期刊
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
卷 13, 期 3, 页码 1390-1400出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAFFC.2020.3003243
关键词
Collaboration; Collaborative work; Task analysis; Emotion recognition; Face recognition; Leadership; Educational technology; Collaborative learning; educational technology; emotional mimicry; facial expressions recognition; multimodality
资金
- Finnish Academy [275440, 297686]
- Jiangsu Specially-Appointed Professor Program [3051107219003]
- Jiangsu joint research project of Sino-foreign cooperative education platform
- Talent Startup project of NJIT [YKJ201982]
This article explores the potential of emotional mimicry in identifying leader and follower students in collaborative learning settings. The findings suggest that video-based facial emotions recognition combined with cross-recurrence quantification analysis can accurately identify leaders and followers. This research highlights the importance of using these methods in collaborative learning research and their ability to explain social and affective dynamics within the setting.
This article 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 percent 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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