Course ontology-based user's knowledge requirement acquisition from behaviors within e-learning systems

  • Authors:

  • Qingtian Zeng;Zhongying Zhao;Yongquan Liang

  • Affiliations:

  • College of Information Science and Engineering, Shandong University of Science and Technology, No.579 Qianwangang Road, Economic and Technical Development Zone, Qingdao 266510, PR China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China and Graduate School of Chinese Academy of Sciences, Beijing 100080, China and Shenzhen Institute of Advanced T ...;College of Information Science and Engineering, Shandong University of Science and Technology, No.579 Qianwangang Road, Economic and Technical Development Zone, Qingdao 266510, PR China

  • Venue:
  • Computers & Education
  • Year:
  • 2009

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Abstract

User's knowledge requirement acquisition and analysis are very important for a personalized or user-adaptive learning system. Two approaches to capture user's knowledge requirement about course content within an e-learning system are proposed and implemented in this paper. The first approach is based on the historical data accumulated by an interactive question-answering process. The association space is proposed to record and formalize the historical interactive information which is used to compute user's knowledge requirement. The second approach is based on user's reading behavior logs in the process of reading e-documents. User's reading actions including underline, highlight, circle, annotation and bookmark, are used to compute user's knowledge requirement. Two experiments are conducted to implement the two proposed approaches and acquire the user's knowledge requirement. The evaluation results show that the user models computed by two approaches are consistent and can reflect user's real knowledge requirements accurately.