LAUSR

Although technical competences are fundamental at engineering degrees, industry is also requesting the promotion of transversal capabilities. Consequently, the map of target competences may vary over time, area and location. In this context, the design of an undergraduate course is not a trivial task if the promotion of several competences is desired. When such design is manually performed by the teacher using his/her previous experience, the perspective of the students and the information of the previous scores are usually disregarded. Furthermore, the determination of the optimal times for the different activities becomes complex to satisfy a multi-objective problem that aims at balancing technical and soft skills. This paper proposes the use of a predictive tool to assist the design of the course. On the one hand, the predictive algorithm automatically determines the duration of the different activities to fit a specific map of competences. Moreover, the predictive tool also offers valuable information about the perspective of the student and the influence of previous scores using objective indices. The assessment of the proposal is done in a course of Electrical Machines at the University of Malaga (Spain), confirming the capability of the proposed predictive tool to provide a valuable insight on the subject and to automatically determine the duration of different methodological tools.