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    Ubiquitous learning architecture to enable learning path design across the cumulative learning continuum

    Karagkiozoglou, Konstantinos and Magoulas, George D. (2016) Ubiquitous learning architecture to enable learning path design across the cumulative learning continuum. Informatics 3 (4), p. 19. ISSN 2227-9709.

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    Abstract

    The past twelve years have seen ubiquitous learning (u-learning) emerging as a new learning paradigm based on ubiquitous technology. By integrating a high level of mobility into the learning environment, u-learning enables learning not only through formal but also through informal and social learning modalities. This makes it suitable for lifelong learners that want to explore, identify and seize such learning opportunities, and to fully build upon these experiences. This paper presents a theoretical framework for designing personalized learning paths for lifelong learners, which supports contemporary pedagogical approaches that can promote the idea of a cumulative learning continuum from pedagogy through andragogy to heutagogy where lifelong learners progress in maturity and autonomy. The framework design builds on existing conceptual and process models for pedagogy-driven design of learning ecosystems. Based on this framework, we propose a system architecture that aims to provide personalized learning pathways using selected pedagogical strategies, and to integrate formal, informal and social training offerings using two well-known learning and development reference models; the 70:20:10 framework and the 3–33 model.

    Metadata

    Item Type: Article
    Additional Information: Special Issue: Ubiquitous Computing: From Interlinking Smart Tabs, Pads and Boards towards Interlinking Smart Skins, Dust and Clay
    Keyword(s) / Subject(s): ubiquitous learning, pervasive learning, personalized learning, lifelong learning, learning path design, Experience Application Programming Interface (xAPI)
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Prof George Magoulas
    Date Deposited: 19 Oct 2016 13:28
    Last Modified: 19 Jun 2017 14:09
    URI: http://eprints.bbk.ac.uk/id/eprint/16294

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