Zhou, Q;
Suraworachet, W;
Cukurova, M;
(2024)
Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning.
In:
LAK '24: Proceedings of the 14th Learning Analytics and Knowledge Conference.
(pp. pp. 392-403).
ACM
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Abstract
Using learning analytics to investigate and support collaborative learning has been explored for many years. Recently, automated approaches with various artificial intelligence approaches have provided promising results for modelling and predicting student engagement and performance in collaborative learning tasks. However, due to the lack of transparency and interpretability caused by the use of "black box"approaches in learning analytics design and implementation, guidance for teaching and learning practice may become a challenge. On the one hand, the black box created by machine learning algorithms and models prevents users from obtaining educationally meaningful learning and teaching suggestions. On the other hand, focusing on group and cohort level analysis only can make it difficult to provide specific support for individual students working in collaborative groups. This paper proposes a transparent approach to automatically detect student's individual engagement in the process of collaboration. The results show that the proposed approach can reflect student's individual engagement and can be used as an indicator to distinguish students with different collaborative learning challenges (cognitive, behavioural and emotional) and learning outcomes. The potential of the proposed collaboration analytics approach for scaffolding collaborative learning practice in face-to-face contexts is discussed and future research suggestions are provided.
| Type: | Proceedings paper |
|---|---|
| Title: | Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative Learning |
| Event: | LAK '24: The 14th Learning Analytics and Knowledge Conference |
| ISBN-13: | 9798400716188 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3636555.3636894 |
| Publisher version: | https://doi.org/10.1145/3636555.3636894 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution International 4.0 License. |
| Keywords: | Multimodal learning analytics, Physical collaborative learning, Individual learning engagement |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10189721 |
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