An Adaptive Mobile Learning System with the Support of Learning Diagnosis

In this article, we present an adaptive mobile learning system to provide learners with adaptive learning contents according to learners' abilities and learning preference by the specifications of mobile devices. We used both Bayesian inference and content adaptation technologies to construct a dynamic learner model and to create adaptive contents for learners in a Web-based mobile learning environment. Bayesian inference mechanism facilitates the diagnostic procedure of learners' abilities (including knowledge levels and learning styles) to construct a complete learner model. Content adaptation facilitates friendliness in a learner-system interaction by using heterogeneous mobile devices from anywhere at anytime to access personalized learning materials.