34 research outputs found

    Bioinorganic Chemistry of Alzheimer’s Disease

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    CMS physics technical design report : Addendum on high density QCD with heavy ions

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    Fluctuating hearing loss with otorrhoea in Hughes syndrome

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    E-learning meets the social semantic Web

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    he social semantic Web has recently emerged as a paradigm in which ontologies (aimed at defining, structuring and sharing information) and collaborative software (used for creating and sharing knowledge) have been merged together. Ontologies provide an effective means of capturing and integrating knowledge for feedback provisioning, while using collaborative activities can support pedagogical theories, such as social constructivism. Both technologies have developed separately in the e-learning domain; representing respectively a teacher-centered and a learner-centered approach for learning environments. In this paper we bridge the gap between these two approaches by leveraging the social semantic Web paradigm, and propose a collaborative semantic-rich learning environment in which folksonomies created from studentspsila collaborative tags contribute to ontology maintenance, and teacher-directed feedback

    Leveraging folksonomies for ontology evolution in e-learning environments

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    One of the main obstacles for wider adoption of semantic rich e-learning systems is the difficulty in creating and maintaining domain ontologies describing courses. Annotations, such as those resulting from collaborative tagging, provide a new source of information which can be used to ease the process of author-ing and updating domain ontologies. This paper presents an extension to the LOCO-Analyst tool, which leverages student folksonomies to support instructors when revising and updating course domain ontologies. The support is based on a computation of relatedness between ontology concepts and students tags which takes into account the "context" defined by the domain ontology. The computed scores are visualized in a tag cloud along with tag popularity scores, to allow instructors to easily comprehend the emergent feedback of their students. This approach allows for a simple and intuitive method for instructors to associate tags with concepts in their domain ontology
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