Enhanced learner model for adaptive mobile learning

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 per-sonalisation by adopting a hybrid approach combining two machine learning techniques.