Bayesian network for predicting students' final grade using e-book logs in university education

Kousuke Mouri, Fumiya Okubo, Atsushi Shimada, Hiroaki Ogata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

This paper describes visualization and analysis methods using educational big data collected by research project at Kyushu University in Japan. The project uses an e-book system called BookLooper, Moodle, and Mahara. Logs for this analytics were collected from 99 first-year students in an information science course at Kyushu University. The number of logs are collected approximately 330,000, and this paper visualize and analyze the collected logs. The purpose of this study is to predict students' final grade and to profile visualization and analysis results. The prediction of this study shows that it leads to discoveries of students who fail to make the grade.

Original languageEnglish
Title of host publicationProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016
EditorsJ. Michael Spector, Chin-Chung Tsai, Ronghuai Huang, Paul Resta, Demetrios G Sampson, Kinshuk, Nian-Shing Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages85-89
Number of pages5
ISBN (Electronic)9781467390415
DOIs
Publication statusPublished - Nov 28 2016
Event16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 - Austin, United States
Duration: Jul 25 2016Jul 28 2016

Publication series

NameProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016

Other

Other16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016
CountryUnited States
CityAustin
Period7/25/167/28/16

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All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Education
  • Computer Networks and Communications
  • Computer Science Applications

Cite this

Mouri, K., Okubo, F., Shimada, A., & Ogata, H. (2016). Bayesian network for predicting students' final grade using e-book logs in university education. In J. M. Spector, C-C. Tsai, R. Huang, P. Resta, D. G. Sampson, Kinshuk, & N-S. Chen (Eds.), Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016 (pp. 85-89). [7756929] (Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICALT.2016.27