Automatic assessment of comment quality in active video watching (2020)
Alternative TitleAutomatic quality assessment of comments in active video watching using machine learning techniques
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.
CitationMohammadhassan 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.
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KeywordsVideo-based Learning; Learning Analytics; Applied Machine Learning; Text Classification
ANZSRC Fields of Research39 - Education::3904 - Specialist studies in education::390405 - Educational technology and computing
39 - Education::3904 - Specialist studies in education::390408 - Learning analytics
46 - Information and computing sciences::4611 - Machine learning::461199 - Machine learning not elsewhere classified
RightsAll rights reserved unless otherwise stated
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Mohammadhassan N; Mitrovic, Antonija; Neshatian, Kourosh (Elsevier BV, 2022)Developing and maintaining constructive engagement is a crucial challenge in learning by watching videos. AVW-Space is an online video-based learning platform which enhances student engagement via note-taking and ...
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