Ontological Evaluation as an Automated Guide to Educational Content Augmentation

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Ontological Evaluation as an Automated Guide to Educational Content Augmentation

The technologies of the Semantic Web have matured to allow for inference processing within real–world productive applications. One application area is concerned about aiding authors with the automated information provisioning with respect to their content. Such a process of content augmentation will rely on ontological knowledge specific to the authors field and context. Educational Content Management has proven to be a context, which is highly suitable for automated processing. IEEE LOM eLearning Objects have established as standard building blocks, providing a meaningful set of metadata and a structure of named relations. Being inherited from the Dublin Core initiative, though, the latter lack an appropriate semantic within the educational context. In the present paper we redefine and sharpen the semantic of LOM relations, thereby extending the set of relations by entities missing from the educational perspective. We construct an ontology and inference rules for these inter–object relations, which are then used for content augmentation. All of our presently ongoing work is being implemented within the Hypermedia Learning Object System HyLOS, our eLearning Content Management platform. HyLOS content management is rigorously built on LOM eLearning Objects, provides a powerful authoring and a rich presentation layer. HyLOS is designed on top of the more general Media Information Repository MIR and the MIR adaptive context linking environment MIRaCLE, its linking extension. MIR is an open system supporting the standards XML, CORBA and JNDI