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Issue No.04 - October-December (2011 vol.4)
pp: 301-314
D. Gasevic , Sch. of Comput. & Inf. Syst., Athabasca Univ., Athabasca, AB, Canada
A. Zouaq , Dept. of Math. & Comput. Sci., R. Mil. Coll. of Canada, Kingston, ON, Canada
C. Torniai , Oregon Health & Sci. Univ. Libr., Portland, OR, USA
J. Jovanovic , Dept. of Software Eng., Univ. of Belgrade, Belgrade, Serbia
M. Hatala , Sch. of Interactive Arts & Technol., Simon Eraser Univ., Surrey, BC, Canada
Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning environments are widely used. In this paper, we present an approach to ontology maintenance based on the use of collaborative tags contributed by learners while using learning environments. Our contribution is twofold: 1) a visualization and user interaction interface supporting the tasks of enriching ontologies with selected collaborative tags; and 2) ontology-enhanced metrics that are used for measuring semantic relatedness between collaborative tags and ontology concepts and for recommending tags which are relevant to a given ontological concept. We developed a software architecture as a proof of concept and a tool for the evaluation of our proposal. This tool is used to conduct the evaluation of the usability and effectiveness of the proposed method.
software architecture, computer aided instruction, ontologies (artificial intelligence), semantic Web, software architecture, folksonomy-based ontology maintenance, learning environments, semantic Web, advanced learning environment, ontology development, ontology-enhanced learning environment, collaborative tags, visualization, user interaction interface, ontology-enhanced metrics, Ontologies, Semantics, Maintenance engineering, Collaboration, Tag clouds, Learning systems, applications and expert knowledge-intensive systems., Computer uses in education, ontology design, collaborative learning
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