Recommender Systems in E-learning

In this era when every aspect of society is accelerating, people are always seeking improvement to stay competitive in their careers. E-learning systems fit into the ever challenging situation and provide learners with remote learning opportunities abundant resources. Facing numerous resources online, users need support deciding which course take, thus recommender applied personalized services by automatically identifying preferences. This position paper systematically discusses main recommendation techniques employed identifies new research directions. Three reviewed paper: content-based, collaborative filtering-based knowledge-based recommendations. The basic mechanism these technique together how they used fulfill specific requirements context highlighted presented. observations could researchers practitioners better understand current development future directions E-learning.