Framework for e-Leaming recommendation based on index of learning styles model

Learning is an important activity for learners. Every learner must learn, but how to learn with the most effective outcome is still in question. A lot of theories about learning styles, for example, Kolb's Learning Styles, VARK Learning Styles and Index of Learning Styles (ILS) were created. This paper has adapted ILS with e-Learning method because e-Learning is an efficient technology that particularly focuses on learners who wish to study anywhere and anytime. A framework of e-Learning recommendation by analyzing Index of Learning Styles Model with data mining was developed. It can reasonably forecast the best learning style for learner by Decision Tree J48 algorithm with an accuracy of 76.92% (49 rules base). According to the experts' evaluation, the framework received the average 3.87 of satisfaction level.