Constructing an Adaptive Mobile Learning System for the Support of Personalized Learning and Device Adaptation

This paper presents an adaptive mobile learning system (AMLS) that provides learners with adaptive content according to their knowledge levels, learning styles, and heterogeneous learning devices. The aim of the proposed work is to provide learners with an adaptive learning environment according to learner's individual capability and the learning device used. The proposed system exploits Bayesian networks and content adaptation technologies to support both learner adaptation and device adaptation, which allows each learner to construct a personalized and adaptive learning environment.