How Real-Time Social Biofeedback could affect University Students’ Presentation Experiences: A Mixed Method Approach

Preprint 2022

Selina He and Youngjun Cho
Department of Computer Science, University College London, London, UK

Public speaking is an essential soft skill for professional development. However, public speaking tends to be one of the stressors to university students. Here, we are interested in biofeedback, an intervention technique that can possibly hinder our negative emotional responses triggered by stress-related problems. Particularly, we investigate to what extent shared use of biofeedback across users (social biofeedback) can improve student presenters’ experiences during academic oral presentations. In a mixed-method study with 15 participants, we demonstrate a significant improvement of presenters’ affective states (toward higher arousal and higher valence) with social biofeedback in comparison with typical biofeedback and control. Also, our thematic analysis suggests its positive influences on presenters’ self-oriented regulations, others’-oriented regulations, and task-oriented regulations. We conclude by highlighting social biofeedback’s potential benefits in enhancing engagement and social connectedness in remote learning/teaching environments.
*This work builds on our previous projects (see details in [1-8]).


[1] Moge, C., Wang, K. and Cho, Y., 2022. Shared user interfaces of physiological data: Systematic review of social biofeedback systems and contexts in HCI. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-16).

[2] Cho, Y., 2021. Rethinking eye-blink: Assessing task difficulty through physiological representation of spontaneous blinking. In Proceedings of the 2021 CHI conference on human factors in computing systems (pp. 1-12).

[3] Cho, Y., Bianchi-Berthouze, N. and Julier, S.J., 2017. DeepBreath: Deep learning of breathing patterns for automatic stress recognition using low-cost thermal imaging in unconstrained settings. In 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 456-463.

[4] Cho, Y., Julier, S. J. and Bianchi-Berthouze, N., 2019. Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging. JMIR mental health, 6(4), e10140.

[5] Cho, Y. and Bianchi-Berthouze, N., 2019. Physiological and affective computing through thermal imaging: A survey. arXiv preprint arXiv:1908.10307.

[6] Cho, Y., et al.,2019. Nose heat: Exploring stress-induced nasal thermal variability through mobile thermal imaging. In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 566-572

[7] Cho, Y., Kim, S. and Joung, M., 2017. Proximity sensor and control method thereof. U.S. Patent 9,703,368.

[8] Cho, Y., Julier, S.J., Marquardt, N. and Bianchi-Berthouze, N., 2017. Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging. Biomedical optics express8(10), pp.4480-4503.