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Toward an Adaptive and Adaptable Architecture to Support Ubiquitous Learning Activities
Malmö högskola, Faculty of Technology and Society (TS). Malmö högskola, Internet of Things and People (IOTAP).
Malmö högskola, Faculty of Technology and Society (TS). Malmö högskola, Internet of Things and People (IOTAP).ORCID iD: 0000-0001-9454-0793
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2015 (English)In: Mobile, Ubiquitous, and Pervasive Learning: Fundaments, Applications, and Trends / [ed] Alejandro Peña-Ayala, Springer, 2015, p. 193-222Chapter in book (Other academic)
Abstract [en]

The continuous evolution of learning technologies combined with the changes within ubiquitous learning environments in which they operate result in dynamic and complex requirements that are challenging to meet. The fact that these systems evolve over time makes it difficult to adapt to the constant changing requirements. Existing approaches in the field of Technology Enhanced Learning (TEL) are generally not addressing those issues and they fail to adapt to those dynamic situations. In this chapter, we investigate the notion of an adaptive and adaptable architecture as a possible solution to address these challenges. We conduct a literature survey upon the state-of-the-art and state-of-practice in this area. The outcomes of those efforts result in an initial model of a Domain Specific Architecture to tackle the issues of adaptability and adaptiveness. To illustrate these ideas, we provide a number of scenarios where this architecture can be applied or is already applied. Our proposed approach serves as a foundation for addressing future ubiquitous learning applications where new technologies constantly emerge and new requirements evolve.

Place, publisher, year, edition, pages
Springer, 2015. p. 193-222
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357, E-ISSN 2194-5365 ; 406
Keywords [en]
Domain-specific architecture, Web-based, Adaptive and adaptable architecture, Technology enhanced learning, Ubiquitous learning
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-16409DOI: 10.1007/978-3-319-26518-6_8Scopus ID: 2-s2.0-84966318500Local ID: 19925ISBN: 978-3-319-26516-2 (print)OAI: oai:DiVA.org:mau-16409DiVA, id: diva2:1419927
Available from: 2020-03-30 Created: 2020-03-30 Last updated: 2024-02-05Bibliographically approved

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Vogel, BahtijarSpikol, Daniel

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