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Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06)
Mining e-Learning Domain Concept Map from Academic Articles
Kerkrade, The Netherlands
July 05-July 07
ISBN: 0-7695-2632-2
Nian-Shing Chen, National Sun Yat-Sen University, Taiwan
Prof. Kinshuk, Massey University, New Zealand
Chun-Wang Wei, National Sun Yat-Sen University, Taiwan
Hong-Jhe Chen, National Sun Yat-Sen University, Taiwan
Recent research has demonstrated the important of ontology and its applications. For example, while designing adaptive learning materials, designers need to refer to the ontology of a subject domain. Moreover, ontology can show the whole picture and core knowledge about a subject domain. Research from literature also suggested that graphical representation of ontology can reduce the problems of information overload and learning disorientation for learners. However, ontology constructions used to rely on domain experts in the past; it is a time consuming and high cost task. Ontology creation for emerging new domains like e-Learning is even more challenging. The aim of this paper is to construct e-Learning domain concept maps, an alternative form of ontology, from academic articles. We adopt some relevant journal articles and conferences papers in e-Learning domain as data sources, and apply text-mining techniques to automatically construct concept maps for e-Learning domain. The constructed concept maps can provide a useful reference for researchers, who are new to e- Leaning field, to study related issues, for teachers to design adaptive courses, and for learners to understand the whole picture of e-Learning domain knowledge.
Citation:
Nian-Shing Chen, Prof. Kinshuk, Chun-Wang Wei, Hong-Jhe Chen, "Mining e-Learning Domain Concept Map from Academic Articles," icalt, pp.694-698, Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06), 2006
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