研究团队在无沟通下如何通过空间移动协调,提升搜救表现。
Measuring Implicit Spatial Coordination in Teams: Effects on Collective Intelligence and Performance
- 用空间移动模式衡量隐性协作,关注探索多样性、角色分工与动态接近度。
- 角色分工越明确,团队表现越好;动态接近度呈倒U型,适度调整最优。
- 适合研究人机协同、应急团队训练或智能辅助系统的开发者参考。
在无需显式沟通的快速决策环境中,团队需依靠隐性空间协调完成任务。本文研究三类空间协调维度——探索多样性、运动专业化和自适应空间邻近性——对协作式在线搜救任务中团队表现的影响。实验基于34支四人团队(共136名参与者),成员分担不同角色,在受限沟通条件下依赖移动模式推断他人意图。结果表明:运动专业化显著正向预测绩效;自适应空间邻近性呈边际倒U型关系,说明适度调整最有效。此外,这些指标的时间动态特征可区分高/低绩效团队。研究揭示了角色分工下的隐性空间协调机制,为团队训练及人工智能辅助协作系统设计提供依据。
原文摘要 · Abstract (English)
Coordinated teamwork is essential in fast-paced decision-making environments that require dynamic adaptation, often without an opportunity for explicit communication. Although implicit coordination has been extensively considered in the existing literature, the majority of work has focused on co-located, synchronous teamwork (such as sports teams) or, in distributed teams, primarily on coordination of knowledge work. However, many teams (firefighters, military, law enforcement, emergency response) must coordinate their movements in physical space without the benefit of visual cues or extensive explicit communication. This paper investigates how three dimensions of spatial coordination, namely exploration diversity, movement specialization, and adaptive spatial proximity, influence team performance in a collaborative online search and rescue task where explicit communication is restricted and team members rely on movement patterns to infer others' intentions and coordinate actions. Our metrics capture the relational aspects of teamwork by measuring spatial proximity, distribution patterns, and alignment of movements within shared environments. We analyze data from 34 four-person teams (136 participants) assigned to specialized roles in a search and rescue task. Results show that spatial specialization positively predicts performance, while adaptive spatial proximity exhibits a marginal inverted U-shaped relationship, suggesting moderate levels of adaptation are optimal. Furthermore, the temporal dynamics of these metrics differentiate high- from low-performing teams over time. These findings provide insights into implicit spatial coordination in role-based teamwork and highlight the importance of balanced adaptive strategies, with implications for training and AI-assisted team support systems.
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