IJIET 2013 Vol.3(6): 587-590 ISSN: 2010-3689
DOI: 10.7763/IJIET.2013.V3.341

Log Data Analysis of Learning Histories in an e-Learning Course

Koichiro Ishikawa, Masako Furukawa, Yutaka Saito, Takahiro Naito, and Mamiko Shichida

Abstract—Unfortunately, it has not yet been established fully the method how to analyze a log data set of learning histories obtained in an e-learning course. On the other hand, the researches in complex systems field report that patterns or regularities, such as power-law distribution, in higher or global level can be observed in many areas e.g., earthquakes, links between Web pages, sales result of books, etc. In this paper, we show that such an undisclosed macroscopic pattern or regularity in global level can emerge from the collective behaviors by learners in an e-learning course. We expect that such the patterns or regularities might be able to be employed as the useful information to understand learners’ behaviors well and to make efficient learning courses.

Index Terms—E-learning, power-law distribution, complex system, learning management system (LMS).

K. Ishikawa is with the Chiba Institute of Technology, Chiba, 275-0023, Japan (e-mail: koichiro.ishikawa@ it-chiba.ac.jp).
M. Furukawa, Y. Saito, and T. Naitoare are with the University of Tsukuba, Ibaraki, 305-8500 Japan (e-mail: furukawa@intersc.tsukuba.ac.jp, saito.yutaka.gf@intersc.tsukuba.ac.jp, tnaito@intersc.tsukuba.ac.jp).
M. Shichida is with the Shimane University, Shimane, 690-8504 Japan (e-mail: mshichida@ hirc.aoyama.ac.jp).

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Cite:Koichiro Ishikawa, Masako Furukawa, Yutaka Saito, Takahiro Naito, and Mamiko Shichida, "Log Data Analysis of Learning Histories in an e-Learning Course," International Journal of Information and Education Technology vol. 3, no. 6, pp. 587-590, 2013.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (Since 2019), EI(INSPEC, IET), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net