Becerra, A;
Daza, R;
Cobos, R;
Morales, A;
Cukurova, M;
Fierrez, J;
(2023)
M2LADS: A System for Generating MultiModal Learning Analytics Dashboards.
In:
Proceedings of the 47th Annual Computers, Software, and Applications Conference (COMPSAC) 2023.
(pp. pp. 1564-1569).
Institute of Electrical and Electronics Engineers (IEEE)
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Abstract
In this article, we present a Web-based System called M2LADS, which supports the integration and visualization of multimodal data recorded in learning sessions in a MOOC in the form of Web-based Dashboards. Based on the edBB platform, the multimodal data gathered contains biometric and behavioral signals including electroencephalogram data to measure learners' cognitive attention, heart rate for affective measures, visual attention from the video recordings. Additionally, learners' static background data and their learning performance measures are tracked using LOGCE and MOOC tracking logs respectively, and both are included in the Web-based System. M2LADS provides opportunities to capture learners' holistic experience during their interactions with the MOOC, which can in turn be used to improve their learning outcomes through feedback visualizations and interventions, as well as to enhance learning analytics models and improve the open content of the MOOC.
| Type: | Proceedings paper |
|---|---|
| Title: | M2LADS: A System for Generating MultiModal Learning Analytics Dashboards |
| Event: | 47th Annual Computers, Software, and Applications Conference (COMPSAC) 2023 |
| Location: | Torino, Italy |
| Dates: | 26th-30th Jun 2023 |
| ISBN-13: | 979-8-3503-2697-0 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/COMPSAC57700.2023.00241 |
| Publisher version: | https://doi.org/10.1109/COMPSAC57700.2023.00241 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Open Education, MOOC, e-Learning, Biometrics and Behavior, Multimodal Learning Analytics, Web-based Technology, Computer Science & Information Technology |
| 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.ucl.ac.uk/id/eprint/10176717 |
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