to develop and validate an environmental thinking learning progression (United States)

    Hashimoto-Martell, Erin A.

    Environmental understanding is highly relevant in today's global society. Social, economic, and political structures are connected to the state of environmental degradation and exploitation, and disproportionately affect those in poor or urban communities (Brulle & Pellow, 2006; Executive Order No. 12898, 1994). Environmental education must challenge the way we live, and our social and ecological quality of life, with the goal of responsible action. The development of a learning progression in environmental thinking, along with a corresponding assessment, could provide a tool that could be used across environmental education programs to help evaluate and guide programmatic decisions. This study sought to determine if a scale could be constructed that allowed individuals to be ordered along a continuum of environmental thinking. First, I developed the Environmental Thinking Learning Progression, a scale of environmental thinking from novice to advanced, based on the current available research and literature. The scale consisted of four subscales, each measuring a different aspect of environmental thinking: place consciousness, human connection, agency, and science concepts. Second, a measurement instrument was developed, so that the data appropriately fit the model using Rasch analysis. A Rasch analysis of the data placed respondents along a continuum, given the range of item difficulty for each subscale. Across three iterations of instrument revision and data collection, findings indicated that the items were ordered in a hierarchical way that corresponded to the construct of environmental thinking. Comparisons between groups showed that the average score of respondents who had participated in environmental education programs was significantly higher than those who had not. A comparison between males and females showed no significant difference in average measure, however, there were varied significant differences between how racial/ethnic groups performed. Overall

  20. A Proposed Framework Between Internal, External and Pedagogy Dimensions in Adoption of Interactive Multimedia e-Learning

    Directory of Open Access Journals (Sweden)

    Fathia LAHWAL


    Full Text Available This study about interactive multimedia e-learning aims to improve our understanding about the dynamics of e-learning. The objective is to critical evaluate and better understand the interrelationships in the proposed framework between internal, external and the pedagogy dimensions in adoption of interactive multimedia and e-learning. It develops a tool to measure creative user adoption of interactive multimedia and e-learning services by using Partial Least Squares algorithm as the method of estimation and the major analytical tool in this study. Finding of a small scale data sampling of students in United Kingdom indicate that the proposed measurement framework is an acceptable fit with the data. Overall, the findings supply a precise tool for measuring creative user adoption of interactive multimedia and e-learning services, providing further insights for researchers and may provide to guide research and practice in interactive multimedia and e-learning by using communication media.

  1. A framework for technological learning in the supply chain: A case study on CdTe photovoltaics

    International Nuclear Information System (INIS)

    Bergesen, Joseph D.; Suh, Sangwon


    Highlights: • A framework for technological learning in the supply chain is proposed. • This framework separates learning effects on value added and intermediate inputs. • Supply-chain learning can project both changing environmental impacts and costs. • Learning upstream in the supply chain can influence observed learning rates. • An example for CdTe photovoltaics illustrates how this framework can be implemented. - Abstract: Accounting for technological changes and innovation is important when assessing the implications of rapidly-developing greenhouse gas (GHG) mitigation technologies. Technological learning curves have been commonly used as a tool to understand technological change as a function of cumulative production. Traditional learning curve approaches, however, do not distinguish the direct and upstream, supply chain technological changes by which cost reductions are achieved. While recent advances in learning curves have focused on distinguishing the different physical and economic drivers of learning, forecasted technological changes have not been applied to estimate the potential changes in the environmental performance of a technology. This article illustrates how distinguishing the different effects of technological learning throughout the supply chain can help assess the changing costs, environmental impacts and natural resource implications of technologies as they develop. We propose a mathematical framework to distinguish the effects of learning on the direct inputs to a technology from the effects of learning on value added, and we incorporate those effects throughout the supply chain of a technology using a life cycle assessment (LCA) framework. An example for cadmium telluride (CdTe) photovoltaics (PV) illustrates how the proposed framework can be implemented. Results show that that life cycle GHG emissions can decrease at least 40% and costs can decrease at least 50% as cumulative production of CdTe reaches 100 GW. Technological

  2. Progressive learning in endoscopy simulation training improves clinical performance: a blinded randomized trial. (United States)

    Grover, Samir C; Scaffidi, Michael A; Khan, Rishad; Garg, Ankit; Al-Mazroui, Ahmed; Alomani, Tareq; Yu, Jeffrey J; Plener, Ian S; Al-Awamy, Mohamed; Yong, Elaine L; Cino, Maria; Ravindran, Nikila C; Zasowski, Mark; Grantcharov, Teodor P; Walsh, Catharine M


    A structured comprehensive curriculum (SCC) that uses simulation-based training (SBT) can improve clinical colonoscopy performance. This curriculum may be enhanced through the application of progressive learning, a training strategy centered on incrementally challenging learners. We aimed to determine whether a progressive learning-based curriculum (PLC) would lead to superior clinical performance compared with an SCC. This was a single-blinded randomized controlled trial conducted at a single academic center. Thirty-seven novice endoscopists were recruited and randomized to either a PLC (n = 18) or to an SCC (n = 19). The PLC comprised 6 hours of SBT, which progressed in complexity and difficulty. The SCC included 6 hours of SBT, with cases of random order of difficulty. Both groups received expert feedback and 4 hours of didactic teaching. Participants were assessed at baseline, immediately after training, and 4 to 6 weeks after training. The primary outcome was participants' performance during their first 2 clinical colonoscopies, as assessed by using the Joint Advisory Group Direct Observation of Procedural Skills assessment tool (JAG DOPS). Secondary outcomes were differences in endoscopic knowledge, technical and communication skills, and global performance in the simulated setting. The PLC group outperformed the SCC group during first and second clinical colonoscopies, measured by JAG DOPS (P PLC group had superior technical and communication skills and global performance in the simulated setting (P  .05). Our findings demonstrate the superiority of a PLC for endoscopic simulation, compared with an SCC. Challenging trainees progressively is a simple, theory-based approach to simulation whereby the performance of clinical colonoscopies can be improved. (Clinical trial registration number: NCT02000180.). Copyright © 2017 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

  3. A unified framework of image latent feature learning on Sina microblog (United States)

    Wei, Jinjin; Jin, Zhigang; Zhou, Yuan; Zhang, Rui


    Large-scale user-contributed images with texts are rapidly increasing on the social media websites, such as Sina microblog. However, the noise and incomplete correspondence between the images and the texts give rise to the difficulty in precise image retrieval and ranking. In this paper, a hypergraph-based learning framework is proposed for image ranking, which simultaneously utilizes visual feature, textual content and social link information to estimate the relevance between images. Representing each image as a vertex in the hypergraph, complex relationship between images can be reflected exactly. Then updating the weight of hyperedges throughout the hypergraph learning process, the effect of different edges can be adaptively modulated in the constructed hypergraph. Furthermore, the popularity degree of the image is employed to re-rank the retrieval results. Comparative experiments on a large-scale Sina microblog data-set demonstrate the effectiveness of the proposed approach.

  4. Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture. (United States)

    Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K


    In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

  5. Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks (United States)

    Karpatne, A.; Kumar, V.


    Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

  6. Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification. (United States)

    Younghak Shin; Balasingham, Ilangko


    Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

  7. Responsibly managing students' learning experiences in student-run clinics: a virtues-based ethical framework. (United States)

    Coverdale, John H; McCullough, Laurence B


    Many medical schools now offer students a distinctive clinical and learning opportunity, the student-run clinic (SRC), in which generalist physicians often play the major role. Although SRCs have become popular, they pose as-yet unexplored ethical challenges for the learning experiences of students. In SRCs students not only take on a significant administrative role especially in coordinating care, but also provide direct patient care for a clinically challenging, biopsychosocially vulnerable, medically indigent population of patients. SRCs provide an exemplar of the ethical challenges of care for such patients. The ethical framework proposed in this article emphasizes that these valued learning opportunities for students should occur in the context of professional formation, with explicit attention to developing the professional virtues, with faculty as role models for these virtues. The valued learning opportunities for students in SRCs should occur in the context of professional formation, with explicit attention to developing the professional virtues of integrity, compassion, self-effacement, self-sacrifice, and courage, which are required for the appropriate care of the vulnerable populations served by SRCs.

  8. Utilization of information communication technology (ICT) - Based training / learning for capacity building in radiation protection framework

    International Nuclear Information System (INIS)

    Oluyemi, I.O.D.


    Full text: Radiation protection is the science of protecting people and the environment from the harmful effects of ionizing radiation, which includes both particle radiation and high energy electromagnetic radiation. It includes occupational radiation protection, which is the protection of workers; medical radiation protection, which is the protection of patients; and public radiation protection, which is about protection of individual members of the public, and of the population as a whole. ICT has made possible the development of e-learning and several Virtual Learning Environments (VLEs) which can support a wide range of capacity building requirements, ranging from under-graduate and post-graduate programmes, continuing professional development courses, right through to short subject specific and research courses, thereby eliminating the problems of conventional forms of training / learning, some of which are: limited access, cost effectiveness and language / cultural barriers. This paper focuses on the utilization of these ICT-based training / learning for capacity building in radiation protection framework and concludes with suggestions on implementation strategies. (author)

  9. The application of language-game theory to the analysis of science learning: Developing an interpretive classroom-level learning framework (United States)

    Ahmadibasir, Mohammad

    In this study an interpretive learning framework that aims to measure learning on the classroom level is introduced. In order to develop and evaluate the value of the framework, a theoretical/empirical study is designed. The researcher attempted to illustrate how the proposed framework provides insights on the problem of classroom-level learning. The framework is developed by construction of connections between the current literature on science learning and Wittgenstein's language-game theory. In this framework learning is defined as change of classroom language-game or discourse. In the proposed framework, learning is measured by analysis of classroom discourse. The empirical explanation power of the framework is evaluated by applying the framework in the analysis of learning in a fifth-grade science classroom. The researcher attempted to analyze how students' colloquial discourse changed to a discourse that bears more resemblance to science discourse. The results of the empirical part of the investigation are presented in three parts: first, the gap between what students did and what they were supposed to do was reported. The gap showed that students during the classroom inquiry wanted to do simple comparisons by direct observation, while they were supposed to do tool-assisted observation and procedural manipulation for a complete comparison. Second, it was illustrated that the first attempt to connect the colloquial to science discourse was done by what was immediately intelligible for students and then the teacher negotiated with students in order to help them to connect the old to the new language-game more purposefully. The researcher suggested that these two events in the science classroom are critical in discourse change. Third, it was illustrated that through the academic year, the way that students did the act of comparison was improved and by the end of the year more accurate causal inferences were observable in classroom communication. At the end of the


    Directory of Open Access Journals (Sweden)

    Noor Azizah


    Full Text Available Perkembangan teknologi saat ini tak bisa dibendung lagi. Kemajuan disetiap bidang tak lepas dari teknologi sebagai penunjangnya, terutama teknologi informasi. Akan tetapi hal tersebut harus dimbangi dengan adanya sebuah evaluasi atau audit terhadap sistem informasi sehingga ancaman atau kerugian dapat  dihindari  ataupun  dicegah.  Penelitian  ini  bertujuan  mengetahui  sejauh  mana  kinerja  sistem informasi pembelajaran yaitu e-learning sebagai layanan publik yang telah diterapkan pada UNISNU Jepara dan  memberikan   rekomendasi tata  kelola perbaikan setelah mengetahui kesenjangan antara tatakelola saat ini dengan tatakelola yang diharapkan sesuai dengan framework yang digunakan. Framework  yang digunakan dalam penelitian ini adalah COBIT versi 4.1 khusus pada domain Deliver and Support (DS. Teknik pengumpulan datanya dilakukan dengan wawancara dan kuisioner dengan narasumber yang telah ditentukan sesuai dengan domain dan Control Objective yang digunakan. Metode analisis data dilakukan beberapa tahap, yaitu penentuan domain, penentuan proses kontrol, penentuan indikator dan pemetaan tingkatkematangan. Hasil dari penelitian ini adalah untuk mengetahui tingkat kematangan (maturity level pada implementasi e-learning UNISNU Jepara khusus pada Domain DS, yaitu berada pada level 4 yang berarti sudah terukur dan terintegrasi antar proses yang berlangsung. Dan analisa GAP antara kondisi yang diharapkan dengan kondisi saat ini rata-rata sebesar 0,6.

  11. A framework for learning and planning against switching strategies in repeated games (United States)

    Hernandez-Leal, Pablo; Munoz de Cote, Enrique; Sucar, L. Enrique


    Intelligent agents, human or artificial, often change their behaviour as they interact with other agents. For an agent to optimise its performance when interacting with such agents, it must be capable of detecting and adapting according to such changes. This work presents an approach on how to effectively deal with non-stationary switching opponents in a repeated game context. Our main contribution is a framework for online learning and planning against opponents that switch strategies. We present how two opponent modelling techniques work within the framework and prove the usefulness of the approach experimentally in the iterated prisoner's dilemma, when the opponent is modelled as an agent that switches between different strategies (e.g. TFT, Pavlov and Bully). The results of both models were compared against each other and against a state-of-the-art non-stationary reinforcement learning technique. Results reflect that our approach obtains competitive results without needing an offline training phase, as opposed to the state-of-the-art techniques.

  12. A pedagogical framework for facilitating parents' learning in nurse-parent partnership. (United States)

    Hopwood, Nick; Clerke, Teena; Nguyen, Anne


    Nursing work increasingly demands forms of expertise that complement specialist knowledge. In child and family nursing, this need arises when nurses work in partnership with parents of young children at risk. Partnership means working with parents in respectful, negotiated and empowering ways. Existing partnership literature emphasises communicative and relational skills, but this paper focuses on nurses' capacities to facilitate parents' learning. Referring to data from home visiting, day-stay and specialist toddler clinic services in Sydney, a pedagogical framework is presented. Analysis shows how nurses notice aspects of children, parents and parent-child interactions as a catalyst for building on parents' strengths, enhancing guided chance or challenging unhelpful constructs. Prior research shows the latter can be a sticking point in partnership, but this paper reveals diverse ways in which challenges are folded into learning process that position parents as agents of positive change. Noticing is dependent on embodied and communicative expertise, conceptualised in terms of sensory and reported channels. The framework offers a new view of partnership as mind-expanding for the parent and specifies the nurse's role in facilitating this process. © 2017 John Wiley & Sons Ltd.

  13. Learner Analysis Framework for Globalized E-Learning: A Case Study

    Directory of Open Access Journals (Sweden)

    Mamta Saxena


    Full Text Available The shift to technology-mediated modes of instructional delivery and increased global connectivity has led to a rise in globalized e-learning programs. Educational institutions face multiple challenges as they seek to design effective, engaging, and culturally competent instruction for an increasingly diverse learner population. The purpose of this study was to explore strategies for expanding learner analysis within the instructional design process to better address cultural influences on learning. A case study approach leveraged the experience of practicing instructional designers to build a framework for culturally competent learner analysis.The study discussed the related challenges and recommended strategies to improve the effectiveness of cross-cultural learner analysis. Based on the findings, a framework for conducting cross-cultural learner analysis to guide the cultural analysis of diverse learners was proposed. The study identified the most critical factors in improving cross-cultural learner analysis as the judicious use of existing research on cross-cultural theories and joint deliberation on the part of all the participants from the management to the learners. Several strategies for guiding and improving the cultural inquiry process were summarized. Barriers and solutions for the requirements are also discussed.

  14. Exploring hypothetical learning progressions for the chemistry of nitrogen and nuclear processes (United States)

    Henry, Deborah McKern

    Chemistry is a bridge that connects a number of scientific disciplines. High school students should be able to determine whether scientific information is accurate, how chemistry applies to daily life, and the mechanism by which systems operate (NRC, 2012). This research focuses on describing hypothetical learning progressions for student understanding of the chemical reactions of nitrogen and nuclear processes and examines whether there is consistency in scientific reasoning between these two distinct conceptual areas. The constant comparative method was used to analyze the written products of students including homework, formative and summative tests, laboratory notebooks, reflective journals, written presentations, and discussion board contributions via Edmodo (an online program). The ten participants were 15 and 16 year old students enrolled in a general high school chemistry course. Instruction took place over a ten week period. The learning progression levels ranged from 0 to 4 and were described as missing, novice, intermediate, proficient, and expert. The results were compared to the standards set by the NRC with a lower anchor (expectations for grade 8) and upper anchor (expectations for grade 12). The results indicate that, on average, students were able to reach an intermediate level of understanding for these concepts.

  15. Artificial grammar learning in vascular and progressive non-fluent aphasias. (United States)

    Cope, Thomas E; Wilson, Benjamin; Robson, Holly; Drinkall, Rebecca; Dean, Lauren; Grube, Manon; Jones, P Simon; Patterson, Karalyn; Griffiths, Timothy D; Rowe, James B; Petkov, Christopher I


    Patients with non-fluent aphasias display impairments of expressive and receptive grammar. This has been attributed to deficits in processing configurational and hierarchical sequencing relationships. This hypothesis had not been formally tested. It was also controversial whether impairments are specific to language, or reflect domain general deficits in processing structured auditory sequences. Here we used an artificial grammar learning paradigm to compare the abilities of controls to participants with agrammatic aphasia of two different aetiologies: stroke and frontotemporal dementia. Ten patients with non-fluent variant primary progressive aphasia (nfvPPA), 12 with non-fluent aphasia due to stroke, and 11 controls implicitly learned a novel mixed-complexity artificial grammar designed to assess processing of increasingly complex sequencing relationships. We compared response profiles for otherwise identical sequences of speech tokens (nonsense words) and tone sweeps. In all three groups the ability to detect grammatical violations varied with sequence complexity, with performance improving over time and being better for adjacent than non-adjacent relationships. Patients performed less well than controls overall, and this was related more strongly to aphasia severity than to aetiology. All groups improved with practice and performed well at a control task of detecting oddball nonwords. Crucially, group differences did not interact with sequence complexity, demonstrating that aphasic patients were not disproportionately impaired on complex structures. Hierarchical cluster analysis revealed that response patterns were very similar across all three groups, but very different between the nonsense word and tone tasks, despite identical artificial grammar structures. Overall, we demonstrate that agrammatic aphasics of two different aetiologies are not disproportionately impaired on complex sequencing relationships, and that the learning of phonological and non

  16. The Predictive Relationship among the Community of Inquiry Framework, Perceived Learning and Online, and Graduate Students' Course Grades in Online Synchronous and Asynchronous Courses (United States)

    Rockinson-Szapkiw, Amanda J.; Wendt, Jillian; Wighting, Mervyn; Nisbet, Deanna


    The Community of Inquiry framework has been widely supported by research to provide a model of online learning that informs the design and implementation of distance learning courses. However, the relationship between elements of the CoI framework and perceived learning warrants further examination as a predictive model for online graduate student…

  17. Making Progress in Content and Language Integrated Learning (CLIL Lessons: An Indonesian Tertiary Context

    Directory of Open Access Journals (Sweden)

    Manafe Novriani Rabeka


    Full Text Available This paper outlines an attempt to discover students’ progress in both content and language skill in a content and language integrated learning (CLIL lessons at an Indonesia’s higher education context. This is a part of a research conducted at Faculty of Science and Technology of Nusa Cendana University in Kupang, East Nusa Tenggara Province. This study employs mixed method approach with 20 participants attending by taking pre-test and post-test as well as joining a focus group interview particularly for 6 students. The tests were aimed at measuring the participants’ comprehension of English as the language of CLIL lesson. They were also used as the tool to evaluate students’ mastery of Mathematics as the content subject. Based on the post-test results, the findings showed that more students made significant progress in content subject in comparison to their achievement in language proficiency. Regarding the interview, the students admitted that their failure to made progress in both subjects were mainly caused by their inadequate level of English. This, therefore, led to rising anxiety among the students to complete the tests.

  18. 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


    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

  19. Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework

    Directory of Open Access Journals (Sweden)

    Juan Carlos Davila


    Full Text Available The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, data losses, and noise, among other experimental constraints, deteriorate data quality and model accuracy. To tackle these issues, this paper presents a data-driven iterative learning framework to classify human locomotion activities such as walk, stand, lie, and sit, extracted from the Opportunity dataset. Data acquired by twelve 3-axial acceleration sensors and seven inertial measurement units are initially de-noised using a two-stage consecutive filtering approach combining a band-pass Finite Impulse Response (FIR and a wavelet filter. A series of statistical parameters are extracted from the kinematical features, including the principal components and singular value decomposition of roll, pitch, yaw and the norm of the axial components. The novel interactive learning procedure is then applied in order to minimize the number of samples required to classify human locomotion activities. Only those samples that are most distant from the centroids of data clusters, according to a measure presented in the paper, are selected as candidates for the training dataset. The newly built dataset is then used to train an SVM multi-class classifier. The latter will produce the lowest prediction error. The proposed learning framework ensures a high level of robustness to variations in the quality of input data, while only using a much lower number of training samples and therefore a much shorter training time, which is an important consideration given the large size of the dataset.

  20. Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework. (United States)

    Davila, Juan Carlos; Cretu, Ana-Maria; Zaremba, Marek


    The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, data losses, and noise, among other experimental constraints, deteriorate data quality and model accuracy. To tackle these issues, this paper presents a data-driven iterative learning framework to classify human locomotion activities such as walk, stand, lie, and sit, extracted from the Opportunity dataset. Data acquired by twelve 3-axial acceleration sensors and seven inertial measurement units are initially de-noised using a two-stage consecutive filtering approach combining a band-pass Finite Impulse Response (FIR) and a wavelet filter. A series of statistical parameters are extracted from the kinematical features, including the principal components and singular value decomposition of roll, pitch, yaw and the norm of the axial components. The novel interactive learning procedure is then applied in order to minimize the number of samples required to classify human locomotion activities. Only those samples that are most distant from the centroids of data clusters, according to a measure presented in the paper, are selected as candidates for the training dataset. The newly built dataset is then used to train an SVM multi-class classifier. The latter will produce the lowest prediction error. The proposed learning framework ensures a high level of robustness to variations in the quality of input data, while only using a much lower number of training samples and therefore a much shorter training time, which is an important consideration given the large size of the dataset.

  1. A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA (United States)

    Nolan, Bernard T.; Fienen, Michael N.; Lorenz, David L.


    We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

  2. Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations. (United States)

    Cario, Clinton L; Witte, John S


    As whole-genome tumor sequence and biological annotation datasets grow in size, number and content, there is an increasing basic science and clinical need for efficient and accurate data management and analysis software. With the emergence of increasingly sophisticated data stores, execution environments and machine learning algorithms, there is also a need for the integration of functionality across frameworks. We present orchid, a python based software package for the management, annotation and machine learning of cancer mutations. Building on technologies of parallel workflow execution, in-memory database storage and machine learning analytics, orchid efficiently handles millions of mutations and hundreds of features in an easy-to-use manner. We describe the implementation of orchid and demonstrate its ability to distinguish tissue of origin in 12 tumor types based on 339 features using a random forest classifier. Orchid and our annotated tumor mutation database are freely available at Software is implemented in python 2.7, and makes use of MySQL or MemSQL databases. Groovy 2.4.5 is optionally required for parallel workflow execution. Supplementary data are available at Bioinformatics online.

  3. Self-Regulated Learning: The Continuous-Change Conceptual Framework and a Vision of New Paradigm, Technology System, and Pedagogical Support (United States)

    Huh, Yeol; Reigeluth, Charles M.


    A modified conceptual framework called the Continuous-Change Framework for self-regulated learning (SRL) is presented. Common elements and limitations among the past frameworks are discussed in relation to the modified conceptual framework. The iterative nature of the goal setting process and overarching presence of self-efficacy and motivational…

  4. Use of the challenge point framework to guide motor learning of stepping reactions for improved balance control in people with stroke: a case series. (United States)

    Pollock, Courtney L; Boyd, Lara A; Hunt, Michael A; Garland, S Jayne


    Stepping reactions are important for walking balance and community-level mobility. Stepping reactions of people with stroke are characterized by slow reaction times, poor coordination of motor responses, and low amplitude of movements, which may contribute to their decreased ability to recover their balance when challenged. An important aspect of rehabilitation of mobility after stroke is optimizing the motor learning associated with retraining effective stepping reactions. The Challenge Point Framework (CPF) is a model that can be used to promote motor learning through manipulation of conditions of practice to modify task difficulty, that is, the interaction of the skill of the learner and the difficulty of the task to be learned. This case series illustrates how the retraining of multidirectional stepping reactions may be informed by the CPF to improve balance function in people with stroke. Four people (53-68 years of age) with chronic stroke (>1 year) and mild to moderate motor recovery received 4 weeks of multidirectional stepping reaction retraining. Important tenets of motor learning were optimized for each person during retraining in accordance with the CPF. Participants demonstrated improved community-level walking balance, as determined with the Community Balance and Mobility Scale. These improvements were evident 1 year later. Aspects of balance-related self-efficacy and movement kinematics also showed improvements during the course of the intervention. The application of CPF motor learning principles in the retraining of stepping reactions to improve community-level walking balance in people with chronic stroke appears to be promising. The CPF provides a plausible theoretical framework for the progression of functional task training in neurorehabilitation.

  5. A Comprehensive Probabilistic Framework to Learn Air Data from Surface Pressure Measurements

    Directory of Open Access Journals (Sweden)

    Ankur Srivastava


    Full Text Available Use of probabilistic techniques has been demonstrated to learn air data parameters from surface pressure measurements. Integration of numerical models with wind tunnel data and sequential experiment design of wind tunnel runs has been demonstrated in the calibration of a flush air data sensing anemometer system. Development and implementation of a metamodeling method, Sequential Function Approximation (SFA, are presented which lies at the core of the discussed probabilistic framework. SFA is presented as a tool capable of nonlinear statistical inference, uncertainty reduction by fusion of data with physical models of variable fidelity, and sequential experiment design. This work presents the development and application of these tools in the calibration of FADS for a Runway Assisted Landing Site (RALS control tower. However, the multidisciplinary nature of this work is general in nature and is potentially applicable to a variety of mechanical and aerospace engineering problems.

  6. Sustainability indicator system and policy processes in Malaysia: a framework for utilisation and learning. (United States)

    Hezri, A A


    Formulation of effective sustainability indicators for national assessment demands a comprehensive understanding of the utilisation, diffusion and dissemination of information in policy processes. To illustrate the dynamic of sustainability assessment within the context of policy processes, this paper uses a case study of national sustainability indicators development in Malaysia. Subsequently, this paper ascribes the limited achievement of national sustainability assessment in Malaysia to four types of constraints: meta-policy issues; technical capacities; communication concerns; and the inherent knowledge gaps within the indicator developer community vis-a-vis their theoretical limitations. It is proposed that such constraints will be encountered in many countries. Drawing from the literature on public policy, this paper outlines a framework for investigating indicator behaviour within policy processes based on well-established concepts such as knowledge utilisation and policy learning. I conclude this paper by elaborating on the corresponding future challenges that must be addressed before effective integration of sustainability indicators within policy systems can occur.

  7. Statistical and Machine-Learning Classifier Framework to Improve Pulse Shape Discrimination System Design

    Energy Technology Data Exchange (ETDEWEB)

    Wurtz, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kaplan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)


    Pulse shape discrimination (PSD) is a variety of statistical classifier. Fully-­realized statistical classifiers rely on a comprehensive set of tools for designing, building, and implementing. PSD advances rely on improvements to the implemented algorithm. PSD advances can be improved by using conventional statistical classifier or machine learning methods. This paper provides the reader with a glossary of classifier-­building elements and their functions in a fully-­designed and operational classifier framework that can be used to discover opportunities for improving PSD classifier projects. This paper recommends reporting the PSD classifier’s receiver operating characteristic (ROC) curve and its behavior at a gamma rejection rate (GRR) relevant for realistic applications.

  8. How can ergonomic practitioners learn to practice a macro-ergonomic framework developed in academia?

    DEFF Research Database (Denmark)

    Broberg, Ole; Seim, Rikke; Andersen, Vibeke


    How can a macro-ergonomic framework developed in academia be “transferred” to ergonomic practitioners and become a new work practice? The purpose of this paper is to reflect upon experiences from an interactive research program in which this transferral was tested by two consecutive approaches......” with the researchers and other practitioners; 3) paying attention to the organizational settings of the ergonomic practitioner to make sure that a new work practice is implemented in the organization and not only by a single practitioner....... and interpretation of results when applying the new concept to a real case in a company; 2) the concept is introduced to practitioners, after which they try to practice the concept in a normal consultancy situation, and afterwards have the opportunity to reflect upon their experiences in a “learning space...

  9. What and how do students learn in an interprofessional student-run clinic? An educational framework for teambased care


    Lie, Désirée A.; Forest, Christopher P.; Walsh, Anne; Banzali, Yvonne; Lohenry, Kevin


    Background: The student-run clinic (SRC) has the potential to address interprofessional learning among health professions students.Purpose: To derive a framework for understanding student learning during team-based care provided in an interprofessional SRC serving underserved patients.Methods: The authors recruited students for a focus group study by purposive sampling and snowballing. They constructed two sets of semi-structured questions for uniprofessional and multiprofessional groups. Ses...

  10. Remote Laboratories Framework : Focus on Reusability and Security in m-Learning Situations

    Directory of Open Access Journals (Sweden)

    Jeremy Lardon


    Full Text Available Remote laboratories is a spreading concept which allows the remote use of devices through Internet connexion. The paper deals with the providing of a framework which is reusable for many devices, from different end-user media such as phone, computer or TV and acceptable in industry, therefore taking into account multi information systems securities. The problem is addressed through the point of view of m-learning situations which involves the lack of rich user interactions and the fact that the user belongs to external information systems when he interacts with the remote device. The modelisation of the remote device with ontologies, the use of a central application server, message oriented middleware and standard web services (database, authentication are the keys allowing the independence of the framework to the device. The adaptation of the GUI to the end-user device is made through a proxy which refactor the requests and responses according to the capabilities of the end-user device (size of screen, interactions tools. The use of a user-centric model of identities federation allows us to provide an efficient way to reach the goal of transparency to security constraints.

  11. Using Communication Technology to Facilitate Scientific Literacy: A Framework for Engaged Learning (United States)

    VanBuskirk, Shireen Adele

    The purpose of this research project is to describe how existing communication technologies are used to foster scientific literacy for secondary students. This study develops a new framework as an analytic tool to categorize the activities of teachers and students involved in scientific literacy to describe what elements of scientific literacy are facilitated by such technologies. Four case studies are analyzed using the framework to describe the scientific literacy initiatives. Data collection at each site included interviews with the teacher, student focus groups, student surveys, and classroom observations. Qualitative analysis of the data provided insight into the learning activities and student experiences in the four cases. This study intentionally provides a platform for student voice. Very few previous empirical studies in the area of scientific literacy include the student experience. This represents a significant gap in the current literature on scientific literacy. An interpretation of scientific literacy that promotes student engagement, interaction, and initiative corresponds to a need to listen to students' perspectives on these experiences. Findings of the study indicated that the classroom activities depended on the teacher's philosophy regarding scientific literacy. Communication technology was ubiquitous; where the teacher did not initiate the use of social media in the classroom, the students did. The goal of supporting scientific literacy in students is an objective that extends beyond the boundaries of classroom walls, and it can be facilitated by technologies that seem both abundant and underutilized. Technology-enhanced pedagogy altered the classroom practices and resulted in more student participation and engagement.

  12. A multidimensional framework of conceptual change for developing chemical equilibrium learning (United States)

    Chanyoo, Wassana; Suwannoi, Paisan; Treagust, David F.


    The purposes of this research is to investigate the existing chemical equilibrium lessons in Thailand based on the multidimensional framework of conceptual change, to determine how the existing lessons could enhance students' conceptual change. This research was conducted based on qualitative perspective. Document, observations and interviews were used to collect data. To comprehend all students conceptions, diagnostic tests were applied comprised of The Chemical Equilibrium Diagnostic Test (the CEDT) and The Chemical Equilibrium Test for Reveal Conceptual Change (the CETforRCC). In addition, to study students' motivations, the Motivated Strategies for Learning Questionnaire (the MSLQ) and students' task engagement were applied. Following each perspective of conceptual change - ontological, epistemological, and social/affective - the result showed that the existing chemical equilibrium unit did not enhance students' conceptual change, and some issues were found. The problems obstructed students conceptual change should be remedy under the multidimensional framework of conceptual change. Finally, some suggestions were provided to enhance students' conceptual change in chemical equilibrium effectively

  13. A Self-Learning Sensor Fault Detection Framework for Industry Monitoring IoT

    Directory of Open Access Journals (Sweden)

    Yu Liu


    Full Text Available Many applications based on Internet of Things (IoT technology have recently founded in industry monitoring area. Thousands of sensors with different types work together in an industry monitoring system. Sensors at different locations can generate streaming data, which can be analyzed in the data center. In this paper, we propose a framework for online sensor fault detection. We motivate our technique in the context of the problem of the data value fault detection and event detection. We use the Statistics Sliding Windows (SSW to contain the recent sensor data and regress each window by Gaussian distribution. The regression result can be used to detect the data value fault. Devices on a production line may work in different workloads and the associate sensors will have different status. We divide the sensors into several status groups according to different part of production flow chat. In this way, the status of a sensor is associated with others in the same group. We fit the values in the Status Transform Window (STW to get the slope and generate a group trend vector. By comparing the current trend vector with history ones, we can detect a rational or irrational event. In order to determine parameters for each status group we build a self-learning worker thread in our framework which can edit the corresponding parameter according to the user feedback. Group-based fault detection (GbFD algorithm is proposed in this paper. We test the framework with a simulation dataset extracted from real data of an oil field. Test result shows that GbFD detects 95% sensor fault successfully.

  14. Modeling Plan-Related Clinical Complications Using Machine Learning Tools in a Multiplan IMRT Framework

    International Nuclear Information System (INIS)

    Zhang, Hao H.; D'Souza, Warren D.; Shi Leyuan; Meyer, Robert R.


    Purpose: To predict organ-at-risk (OAR) complications as a function of dose-volume (DV) constraint settings without explicit plan computation in a multiplan intensity-modulated radiotherapy (IMRT) framework. Methods and Materials: Several plans were generated by varying the DV constraints (input features) on the OARs (multiplan framework), and the DV levels achieved by the OARs in the plans (plan properties) were modeled as a function of the imposed DV constraint settings. OAR complications were then predicted for each of the plans by using the imposed DV constraints alone (features) or in combination with modeled DV levels (plan properties) as input to machine learning (ML) algorithms. These ML approaches were used to model two OAR complications after head-and-neck and prostate IMRT: xerostomia, and Grade 2 rectal bleeding. Two-fold cross-validation was used for model verification and mean errors are reported. Results: Errors for modeling the achieved DV values as a function of constraint settings were 0-6%. In the head-and-neck case, the mean absolute prediction error of the saliva flow rate normalized to the pretreatment saliva flow rate was 0.42% with a 95% confidence interval of (0.41-0.43%). In the prostate case, an average prediction accuracy of 97.04% with a 95% confidence interval of (96.67-97.41%) was achieved for Grade 2 rectal bleeding complications. Conclusions: ML can be used for predicting OAR complications during treatment planning allowing for alternative DV constraint settings to be assessed within the planning framework.

  15. Self-Efficacy, Achievement Motivation, and Academic Progress of Students with Learning Disabilities: A Comparison with Typical Students

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    Sepideh Seyed


    Full Text Available Introduction Many factors including self-efficacy and achievement motivation can affect children’s academic progress. Studies have shown that socioeconomic status can affect people’s life, education, and vocation. However, not many studies looked at the relations between the intrinsic factors and socioeconomic status, and between these 2 categories and students’ academic progress in children with learning disabilities. Thus, the present study aimed at examining self-efficacy, achievement motivation, and academic progress of students with learning disabilities compared with typical students and looking for any possible relation between these variables and socioeconomic status (parental education and occupation. Methods This was a cross sectional study, which included 34 students with learning disabilities and 32 typical students matched on age, gender, and school grade. The participants answered Sherer et al.’s self-efficacy scale (1982 and Herman’s achievement motivation questionnaire (2000. Students’ academic progress was evaluated based on the descriptive scores in the first semester. Findings Scores of children with learning disabilities in self-efficacy, achievement motivation, and academic progress were significantly lower than those of matched controls (P<0.0001. Results revealed moderate positive correlations between academic progress and different levels of self-efficacy (rs = 0.441, P<0.0001, N = 66; and between academic progress and achievement motivation (rs = 0.645, P<0.0001, N = 66. The results of the correlation analysis demonstrated weak to moderate positive correlations between academic progress and parental education (rs = 0.39, P = 0.001, academic progress and father’s occupation (rs = 0.323, P = 0.008, achievement motivation and parental education (rs = .34, p = 0.009, N = 66, and finally achievement motivation and father’s occupation (rs = 0.285, P = 0.02, N = 66. Conclusions Lower levels of self-efficacy and


    Directory of Open Access Journals (Sweden)

    A. Scherbyna


    Full Text Available The article considers usage of Moodle learning management system for current progress and attendance tracking of full time students. Evaluation systems, which are used in universities of Ukraine, are analyzed. Their basis in most cases is point accumulation system, which is useful for manual calculation of final grades at the end of the semester, but it is not useful for comparison of current students’ achievements at different subjects or achievements at any time during the semester. Also this system is not useful for putting current grades, because teaches often have to use unusual grade scales which are different from 5-point system. Because of that it is proposed to use mathematically equivalent weighted average grade, which allows to avoid mentioned disadvantages. Questions of implementation of proposed system are considered by means of gradebook of Moodle learning management system. Attendance accounting module is considered and method of using subcourse module for attendance and grades shared data import in course gradebook, where student’s rating is calculated for all disciplines is proposed.

  17. Legitimate Peripheral Participation as a Framework for Conversation Analytic Work in Second Language Learning

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    Gitte Rasmussen Hougaard


    Full Text Available Since its inception, Conversation Analysis (CA has become not only a framework and a set of methods for studying the generic machinery of talk-in-interaction but also a celebrated, qualitative method for studying a wealth of phenomena and exploring and testing concepts and hypotheses from numerous disciplines, including linguistics, psychology, anthropology and Second Language Acquisition (SLA. CA is often resorted to as the key to resolving knots and dead-ends in these neighboring disciplines. Despite the very interesting results that such work admittedly produces, it is too often not accompanied by focused considerations of how the specific concerns from one field match with the aims that CA procedures have been developed for and hence with the procedures themselves. This paper takes recent applications of CA to the study of SLA as a case in point. It discusses a whether CA can shed light on "learning" as commonly defined in SLA and b whether the resort to a particular model of learning (LAVE & WENGER, 1991, Legitimate Peripheral Participation (LPP helps overcoming some of the problems with which CA work in SLA is confronted. It is hoped that the specific discussions of problems involved in the project, CA-for-SLA, will contribute to the ongoing, general discussion of qualitative research methods and their prospects and problems. URN: urn:nbn:de:0114-fqs090247

  18. Automatic Depth Extraction from 2D Images Using a Cluster-Based Learning Framework. (United States)

    Herrera, Jose L; Del-Blanco, Carlos R; Garcia, Narciso


    There has been a significant increase in the availability of 3D players and displays in the last years. Nonetheless, the amount of 3D content has not experimented an increment of such magnitude. To alleviate this problem, many algorithms for converting images and videos from 2D to 3D have been proposed. Here, we present an automatic learning-based 2D-3D image conversion approach, based on the key hypothesis that color images with similar structure likely present a similar depth structure. The presented algorithm estimates the depth of a color query image using the prior knowledge provided by a repository of color + depth images. The algorithm clusters this database attending to their structural similarity, and then creates a representative of each color-depth image cluster that will be used as prior depth map. The selection of the appropriate prior depth map corresponding to one given color query image is accomplished by comparing the structural similarity in the color domain between the query image and the database. The comparison is based on a K-Nearest Neighbor framework that uses a learning procedure to build an adaptive combination of image feature descriptors. The best correspondences determine the cluster, and in turn the associated prior depth map. Finally, this prior estimation is enhanced through a segmentation-guided filtering that obtains the final depth map estimation. This approach has been tested using two publicly available databases, and compared with several state-of-the-art algorithms in order to prove its efficiency.

  19. Information processing in illness representation: Implications from an associative-learning framework. (United States)

    Lowe, Rob; Norman, Paul


    The common-sense model (Leventhal, Meyer, & Nerenz, 1980) outlines how illness representations are important for understanding adjustment to health threats. However, psychological processes giving rise to these representations are little understood. To address this, an associative-learning framework was used to model low-level process mechanics of illness representation and coping-related decision making. Associative learning was modeled within a connectionist network simulation. Two types of information were paired: Illness identities (indigestion, heart attack, cancer) were paired with illness-belief profiles (cause, timeline, consequences, control/cure), and specific illness beliefs were paired with coping procedures (family doctor, emergency services, self-treatment). To emulate past experience, the network was trained with these pairings. As an analogue of a current illness event, the trained network was exposed to partial information (illness identity or select representation beliefs) and its response recorded. The network (a) produced the appropriate representation profile (beliefs) for a given illness identity, (b) prioritized expected coping procedures, and (c) highlighted circumstances in which activated representation profiles could include self-generated or counterfactual beliefs. Encoding and activation of illness beliefs can occur spontaneously and automatically; conventional questionnaire measurement may be insensitive to these automatic representations. Furthermore, illness representations may comprise a coherent set of nonindependent beliefs (a schema) rather than a collective of independent beliefs. Incoming information may generate a "tipping point," dramatically changing the active schema as a new illness-knowledge set is invoked. Finally, automatic activation of well-learned information can lead to the erroneous interpretation of illness events, with implications for [inappropriate] coping efforts. (PsycINFO Database Record (c) 2017 APA, all

  20. Learning Frameworks for Cooperative Spectrum Sensing and Energy-Efficient Data Protection in Cognitive Radio Networks

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    Vinh Quang Do


    Full Text Available This paper studies learning frameworks for energy-efficient data communications in an energy-harvesting cognitive radio network in which secondary users (SUs harvest energy from solar power while opportunistically accessing a licensed channel for data transmission. The SUs perform spectrum sensing individually, and send local decisions about the presence of the primary user (PU on the channel to a fusion center (FC. We first design a new cooperative spectrum-sensing technique based on a convolutional neural network in which the FC uses historical sensing data to train the network for classification problem. The system is assumed to operate in a time-slotted manner. At the beginning of each time slot, the FC uses the current local decisions as input for the trained network to decide whether the PU is active or not in that time slot. In addition, legitimate transmissions can be vulnerable to a hidden eavesdropper, which always passively listens to the communication. Therefore, we further propose a transfer learning actor–critic algorithm for an SU to decide its operation mode to increase the security level under the constraint of limited energy. In this approach, the SU directly interacts with the environment to learn its dynamics (i.e., an arrival of harvested energy; then, the SU can either stay idle to save energy or transmit to the FC secured data that are encrypted using a suitable private-key encryption method to maximize the long-term effective security level of the network. We finally present numerical simulation results under various configurations to evaluate our proposed schemes.

  1. The Application of SECI Model as a Framework of Knowledge Creation in Virtual Learning: Case Study of IUST Virtual Classes (United States)

    Hosseini, Seyede Mehrnoush


    The research aims to define SECI model of knowledge creation (socialization, externalization, combination, and internalization) as a framework of Virtual class management which can lead to better online teaching-learning mechanisms as well as knowledge creation. It has used qualitative research methodology including researcher's close observation…

  2. Introducing a New Learning and Teaching Evaluation Planning Framework for Small Internally Funded Projects in Higher Education (United States)

    Huber, Elaine


    Scholarly evaluation practices in learning and teaching projects are under-reported in the literature. In order for robust evaluative measures to be implemented, a project requires a well-designed evaluation plan. This research study describes the development of a practical evaluation planning framework through an action research approach, using…

  3. Using Campinha-Bacote's Framework to Examine Cultural Competence from an Interdisciplinary International Service Learning Program (United States)

    Wall-Bassett, Elizabeth DeVane; Hegde, Archana Vasudeva; Craft, Katelyn; Oberlin, Amber Louise


    The purpose of this study was to investigate an interdisciplinary international service learning program and its impact on student sense of cultural awareness and competence using the Campinha-Bacote's (2002) framework of cultural competency model. Seven undergraduate and one graduate student from Human Development and Nutrition Science…

  4. Promoting Socially Shared Metacognitive Regulation in Collaborative Project-Based Learning: A Framework for the Design of Structured Guidance (United States)

    Kim, Dongho; Lim, Cheolil


    Despite the emergence of collaborative project-based learning in higher education settings, how it can be supported has received little attention. We noted the positive impact of socially shared metacognitive regulation on students' collaboration processes. The purpose of this study was to present a framework for the design and implementation of…

  5. Can Children and Young People "Learn from" Atheism for Spiritual Development? A Response to the National Framework for Religious Education (United States)

    Watson, Jacqueline


    The new National Framework for Religious Education (RE) suggests, for the first time in national advice on agreed syllabuses, that atheism can be included in the curriculum alongside world religions. This article counters objections to the inclusion of atheism in RE and argues that children and young people can learn from atheistic beliefs and…

  6. Perry's Scheme of Intellectual and Epistemological Development as a Framework for Describing Student Difficulties in Learning Organic Chemistry (United States)

    Grove, Nathaniel P.; Bretz, Stacey Lowery


    We have investigated student difficulties with the learning of organic chemistry. Using Perry's Model of Intellectual Development as a framework revealed that organic chemistry students who function as dualistic thinkers struggle with the complexity of the subject matter. Understanding substitution/elimination reactions and multi-step syntheses is…

  7. Preparing Teacher-Students for Twenty-First-Century Learning Practices (PREP 21): A Framework for Enhancing Collaborative Problem-Solving and Strategic Learning Skills (United States)

    Häkkinen, Päivi; Järvelä, Sanna; Mäkitalo-Siegl, Kati; Ahonen, Arto; Näykki, Piia; Valtonen, Teemu


    With regard to the growing interest in developing teacher education to match the twenty-first-century skills, while many assumptions have been made, there has been less theoretical elaboration and empirical research on this topic. The aim of this article is to present our pedagogical framework for the twenty-first-century learning practices in…

  8. The Significance of Trust in the Political System and Motivation for Pupils' Learning Progress in Politics Lessons (United States)

    Landwehr, Barbara; Weisseno, Georg


    Very little research has been conducted on the contribution of political education to learning progress in Germany. Hence, there is a need for intervention studies measuring performance against the theoretical background of a political competence model. This model comprises three constructs: subject knowledge, motivation and attitudes. According…

  9. A Canine Audience: The Effect of Animal-Assisted Therapy on Reading Progress among Students Identified with Learning Disabilities (United States)

    Griess, Julie Omodio


    This study explored the use of animal-assisted therapy with students identified with a learning disability and limited reading success. Initially, reading progress was defined as the participants' comprehension rate obtained from an oral Informal Reading Inventory (IRI) passage. The nature of the Informal Reading Inventory requires the…

  10. Evaluating mobile learning practice. Towards a framework for analysis of user-generated contexts with reference to the socio-cultural ecology of mobile learning

    Directory of Open Access Journals (Sweden)

    Judith Seipold


    Full Text Available Against the conceptual and theoretical background of a socio-culturally orientated approach to mobile learning (Pachler, Bachmair and Cook, 2010, this paper examines the evaluation of user-generated contexts by referring to an example from the use of mobile phones in schools. We discuss how mobile device-related, user- generated contexts around structures, agency and cultural practices might be brought into a fruitful relationship with institution-based learning. And, we provide categories for evaluating the use of mobile devices to generate meaning from and with fragmented and discontinuous media and modes at the interface of learning in formal, institutionalised and informal, self-directed settings. The evaluation criteria build on the framework of a socio-cultural ecology of mobile learning developed by the London Mobile Learning Group.

  11. A Critical Review of the Use of Wenger's Community of Practice (CoP) Theoretical Framework in Online and Blended Learning Research, 2000-2014 (United States)

    Smith, Sedef Uzuner; Hayes, Suzanne; Shea, Peter


    After presenting a brief overview of the key elements that underpin Etienne Wenger's communities of practice (CoP) theoretical framework, one of the most widely cited and influential conceptions of social learning, this paper reviews extant empirical work grounded in this framework to investigate online/blended learning in higher education and in…

  12. A deep learning framework for financial time series using stacked autoencoders and long-short term memory. (United States)

    Bao, Wei; Yue, Jun; Rao, Yulei


    The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

  13. A deep learning framework for financial time series using stacked autoencoders and long-short term memory (United States)

    Bao, Wei; Rao, Yulei


    The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

  14. Integration of a framework with a learning management system for detection, assessment and assistance of university students with reading difficulties

    Directory of Open Access Journals (Sweden)

    Carolina Mejía Corredor


    Full Text Available Rev.esc.adm.neg Dyslexia is a common learning disability in Spanish-speaking university students, and requires special attention from higher educational institutions in order to support affected individuals during their learning process. In previous studies, a framework to detect, assess and assist university students with reading difficulties related to dyslexia was developed. In this paper, the integration of this framework with a Learning Management System (LMS is presented. Two case studies were performed to test the functionality and the usability of this integration. The first case study was carried out with 20 students, while the second one with four teachers. The results show that both students and teachers were satisfied with the integration performed in Moodle.ce, among others.

  15. A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

    Directory of Open Access Journals (Sweden)

    Wei Bao

    Full Text Available The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT, stacked autoencoders (SAEs and long-short term memory (LSTM are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

  16. A stacking ensemble learning framework for annual river ice breakup dates (United States)

    Sun, Wei; Trevor, Bernard


    River ice breakup dates (BDs) are not merely a proxy indicator of climate variability and change, but a direct concern in the management of local ice-caused flooding. A framework of stacking ensemble learning for annual river ice BDs was developed, which included two-level components: member and combining models. The member models described the relations between BD and their affecting indicators; the combining models linked the predicted BD by each member models with the observed BD. Especially, Bayesian regularization back-propagation artificial neural network (BRANN), and adaptive neuro fuzzy inference systems (ANFIS) were employed as both member and combining models. The candidate combining models also included the simple average methods (SAM). The input variables for member models were selected by a hybrid filter and wrapper method. The performances of these models were examined using the leave-one-out cross validation. As the largest unregulated river in Alberta, Canada with ice jams frequently occurring in the vicinity of Fort McMurray, the Athabasca River at Fort McMurray was selected as the study area. The breakup dates and candidate affecting indicators in 1980-2015 were collected. The results showed that, the BRANN member models generally outperformed the ANFIS member models in terms of better performances and simpler structures. The difference between the R and MI rankings of inputs in the optimal member models may imply that the linear correlation based filter method would be feasible to generate a range of candidate inputs for further screening through other wrapper or embedded IVS methods. The SAM and BRANN combining models generally outperformed all member models. The optimal SAM combining model combined two BRANN member models and improved upon them in terms of average squared errors by 14.6% and 18.1% respectively. In this study, for the first time, the stacking ensemble learning was applied to forecasting of river ice breakup dates, which appeared

  17. Progressive paradoxical sleep deprivation impairs partial memory following learning tasks in rats

    Institute of Scientific and Technical Information of China (English)

    Chunmin Zhu; Xiangrong Yao; Weisheng Zhang; Yanfeng Song; Yiping Hou


    BACKGROUND: Complex learning tasks result in a greater number of paradoxical sleep phases, which can improve memory. The effect of paradoxical sleep deprivation, induced by "flower pot" technique, on spatial reference memory and working memory require further research. OBJECTIVE: To observe the effect of progressive paradoxical sleep deprivation in rats, subsequent to learning, on memory using the Morris Water Maze. DESIGN, TIME AND SETTING: Controlled observation experiment. The experiment was performed at the Laboratory of Neurobiology, Department of Anatomy, Histology and Embryology, School of Basic Medical Sciences, Lanzhou University from December 2006 to October 2007. MATERIALS: Twenty-eight, male, Wistar rats, 3-4 months old, were provided by the Experimental Animal Center of Lanzhou University. The Morris Water Maze and behavioral analyses system was purchased from Genheart Company, Beijing, China. METHODS: All animals, according to a random digits table, were randomly divided into paradoxical sleep deprivation, tank control, and home cage control groups. Paradoxical sleep deprivation was induced by the "flower pot" technique for 72 hours, housing the rats on small platforms over water. Rats in the "tank control" and "home cage control" groups were housed either in a tank with large platforms over the water or in normal cages without paradoxical sleep deprivation. MAIN OUTCOME MEASURES: Morris Water Maze was employed for task learning and spatial memory testing. Rats in all groups were placed at six random starting points each day for four consecutive days. Each placement was repeated for two trials; the first trial represented reference memory and the second working memory. Rats in the first trial were allowed to locate the submerged platform within 120 seconds. Data, including swimming distance, escape latency, swimming velocity, percentage of time in correct quarter, and memory scores were recorded and analyzed automatically by behavioral analyses

  18. Carbon Monitoring System Applications Framework: Lessons Learned from Stakeholder Engagement Activities (United States)

    Sepulveda Carlo, E.; Escobar, V. M.; Delgado Arias, S.; Forgotson, C.


    forestry, conservation, and ecosystem services applications in the tristate area of Maryland, Delaware and Pennsylvania. The presentation will discuss the applications framework methodology and strategy, as well as highlight some of the results and lessons learned from these applications efforts.

  19. Evaluating the Quality of Competency Assessment in Pharmacy: A Framework for Workplace Learning

    Directory of Open Access Journals (Sweden)

    Shailly Shah


    Full Text Available Demonstration of achieved competencies is critical in the pharmacy workplace. The purpose of this study was to evaluate the quality of the competency assessment program for pharmacy residents at an academic medical center. The competency assessment program (CAP survey is a validated, 48-item instrument that evaluates the quality of an assessment program based on 12 criteria, each measured by four questions on a scale of 0 to 100. The CAP was completed by residents (n = 23 and preceptors (n = 28 from the pharmacy residency program between 2010 and 2013. Results were analyzed using descriptive statistics, Cronbach’s alpha, and non-parametric tests. Educational Consequences was the only quality criteria falling below the standard for “good quality.” Participants that completed residency training elsewhere rated the Comparability (0.04 and Meaningfulness (0.01 of the assessment program higher than those that completed residency at the academic medical center. There were no significant differences between resident and preceptor scores. Overall, the quality of the assessment program was rated highly by residents and preceptors. The process described here provides a useful framework for understanding the quality of workplace learning assessments in pharmacy practice.

  20. A deep learning framework for supporting the classification of breast lesions in ultrasound images (United States)

    Han, Seokmin; Kang, Ho-Kyung; Jeong, Ja-Yeon; Park, Moon-Ho; Kim, Wonsik; Bang, Won-Chul; Seong, Yeong-Kyeong


    In this research, we exploited the deep learning framework to differentiate the distinctive types of lesions and nodules in breast acquired with ultrasound imaging. A biopsy-proven benchmarking dataset was built from 5151 patients cases containing a total of 7408 ultrasound breast images, representative of semi-automatically segmented lesions associated with masses. The dataset comprised 4254 benign and 3154 malignant lesions. The developed method includes histogram equalization, image cropping and margin augmentation. The GoogLeNet convolutionary neural network was trained to the database to differentiate benign and malignant tumors. The networks were trained on the data with augmentation and the data without augmentation. Both of them showed an area under the curve of over 0.9. The networks showed an accuracy of about 0.9 (90%), a sensitivity of 0.86 and a specificity of 0.96. Although target regions of interest (ROIs) were selected by radiologists, meaning that radiologists still have to point out the location of the ROI, the classification of malignant lesions showed promising results. If this method is used by radiologists in clinical situations it can classify malignant lesions in a short time and support the diagnosis of radiologists in discriminating malignant lesions. Therefore, the proposed method can work in tandem with human radiologists to improve performance, which is a fundamental purpose of computer-aided diagnosis.

  1. A Machine-Learning and Filtering Based Data Assimilation Framework for Geologic Carbon Sequestration Monitoring Optimization (United States)

    Chen, B.; Harp, D. R.; Lin, Y.; Keating, E. H.; Pawar, R.


    Monitoring is a crucial aspect of geologic carbon sequestration (GCS) risk management. It has gained importance as a means to ensure CO2 is safely and permanently stored underground throughout the lifecycle of a GCS project. Three issues are often involved in a monitoring project: (i) where is the optimal location to place the monitoring well(s), (ii) what type of data (pressure, rate and/or CO2 concentration) should be measured, and (iii) What is the optimal frequency to collect the data. In order to address these important issues, a filtering-based data assimilation procedure is developed to perform the monitoring optimization. The optimal monitoring strategy is selected based on the uncertainty reduction of the objective of interest (e.g., cumulative CO2 leak) for all potential monitoring strategies. To reduce the computational cost of the filtering-based data assimilation process, two machine-learning algorithms: Support Vector Regression (SVR) and Multivariate Adaptive Regression Splines (MARS) are used to develop the computationally efficient reduced-order-models (ROMs) from full numerical simulations of CO2 and brine flow. The proposed framework for GCS monitoring optimization is demonstrated with two examples: a simple 3D synthetic case and a real field case named Rock Spring Uplift carbon storage site in Southwestern Wyoming.

  2. Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework (United States)

    Wang, Weibao; Overall, Gary; Riggs, Travis; Silveston-Keith, Rebecca; Whitney, Julie; Chiu, George; Allebach, Jan P.


    Assessment of macro-uniformity is a capability that is important for the development and manufacture of printer products. Our goal is to develop a metric that will predict macro-uniformity, as judged by human subjects, by scanning and analyzing printed pages. We consider two different machine learning frameworks for the metric: linear regression and the support vector machine. We have implemented the image quality ruler, based on the recommendations of the INCITS W1.1 macro-uniformity team. Using 12 subjects at Purdue University and 20 subjects at Lexmark, evenly balanced with respect to gender, we conducted subjective evaluations with a set of 35 uniform b/w prints from seven different printers with five levels of tint coverage. Our results suggest that the image quality ruler method provides a reliable means to assess macro-uniformity. We then defined and implemented separate features to measure graininess, mottle, large area variation, jitter, and large-scale non-uniformity. The algorithms that we used are largely based on ISO image quality standards. Finally, we used these features computed for a set of test pages and the subjects' image quality ruler assessments of these pages to train the two different predictors - one based on linear regression and the other based on the support vector machine (SVM). Using five-fold cross-validation, we confirmed the efficacy of our predictor.

  3. Developing an integrated framework of problem-based learning and coaching psychology for medical education: a participatory research. (United States)

    Wang, Qing; Li, Huiping; Pang, Weiguo; Liang, Shuo; Su, Yiliang


    Medical schools have been making efforts to develop their own problem-based learning (PBL) approaches based on their educational conditions, human resources and existing curriculum structures. This study aimed to explore a new framework by integrating the essential features of PBL and coaching psychology applicable to the undergraduate medical education context. A participatory research design was employed. Four educational psychology researchers, eight undergraduate medical school students and two accredited PBL tutors participated in a four-month research programme. Data were collected through participatory observation, focus groups, semi-structured interviews, workshop documents and feedback surveys and then subjected to thematic content analysis. The triangulation of sources and member checking were used to ensure the credibility and trustworthiness of the research process. Five themes emerged from the analysis: current experience of PBL curriculum; the roles of and relationships between tutors and students; student group dynamics; development of self-directed learning; and coaching in PBL facilitation. On the basis of this empirical data, a systematic model of PBL and coaching psychology was developed. The findings highlighted that coaching psychology could be incorporated into the facilitation system in PBL. The integrated framework of PBL and coaching psychology in undergraduate medical education has the potential to promote the development of the learning goals of cultivating clinical reasoning ability, lifelong learning capacities and medical humanity. Challenges, benefits and future directions for implementing the framework are discussed in this paper.

  4. Academic Progress Depending on the Skills and Qualities of Learning in Students of a Business School (United States)

    de Jesús, Araiza Vázquez María; Claudia, Dörfer; Rosalinda, Castillo Corpus


    This research was to establish the relationship between qualities of learning; learning skills and academic performance in undergraduate students. 310 undergraduates participated in this research of which 72% are female and 28% male. All responded Scale Learning Strategies of Roman and Gallego (1994) and Questionnaire Learning Styles of…

  5. The discipline of hospital development: a conceptual framework incorporating marketing, managerial, consumer behavior, and adult learning theories. (United States)

    Shirley, S; Stampfl, R


    The purpose of this explanatory and prescriptive article is to identify interdisciplinary theories used by hospital development to direct its practice. The article explores, explains, and applies theories and principles from behavioral, social, and managerial disciplines. Learning, motivational, organizational, marketing, and attitudinal theories are incorporated and transformed into the fundamental components of a conceptual framework that provides an overview of the practice of hospital development. How this discipline incorporates these theories to design, explain, and prescribe the focus of its own practice is demonstrated. This interdisciplinary approach results in a framework for practice that is adaptable to changing social, cultural, economic, political, and technological environments.

  6. Virtual Learning Ecosystems: A Proposed Framework for Integrating Educational Games, E-Learning Methods, and Virtual Community Platforms (United States)

    Washington, Christopher


    Digitally delivered learning shows the promise of enhancing learner motivation and engagement, advancing critical thinking skills, encouraging reflection and knowledge sharing, and improving professional self-efficacy. Digital learning objects take many forms including interactive media, apps and games, video and other e-learning activities and…

  7. Evaluation of iTunes University Courses through Instructional Design Strategies and m-Learning Framework (United States)

    Tseng, Hung Wei; Tang, Yingqi; Morris, Betty


    As mobile learning technology promotes learning accessibility and flexibility, students benefit from social interactivity and connective learning process which will also foster students' performance and satisfaction on learning content. The primary purpose of this research was to evaluate iTunes U courses based on instructional design strategies…

  8. Self-Regulated Workplace Learning: A Pedagogical Framework and Semantic Web-Based Environment (United States)

    Siadaty, Melody; Gasevic, Dragan; Jovanovic, Jelena; Pata, Kai; Milikic, Nikola; Holocher-Ertl, Teresa; Jeremic, Zoran; Ali, Liaqat; Giljanovic, Aleksandar; Hatala, Marek


    Self-regulated learning processes have a potential to enhance the motivation of knowledge workers to take part in learning and reflection about learning, and thus contribute to the resolution of an important research challenge in workplace learning. An equally important research challenge for the successful completion of each step of a…

  9. A Conceptual Framework for Organizing Active Learning Experiences in Biology Instruction (United States)

    Gardner, Joel; Belland, Brian R.


    Introductory biology courses form a cornerstone of undergraduate instruction. However, the predominantly used lecture approach fails to produce higher-order biology learning. Research shows that active learning strategies can increase student learning, yet few biology instructors use all identified active learning strategies. In this paper, we…

  10. Development and Validation of a Learning Analytics Framework: Two Case Studies Using Support Vector Machines (United States)

    Ifenthaler, Dirk; Widanapathirana, Chathuranga


    Interest in collecting and mining large sets of educational data on student background and performance to conduct research on learning and instruction has developed as an area generally referred to as learning analytics. Higher education leaders are recognizing the value of learning analytics for improving not only learning and teaching but also…

  11. Il workshop in architettura. Un processo di apprendimento in progress / The Workshop in Architecture. A learning process in progress

    Directory of Open Access Journals (Sweden)

    João Barros Matos


    Full Text Available Si riconosce che il workshop costituisce un modello dinamico di apprendimento, in continua evoluzione e sperimentazione, e in grado di essere costantemente riformulato per giungere a nuove e stimolanti situazioni per insegnare la pratica dell'architettura. Si tratta infatti di un modello particolarmente adatto alla ricerca di un approccio globale e coerente al progetto architettonico, dato che evita di separare gli argomenti in frammenti isolati nel processo progettuale. Riunire i gruppi di lavoro nello stesso spazio e nel tempo limitato a disposizione richiede un pensiero intenso e un ritmo di produzione che aiuta a migliorare il rapporto tra i riferimenti teorici riportabili al soggetto trattato e gli aspetti relativi all'elaborazione e alla comunicazione del progetto architettonico. / We recognize the workshop as a dynamic model of learning, which is continuously changing and experimenting, and is able to be constantly redesigned to achieve new and stimulating situations for teaching the practice of architecture. In fact it is a particularly suitable model for seeking a global and coherent approach to the architectural project, while avoiding separating the topics into isolated fragments, throughout the project’s process. Bringing work teams together in the same space and within a reduced time limit requires intensive thought and a rhythm of production which helps improve the relation between the theoretical references of the subject’s production and the aspects related to producing work and communication elements for the architectural project.

  12. Conceptual Frameworks for the Workplace Change Adoption Process: Elements Integration from Decision Making and Learning Cycle Process. (United States)

    Radin Umar, Radin Zaid; Sommerich, Carolyn M; Lavender, Steve A; Sanders, Elizabeth; Evans, Kevin D


    Sound workplace ergonomics and safety-related interventions may be resisted by employees, and this may be detrimental to multiple stakeholders. Understanding fundamental aspects of decision making, behavioral change, and learning cycles may provide insights into pathways influencing employees' acceptance of interventions. This manuscript reviews published literature on thinking processes and other topics relevant to decision making and incorporates the findings into two new conceptual frameworks of the workplace change adoption process. Such frameworks are useful for thinking about adoption in different ways and testing changes to traditional intervention implementation processes. Moving forward, it is recommended that future research focuses on systematic exploration of implementation process activities that integrate principles from the research literature on sensemaking, decision making, and learning processes. Such exploration may provide the groundwork for development of specific implementation strategies that are theoretically grounded and provide a revised understanding of how successful intervention adoption processes work.

  13. Employability and Related Context Prediction Framework for University Graduands: A Machine Learning Approach

    Directory of Open Access Journals (Sweden)

    Manushi P. Wijayapala


    Full Text Available In Sri Lanka (SL, graduands’ employability remains a national issue due to the increasing number of graduates produced by higher education institutions each year. Thus, predicting the employability of university graduands can mitigate this issue since graduands can identify what qualifications or skills they need to strengthen up in order to find a job of their desired field with a good salary, before they complete the degree. The main objective of the study is to discover the plausibility of applying machine learning approach efficiently and effectively towards predicting the employability and related context of university graduands in Sri Lanka by proposing an architectural framework which consists of four modules; employment status prediction, job salary prediction, job field prediction and job relevance prediction of graduands while also comparing performance of classification algorithms under each prediction module. Series of machine learning algorithms such as C4.5, Naïve Bayes and AODE have been experimented on the Graduand Employment Census - 2014 data. A pre-processing step is proposed to overcome challenges embedded in graduand employability data and a feature selection process is proposed in order to reduce computational complexity. Additionally, parameter tuning is also done to get the most optimized parameters. More importantly, this study utilizes several types of Sampling (Oversampling, Undersampling and Ensemble (Bagging, Boosting, RF techniques as well as a newly proposed hybrid approach to overcome the limitations caused by the class imbalance phenomena. For the validation purposes, a wide range of evaluation measures was used to analyze the effectiveness of applying classification algorithms and class imbalance mitigation techniques on the dataset. The experimented results indicated that RandomForest has recorded the highest classification performance for 3 modules, achieving the selected best predictive models under hybrid

  14. Design and development of a learning progression about stellar structure and evolution

    Directory of Open Access Journals (Sweden)

    Arturo Colantonio


    Full Text Available [This paper is part of the Focused Collection on Astronomy Education Research.] In this paper we discuss the design and development of a learning progression (LP to describe and interpret students’ understanding about stellar structure and evolution (SSE. The LP is built upon three content dimensions: hydrostatic equilibrium; composition and aggregation state; functioning and evolution. The data to build up the levels of the hypothetical LP (LP1 came from a 45-minute, seven-question interview, with 33 high school students previously taught about the topic. The questions were adapted from an existing multiple-choice instrument. Data were analyzed using Minstrell’s “facets” approach. To assess the validity of LP1, we designed a twelve-hour teaching module featuring paper-and-pencil tasks and practical activities to estimate the stellar structure and evolution parameters. Twenty high school students were interviewed before and after the activities using the same interview protocol. Results informed a revision of LP1 (LP2 and, in parallel, of the module. The revised module included supplementary activities corresponding to changes made to LP1. We then assessed LP2 with 30 high school students through the same interview, submitted before and after the teaching intervention. A final version of the LP (LP3 was then developed drawing on students’ emerging reasoning strategies. This paper contributes to research in science education by providing an example of the iterative development of the instruction required to support the student thinking that LPs’ levels describe. Concerning astronomy education research, our findings can inform suitable instructional activities more responsive to students’ reasoning strategies about stellar structure and evolution.

  15. Effect of Topography on Learning Military Tactics - Integration of Generalized Intelligent Framework for Tutoring (GIFT) and Augmented REality Sandtable (ARES) (United States)


    Dunleavy M, Dede C. Augmented reality teaching and learning. Handbook of research on educational communications and technology . New York (NY): Springer...taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems. 1994;77(12):1321–1329. Noordzij ML, Scholten P, Laroy-Noordzij...Generalized Intelligent Framework for Tutoring (GIFT) and Augmented REality Sandtable (ARES) by Michael W Boyce, Ramsamooj J Reyes, Deeja E Cruz, Charles

  16. SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media. (United States)

    Liu, Jing; Zhao, Songzheng; Wang, Gang


    With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., drug indication and beneficial effect) could hold between the drug and adverse event mentions, making ADE relation extraction - distinguishing ADE relationship from other relation types - necessary. However, conducting ADE relation extraction in social media environment is not a trivial task because of the expertise-dependent, time-consuming and costly annotation process, and the feature space's high-dimensionality attributed to intrinsic characteristics of social media data. This study aims to develop a framework for ADE relation extraction using patient-generated content in social media with better performance than that delivered by previous efforts. To achieve the objective, a general semi-supervised ensemble learning framework, SSEL-ADE, was developed. The framework exploited various lexical, semantic, and syntactic features, and integrated ensemble learning and semi-supervised learning. A series of experiments were conducted to verify the effectiveness of the proposed framework. Empirical results demonstrate the effectiveness of each component of SSEL-ADE and reveal that our proposed framework outperforms most of existing ADE relation extraction methods The SSEL-ADE can facilitate enhanced ADE relation extraction performance, thereby providing more reliable support for pharmacovigilance. Moreover, the proposed semi-supervised ensemble methods have the potential of being applied to effectively deal with other social media-based problems. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Can Creativity Be Assessed? Towards an Evidence-Informed Framework for Assessing and Planning Progress in Creativity (United States)

    Blamires, Mike; Peterson, Andrew


    This article considers the role of constructions of creativity in the classroom and their consequences for learning and, in particular, for the assessment of creativity. Definitions of creativity are examined to identify key implications for supporting the development of children's creativity within the classroom. The implications of assessing…

  18. Designing for Learning and Play - The Smiley Model as a Framework

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    is relevant to the professional creation of small digital learning games as well as the big Game [3], that is, the learning and play situations that exist surrounding the use of small learning games, when students discuss, negotiate, develop, and decide what to do next inside the learning games. The desired...... balance is lost if the learning processes become shallow – at a low level of cognitive complexity – though it may be great fun [4]. Conversely, a game may facilitate good learning processes and many learning activities but result in low motivation among students because it is considered boring.......When seeking to create ideal learning environments for students and teachers, it can be a challenge to find a balance between facilitating learning processes at high levels of cognitive complexity [1] and creating playful and engaging experiences for students and teachers [2]. This challenge...

  19. From Field Notes to Data Portal - A Scalable Data QA/QC Framework for Tower Networks: Progress and Preliminary Results (United States)

    Sturtevant, C.; Hackley, S.; Lee, R.; Holling, G.; Bonarrigo, S.


    Quality assurance and control (QA/QC) is one of the most important yet challenging aspects of producing research-quality data. Data quality issues are multi-faceted, including sensor malfunctions, unmet theoretical assumptions, and measurement interference from humans or the natural environment. Tower networks such as Ameriflux, ICOS, and NEON continue to grow in size and sophistication, yet tools for robust, efficient, scalable QA/QC have lagged. Quality control remains a largely manual process heavily relying on visual inspection of data. In addition, notes of measurement interference are often recorded on paper without an explicit pathway to data flagging. As such, an increase in network size requires a near-proportional increase in personnel devoted to QA/QC, quickly stressing the human resources available. We present a scalable QA/QC framework in development for NEON that combines the efficiency and standardization of automated checks with the power and flexibility of human review. This framework includes fast-response monitoring of sensor health, a mobile application for electronically recording maintenance activities, traditional point-based automated quality flagging, and continuous monitoring of quality outcomes and longer-term holistic evaluations. This framework maintains the traceability of quality information along the entirety of the data generation pipeline, and explicitly links field reports of measurement interference to quality flagging. Preliminary results show that data quality can be effectively monitored and managed for a multitude of sites with a small group of QA/QC staff. Several components of this framework are open-source, including a R-Shiny application for efficiently monitoring, synthesizing, and investigating data quality issues.

  20. A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval. (United States)

    Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev


    Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming

  1. A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD). (United States)

    Mumtaz, Wajid; Ali, Syed Saad Azhar; Yasin, Mohd Azhar Mohd; Malik, Aamir Saeed


    Major depressive disorder (MDD), a debilitating mental illness, could cause functional disabilities and could become a social problem. An accurate and early diagnosis for depression could become challenging. This paper proposed a machine learning framework involving EEG-derived synchronization likelihood (SL) features as input data for automatic diagnosis of MDD. It was hypothesized that EEG-based SL features could discriminate MDD patients and healthy controls with an acceptable accuracy better than measures such as interhemispheric coherence and mutual information. In this work, classification models such as support vector machine (SVM), logistic regression (LR) and Naïve Bayesian (NB) were employed to model relationship between the EEG features and the study groups (MDD patient and healthy controls) and ultimately achieved discrimination of study participants. The results indicated that the classification rates were better than chance. More specifically, the study resulted into SVM classification accuracy = 98%, sensitivity = 99.9%, specificity = 95% and f-measure = 0.97; LR classification accuracy = 91.7%, sensitivity = 86.66%, specificity = 96.6% and f-measure = 0.90; NB classification accuracy = 93.6%, sensitivity = 100%, specificity = 87.9% and f-measure = 0.95. In conclusion, SL could be a promising method for diagnosing depression. The findings could be generalized to develop a robust CAD-based tool that may help for clinical purposes.

  2. A Framework for Process Reengineering in Higher Education: A case study of distance learning exam scheduling and distribution

    Directory of Open Access Journals (Sweden)

    M'hammed Abdous


    Full Text Available In this paper, we propose a conceptual and operational framework for process reengineering (PR in higher education (HE institutions. Using a case study aimed at streamlining exam scheduling and distribution in a distance learning (DL unit, we outline a sequential and non-linear four-step framework designed to reengineer processes. The first two steps of this framework – initiating and analyzing – are used to initiate, document, and flowchart the process targeted for reengineering, and the last two steps – reengineering/ implementing and evaluating – are intended to prototype, implement, and evaluate the reengineered process. Our early involvement of all stakeholders, and our in-depth analysis and documentation of the existing process, allowed us to avoid the traditional pitfalls associated with business process reengineering (BPR. Consequently, the outcome of our case study indicates a streamlined and efficient process with a higher faculty satisfaction at substantial cost reduction.

  3. The progress and challenges of implementation of the Framework Convention on Tobacco Control (WHO FCTC) in Kyrgyz Republic


    Chinara Bekbasarova


    Background and challenges to implementation The Kyrgyz Republic is Party of the WHO FCTC since August 23, 2006. This abstract analyzes progress and challenges during 10 years of implementation of WHO´s FCTC Intervention or response National Tobacco Control (TC) Law was adopted on August 21, 2006, entered into force on December 19, 2006 and was amended and supplemented during 10 years 2 times. TC measures were included, as one of main priorities, in the National Program on Heal...

  4. A transfer learning framework for traffic video using neuro-fuzzy ...

    Indian Academy of Sciences (India)

    P M Ashok Kumar


    Aug 4, 2017 ... The proposed ANFIS-LCTE transfer learning model consists of four steps. (1) Low level visual items .... algorithm clusters object trajectories based on the distance parameters like Euclidean ..... Machine Learning, pp. 113–120.

  5. The MVP Model as an Organizing Framework for Neuroscience Findings Related to Learning (United States)

    Zakrajsek, Todd M.


    This chapter describes the ways in which the MVP model relates to recent research on neuroscience and learning, and demonstrates how those relationships may be used to better understand physiological impacts on motivation, and to facilitate improved learning.


    Directory of Open Access Journals (Sweden)

    Adi Suryani


    Full Text Available Family and school are not separated social institution. Many parents view that it is schools and teachers which and who should be responsible for their children education. These views should be challenged by arising concern and awareness of parents and teachers of the importance of shared responsibility and cooperativeness. Parents are responsible for laying the basic/foundation of children’s learning, basic values, moral education, and basic social learning. Teachers and schools bear responsibility for developing those basic education. During their learning at school, students have a chance to develop their social competence. School also can be environment where children are gradually learning to be adult learners. They can be adult learners through engaging in collaborative learning activities. Through this social learning, children can learn develop social concern and sensitivity. Moreover, they can develop their learning through experience.

  7. Enhancing Collaborative Learning in Web 2.0-Based E-Learning Systems: A Design Framework for Building Collaborative E-Learning Contents (United States)

    El Mhouti, Abderrahim; Nasseh, Azeddine; Erradi, Mohamed; Vasquèz, José Marfa


    Today, the implication of Web 2.0 technologies in e-learning allows envisaging new teaching and learning forms, advocating an important place to the collaboration and social interaction. However, in e-learning systems, learn in a collaborative way is not always so easy because one of the difficulties when arranging e-learning courses can be that…

  8. From eLearning to Digital Transformation: A Framework and Implications for L&D


    Seufert, Sabine; Meier, Christoph


    How can the learning function (L&D) support learning and innovation ability of the entire organization in times of digital transformation? The core challenges for the learning function are twofold. Competence clarification: What are relevant “digital competences” in terms of knowledge, skills and attitudes that employees need in order to cope with digital transformation? Competence development: How to organize, design and support learning processes contributing to digital competences and digi...

  9. The Learning of Grammar: An Experimental Study. Experimental Studies on the Learning of Language, Progress Report II, Revised. (United States)

    Torrey, Jane W.

    An experiment in language behavior comparing two methods of learning grammatical word order in a new language presents scientific evidence supporting the use of pattern drills in foreign language teaching. The experiment reviews the performance of three groups attempting to learn small segments of Russian "microlanguage": (1) a drill group learned…

  10. Building a world-wide open source community around a software framework: progress, dos, and don'ts (United States)

    Ibsen, Jorge; Antognini, Jonathan; Avarias, Jorge; Caproni, Alessandro; Fuessling, Matthias; Gimenez, Guillermo; Verma, Khushbu; Mora, Matias; Schwarz, Joseph; Staig, Tomás.


    As we all know too well, building up a collaborative community around a software infrastructure is not easy. Besides recruiting enthusiasts to work as part of it, mostly for free, to succeed you also need to overcome a number of technical, sociological, and, to our surprise, some political hurdles. The ALMA Common Software (ACS) was developed at ESO and partner institutions over the course of more than 10 years. While it was mainly intended for the ALMA Observatory, it was early on thought as a generic distributed control framework. ACS has been periodically released to the public through an LGPL license, which encouraged around a dozen non-ALMA institutions to make use of ACS for both industrial and educational applications. In recent years, the Cherenkov Telescope Array and the LLAMA Observatory have also decided to adopt the framework for their own control systems. The aim of the "ACS Community" is to support independent initiatives in making use of the ACS framework and to further contribute to its development. The Community provides access to a growing network of volunteers eager to develop ACS in areas that are not necessarily in ALMA's interests, and/or were not within the original system scope. Current examples are: support for additional OS platforms, extension of supported hardware interfaces, a public code repository and a build farm. The ACS Community makes use of existing collaborations with Chilean and Brazilian universities, reaching out to promising engineers in the making. At the same time, projects actively using ACS have committed valuable resources to assist the Community's work. Well established training programs like the ACS Workshops are also being continued through the Community's work. This paper aims to give a detailed account of the ongoing (second) journey towards establishing a world-wide open source collaboration around ACS. The ACS Community is growing into a horizontal partnership across a decentralized and diversified group of

  11. A Framework to Support Global Corporate M-Learning: Learner Initiative and Technology Acceptance across Cultures (United States)

    Farrell, Wendy


    Corporations are growing more and more international and accordingly need to train and develop an increasingly diverse and dispersed employee based. M-learning seems like it may be the solution if it can cross cultures. Learner initiative has been shown to be a disadvantage of distant learning environments, which would include m-learning.…

  12. Revisiting the Blended Learning Literature: Using a Complex Adaptive Systems Framework (United States)

    Wang, Yuping; Han, Xibin; Yang, Juan


    This research has two aims: (1) to bridge a gap in blended learning research--the lack of a systems approach to the understanding of blended learning research and practice, and (2) to promote a more comprehensive understanding of what has been achieved and what needs to be achieved in blended learning research and practice. To achieve these aims,…

  13. A Framework for Institutional Adoption and Implementation of Blended Learning in Higher Education (United States)

    Graham, Charles R.; Woodfield, Wendy; Harrison, J. Buckley


    There has been rapid growth in blended learning implementation and research focused on course-level issues such as improved learning outcomes, but very limited research focused on institutional policy and adoption issues. More institutional-level blended learning research is needed to guide institutions of higher education in strategically…

  14. A Framework for Collaborative and Convenient Learning on Cloud Computing Platforms (United States)

    Sharma, Deepika; Kumar, Vikas


    The depth of learning resides in collaborative work with more engagement and fun. Technology can enhance collaboration with a higher level of convenience and cloud computing can facilitate this in a cost effective and scalable manner. However, to deploy a successful online learning environment, elementary components of learning pedagogy must be…

  15. Learning Barriers: a framework for the examination of structural impediments to organizational change

    NARCIS (Netherlands)

    Schimmel, R.; Schimmel, Remco; Muntslag, Dennis R.


    The body of knowledge on organizational learning is believed to be large and fragmented. Therefore, this knowledge seems to be of limited use to practitioners. We, however, present an alternative review of the most important publications on organizational learning that deals explicitly with learning

  16. A Social-Cognitive Framework for Pedagogical Agents as Learning Companions (United States)

    Kim, Yanghee; Baylor, Amy L.


    Teaching and learning are highly social activities. Seminal psychologists such as Vygotsky, Piaget, and Bandura have theorized that social interaction is a key mechanism in the process of learning and development. In particular, the benefits of peer interaction for learning and motivation in classrooms have been broadly demonstrated through…

  17. A Constructionism Framework for Designing Game-Like Learning Systems: Its Effect on Different Learners (United States)

    Li, Zhong-Zheng; Cheng, Yuan-Bang; Liu, Chen-Chung


    Game-like learning systems such as simulation games and digital toys are increasingly being applied to foster higher-level abilities in educational contexts, as they may facilitate an active learning experience. However, the effect of such game-like learning systems is not guaranteed because students may only be interested in the fantasy…

  18. Mobile-Assisted Second Language Learning: Developing a Learner-Centered Framework (United States)

    Leow, Choy Khim; Yahaya, Wan Ahmad Jaafar Wan; Samsudin, Zarina


    The Mobile Assisted Language Learning concept has offered infinite language learning opportunities since its inception 20 years ago. Second Language Acquisition however embraces a considerably different body of knowledge from first language learning. While technological advances have optimized the psycholinguistic environment for language…

  19. A Pedagogical Framework for Mobile Learning: Categorizing Educational Applications of Mobile Technologies into Four Types (United States)

    Park, Yeonjeong


    Instructional designers and educators recognize the potential of mobile technologies as a learning tool for students and have incorporated them into the distance learning environment. However, little research has been done to categorize the numerous examples of mobile learning in the context of distance education, and few instructional design…

  20. Classification Framework for ICT-Based Learning Technologies for Disabled People (United States)

    Hersh, Marion


    The paper presents the first systematic approach to the classification of inclusive information and communication technologies (ICT)-based learning technologies and ICT-based learning technologies for disabled people which covers both assistive and general learning technologies, is valid for all disabled people and considers the full range of…

  1. Ubiquitous Knowledge Construction: Mobile Learning Re-Defined and a Conceptual Framework (United States)

    Peng, Hsinyi; Su, Yi-Ju; Chou, Chien; Tsai, Chin-Chung


    Emerging from recent mobile technologies, mobile learning, or m-learning, is beginning to offer "stunning new technical capabilities" in education (DiGiano et al., 2003). This new genre of learning is viewed as a revolutionary stage in educational technology. However, ubiquitous computing technologies have given rise to several issues. This…

  2. Teacher design knowledge for technology enhanced learning: a framework for investigating assets and needs

    NARCIS (Netherlands)

    McKenney, Susan; Kali, Y.; Mauiskaite, L.; Voogt, Joke


    Design of (technology-enhanced) learning activities and materials is one fruitful process through which teachers learn and become professionals. To facilitate this process, research is needed to understand how teachers learn through design, how this process may be supported, and how teacher

  3. Offering a Framework for Value Co-Creation in Virtual Academic Learning Environments (United States)

    Ranjbarfard, Mina; Heidari Sureshjani, Mahboobeh


    Purpose: This research aims to convert the traditional teacher-student models, in which teachers determine the learning resources, into a flexible structure and an active learning environment so that students can participate in the educational processes and value co-creation in virtual academic learning environments (VALEs).…

  4. Building an Inclusive Definition of E-Learning: An Approach to the Conceptual Framework (United States)

    Sangra, Albert; Vlachopoulos, Dimitrios; Cabrera, Nati


    E-learning is part of the new dynamic that characterises educational systems at the start of the 21st century. Like society, the concept of e-learning is subject to constant change. In addition, it is difficult to come up with a single definition of e-learning that would be accepted by the majority of the scientific community. The different…

  5. A Framework for Adaptive Learning Design in a Web-Conferencing Environment (United States)

    Bower, Matt


    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…

  6. Goal rationalities as a framework for evaluating the learning potential of the workplace.

    NARCIS (Netherlands)

    Nieuwenhuis, Loek; van Woerkom, M.


    There is conflicting empirical evidence regarding the learning potential of the workplace. Some studies conclude that workplaces should be seen as strong learning environments, whereas others show evidence of the ineffectiveness of the workplace as a learning environment. In this article, we argue

  7. More than "Continuing Professional Development": A Proposed New Learning Framework for Professional Accountants (United States)

    Lindsay, Hilary


    This paper explores literature relating to continuing professional development (CPD) and lifelong learning to develop an understanding of how the learning landscape has evolved in recent years, both in the accountancy profession and more widely. Three different perspectives on learning are drawn together and this synthesis is used to develop a…

  8. Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task. (United States)

    Wirzberger, Maria; Esmaeili Bijarsari, Shirin; Rey, Günter Daniel


    Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing. Copyright © 2017 Elsevier B.V. All rights reserved.


    Directory of Open Access Journals (Sweden)

    Tel'noy Viktor Ivanovich


    Full Text Available Development of computer-assisted computer technologies and their integration into the academic activity with a view to the control of the academic performance within the framework of distance learning programmes represent the subject matter of the article. The article is a brief overview of the software programme designated for the monitoring of the academic performance of students enrolled in distance learning programmes. The software is developed on Delphi 7.0 for Windows operating system. The strength of the proposed software consists in the availability of the two modes of its operation that differ in the principle of the problem selection and timing parameters. Interim academic performance assessment is to be performed through the employment of computerized testing procedures that contemplate the use of a data base of testing assignments implemented in the eLearning Server media. Identification of students is to be performed through the installation of video cameras at workplaces of students.



    Vladimir Tatochenko; Andrii Shypko


    The article is devoted to theoretical substantiation of modern methodical system of Mathematics teaching of poor progressing secondary school pupils. A systematic approach to the study of psycho-pedagogical determinants of poor progress of pupils in math was implemented. The dynamic of interfunctional relationship of structure of educational and informative sphere of poor progressing pupils in mathematics was disclosed and scientific understanding of this process was expanded. The introducti...

  11. Exploring Middle School Students' Representational Competence in Science: Development and Verification of a Framework for Learning with Visual Representations (United States)

    Tippett, Christine Diane

    Scientific knowledge is constructed and communicated through a range of forms in addition to verbal language. Maps, graphs, charts, diagrams, formulae, models, and drawings are just some of the ways in which science concepts can be represented. Representational competence---an aspect of visual literacy that focuses on the ability to interpret, transform, and produce visual representations---is a key component of science literacy and an essential part of science reading and writing. To date, however, most research has examined learning from representations rather than learning with representations. This dissertation consisted of three distinct projects that were related by a common focus on learning from visual representations as an important aspect of scientific literacy. The first project was the development of an exploratory framework that is proposed for use in investigations of students constructing and interpreting multimedia texts. The exploratory framework, which integrates cognition, metacognition, semiotics, and systemic functional linguistics, could eventually result in a model that might be used to guide classroom practice, leading to improved visual literacy, better comprehension of science concepts, and enhanced science literacy because it emphasizes distinct aspects of learning with representations that can be addressed though explicit instruction. The second project was a metasynthesis of the research that was previously conducted as part of the Explicit Literacy Instruction Embedded in Middle School Science project (Pacific CRYSTAL, Five overarching themes emerged from this case-to-case synthesis: the engaging and effective nature of multimedia genres, opportunities for differentiated instruction using multimodal strategies, opportunities for assessment, an emphasis on visual representations, and the robustness of some multimodal literacy strategies across content areas. The third project was a mixed

  12. A Behavioral Framework for Managing Massive Airline Flight Disruptions through Crisis Management, Organization Development, and Organization Learning (United States)

    Larsen, Tulinda Deegan

    In this study the researcher provides a behavioral framework for managing massive airline flight disruptions (MAFD) in the United States. Under conditions of MAFD, multiple flights are disrupted throughout the airline's route network, customer service is negatively affected, additional costs are created for airlines, and governments intervene. This study is different from other studies relating to MAFD that have focused on the operational, technical, economic, financial, and customer service impacts. The researcher argues that airlines could improve the management of events that led to MAFD by applying the principles of crisis management where the entire organization is mobilized, rather than one department, adapting organization development (OD) interventions to implement change and organization learning (OL) processes to create culture of innovation, resulting in sustainable improvement in customer service, cost reductions, and mitigation of government intervention. At the intersection of crisis management, OD, and OL, the researcher has developed a new conceptual framework that enhances the resiliency of individuals and organizations in responding to unexpected-yet-recurring crises (e.g., MAFD) that impact operations. The researcher has adapted and augmented Lalonde's framework for managing crises through OD interventions by including OL processes. The OD interventions, coupled with OL, provide a framework for airline leaders to manage more effectively events that result in MAFD with the goal of improving passenger satisfaction, reducing costs, and preventing further government intervention. Further research is warranted to apply this conceptual framework to unexpected-yet-recurring crises that affect operations in other industries.

  13. Incremental online object learning in a vehicular radar-vision fusion framework

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Zhengping [Los Alamos National Laboratory; Weng, Juyang [Los Alamos National Laboratory; Luciw, Matthew [IEEE; Zeng, Shuqing [IEEE


    In this paper, we propose an object learning system that incorporates sensory information from an automotive radar system and a video camera. The radar system provides a coarse attention for the focus of visual analysis on relatively small areas within the image plane. The attended visual areas are coded and learned by a 3-layer neural network utilizing what is called in-place learning, where every neuron is responsible for the learning of its own signal processing characteristics within its connected network environment, through inhibitory and excitatory connections with other neurons. The modeled bottom-up, lateral, and top-down connections in the network enable sensory sparse coding, unsupervised learning and supervised learning to occur concurrently. The presented work is applied to learn two types of encountered objects in multiple outdoor driving settings. Cross validation results show the overall recognition accuracy above 95% for the radar-attended window images. In comparison with the uncoded representation and purely unsupervised learning (without top-down connection), the proposed network improves the recognition rate by 15.93% and 6.35% respectively. The proposed system is also compared with other learning algorithms favorably. The result indicates that our learning system is the only one to fit all the challenging criteria for the development of an incremental and online object learning system.

  14. Analysis of sustainable leadership for science learning management in the 21st Century under education THAILAND 4.0 framework (United States)

    Jedaman, Pornchai; Buaraphan, Khajornsak; Pimdee, Paitoon; Yuenyong, Chokchai; Sukkamart, Aukkapong; Suksup, Charoen


    This article aims to study and analyze the 21st Century of sustainable leadership under the education THAILAND 4.0 Framework, and factor analysis of sustainable leadership for science learning. The study employed both quantitative and qualitative approaches in collecting data including a questionnaire survey, a documentary review and a Participatory Action Learning (PAL). The sample were sampling purposively. There were 225 administrators of Primary and Secondary Education Area Offices throughout Thailand. Out of 225, 183 (83.33%) and 42 (16.67%) respondents were the administrators of Primary and Secondary Education Offices, respectively. The quantitative data was analyzed by descriptive statistical analysis including mean, standard deviation. Also, the Confirmatory Factor Analysis (CFA) was conducted to analyze the factors associated with sustainable leadership under the education THAILAND 4.0 Framework. The qualitative data was analyzed by using three main stages, i.e., data reduction, data organization, data interpretation to conclusion. The study revealed that sustainable leadership under the education THAILAND 4.0 Framework needs to focus on development, awareness of duty and responsibility, equality, moral and knowledge. All aspects should be integrated together in order to achieve the organizational goals, good governance culture and identity. Importantly, there were six "key" elements of sustainable leadership under the education THAILAND 4.0 framework: i) Professional Leadership Role, ii) Leadership Under Change, iii) Leadership Skills 4.0 in the 21st Century, iv) Development in the Pace With Change, v) Creativity and Creative Tension, and vi) Hold True Assessments. The CFA showed that the six key elements of sustainable leadership under the education THAILAND 4.0 framework by weight of each elements were significant at the .01 significance level.

  15. A Method to Reveal Fine-Grained and Diverse Conceptual Progressions during Learning (United States)

    Lombard, François; Merminod, Marie; Widmer, Vincent; Schneider, Daniel K.


    Empirical data on learners' conceptual progression is required to design curricula and guide students. In this paper, we present the Reference Map Change Coding (RMCC) method for revealing students' progression at a fine-grained level. The method has been developed and tested through the analysis of successive versions of the productions of eight…

  16. Commentary: Prevention of violence against children: a framework for progress in low- and middle-income countries. (United States)

    Chandran, Aruna; Puvanachandra, Prasanthi; Hyder, Adnan A


    Violence against children has been the least reported, studied, and understood area of child injuries. Initial awareness emerged from international conferences and resolutions, followed by national policies and statements. More effective responses around the world will require action. Although previous calls for action have pointed to important activities (gathering of baseline data, passing of legal reforms, and providing services to those who experience violence), the agenda is limited. Data collection needs to be continuous, systematic, and sustainable, and should enable ongoing evaluation of intervention programs. An inter-sectoral approach to violence against children incorporating public health, criminal justice, social services, education, non-governmental organizations, media, and businesses is imperative if the growing burden is to be mitigated. Thus we offer a framework, building on earlier recommendations, to focus on four domains: national surveillance, intervention research, legislation and policy, and partnerships and collaboration.

  17. Work in Progress - Developing Joint Degrees through E-Learning Systems


    Aguirre Herrera, Sandra; Quemada Vives, Juan; Salvachúa Rodríguez, Joaquín


    The development of Joint Degrees is an important mechanism for opening higher education systems nationwide, adapting them to the international standard, and promoting quality assessment to a broader environment. Since e-Learning systems covers a wide range of academic programs, and as joint degrees such as e-Learning are rapidly growing trends, finding a suitable solution that enables universities to design joint degrees through their own e-Learning systems becomes necessary. This paper intro...

  18. Approximation Methods for Inference and Learning in Belief Networks: Progress and Future Directions

    National Research Council Canada - National Science Library

    Pazzan, Michael


    .... In this research project, we have investigated methods and implemented algorithms for efficiently making certain classes of inference in belief networks, and for automatically learning certain...

  19. PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology. (United States)

    Araki, Tadashi; Ikeda, Nobutaka; Shukla, Devarshi; Jain, Pankaj K; Londhe, Narendra D; Shrivastava, Vimal K; Banchhor, Sumit K; Saba, Luca; Nicolaides, Andrew; Shafique, Shoaib; Laird, John R; Suri, Jasjit S


    Percutaneous coronary interventional procedures need advance planning prior to stenting or an endarterectomy. Cardiologists use intravascular ultrasound (IVUS) for screening, risk assessment and stratification of coronary artery disease (CAD). We hypothesize that plaque components are vulnerable to rupture due to plaque progression. Currently, there are no standard grayscale IVUS tools for risk assessment of plaque rupture. This paper presents a novel strategy for risk stratification based on plaque morphology embedded with principal component analysis (PCA) for plaque feature dimensionality reduction and dominant feature selection technique. The risk assessment utilizes 56 grayscale coronary features in a machine learning framework while linking information from carotid and coronary plaque burdens due to their common genetic makeup. This system consists of a machine learning paradigm which uses a support vector machine (SVM) combined with PCA for optimal and dominant coronary artery morphological feature extraction. Carotid artery proven intima-media thickness (cIMT) biomarker is adapted as a gold standard during the training phase of the machine learning system. For the performance evaluation, K-fold cross validation protocol is adapted with 20 trials per fold. For choosing the dominant features out of the 56 grayscale features, a polling strategy of PCA is adapted where the original value of the features is unaltered. Different protocols are designed for establishing the stability and reliability criteria of the coronary risk assessment system (cRAS). Using the PCA-based machine learning paradigm and cross-validation protocol, a classification accuracy of 98.43% (AUC 0.98) with K=10 folds using an SVM radial basis function (RBF) kernel was achieved. A reliability index of 97.32% and machine learning stability criteria of 5% were met for the cRAS. This is the first Computer aided design (CADx) system of its kind that is able to demonstrate the ability of coronary

  20. The allocation of attention to learning of goal-directed actions: A cognitive neuroscience framework focusing on the basal ganglia

    Directory of Open Access Journals (Sweden)

    Liz eFranz


    Full Text Available The present paper builds on the idea that attention is largely in service of our actions. A framework and model which captures the allocation of attention for learning of goal-directed actions is proposed and developed. This framework highlights an evolutionary model based on the notion that rudimentary brain functions have become embedded into increasingly higher levels of networks which all contribute to adaptive learning. Background literature is presented alongside key evidence based on experimental studies in the so-called ‘split-brain’ (surgically divided cerebral hemispheres with a key focus on bimanual actions. The proposed multilevel cognitive-neural system of attention is built upon key processes of a highly-adaptive basal-ganglia-thalamic-cortical system. Although overlap with other existing findings and models is acknowledged where appropriate, the proposed framework is an original synthesis of cognitive experimental findings with supporting evidence of a neural system and a carefully formulated model of attention. It is the hope that this new synthesis will be informative in fields of cognition and other fields of brain sciences and will lead to new avenues for experimentation across domains.