Personalized e-learning recommender system using multimedia data

Abstract

Due to the huge amounts of online learning materials, e-learning environments are becoming very popular as means of delivering lectures. One of the most common e-learning challenges is how to recommend quality learning materials to the students. Personalized e-learning recommender systems help to reduce information overload, which tailor learning material to meet individual student's learning needs. This research focuses on using various recommendation and data mining techniques for personalized learning in e-learning environment.