Identifying multimodal dynamics of coordination to understand joint performance in diverse tasks

为了进行广泛的日常活动，人们需要协调他们的行动。例如，一起做饭，搬一个大沙发，在体育或商业中作为一个团队工作，都需要参与者之间的协调。尽管有证据表明，在这些联合任务中的合作伙伴会实时调整他们的行为以适应彼此，但尚不清楚协调的哪些特征会导致最佳结果。该项目的目的是建立一个框架，以预测不同背景和角色的人员之间的最佳协调。结合实证研究和动态计算模型，研究人员将围绕对话、换位思考和合作在成功执行联合任务中的作用展开问题。了解参与联合任务的人员之间成功协调的基础原则，在各种各样的环境中具有潜在的商业和社会影响，包括医疗保健、教育、航空、军事行动和搜救场景。该项目还将通过增加两个学术机构的本科生和研究生参与认知科学研究的机会，促进跨学科劳动力的发展。人际协调如何影响任务绩效的一个突出观点是，当任务伙伴的行为一致或匹配时，他们的共同任务绩效会得到改善。例如，发音、单词选择、句子结构或动作的一致性已经在需要合作伙伴监视彼此视角的任务中得到了记录。然而，不同的任务如何增加或减少成功性能的一致性是未知的。在这个项目中，研究人员将操纵一些任务特征：任务的目标，合作伙伴角色的对称性，以及合作伙伴必须采用的视角的数量。将分析眼动测量和对话记录，以量化合作伙伴在注意力和语言使用方面的一致程度。目的是评估和建模任务绩效如何通过任务特征和人际协调程度来预测。例如，人际关系一致性可能会增加，并且在需要合作伙伴密切监视彼此的任务中更有用（例如，当合作伙伴由于掌握不同的信息而具有不对称的角色时）。在需要较少监控的任务中，过度的一致性可能对任务结果有害。一个具有任务约束和人际协调参数的协作绩效动态模型将根据实验数据进行评估，并将用于生成关于新任务绩效的预测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

People need to coordinate their actions in order to carry out a wide range of daily activities. For example, cooking a meal together, moving a large couch, and working as a team in sport or business, all require coordination among the participants. Despite evidence that collaborating partners in these joint tasks adapt their behavior to one another in real time, it is unclear what features of coordination lead to the best outcomes. The aim of this project is to develop a framework for predicting optimal coordination among people across diverse settings and roles. Using a combination of empirical studies and dynamical computational modeling, the investigators will unpack issues surrounding the roles of dialogue, perspective-taking, and collaboration in successfully performing joint tasks. Understanding the principles that underlie successful coordination among people engaged in a joint task has potential commercial and societal impact in a wide variety of settings, including health care, education, aviation, military operations, and search-and-rescue scenarios. The project will also contribute to the development of an interdisciplinary workforce by increasing opportunities to engage undergraduate and graduate students in cognitive science research at two academic institutions.A prominent view of how interpersonal coordination influences task performance is that when task partners align or match their behavior, their joint task performance improves. Alignment of, for example, pronunciation, word choices, sentence structure, or movement has been documented in tasks that require partners to monitor each other’s perspective. However, it is unknown how different tasks may increase or decrease alignment for successful performance. In this project, the investigators will manipulate a number of task features: the goals of the task, the symmetry of the partners’ roles, and the number of perspectives that partners have to adopt. Eye movement measurements and dialogue transcripts will be analyzed in order to quantify how aligned partners are in their attention and language use. The aim is to evaluate and model how task performance is predicted by task features and by the degree of interpersonal coordination. For example, interpersonal alignment might increase and be more useful in tasks that require partners to monitor one another closely (e.g., when partners have asymmetrical roles because they hold distinct information). In tasks that require less monitoring, excessive alignment might be detrimental to task outcomes. A dynamical model of collaborative performance, which has parameters for task constraints and interpersonal coordination, will be evaluated against the experimental data and will be used to generate predictions about performance in new tasks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.