A Semantic Web Approach to Recommend Learning Objects

This work explores the use of Semantic Web techniques as an alternative to traditional educational recommender systems. The proposed model explores the use of Learning Object metadata information and Student academic profile described by knowledge ontologies in order to provide a knowledge structure. This knowlege is stored in an OWL ontology providing domain knowledge and knowledge interoperability. Such ontologies can be used by Recommender Systems to provide educational material recommendations. For a common vocabulary, the core of the ontologies were described with the use of OBAA, a metadata standard that extends IEEE LOM and provides interoperability among hardware platforms to cope with the Brazilian educational context.