Cognitive Collaboration Found in Cardiac Physiology: Study in Classroom Environment
Author(s) -
Lauri Ahonen,
Benjamin Ultan Cowley,
Jari Torniainen,
Antti Ukkonen,
Arto Vihavainen,
Kai Puolamäki
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0159178
Subject(s) - workload , teamwork , session (web analytics) , heart rate variability , computer science , quality (philosophy) , cognition , field (mathematics) , compliance (psychology) , heart rate , applied psychology , psychology , medicine , neuroscience , blood pressure , world wide web , philosophy , epistemology , political science , law , radiology , operating system , social psychology , mathematics , pure mathematics
It is known that periods of intense social interaction result in shared patterns in collaborators’ physiological signals. However, applied quantitative research on collaboration is hindered due to scarcity of objective metrics of teamwork effectiveness. Indeed, especially in the domain of productive, ecologically-valid activity such as programming, there is a lack of evidence for the most effective, affordable and reliable measures of collaboration quality. In this study we investigate synchrony in physiological signals between collaborating computer science students performing pair-programming exercises in a class room environment. We recorded electrocardiography over the course of a 60 minute programming session, using lightweight physiological sensors. We employ correlation of heart-rate variability features to study social psychophysiological compliance of the collaborating students. We found evident physiological compliance in collaborating dyads’ heart-rate variability signals. Furthermore, dyads’ self-reported workload was associated with the physiological compliance. Our results show viability of a novel approach to field measurement using lightweight devices in an uncontrolled environment, and suggest that self-reported collaboration quality can be assessed via physiological signals.
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