EduBrowser : a multimodal automated monitoring system for co-located collaborative learning
Majority of learning analytics systems are designed to monitor and analyze students’ online interactions during collaborative learning. In the case of co-located collaborative learning, student interactions take place in the physical space as well as online. While existing learning management system...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Language: | English |
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Springer
2021
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| Online Access: | https://hdl.handle.net/10356/148324 |
| _version_ | 1811679175026671616 |
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| author | Chua, Victoria Yi Han Rajalingam, Preman Tan, Seng Chee Dauwels, Justin |
| author2 | Uden, Lorna |
| author_facet | Uden, Lorna Chua, Victoria Yi Han Rajalingam, Preman Tan, Seng Chee Dauwels, Justin |
| author_sort | Chua, Victoria Yi Han |
| collection | NTU |
| description | Majority of learning analytics systems are designed to monitor and analyze students’ online interactions during collaborative learning. In the case of co-located collaborative learning, student interactions take place in the physical space as well as online. While existing learning management systems provide specific logs and snapshots of students’ online responses that are automatically captured, the potential of insights that can be derived from students’ non-digital face-to-face interactions during collaborative discourse remains untapped. In this paper, we propose an architecture for data acquisition and processing from co-located face-to-face collaborative learning, designed to be scalable beyond dyadic and triadic collaborative learning and across different curricula. We outline the system design, current experience of deployment across 4 sessions of co-located collaborative learning sessions, as well as brief examples of acquired data. |
| first_indexed | 2024-10-01T03:04:58Z |
| format | Book Chapter |
| id | ntu-10356/148324 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:04:58Z |
| publishDate | 2021 |
| publisher | Springer |
| record_format | dspace |
| spelling | ntu-10356/1483242022-07-21T07:17:22Z EduBrowser : a multimodal automated monitoring system for co-located collaborative learning Chua, Victoria Yi Han Rajalingam, Preman Tan, Seng Chee Dauwels, Justin Uden, Lorna Liberona, Dario Sanchez, Galo Rodríguez-González, Sara Lee Kong Chian School of Medicine (LKCMedicine) School of Electrical and Electronic Engineering Centre for Research and Development in Learning (CRADLE) Engineering::Electrical and electronic engineering Collaborative Learning Multimodal Learning Analytics Majority of learning analytics systems are designed to monitor and analyze students’ online interactions during collaborative learning. In the case of co-located collaborative learning, student interactions take place in the physical space as well as online. While existing learning management systems provide specific logs and snapshots of students’ online responses that are automatically captured, the potential of insights that can be derived from students’ non-digital face-to-face interactions during collaborative discourse remains untapped. In this paper, we propose an architecture for data acquisition and processing from co-located face-to-face collaborative learning, designed to be scalable beyond dyadic and triadic collaborative learning and across different curricula. We outline the system design, current experience of deployment across 4 sessions of co-located collaborative learning sessions, as well as brief examples of acquired data. 2021-04-22T08:58:05Z 2021-04-22T08:58:05Z 2019 Book Chapter Chua, V. Y. H., Rajalingam, P., Tan, S. C. & Dauwels, J. (2019). EduBrowser : a multimodal automated monitoring system for co-located collaborative learning. Uden, L., Liberona, D., Sanchez, G. & Rodríguez-González, S. (Eds.), Learning Technology for Education Challenges: 8th International Workshop, LTEC 2019, Zamora, Spain, July 15–18, 2019, Proceedings (pp. 125-138). Springer. 978-3-030-20798-4 https://hdl.handle.net/10356/148324 10.1007/978-3-030-20798-4 2-s2.0-85066961195 125 138 en Learning Technology for Education Challenges: 8th International Workshop, LTEC 2019, Zamora, Spain, July 15–18, 2019, Proceedings © 2019 Springer Nature Switzerland AG. All rights reserved. Springer |
| spellingShingle | Engineering::Electrical and electronic engineering Collaborative Learning Multimodal Learning Analytics Chua, Victoria Yi Han Rajalingam, Preman Tan, Seng Chee Dauwels, Justin EduBrowser : a multimodal automated monitoring system for co-located collaborative learning |
| title | EduBrowser : a multimodal automated monitoring system for co-located collaborative learning |
| title_full | EduBrowser : a multimodal automated monitoring system for co-located collaborative learning |
| title_fullStr | EduBrowser : a multimodal automated monitoring system for co-located collaborative learning |
| title_full_unstemmed | EduBrowser : a multimodal automated monitoring system for co-located collaborative learning |
| title_short | EduBrowser : a multimodal automated monitoring system for co-located collaborative learning |
| title_sort | edubrowser a multimodal automated monitoring system for co located collaborative learning |
| topic | Engineering::Electrical and electronic engineering Collaborative Learning Multimodal Learning Analytics |
| url | https://hdl.handle.net/10356/148324 |
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