TY - GEN
T1 - Exploring collective physiology sharing as social cues to support engagement in online learning
AU - Han, Jiawen
AU - Yang, Chi Lan
AU - Chernyshov, George
AU - Fu, Zhuoqi
AU - Horii, Reiya
AU - Narumi, Takuji
AU - Kunze, Kai
N1 - Funding Information:
This work is conducted under the Cybernetic Being project supported by JST Moonshot R&D Program Grant Number JPMJMS2013 and the Keio University Doctorate Student Grant-in-Aid Program from Ushioda Memorial Fund.
Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/5/12
Y1 - 2021/5/12
N2 - Insufficient social cues between distributed learners in online learning could result in lack of engagement and social bonds. With the development of wearable sensing, sharing physiological data can be used to enhance mutual understanding and connectedness among sharers. Our work aims to explore the potential of sharing heart rate (HR) and heart rate variability (HRV) collected from distributed learners to enhance their online learning experiences. We implemented a physiological streaming system and conducted a field study with 11 learners in online classes. This paper describes the study and discusses our interview findings by contrasting the influence of visualized collective physiological data from viewpoints of data contributors and viewers. Our exploratory results suggest streaming collective HR and HRV from multiple distributed learners could be used in online classes to improve engagement and sense of community.
AB - Insufficient social cues between distributed learners in online learning could result in lack of engagement and social bonds. With the development of wearable sensing, sharing physiological data can be used to enhance mutual understanding and connectedness among sharers. Our work aims to explore the potential of sharing heart rate (HR) and heart rate variability (HRV) collected from distributed learners to enhance their online learning experiences. We implemented a physiological streaming system and conducted a field study with 11 learners in online classes. This paper describes the study and discusses our interview findings by contrasting the influence of visualized collective physiological data from viewpoints of data contributors and viewers. Our exploratory results suggest streaming collective HR and HRV from multiple distributed learners could be used in online classes to improve engagement and sense of community.
KW - engagement
KW - online learning system
KW - physiological sensing
KW - visualization
UR - http://www.scopus.com/inward/record.url?scp=85125856722&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85125856722&partnerID=8YFLogxK
U2 - 10.1145/3490632.3497827
DO - 10.1145/3490632.3497827
M3 - Conference contribution
AN - SCOPUS:85125856722
T3 - ACM International Conference Proceeding Series
SP - 192
EP - 194
BT - Proceedings of the 20th International Conference on Mobile and Ubiquitous Multimedia, MUM 2021
PB - Association for Computing Machinery
T2 - 20th International Conference on Mobile and Ubiquitous Multimedia, MUM 2021
Y2 - 5 December 2021 through 8 December 2021
ER -