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Context modeling to support the design of mobile learning
Source Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology table of contents
Cergy-Pontoise, France
WORKSHOP SESSION: CAML-I: workshop on context-aware mobile learning table of contents
Pages 536-541  
Year of Publication: 2008
ISBN:978-1-60558-046-3
Author
Arianit Kurti  Växjö University, Vaxjo, Sweden
Sponsors
: Institute of Electrical and Electronics Engineers France Section
: Ministère des Affaires Etrangères et Européennes
: Communauté d'Agglomération de Cergy-Pontoise
: Comité d'Expansion Economique du Val d'Oise
: Association Francophone d'Interaction Homme-Machine
: University of Cergy-Pontoise
: Institute of Electrical and Electronics Engineers Systems, Man and Cybernetics Society
: Région Ile de France
: Laboratoire des Equipes Traitement des Images et du Signal
: The French Chapter of ACM Special Interest Group on Applied Computing
: The World Federation of Soft Computing
: Agence de Développement Economique de Cergy-Pontoise
: The European Neural Network Society
: The European Society For Fuzzy And technology
: The International Fuzzy System Association
: Laboratoire Innovation Développement
Publisher
ACM  New York, NY, USA
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ABSTRACT

The evolution of information and communication technologies in the last three decades has had an impact in all aspects of human activities. Learning has also been subject of these changes. Current research efforts in the field of mobile learning have been in many cases guided by a learner-centered approach. Context awareness and content adaptivity are crucial components in mobile learning environments. One important challenge is how to design and implement technological tools and methods to support them. In order to tackle this challenge, learners' context should be defined. In this paper, we describe our current efforts regarding how to model context in mobile learning activities. We introduce a time dependent context model based on a three pole structure that can be used to design and support context awareness in mobile learning environments. We illustrate its applicability in four different cases where mobile learning activities and implementations have been guided by the use of this model.


REFERENCES

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