University of Oulu

M. Dindar, S. Järvelä, S. Ahola, X. Huang and G. Zhao, "Leaders and Followers Identified by Emotional Mimicry During Collaborative Learning: A Facial Expression Recognition Study on Emotional Valence," in IEEE Transactions on Affective Computing, vol. 13, no. 3, pp. 1390-1400, 1 July-Sept. 2022, doi: 10.1109/TAFFC.2020.3003243

Leaders and followers identified by emotional mimicry during collaborative learning : a facial expression recognition study on emotional valence

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Author: Dindar, Muhterem1; Järvelä, Sanna1; Ahola, Sara1;
Organizations: 1Learning and Educational Technology (LET) research group, University of Oulu, Oulu 90014, Finland
2School of Computer Engineering, Nanjing Institute of Technology, Nanjing, China
3Center for Machine Vision and Signal Analysis, University of Oulu, Oulu 90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021102051679
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-20
Description:

Abstract

This study explores the potential of emotional mimicry in identifying the leader and follower students in collaborative learning settings. Our data include video recorded interactions of 24 high school students who worked together in groups of three during a collaborative exam. A facial emotions recognition method was used to capture participants’ facial emotions during the collaborative work. Cross-recurrence quantification analysis was applied on the detected facial emotions to see the level and direction of emotional mimicry among the dyads in the same groups. In order to validate the cross-recurrence quantification analysis results, student interactions in terms of leading or following the task were video coded. Our findings showed that the leaders and followers identified by cross-recurrence quantification analysis findings matched the leaders and followers identified by the video coding in 70% of the dyadic interactions across the collaborating groups. The current findings show that video-based facial emotions recognition as a method can add to collaborative learning research, especially explaining some social, and affective dynamics about it. The study further discusses the possible variables that might confound the relationship between emotional mimicry and leader-follower interactions during collaboration.

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Series: IEEE transactions on affective computing
ISSN: 2371-9850
ISSN-E: 1949-3045
ISSN-L: 2371-9850
Volume: 13
Issue: 3
Pages: 1390 - 1400
DOI: 10.1109/TAFFC.2020.3003243
OADOI: https://oadoi.org/10.1109/TAFFC.2020.3003243
Type of Publication: A1 Journal article – refereed
Field of Science: 516 Educational sciences
113 Computer and information sciences
Subjects:
Funding: This study was supported by the Finnish Academy grants 275440; 297686. University of Oulu LeaF research infrastructure has been used in data collection.
Academy of Finland Grant Number: 275440
297686
Detailed Information: 275440 (Academy of Finland Funding decision)
297686 (Academy of Finland Funding decision)
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