Synerg-eye-zing: Decoding Nonlinear Gaze Dynamics Underlying Successful Collaborations in Co-located Teams

G. S. Rajshekar Reddy, Lucca Eloy, Rachel Dickler, Jason G. Reitman, Samuel L. Pugh, Peter W. Foltz, Jamie C. Gorman, Julie L. Harrison, Leanne Hirshfield
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Abstract

Joint Visual Attention (JVA) has long been considered a critical component of successful collaborations, enabling coordination and construction of a shared knowledge space. However, recent studies challenge the notion that JVA alone ensures effective collaboration. To gain deeper insights into JVA’s influence, we examine nonlinear gaze coupling and gaze regularity in the collaborators’ visual attention. Specifically, we analyze gaze data from 19 dyadic and triadic teams engaged in a co-located programming task using Recurrence Quantification Analysis (RQA). Our results emphasize the significance of team-level gaze regularity for improving task performance - highlighting the importance of maintaining stable or sustained episodes of joint or individual attention, than disjointed patterns. Additionally, through regression analyses, we examine the predictive capacity of recurrence metrics for subjective traits such as social cohesion and social loafing, revealing unique interpersonal and team dynamics behind productive collaborations. We elaborate on our findings via qualitative anecdotes and discuss their implications in shaping real-time interventions for optimizing collaborative success.
协同注视:解码同地团队成功合作的非线性注视动力学
长期以来,联合视觉注意(JVA)一直被认为是成功协作的关键组成部分,它使共享知识空间的协调和构建成为可能。然而,最近的研究挑战了JVA单独确保有效协作的概念。为了更深入地了解JVA的影响,我们研究了合作者视觉注意中的非线性凝视耦合和凝视规律。具体来说,我们使用递归量化分析(RQA)分析了19个参与同一地点编程任务的二元和三元团队的凝视数据。我们的研究结果强调了团队层面的凝视规律对提高任务表现的重要性——强调了保持稳定或持续的联合或个人注意力的重要性,而不是不连贯的模式。此外,通过回归分析,我们研究了重现度量对主观特征(如社会凝聚力和社会懒惰)的预测能力,揭示了高效合作背后独特的人际关系和团队动态。我们通过定性轶事详细阐述了我们的发现,并讨论了它们在塑造实时干预措施以优化合作成功方面的意义。
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