Spikol, D;
Ruffaldi, E;
Landolfi, L;
Cukurova, M;
(2017)
Estimation of Success in Collaborative Learning Based on Multimodal Learning Analytics Features.
In:
(Proceedings) 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT).
(pp. pp. 269-273).
IEEE
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Abstract
Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates high-fidelity synchronised multimodal recordings of small groups of learners interacting from diverse sensors that include computer vision, user generated content, and data from the learning objects (like physical computing components or laboratory equipment). We processed and extracted different aspects of the students' interactions to answer the following question: which features of student group work are good predictors of team success in open-ended tasks with physical computing? The answer to the question provides ways to automatically identify the students' performance during the learning activities.
| Type: | Proceedings paper |
|---|---|
| Title: | Estimation of Success in Collaborative Learning Based on Multimodal Learning Analytics Features |
| Event: | 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) |
| ISBN-13: | 9781538638705 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICALT.2017.122 |
| Publisher version: | http://doi.org/10.1109/ICALT.2017.122 |
| 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: | Multimodal learning analytics, collaborative learning, practice-based learning |
| 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/10028156 |
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