Mining e-Learning domain concept map from academic articles

  • Authors:

  • Nian-Shing Chen; Kinshuk;Chun-Wang Wei;Hong-Jhe Chen

  • Affiliations:

  • Department of Information Management, National Sun Yat-sen University, Taiwan;School of Computing and Information Systems, Athabasca University,1 University Drive Athabasca Alberta, Athabasca, Canada;Department of Information Management, National Sun Yat-sen University, Taiwan;Department of Information Management, National Sun Yat-sen University, Taiwan

  • Venue:
  • Computers & Education
  • Year:
  • 2008

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Abstract

Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials, designers need to refer to the concept map of a subject domain. Moreover, concept maps can show the whole picture and core knowledge about a subject domain. Research from literature also suggests that graphical representation of domain knowledge can reduce the problems of information overload and learning disorientation for learners. However, construction of concept maps typically relied upon domain experts in the past; it is a time consuming and high cost task. Concept maps creation for emerging new domains such as e-Learning is even more challenging due to its ongoing development nature. The aim of this paper is to construct e-Learning domain concept maps from academic articles. We adopt some relevant journal articles and conference 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 the e-Leaning field, to study related issues, for teachers to design adaptive learning materials, and for learners to understand the whole picture of e-Learning domain knowledge.