Educational Recommender System based on Learner’s Annotative Activity

In recent years, Educational Recommender Systems (ERSs) have attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. These systems play key role helping learners find educational resources pertinent their profiles context. So, it is necessary identify that helps learner’s profile definition identifying requests interests. this context, we suggest take advantage annotation activity used usually learning context for different purposes which may reflect certain characteristics useful input data recommendation process. Therefore, propose an recommender system web services based on annotative assist him his activity. This process founded two preparatory phases: phase modelling personality through analysis digital traces environment realized constructor module discovery can meet goals annotations made by learner via service module. The evaluation developed empirical studies groups Student’s t-test showed significant results.