An Investigation of Pre-Service Teachers Using Mobile and Wearable Devices for Emotion Recognition and Social Sharing of Emotion to Support Emotion Regulation in mCSCL Environments

Autor/inn/en	Wetcho, Suthanit; Na-Songkhla, Jaitip
Titel	An Investigation of Pre-Service Teachers Using Mobile and Wearable Devices for Emotion Recognition and Social Sharing of Emotion to Support Emotion Regulation in mCSCL Environments
Quelle	In: Contemporary Educational Technology, 14 (2022) 2, S.359 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Wetcho, Suthanit) ORCID (Na-Songkhla, Jaitip)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1309-517X
Schlagwörter	Preservice Teachers; Social Emotional Learning; Assistive Technology; Handheld Devices; Learning Processes; Foreign Countries; Emotional Response; Physiology; Cooperative Learning; Emotional Intelligence; Empathy; Thailand + Suchen Sie Ihr Suchwort? Learning process; Lernprozess; Ausland; Emotionales Verhalten; Physiologie; Kooperatives Lernen; Emotionale Intelligenz; Empathie
Abstract	In the era of a workforce driven by automation and artificial intelligence, social and emotional skills are becoming increasingly relevant to online learning environments. Since social-emotional learning may be defined as a vital component of the learning process in professional instructional design practices, online learners not only need to develop the ability to apply their knowledge, attitudes, and skills but also to understand and manage their emotions. In which setting and achieving positive goals through social interaction, sharing feelings, and developing empathy for others can help with the process. This paper outlines the possibility of using emotion recognition, and social sharing of emotion techniques to support the regulation of emotion in pre-service teacher education. This study aimed to investigate pre-service teachers' emotion recognition tools acquired by emotion tracker and physiological signals based on their perceptions (without a concrete experience and knowledge). Moreover, the predictive ability was examined along with the relationships between emotion recognition, social sharing of emotion, and emotion regulation. Finally, we investigated emotion adjustment techniques that can be adapted into mobile computer-supported collaborative learning (mCSCL). In this study, 183 pre-service teachers from three different teacher-education institutions in Thailand, were voluntarily participated based on convenience sampling. The results of a self-report via online survey revealed that most pre-service teachers own at least one of the mobile technologies e.g., smartphones, tablets, or laptops. However, there is an increasing number of additional gadgets and wearable devices like EarPods and smartwatches. At the current time, it is nearly impossible to use of the IoT and other wearable devices. According to their subjective impressions in which corresponded to emotion recognition in the scientific literature, Heart rate (HR) and Heart rate variability (HRV) have recognized the most possibilities for emotion detection among physiological signals. Regarding regression analysis, the two-predictor models of emotion recognition and the social sharing of emotion were also able to account for 31% of the variance in emotion regulation, p<0.001, R[superscript 2]=0.31, and 95% CI [0.70, 0.77]. In addition, the mCSCL applications and the importance of these variables in different collaboration levels are also discussed. (As Provided).
Anmerkungen	Contemporary Educational Technology. Faculty of Communication Sciences, Anadolu University, Yunus Emre Campus, Eskisehir 26470, Turkey. e-mail: editor@cedtech.net; Web site: http://www.cedtech.net
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01