Content personalization in e learning environment

For facilitating the use of e learning environments by teachers, we have proposed an approach that aid them to propose documents for learners taking in account their preferences and abilities, so allowing the personalization of these environments. This approach combines a pedagogical scenario design approach [1], using one of most used modelling languages IMS Learning Design (IMSLD), and taxonomy based one which is boosted-CSHTRL (Boosted Cold Start Hybrid Taxonomy Recommender for e Learning), developed to generate recommendation to learners, taking into consideration their preferences and abilities in order to motivate them, and consequently, improve efficiency and increase veracity of learner in the learning situation.