Abstract
Active Video Watching (AVW-Space) is an online platform for video-based learning which supports engagement via note-taking and personalized nudges. In this paper, we focus on the quality of the comments students write. We propose two schemes for assessing the quality of comments. Then, we evaluate these schemes by computing the inter-coder agreement. We also evaluate various machine learning classifiers to automate the assessment of comments. The selected cost-sensitive classifier shows that the quality of comments can be assessed with high weighted-F1 scores. This study contributes to the automation of comment quality assessment and the development of personalized educational support for engagement in video-based learning through commenting.
| Original language | English (US) |
|---|---|
| Title of host publication | ICCE 2020 - 28th International Conference on Computers in Education, Proceedings |
| Editors | Hyo-Jeong So, Ma. Mercedes Rodrigo, Jon Mason, Antonija Mitrovic, Daniel Bodemer, Weichao Chen, Zhi-Hong Chen, Brendan Flanagan, Marc Jansen, Roger Nkambou, Longkai Wu |
| Publisher | Asia-Pacific Society for Computers in Education |
| Pages | 1-10 |
| Number of pages | 10 |
| ISBN (Electronic) | 9789869721455 |
| State | Published - Nov 23 2020 |
| Externally published | Yes |
| Event | 28th International Conference on Computers in Education, ICCE 2020 - Virtual, Online Duration: Nov 23 2020 → Nov 27 2020 |
Conference
| Conference | 28th International Conference on Computers in Education, ICCE 2020 |
|---|---|
| City | Virtual, Online |
| Period | 11/23/20 → 11/27/20 |
Keywords
- Applied Machine Learning
- Learning Analytics
- Text Classification
- Video-based Learning
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Computer Science Applications
- Education