Semantic-Based Automated Composition of Distributed Learning Objects for Personalized E-Learning

Recent advances in e-learning techonologies and web services make realistic the idea that courseware for personalized e-learning can be built by dynamic composition of distributed learning objects, available as web-services. To be assembled in au automated way, learning objects metadata have to be exploited, associating unambiguous, semantically rich, descriptions, to be used for such an automated composition. To this aim, we present a framework and algorithms for semantic-based learning objects composition, fully compliant with Semantic Web technologies. In particular our metadata refer to ontologies built on a subset of OWL-DL, and we show how novel inference services in Description Logics can be used to compose dynamically, in an approximated –but computationally tractable– way learning resources, given a requested courseware description.

• Type: Conference
• Year: 2005
• Where: ESWS
• Authors: Simona Colucci, Tommaso Di Noia, Eugenio Di Sciascio, Francesco M. Donini, Azzurra Ragone
• Keywords: Au Automated Way, ESWS 2005, Learning Objects, Learning Objects Composition