André Behr

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This paper proposes ontologies for the LOM, OBAA, and IMS AccessForAll learning object metadata standards. Those standards define the hierarchical structure and the axioms for the proposed ontologies. The OWL 2 was used to describe those ontologies. The lowest granularity as possible among the individuals that compose a learning object is aimed. The results(More)
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(More)
Metadata is broadly used to describe learning objects and its standards have been developed to improve interoperability. With the current Web extension by the Semantic Web, learning object metadata has been migrating from XML-based metadata formats to semantic metadata formats. This work explores XSLT to provide a solution for this transition of(More)
This paper proposes an editor for Learning Object Metadata compatible with the Semantic Web. This tool uses two base ontologies, OBAA and VideoAula to provide the semantics to describe learning objects. These ontologies are the core for a tool to verify the consistency of the user-input data and realize inferences about the described information.(More)
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