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Coupling Interactions and Performance: Predicting Team Performance from Thin Slices of Conflict

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Malte F. JungAuthors Info & Claims

ACM Transactions on Computer-Human Interaction (TOCHI), Volume 23, Issue 3

Article No.: 18, Pages 1 - 32

https://doi.org/10.1145/2753767

Published: 14 June 2016 Publication History

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Abstract

Do teams show stable conflict interaction patterns that predict their performance hours, weeks, or even months in advance? Two studies demonstrate that two of the same patterns of emotional interaction dynamics that distinguish functional from dysfunctional marriages also distinguish high from low-performance design teams in the field, up to 6 months in advance, with up to 91% accuracy, and based on just 15minutes of interaction data: Group Affective Balance, the balance of positive to negative affect during an interaction, and Hostile Affect, the expression of a set of specific negative behaviors were both found as predictors of team performance. The research also contributes a novel method to obtain a representative sample of a team's conflict interaction. Implications for our understanding of design work in teams and for the design of groupware and feedback intervention systems are discussed.

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Coupling Interactions and Performance: Predicting Team Performance from Thin Slices of Conflict

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Reviews

Reviewer: Barrett Hazeltine

The basic question is whether the performance of a team can be predicted from a 15-minute observation, a "thin slice" of the team resolving a conflict. The answer appears to be "yes." A follow-on study, again based on a short observation, teased out particularly harmful individual behaviors. The approach is based on a highly effective predictor of whether a couple will stay married [1]. The research used video recordings of an engineering design team working through a significant design disagreement. After the discussion/conflict, each team member was shown the video and asked to record her/his emotional state, positive or negative, at particular moments of the discussion. The predictor is the arithmetic difference between the amount of time the state was positive and the state was negative; 35 percent of team performance, measured 2.5 months after the experiment, was predicted by this difference. (Team performance was evaluated through a self-report survey.) In a second study, the videos were analyzed looking at facial expressions, tone of voice, verbal content, and body posture. Hostile behavior, gleaned from the video analyses, was found to be highly correlated (negatively) with measures of team performance. This paper is recommended because the approach is novel and promising, although it is unnecessarily long. Also, the word "affect" is used with a particular meaning that needs clarification. Online Computing Reviews Service

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cover image ACM Transactions on Computer-Human Interaction

ACM Transactions on Computer-Human Interaction Volume 23, Issue 3

July 2016

169 pages

ISSN:1073-0516

EISSN:1557-7325

DOI:10.1145/2952594

Editor:
Ken Hinckley
Microsoft Research

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Publication History

Published: 14 June 2016

Accepted: 01 April 2016

Revised: 01 March 2016

Received: 01 March 2015

Published in TOCHI Volume 23, Issue 3

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Ferguson SVan De Zande GOlechowski A(2024)No Risk, No Reward: Towards An Automated Measure of Psychological Safety from Online CommunicationExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650923(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650923
Annelin AChe L(2023)Audit Team Distance and Audit Quality Threatening BehaviorAuditing: A Journal of Practice & Theory10.2308/AJPT-2019-514(1-23)Online publication date: 8-Sep-2023
https://doi.org/10.2308/AJPT-2019-514
Zhang QNarcomey ACandon KVázquez MCastellano GRiek LCakmak MLeite I(2023)Self-Annotation Methods for Aligning Implicit and Explicit Human Feedback in Human-Robot InteractionProceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3568162.3576986(398-407)Online publication date: 13-Mar-2023
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