Ontology extraction from existing educational content to improve personalized e-Learning experiences

Nowadays, the use of domain ontologies in e-Learning applications is rapidly increasing due to the important role they play in knowledge representation, sharing of didactical material and content personalization. However, the ontology building processes is still extremely difficult to achieve. In this paper we present a semi-automatic process based on knowledge extraction from existing SCORM educational content aimed to speed up and facilitate the realization of domain ontologies and the breakdown of SCORM packages in fine-grained, rearrangeable learning objects appropriate for building personalized e-Learning experience. © 2009 IEEE.