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

PROCEEDINGS OF THE 25TH INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, ICMI 2023(2023)

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摘要
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.
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关键词
Recurrence quantification analysis,Eye tracking,Group programming,Collaborative problem solving
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