How to Mine Student Behavior Patterns in the Traditional Classroom

DOI

10.2991/icat2e-17.2016.24How to use a DOI?

Keywords

Learning Analytics, Data of Traditional Classroom, Clustering, Backtrack Reading

Abstract

Many learning analyses focus on online learning courses, such as massive open online courses (MOOCs). The analysis of learning behaviors from access log data is expected to be of benefit to instructors and learners. However, there are few studies that focus on the reading logs of digital textbooks in the traditional classroom. This study adopts a new approach to analyzing learning behavior patterns through digital textbook use. Students were grouped into four clusters using k-means clustering to analyze their learning behavior patterns.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chengjiu Yin
PY  - 2017/03
DA  - 2017/03
TI  - How to Mine Student Behavior Patterns in the Traditional Classroom
BT  - Proceedings of The 2017 International Conference on Advanced Technologies Enhancing Education (ICAT2E 2017)
PB  - Atlantis Press
SP  - 103
EP  - 106
SN  - 2352-5398
UR  - https://doi.org/10.2991/icat2e-17.2016.24
DO  - 10.2991/icat2e-17.2016.24
ID  - Yin2017/03
ER  -