Detecting Incomplete Learners in a Blended Learning Environment Among Japanese University Students

Authors

  • Minoru Nakayama CRADLE, Tokyo Institute of Technology
  • H. Kanazawa Uchida Yoko Co., Ltd.
  • H. Yamamoto CRADLE, Tokyo Institute of Technology, 152-8552 Japan

DOI:

https://doi.org/10.3991/ijet.v4i1.659

Keywords:

Blended learning, Incomplete participants, Access log, Discrimination

Abstract


To examine the feasibility of identifying incomplete participants who had not eventually completed a course in a blended learning environment using current learning behavioral data, access log data of complete and incomplete participants were analyzed. There is a significant difference between the two sets, and the number of accesses correlates with the final test score. Discrimination analysis was conducted using several variables across the learning process, and the ratio of those taking part in online tests was significant. Discrimination performance improved in relation to the number of accesses. The estimation performance was determined for two disparate courses in order to detect incomplete participants.

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Published

2008-11-15

How to Cite

Nakayama, M., Kanazawa, H., & Yamamoto, H. (2008). Detecting Incomplete Learners in a Blended Learning Environment Among Japanese University Students. International Journal of Emerging Technologies in Learning (iJET), 4(1), pp. 47–51. https://doi.org/10.3991/ijet.v4i1.659

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Section

Papers