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Towards a Decentralized and Self-Adaptive System for M-Learning Applications
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics. (CeLeKT)
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics. (CeLeKT)ORCID iD: 0000-0002-6937-345X
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
2012 (English)In: Seventh IEEE International Conference on Wireless, Mobile and Ubiquitous Technology in Education: Takamatsu, Kagawa, Japan, 27-30 March 2012, IEEE, 2012, 162-166 p.Conference paper, (Refereed)
Abstract [en]

Through the analysis of the different iterations of the Geometry Mobile (GEM) project, a mobile learning effort in the field of mathematics, we have identified a major architectural issue to be addressed in the design and implementation of m-learning applications. Due to the dynamic nature of the field many challenging requirements are continuously emerging. One of them relates to the possibility to support collaborative activities that demand sharing resources between students and their mobile devices in constantly changing conditions. These situations generate the need of using decentralized distributed architectures in which mobile devices can share resources to carry out the activity covering the concerns defined by the different stakeholders. This paper describes our current efforts connected to identifying a set of requirements for M-Learning activities. Thereafter, we elaborate on why a decentralized distributed system (DDS) can be used to provide a novel solution to tackle the mentioned above problems. Moreover, initial aspects related to the design of a DDS, including a self-adaptation mechanism are presented.

Place, publisher, year, edition, pages
IEEE, 2012. 162-166 p.
Keyword [en]
mobile learning, self-adaptation, decentralized distributed system
National Category
Computer Systems Media Engineering Interaction Technologies
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
URN: urn:nbn:se:lnu:diva-16404DOI: 10.1109/WMUTE.2012.37ISBN: 978-1-4673-0884-7 (print)OAI: oai:DiVA.org:lnu-16404DiVA: diva2:477470
Conference
IEEE Seventh International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, (WMUTE), Takamatsu, 27-30 March, 2012
Projects
AMULETS
Available from: 2012-01-13 Created: 2011-12-28 Last updated: 2017-04-25Bibliographically approved
In thesis
1. Uncertainties in Mobile Learning applications: Software Architecture Challenges
Open this publication in new window or tab >>Uncertainties in Mobile Learning applications: Software Architecture Challenges
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The presence of computer technologies in our daily life is growing by leaps and bounds. One of the recent trends is the use of mobile technologies and cloud services for supporting everyday tasks and the sharing of information between users. The field of education is not absent from these developments and many organizations are adopting Information and Communication Technologies (ICT) in various ways for supporting teaching and learning. The field of Mobile Learning (M-Learning) offers new opportunities for carrying out collaborative educational activities in a variety of settings and situations. The use of mobile technologies for enhancing collaboration provides new opportunities but at the same time new challenges emerge.

One of those challenges is discussed in this thesis and it con- cerns with uncertainties related to the dynamic aspects that characterized outdoor M-Learning activities. The existence of these uncertainties force software developers to make assumptions in their developments. However, these uncertainties are the cause of risks that may affect the required outcomes for M-Learning activities. Mitigations mechanisms can be developed and included to reduce the risks’ impact during the different phases of development. However, uncertainties which are present at runtime require adaptation mechanisms to mitigate the resulting risks.

This thesis analyzes the current state of the art in self-adaptation in Technology-Enhanced Learning (TEL) and M-Learning. The results of an extensive literature survey in the field and the outcomes of the Geometry Mobile (GEM) research project are reported. A list of uncertainties in collaborative M-Learning activities and the associated risks that threaten the critical QoS outcomes for collaboration are identified and discussed. A detailed elaboration addressing mitigation mechanisms to cope with these problems is elaborated and presented. The results of these efforts provide valuable insights and the basis towards the design of a multi-agent self-adaptive architecture for multiple concerns that is illustrated with a prototype implementation. The proposed conceptual architecture is an initial cornerstone towards the creation of a decentralized distributed self-adaptive system for multiple concerns to guarantee collaboration in M-Learning. 

Place, publisher, year, edition, pages
Växjö, Sweden: Linnaeus University, 2012. 136 p.
Keyword
distributed systems, uncertainties, self-adaptation, QoS, collaboration, M-Learning, TEL, Mobile Learning, Distributed Systems, Uncertainties, Quality of Service, Self-Adaptation
National Category
Computer Science
Identifiers
urn:nbn:se:lnu:diva-18547 (URN)
Presentation
2012-03-12, Homeros, Linnaeus University, Växjö, 10:20 (English)
Opponent
Supervisors
Available from: 2012-05-09 Created: 2012-05-04 Last updated: 2017-02-13Bibliographically approved

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