Personalized learning objects recommendation based on the semantic-aware discovery and the learner preference pattern

Tzone I. Wang, Kun Hua Tsai, Ming Che Lee, Ti Kai Chiu

研究成果: Review article同行評審

69 引文 斯高帕斯(Scopus)

摘要

With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future, a vast amount of SCORM-compliant learning objects will be published and distributed cross the Internet. Facing huge volumes of learning objects, learners may be lost in selecting suitable and favorite learning objects. In this paper, an adaptive personalized recommendation model is proposed in order to help recommend SCORM-compliant learning objects from repositories in the Internet. This model adopts an ontological approach to perform semantic discovery as well as both preference-based and correlation-based approaches to rank the degree of relevance of learning objects to a learner's intension and preference. By implementing this model, a tutoring system is able to provide easily and efficiently suitable learning objects for active learners.

原文English
頁(從 - 到)84-105
頁數22
期刊Educational Technology and Society
10
發行號3
出版狀態Published - 2007 7月

All Science Journal Classification (ASJC) codes

  • 教育
  • 社會學與政治學
  • 工程 (全部)

指紋

深入研究「Personalized learning objects recommendation based on the semantic-aware discovery and the learner preference pattern」主題。共同形成了獨特的指紋。

引用此