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Enhanced learner model for adaptive mobile learning
Faculty of Informatics - Papers (Archive)
  • Ahmed Alhmouz, University of Wollongong
  • Jun Shen, University of Wollongong
  • Jun Yan, University of Wollongong
  • Rami Al-Hmouz, Isra Private University
RIS ID
31653
Publication Date
1-1-2010
Publication Details

Al-Hmouz, A., Shen, J., Yan, J. & Al-Hmouz, R. (2010). Enhanced learner model for adaptive mobile learning. iiWAS2010: The 12th International Conference on Information Integration and Web-based Applications & Services (pp. 781-784). USA: ACM.

Abstract

Personalisation and learner modelling are becoming more important in the area of mobile learning applications, taking into consideration learners' interests, preferences and contextual information. Students nowadays are able to learn anywhere and at any time. Mobile learning application content is one of several factors within various contexts that play an important role in the success of the adaptation process. The vast amount of data involved in any successful adaptation process creates complexity and poses serious challenges. This paper focuses on how to model the learner and all possible contexts in an extensible way that can be used for personalisation in mobile learning. The enhanced learner modelling structure to be used in a mobile learning system is proposed. The proposed structure provides personalisation by adopting a hybrid approach combining two machine learning techniques.

Citation Information
Ahmed Alhmouz, Jun Shen, Jun Yan and Rami Al-Hmouz. "Enhanced learner model for adaptive mobile learning" (2010) p. 781 - 784
Available at: http://works.bepress.com/jshen/33/