Intelligent Adaptive E-learning Model for Learning Management System

In this study we have proposed an Intelligent Adaptive e-Learning Model that incorporates the ability to intelligently classify learners. There is a need for learning to continue, whether learners are onor off-line. This study emphasize on developing an agent-based personalized adaptive learning model. This model is deployed as a service using agent technology and not just as an application as is the case with all other available LMS. We tested Intelligent Adaptive e-Learning Model prototype that implements an adaptive presentation of course content under conditions of intermittent Internet connections on postgraduate students studying a networking course. The study found out that it is possible for learners to study under both off-line and on-line modes through adaptive learning and the Intelligent Adaptive E-Learning system successfully classified learners and the accuracy was 85%.