Emotional Synchrony Through Regulatory Triggers in Collaborative Learning: A Facial Expression Recognition Study

Abstract

Despite the importance of socially shared regulation of learning (SSRL) in collaborative learning success, there remains a paucity of evidence on how it could be detected and supported effectively. In this paper, we present an experimental study with a systematic analysis approach that utilizes facial expression recognition technology to examine emotional triggers for collaborative learning regulation. The study involved high school students (N=27) working in groups of three with a collaborative learning task. During the learning process, the collaborative groups were intervened with a controlled cognitive trigger followed by three emotional triggers. AI facial expression recognition was utilized for analyzing students' continuous valence and changes in emotions throughout the collaborative learning task. Cross-recurrence quantification analysis (cRQA) approach has been employed to examine emotional synchrony through regulatory triggers. Our findings present evidence for the regulatory trigger concept and offer novel insights into how the regulatory triggers facilitate emotional synchronization among learners in collaborative learning. Furthermore, the study also demonstrates the use of AI technology for examining collaborative learning regulation. The study further discusses not only the potential role of the trigger concept in generating a better understanding of the regulatory processes but also its contribution to establishing foundations for designing support for regulation in collaborative learning.