Title: Do birds of a feather work better together? The impact of a match in personality between humans and virtual agents on a shared mental model during collaboration

Authors: Nader Hanna; Deborah Richards

Addresses: Computing Department, Macquarie University, NSW 2109, Sydney, Australia ' Computing Department, Macquarie University, NSW 2109, Sydney, Australia

Abstract: A shared mental model (SMM) between human team members has been found to improve teamwork performance. In the literature, multimodal communication of shared knowledge has been reported to influence the development of a SMM. In virtual worlds, within a team comprised of a human and an intelligent virtual agent (IVA), the influence of IVA personality on collaboration and development of a SMM has not been previously studied. In this study, we explore the impact of an IVA's personality traits on the development of taskwork and teamwork SMMs with human teammates. Moreover, this study investigated the influence of a match in personality traits between IVAs and humans on the development of a SMM. In this study, five versions of an IVA performing the same scenario were developed. Besides a neutral personality, four combinations of two personality traits, i.e., extraversion and agreeableness were created. Participants were divided into five groups each assigned one version of the IVA. The results showed that agreeable IVAs positively impacted on the development of taskwork and teamwork SMMs; whereas extraversion did not influence development of the SMM. Moreover, when the human and IVA had matching agreeableness personality traits, SMM development and performance improved.

Keywords: personality traits; extraversion; agreeableness; five factor model; FFM; shared mental model; SMM; human-agent teamwork; intelligent agents; virtual agents; multi-agent systems; MAS; agent-based systems; collaboration; teamwork performance; extraverts.

DOI: 10.1504/IJCISTUDIES.2016.077134

International Journal of Computational Intelligence Studies, 2016 Vol.5 No.2, pp.162 - 179

Available online: 19 Jun 2016

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