E-Learning Personalization Based on Dynamic Learners' Preference

Personalized e-learning implementation is recognized one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different we must to fit elearning to the different needs of learners. This paper discusses teaching strategies matching with learner's personality using the Myers-Briggs Type Indicator (MBTI) tools. Based on an innovative approach, a framework for building an adaptive learning management system by considering learner's preference has been developed. The learner's profile is initialized according to the results obtained by the student in the index of learning styles questionnaire and then fine-tuned during the course of the interaction using the Bayesian model. Moreover, an experiment was conducted to evaluate the performance of our approach. The result reveals the system effectiveness for which it appears that the proposed approach may be promising.