Abstract—Personalized E-learning based on recommender system is recognized as one of the most interesting research field in the education and teaching in this last decade, since, the learning style is specific with each student. In fact from the knowledge his/her learning style; it is easier to recommend a learning scenario builds around a collection of the most adequate learning objects to give a better return on the educational level. This work focuses on the design of a personalized E-learning system based on a psychological model of Felder and Solomon and the collaborative filtering techniques. Using the learner profile, the device proposes a personalize learning scenario by selecting the most appropriate learning objects. 
 

Index Terms—E-learning, recommender system, collaborative filtering, learning styles, learning objects

Cite: Outmane Bourkoukou, Essaid El Bachari, and Mohamed El Adnani, "A Personalized E-Learning Based on Recommender System," International Journal of Learning and Teaching, Vol. 2, No. 2, pp. 99-103, December 2016. doi: 10.18178/ijlt.2.2.99-103