This paper deals with one of our research directions on software tools enhancing self-learning in computer science disciplines. In this study, we discuss an experiment on relational data bases learning using a tool for the edition and automated evaluation of learners’ solutions given as relational algebra trees. Indeed, in addition to the interest of the graphic languages for any training, the evaluation of our precedent works on modeling and evaluating solutions as algebraic expressions showed us some problems: first, there are various languages for the algebraic expressions. Second, among the detected errors by the prototype, developed in our precedent works for algebraic expressions, the form errors about the algebraic language have to be corrected before starting the semantic analysis. Third, in some cases, errors in the form have led to other non-committed errors which can cause inconsistencies in the errors’ diagnosis process. Starting from these problems, the two principal objectives of the work presented in this article concern the algebraic trees construction and the evaluation assisted by a graphic tool which essentially consists in a semantic analysis as recommended in ODALA (ontology driven auto-evaluation learning approach) that we have already proposed. The tool was evaluated by a set of tests and experimented with second year LMD license students. These experiments results were interesting and showed that the tool is particularly helpful for novice students and their teachers.