Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/6662
Title: Emotional and Cognitive Affordances of Collaborative Learning Environments
Authors: Zhu, Gaoxia
Teo, Chew Lee
Scardamalia, Marlene
Badron, Mohamed Faizal
Martin, Kit
Raman, Preeti
Hewitt, Jim
Teo, Tang Wee
Tan, Aik Ling
Ng, Andy
Nazeem, Raadiyah
Donoahue, Zoe
Lai, Zhixin
Ma, Leanne
Woodruff, Earl
Keywords: Learning and Identity
Issue Date: Jun-2020
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Zhu, G., Teo, C. L., Scardamalia, M., Badron, M. F., Martin, K., Raman, P., Hewitt, J., Teo, T. W., Tan, A. L., Ng, A., Nazeem, R., Donoahue, Z., Lai, Z., Ma, L., & Woodruff, E. (2020). Emotional and Cognitive Affordances of Collaborative Learning Environments. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 1 (pp. 382-389). Nashville, Tennessee: International Society of the Learning Sciences.
Abstract: Collaborative learning involves intricate interactions in which students participate in cognitive activities within social-emotional environments. Cognitive interactions mediate knowledge sharing, construction, and creation, while social-emotional interactions shape student perception of community climate and influence their emotional expressions, which, in turn, have a significant impact on their cognitive interactions. Although research has consistently found that social presence and student-student interaction has a positive influence on students' learning through emotional engagement, subject-based teaching remained largely more of cognitive activities. Teachers tend to treat lessons that heightened social-emotional aspects separate from subject-based lessons. This symposium brings together an international group of scholars to present recent studies on emotion and cognition in collaborative learning environments. Methods, such as self-report, video observation, affective state detection using FACET, and machine learning models, were adopted to investigate students' emotions. The results collectively suggest that these methods indeed served to uncover students' emotions; emotions such as joy/enjoyment/happiness, confidence, and surprise were associated with students' knowledge building progress; and that students' online interactions had a high impact on the emotional and linguistic tone of learners. The symposium aims to discuss the theoretical, practical and policy implications of these studies on collaborative learning.
URI: https://doi.dx.org/10.22318/icls2020.382
https://repository.isls.org//handle/1/6662
Appears in Collections:ICLS 2020

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