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A Self-Adaptive Multi-Agent System Approach for Collaborative Mobile Learning
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)
Pontificia Universidad de Chile, Chile.
Linnaeus University, Faculty of Technology, Department of Computer Science.ORCID iD: 0000-0002-1162-0817
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0002-6937-345X
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2015 (English)In: IEEE Transactions on Learning Technologies, ISSN 1939-1382, E-ISSN 1939-1382, Vol. 8, no 2, 158-172 p.Article in journal (Refereed) Published
Abstract [en]

Mobile technologies have emerged as facilitators in the learning process, extending traditional classroom activities. However, engineering mobile learning applications for outdoor usage poses severe challenges. The requirements of these applications are challenging, as many different aspects need to be catered, such as resource access and sharing, communication between peers, group management, activity flow, etc. Robustness is particularly important for learning scenarios to guarantee undisturbed and smooth user experiences, pushing the technological aspects in the background. Despite significant research in the field of mobile learning, very few efforts have focused on collaborative mobile learning requirements from a software engineering perspective. This paper focuses on aspects of the software architecture, aiming to address the challenges related to resource sharing in collaborative mobile learning activities. This includes elements such as autonomy for personal interactive learning, richness for large group collaborative learning (indoor and outdoor), as well as robustness of the learning system. Additionally, we present self-adaptation as a solution to mitigate risks of resource unavailability and organization failures that arise from environment and system dynamism. Our evaluation provides indications regarding the system correctness with respect to resource sharing and collaboration concerns, and offers qualitative evidence of self-adaptation benefits for collaborative mobile learning applications.

Place, publisher, year, edition, pages
IEEE, 2015. Vol. 8, no 2, 158-172 p.
Keyword [en]
Mobile Learning, Software Architecture, Multi-Agent Systems, Self-Adaptation
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science; Computer and Information Sciences Computer Science, Media Technology
Identifiers
URN: urn:nbn:se:lnu:diva-39602DOI: 10.1109/TLT.2014.2367493ISI: 000358585000002OAI: oai:DiVA.org:lnu-39602DiVA: diva2:784847
Available from: 2015-01-30 Created: 2015-01-30 Last updated: 2017-04-24Bibliographically approved

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Gil de la Iglesia, DidacWeyns, DannyMilrad, Marcelo
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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
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  • fi-FI
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