doi: 10.18178/ijiet.2019.9.5.1226
Measuring Students Affective States through Online Learning Logs — An Application of Learning Analytics
Yang Wang1
,
Qingtang Liu1 ,
David Stein2 ,
Qihui Xia3
- 1Central China Normal University, China
- 2Ohio State University, USA
- 3Nanjing Normal University, China
Abstract
The affective state is determinate to online learning quality. It is related to students’ attitude, learning motivation, and learning engagement. Learning affective states consists of engagement, frustration, confusion, and off-task state in this study. Different affective states are associated with different online learning behavior features. Affective states analysis consists of data collecting, data processing, affective states analyzing, evaluating, and intervening. Students’ affective states can be analyzed by the affective state detectors. 12,912 online learning operations from an online course are used to construct the affective state detectors and examine the effectiveness. The consistency of the analysis results with the self-reports supported that the model is reliable to analyze students’ affective state.
Keywords
- Research and application
- online affective state
- analysis model
How to Cite
Yang Wang, Qingtang Liu, David Stein, and Qihui Xia, "Measuring Students Affective States through Online Learning Logs — An Application of Learning Analytics," International Journal of Information and Education Technology, vol. 9, no. 5, pp. 356-361, 2019. https://doi.org/10.18178/ijiet.2019.9.5.1226
Copyright & License
Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).