The effectiveness of an Intelligent Annotation Sharing System on e-learning

  • Authors:

  • Chun-Hsiung Lee;Gwo-Guang Lee;Yungho Leu

  • Affiliations:

  • Department of Information Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan;Department of Information Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan;Department of Information Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Reading is a very important part in learning process. When reading the teaching materials of textbooks in a traditional way, students usually underline the main points and take notes to help memorizing, thinking and understanding the contents of the teaching materials. With the progress of network technology, e-learning has gradually become a new learning trend. However, the digital e-teaching materials of e-learning are always the texts that cannot be changed by students as an easier reading format. In this paper, we propose an algorithm named Expert Keywords Annotation Alignment Algorithm (EKAAA) and based on which we have developed an Intelligent Annotation Sharing System (IASS) as an auxiliary tool for students to read the e-teaching materials. Based on the cluster to which a student belongs, the annotation sharing system adaptively provides the student a suitable sharing model. The models serve as a ''scaffolding'' to guide the students' learning, intending to achieve the purposes of auxiliary learning and knowledge sharing. Finally, we use statistics to analyze the effectiveness of the Intelligent Annotation Sharing System on e-learning.