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    Automatic assessment of comment quality in active video watching (2020)

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    Type of Content
    Conference Contributions - Published
    UC Permalink
    https://hdl.handle.net/10092/101306
    
    Publisher
    Asia-Pacific Society for Computers in Education
    Collections
    • Engineering: Conference Contributions [2338]
    Authors
    Mohammadhassan N
    Mitrovic, Antonija cc
    Neshatian, Kourosh cc
    Dunn J
    show all
    Editors
    So H-J
    Rodrigo MM
    Mason J
    Mitrovic A
    Alternative Title
    Automatic quality assessment of comments in active video watching using machine learning techniques
    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.

    Citation
    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.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    Video-based Learning; Learning Analytics; Applied Machine Learning; Text Classification
    ANZSRC Fields of Research
    39 - 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
    Rights
    All rights reserved unless otherwise stated
    http://hdl.handle.net/10092/17651

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