What can instructors and policy makers learn about Web-supported learning through Web-usage mining

Anat Cohen, Rafi Nachmias

Research output: Contribution to journalArticlepeer-review

Abstract

This paper focuses on a Web-log based tool for evaluating pedagogical processes occurring in Web-supported academic instruction and students' attitudes. The tool consists of computational measures which demonstrate what instructors and policy makers can learn about Web-supported instruction through Web-usage mining. The tool can provide different measures and reports for instructors at the micro level, and for policy makers at the macro level. The instructors' reports provide feedback relating to the pedagogical processes in their course Websites in comparison to other similar courses on campus. The policy makers' reports provide data about the extent of use of course Websites across the campus, the benefits of such use, and the return on investment. This paper describes the tool and its computational measures as well as its implementation, first on a sample course and next on 3453 course Websites at Tel-Aviv University.

Original languageEnglish
Pages (from-to)67-76
Number of pages10
JournalInternet and Higher Education
Volume14
Issue number2
DOIs
StatePublished - Mar 2011

Keywords

  • Campus-wide
  • Computational measures
  • Web-supported learning
  • Web-usage mining

All Science Journal Classification (ASJC) codes

  • Education
  • Computer Science Applications
  • Computer Networks and Communications

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