Automatic assessment of comment quality in active video watching

Type of content
Conference Contributions - Published
Publisher's DOI/URI
Thesis discipline
Degree name
Asia-Pacific Society for Computers in Education
Journal Title
Journal ISSN
Volume Title
Mohammadhassan N
Mitrovic, Antonija
Neshatian, Kourosh
Dunn J

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.

Mohammadhassan N, Mitrovic A, Neshatian K, Dunn J (2020). Automatic quality assessment of comments in active video watching using machine learning techniques. Virtual conference: the 28th International Conference on Computers in Education. 23/11/2020-27/11/2020. I. 1-10.
Video-based Learning, Learning Analytics, Applied Machine Learning, Text Classification
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Fields of Research::39 - Education::3904 - Specialist studies in education::390405 - Educational technology and computing
Fields of Research::39 - Education::3904 - Specialist studies in education::390408 - Learning analytics
Fields of Research::46 - Information and computing sciences::4611 - Machine learning::461199 - Machine learning not elsewhere classified
All rights reserved unless otherwise stated