Abstract
Literature has indicated that negative emotions may lead students to disengagement in teaching activities. Furthermore, the contagion of negative emotion is similar to infectious disease diffusion that drives more students into negative emotions. However, few methods have been brought forward to intervene in negative emotional contagion in real time, and most of them are limited to interventions of teachers, which are often not timely and even cause students to resist. Intervention in negative emotional contagion in classroom imposes several fundamental challenges on model and system design. In this paper, we address these issues from the following three aspects: (1) to design an emotional contagion model for classroom scene to locate the source of negative emotional contagion; (2) to develop deep learning-based visual emotion recognition system to recognize emotions of all students in the classroom; (3) to design and deploy the emotion recognition system as an edge computing-based service for minimizing response time to achieve multi-person emotional recognition and intervene in real time. We have applied the system to real-world classroom. Our results have shown that the system achieved two objectives: (1) reducing the number of students with negative emotions; (2) reducing response time to achieve real-time recognition and intervention. Meanwhile, this work provides a new perspective on research into emotional contagion in the classroom and smart education.
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Acknowledgments
This work is supported by Jilin Province Development and Reform Commission, China (No. 2019C053-1), Development Project of Jilin Province of China (20170101006JC), the National Natural Science Foundation of China (No. 71620107001) and Jilin Provincial Key Laboratory of Big Date Intelligent Computing (20180622002JC).
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All authors have contributed to the intellectual content of this paper. Jian LI designed and conducted the models and experiments. Daqian Shi implemented the algorithms and analyzed the data. Piyaporn Tumnark designed the experiments and intervention mechanisms. Hao XU designed the research and conducted the project.
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This article belongs to the Topical Collection: Special Issue on Emerging Trends on Data Analytics at the Network Edge
Guest Editors: Deyu Zhang, Geyong Min, and Mianxiong Dong
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Li, J., Shi, D., Tumnark, P. et al. A system for real-time intervention in negative emotional contagion in a smart classroom deployed under edge computing service infrastructure. Peer-to-Peer Netw. Appl. 13, 1706–1719 (2020). https://doi.org/10.1007/s12083-019-00863-8
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DOI: https://doi.org/10.1007/s12083-019-00863-8