The purpose of this paper is to provide a solution which allows automatic reasoning processes over Moodle activities logs, in order to obtain user-personalized recommendations. Activities logs are mined for association rules, which are the translated into Jena Rules. The information is then used by specific learning rules to create recommendations for specific users. Using this technique, additional information is obtained starting from activities database.