Enhanced learner model for adaptive mobile learning

Authors:
Ahmed Al-Hmouz;Jun Shen;Jun Yan;Rami Al-Hmouz
Affiliations:
University of Wollongong, Wollongong, Australia;University of Wollongong, Wollongong, Australia;University of Wollongong, Wollongong, Australia;Isra Private University, Amman, Jordan
Venue:
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
Year:
2010

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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.