Semi-Automated Academic Tutor for the Selection of Learning Paths in a Curriculum: An Ontology-Based Approach

In higher education globalization brings challenges as part of a reform process. An important aspect of such a reform has to do with the flexibility of the contents of a curriculum. Normally curricula offer students a whole set of possibilities to make decisions regarding optional courses recommended in an educational programme. In this work we present the design of a semi-automated Academic Tutor to support students in selecting learning paths (that consist of a set of courses which form the individual curricula) to achieve a particular professional profile. We designed the Academic Tutor considering the case of an Electrical Engineering Curriculum, which is represented through ontologies, a Semantic Web technology that provides a logical and formal description that can be interpreted by people and machines. The curriculum was divided into three interrelated main structures called sources of conceptualization. The sources that were transformed into ontologies were: subjects from the programme curriculum's core and subjects from the variable part of the programme curriculum; skills and thematic contents. Preliminary findings present a broad and formal representation of the curriculum's knowledge to be shared and reused in the field of education and engineering.