Recommender System Role in e - Learning Environment

A recommender system in e-learning context is a software agent that tries to " intelligently " recommend actions to a learner based on the actions of previous learners. These recommendation systems have been tried in e-commerce to entice purchasing of goods, but haven't been tried in e-learning. The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. The proposed framework for building automatic recommendations in e-learning platforms is composed of two modules: an off-line module which preprocesses data to build learner and content models, and an online module which uses these models on-the-fly to recognize the students' needs and goals, and predict a recommendation list. Recommended learning objects are obtained by using a range of recommendation strategies based mainly on content based filtering and collaborative filtering approaches, each applied separately or in combination.