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On the Issue of Reusability and Adaptability in M-learning Systems
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. (CeLeKT)
2010 (English)In: Proceedings of the 6th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, Los Alamitos, CA, USA: IEEE Press, 2010, 161-165 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a brief overview over some of the conceptual and technical issues associated with reusability and adaptability. The specific orientation of our efforts is oriented towards systems supporting Mobile Learning. The field of M-learning domain has during recent years been suffering from severe configuration problems caused by the plethora of mobile devices present on the market. This paper presents a conceptual architecture that has been conceived to remedy some of these issues. Furthermore, a possible instantiation of this architecture with self-adaptivity features is discussed and a first prototype implementation is presented. The notion of ecosystems is introduced, as we believe it is an important building block towards increasing the reusability of components and content in this field where composition is one of the major issues to be addressed.

Place, publisher, year, edition, pages
Los Alamitos, CA, USA: IEEE Press, 2010. 161-165 p.
Keyword [en]
M-learning, Self-adaptation, Software Ecosystem
National Category
Computer Science
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-6523DOI: 10.1109/WMUTE.2010.48ISBN: 978-0-7695-3992-8 (print)OAI: oai:DiVA.org:lnu-6523DiVA: diva2:326951
Conference
WMUTE2010, 12-16 April 2010
Available from: 2010-06-24 Created: 2010-06-24 Last updated: 2016-08-15Bibliographically approved
In thesis
1. Towards a Mobile Learning Software Ecosystem
Open this publication in new window or tab >>Towards a Mobile Learning Software Ecosystem
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The ability to carry communication services around, combined with the ubiquitous presence of computing technology, affects everything we do from how we pay for things to how we expect to interact with public institutions such as schools. There are now plenty of systems that convey education by utilizing mobile devices. As an extension of technology moving towards ubiquity, there are efforts aiming to bring this to an educational use as well. Efforts in this direction are channelized in the field of mobile learning. The speed of technological development, and the possibilities it brings introduces a large number of challenges when implemented in educational settings. These challenges can be related to for example pedagogical aspects, tools, implementations and organizations. Recent developments including the notions of learning ecosystems, learning landscapes and organizations suggest that the domain of mobile learning can be negatively affected from the lack of a systematic reuse approach. This thesis pursues these challenges by investigating how systematic reuse can be promoted in mobile learning systems.

A collection of five peer-reviewed publications that elaborates on the different stages of the research process pursuing the main research question forms the core of this thesis. This research process includes a survey stage, elaborating on different aspects related to reuse and mobile learning, an analysis stage that resulted in a descriptive model and several additional domain models; and finally a stage where the descriptive model is refined into a reference model for mobile learning ecosystems. The outcomes of these activities and the analysis of these results provide some fundamental building blocks regarding how to approach the challenge of reuse in mobile learning systems. The proposed reference model can be considered as the first step towards the creation of a common vocabulary that can be used to compare Software Ecosystems within the domain of mobile learning. 

Place, publisher, year, edition, pages
Linnéuniversitetet, 2011
Keyword
Technology-Enhanced Learning, Mobile Learning, Software Reuse, Software Ecosystem, Domain analysis
National Category
Computer Science
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
urn:nbn:se:lnu:diva-16595 (URN)
Presentation
2011-06-10, D1136, Växjö, 13:15 (English)
Opponent
Supervisors
Available from: 2012-01-09 Created: 2012-01-04 Last updated: 2012-01-09Bibliographically approved
2. 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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