Deep Structures of Collaboration - Robotics Institute Carnegie Mellon University

Deep Structures of Collaboration

Master's Thesis, Tech. Report, CMU-RI-TR-17-36, Robotics Institute, Carnegie Mellon University, August, 2017

Abstract

Collective intelligence (CI), a group’s capacity to perform a wide variety of tasks, is a key factor in successful collaboration. Group composition, particularly diversity and member social perceptiveness, are consistent predictors of CI, but we have limited knowledge about the mechanisms underlying their effects. To address this gap, we examine how physiological synchrony, as an indicator of coordination and rap- port, relates to CI in computer-mediated teams, and if synchrony might serve as a mechanism explaining the effect of group composition on CI. We present results from a laboratory experiment where 120 dyads completed the Test of Collective Intelligence (TCI) together online and rated their group satisfaction, while wear- ing physiological sensors. The first 60 dyads communicated via video and audio in study 1, while the next 60 dyads communicated via audio only in study 2. In study 1, we find that synchrony in facial expressions and synchrony in standard deviation of loudness in speech (both indicative of shared experience) was associated with CI and synchrony in electrodermal activity (indicative of shared arousal) with group satisfaction. Furthermore, various forms of synchrony mediated the effect of member diversity and social perceptiveness on CI and group satisfaction. In study 2, synchrony in facial expressions no longer had an effect on CI, but synchrony in standard deviation of loudness in speech continued to positively effect CI. Our results have important implications for online collaborations and distributed teams.

BibTeX

@mastersthesis{Chikersal-2017-27194,
author = {Prerna Chikersal},
title = {Deep Structures of Collaboration},
year = {2017},
month = {August},
school = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-17-36},
keywords = {Physiological synchrony, Behavioral similarity, Collective Intelligence, Distributed/ virtual teams},
}