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Designing and eXperiencing smart objects based learning scenarios: an approach combining IMS LD, XAPI and IoT

Published: 01 October 2014 Publication History

Abstract

The Internet of Things paradigm when combined to Learning Enhanced Technology pushes instructional designers to rethink learning scenarios. The use of smart objects including smart learning objects in learning environments is an increasing trend to evolve the learner's progress in learning. Learning scenarios in such environments are characterized by the detection of the learner's contextual information are as well as the adaptation of pedagogical strategies and services according to this context. In order to enhance the user's experience, we propose ontological models that allow intelligent interpretation of contextual data including tracked one and so relevant adaptation of the learning scenario is proposed.

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Cited By

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  • (2024)Thematic evolution of smart learning environments, insights and directions from a 20-year research milestones: A bibliometric analysisHeliyon10.1016/j.heliyon.2024.e2619110:5(e26191)Online publication date: Mar-2024
  • (2021)Affordances and Core Functions of Smart Learning Environments: A Systematic Literature ReviewIEEE Transactions on Learning Technologies10.1109/TLT.2021.306794614:2(129-145)Online publication date: 1-Apr-2021
  • (2020)Mesleki Eğitime Yönelik Yeni Nesil Öğrenme Nesnelerinin Tasarlanması, Geliştirilmesi ve DeğerlendirilmesiDesign, Development and Evaluation of New Generation Learning Objects for Vocational EducationJournal of Computer and Education Research10.18009/jcer.7700348:16(757-786)Online publication date: 20-Oct-2020
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    cover image ACM Other conferences
    TEEM '14: Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality
    October 2014
    711 pages
    ISBN:9781450328968
    DOI:10.1145/2669711
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 01 October 2014

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    Author Tags

    1. IMS LD
    2. IoT
    3. experience (tin can) API
    4. learning objects
    5. learning scenarios
    6. pervasive learning
    7. smart learning environments

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    Overall Acceptance Rate 496 of 705 submissions, 70%

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    Cited By

    View all
    • (2024)Thematic evolution of smart learning environments, insights and directions from a 20-year research milestones: A bibliometric analysisHeliyon10.1016/j.heliyon.2024.e2619110:5(e26191)Online publication date: Mar-2024
    • (2021)Affordances and Core Functions of Smart Learning Environments: A Systematic Literature ReviewIEEE Transactions on Learning Technologies10.1109/TLT.2021.306794614:2(129-145)Online publication date: 1-Apr-2021
    • (2020)Mesleki Eğitime Yönelik Yeni Nesil Öğrenme Nesnelerinin Tasarlanması, Geliştirilmesi ve DeğerlendirilmesiDesign, Development and Evaluation of New Generation Learning Objects for Vocational EducationJournal of Computer and Education Research10.18009/jcer.7700348:16(757-786)Online publication date: 20-Oct-2020
    • (2019)A Conceptual Multi-Dimensional Model for Smart Learning Environments2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)10.1109/ICACSIS47736.2019.8979679(505-512)Online publication date: Oct-2019
    • (2019)Towards a Framework for Participatory Strategy Design in Smart CitiesInnovations in Smart Cities Applications Edition 210.1007/978-3-030-11196-0_17(179-192)Online publication date: 7-Feb-2019
    • (2018)Toward a Framework for Smart City Strategies DesignProceedings of the 3rd International Conference on Smart City Applications10.1145/3286606.3286833(1-7)Online publication date: 10-Oct-2018
    • (2017)Using Sequential Pattern Mining to Explore Learners’ Behaviors and Evaluate Their Correlation with Performance in Inquiry-Based LearningData Driven Approaches in Digital Education10.1007/978-3-319-66610-5_21(286-299)Online publication date: 5-Sep-2017
    • (2017)Building Context-Aware Gamified Apps by Using Ontologies as Unified Representation and Reasoning-Based ModelsSerious Games and Edutainment Applications10.1007/978-3-319-51645-5_29(675-702)Online publication date: 4-Mar-2017
    • (2016)Toward an Adaptive Architecture for Integrating Mobile Affective Computing to Intelligent Learning EnvironmentsInnovations in Smart Learning10.1007/978-981-10-2419-1_18(123-128)Online publication date: 17-Sep-2016
    • (2015)Proporcionar experiencias de aprendizaje ubicuo mediante la combinación de Internet de las Cosas y los estándares de e-LearningEducation in the Knowledge Society (EKS)10.14201/eks20151649811716:4(98)Online publication date: 9-Dec-2015

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