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Contextualization of Mobile Learners
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0001-9062-1609
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0002-6893-0461
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0001-7072-1063
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0002-6937-345X
2015 (English)In: Mobile Learning: Trends, Attitudes and Effectiveness / [ed] Mohamed Hamada, Nova Science Publishers, Inc., 2015, p. 39-54Chapter in book (Refereed)
Abstract [en]

This chapter describes our current research efforts related to the contextualization of learners in mobile learning activities. Substantial research in the field of mobile learning has explored aspects related to contextualized learning scenarios. However, new ways of interpretation and consideration of contextual information of mobile learners are necessary. This chapter provides an overview regarding the state of the art of innovative approaches for supporting contextualization in mobile learning. Additionally, we provide the description of the design and implementation of a flexible multi-dimensional vector space model to organize and process contextual data together with visualization tools for further analysis and interpretation. We also present a study with outcomes and insights on the usage of the contextualization support for mobile learners. To conlcude, we discuss the benefits of using contextualization models for learners in different use-cases. Moreover, a description is presented in order to illustrate how the proposed contextual model can easily be adapted and reused for different use-cases in mobile learning scenarios and potentially other mobile fields.

Place, publisher, year, edition, pages
Nova Science Publishers, Inc., 2015. p. 39-54
Series
Education in a Competitive and Globalizing World
Keywords [en]
Contextualization, mobile learning, rich context model, learners’ context, learning object, learning format, contextualized mobile learning, contextual information, personalization, flexible context model
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
URN: urn:nbn:se:lnu:diva-46099ISBN: 978-1-63483-429-2 (print)ISBN: 1634834291 (print)OAI: oai:DiVA.org:lnu-46099DiVA, id: diva2:851480
Available from: 2015-09-05 Created: 2015-09-05 Last updated: 2016-12-15Bibliographically approved

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Sotsenko, AlisaZbick, JanoschJansen, MarcMilrad, Marcelo

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
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  • fi-FI
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  • nn-NB
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  • Other locale
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Output format
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