Intelligent web-based tutoring system with personalized learning path guidance

Abstract

Personalized curriculum sequencing is an important research issue for Web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist online Web-based learning and adaptively provide learning paths in order to promote the learning performance of individual learners. Generally, inappropriate courseware leads to learner cognitive overload or disorientation during learning processes, thus reducing learning performance. Therefore, compared with the freely browsing learning mode used in most web-based learning systems, this paper assesses whether the proposed genetic-based personalized e-learning system which can generate appropriate learning paths according to the incorrect testing responses of individual learners in a pre-test provides benefits in terms of learning performance promotion. Experiment results indicated that applying the proposed genetic-based personalized e-learning system for Web-based learning is superior to the freely browsing learning mode because of high quality and concise learning path for individual learners. © 2007 IEEE.