Modelling collaborative problem-solving competence with transparent learning analytics: Is video data enough?
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
In this study, we describe the results of our research to model collaborative problem-solving (CPS) competence based on analytics generated from video data. We have collected ~500 mins video data from 15 groups of 3 students working to solve design problems collaboratively. Initially, with the help of OpenPose, we automatically generated frequency metrics such as the number of the face-in-the-screen; and distance metrics such as the distance between bodies. Based on these metrics, we built decision trees to predict students' listening, watching, making, and speaking behaviours as well as predicting the students' CPS competence. Our results provide useful decision rules mined from analytics of video data which can be used to inform teacher dashboards. Although, the accuracy and recall values of the models built are inferior to previous machine learning work that utilizes multimodal data, the transparent nature of the decision trees provides opportunities for explainable analytics for teachers and learners. This can lead to more agency of teachers and learners, therefore can lead to easier adoption. We conclude the paper with a discussion on the value and limitations of our approach.
Original language | English |
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Title of host publication | LAK 2020 Conference Proceedings - Celebrating 10 years of LAK : Shaping the Future of the Field - 10th International Conference on Learning Analytics and Knowledge |
Number of pages | 6 |
Publisher | ACM Association for Computing Machinery |
Publication date | 23 Mar 2020 |
Pages | 270-275 |
ISBN (Electronic) | 9781450377126 |
DOIs | |
Publication status | Published - 23 Mar 2020 |
Externally published | Yes |
Event | 10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020 - Frankfurt, Germany Duration: 23 Mar 2020 → 27 Mar 2020 |
Conference
Conference | 10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020 |
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Land | Germany |
By | Frankfurt |
Periode | 23/03/2020 → 27/03/2020 |
Series | ACM International Conference Proceeding Series |
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- Collaborative problem-solving, Decision trees, Multimodal learning analytics, Physical learning analytics, Video analytics
Research areas
ID: 256266108