A Recommendation System Operating after Assessment to Correct Learning Paths in a Content Adapting System

In this paper we present a model of an adapting learning system based on a recommendation system, operating after assessment to correct learning path of the learners who have experienced difficulties in the assessment. The approach aims to correct the learning path of the learners who have failed at the assessment, by calculating the similarities in behaviors between them and those who did, then recommend them the learning objects that can build the most relevant learning path.