Facilitating Online Collaborative Learning Through Affective Computing

DOI

10.2991/978-94-6463-040-4_133How to use a DOI?

Keywords

Collaborative learning; Affective Computing; CNNs; emotion; e-learner

Abstract

Affective Computing (AC) has immersed potential to improve the performance and experience for Collaborative Learning (CL) e-learners by inferring, recognizing and processing e-learners’ affective information. Exploring the online CL involves AC algorithm with two groups of identical activities supported by the project of the CSC-UBC. One group implements EmotionSence platform to detect e-learners’ emotional states that is based on Convolutional neural networks (CNNs) model, while the other group only employs the traditional online CL. Finally, the results reveal that the better learning performance and experience are from the second group, whereas barely difference of learning outcome between individuals.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhuting Sun
PY  - 2022
DA  - 2022/12/27
TI  - Facilitating Online Collaborative Learning Through Affective Computing
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 882
EP  - 888
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_133
DO  - 10.2991/978-94-6463-040-4_133
ID  - Sun2022
ER  -