EAGER: SaTC: Early-Stage Interdisciplinary Collaboration: Knowledge Convergence and Divergence in Team Performance

利用知识资源是成功团队的标志之一。拥有不同专业知识和“谁知道什么”意识的团队成员比观点不那么多样化的团队表现得更好。自2013年以来，美国国家科学基金会（National Science Foundation）的SaTC项目已经试点了“高风险-高回报”EAGER项目，以鼓励计算机和信息科学家与行为、社会和经济科学家之间的早期合作，以提高SaTC研究的创新和有效性。目前的研究将审查研究人员的经验及其项目的成果，以便更好地理解这一倡议。该项目还将允许深入了解跨学科团队如何管理知识趋同和分歧之间的内在紧张关系。需要分散时聚合或需要聚合时分散会错误地处理团队资源，损害团队流程和绩效。因此，在未来几十年里，揭示知识趋同和知识分化的同时影响对于提高团队效率和推进团队研究至关重要。由于NSF和其他资助机构越来越多地要求团队成员代表不同的学科，因此迫切需要发现促进NSF理事之间合作的好处、限制和客观结果。因此，这项研究有可能提高SaTC的效率，更广泛地说，提高科学团队的效率，从而促进科学突破。如何平衡团队中的知识聚合和分歧，以最大化绩效、创新和成员满意度？本研究的目标是：1)从概念上整合之前专注于知识趋同或知识发散的独立团队研究领域；2)创造新的方法来评估团队中知识趋同和知识发散之间的平衡（或缺乏平衡）；3)开始评估知识趋同和知识发散对团队有效性的同时影响。这些目标在近100个SaTC nsf资助的跨学科团队的背景下进行了适当的探索。该项目的第一阶段包括与跨学科团队子集的成员进行访谈，以制定评估知识趋同和分歧平衡的指标。第二阶段包括对过去和当前资助的团队成员的调查，以衡量知识聚合和分歧对客观结果的同时影响。结果指标根据可公开获得的数据评估项目是否有成效，以及研究人员是否共同发表并继续他们的跨学科合作。这些定性和定量研究共同推动了快速发展的团队科学文献科学，这些文献主要依赖于描述性和档案研究，而不是原始数据收集。学生将参与研究的所有阶段。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。

Leveraging knowledge resources is one of the hallmarks of successful teams. Team members with diverse expertise and an awareness of "who knows what" perform better than teams with less diverse perspectives. Since 2013, the National Science Foundation's SaTC program has piloted groups of "high risk-high reward" EAGER projects to encourage early collaborations between computer and information scientists and behavioral, social, and economic scientists towards improving innovation and effectiveness in SaTC research. The current research will review the experiences of researchers and the outcomes of their projects to better understand that initiative. The project will also allow for insights into how interdisciplinary teams manage the inherent tension between knowledge convergence and divergence. Converging when diverging is needed or diverging when converging is needed mishandles team resources, impairing team processes and performance. Therefore, unlocking the simultaneous influences of knowledge convergence and divergence is central to improving team effectiveness as well as advancing team research in the decades to come. Because NSF and other granting agencies increasingly require team members to represent different disciplines, it is urgent to discover the benefits, limitations, and objective outcomes of promoting collaboration across NSF's directorates. As such, this research has the potential to improve the effectiveness of SaTC, and more generally, science teams, thereby fostering scientific breakthroughs.How should knowledge convergence and divergence in teams be balanced to maximize performance, innovation, and member satisfaction? The objectives of this research are to 1) conceptually integrate the previously independent areas of team research that have focused either on knowledge convergence or knowledge divergence 2) create new methods to assess the balance (or lack of balance) between knowledge convergence and divergence in teams, and 3) begin to assess the simultaneous effect of knowledge convergence and divergence on team effectiveness. These objectives are fittingly explored in the context of nearly 100 SaTC NSF-funded, cross-disciplinary teams. The first phase of the project involves interviews with members of a subset of interdisciplinary teams to develop metrics to assess the balance of knowledge convergence and divergence. The second phase involves surveys of past and currently funded team members to measure the simultaneous effect of knowledge convergence and divergence on objective outcomes. Outcome metrics assess, from publicly-available data, whether the projects were productive and whether investigators co-published and continued their cross-disciplinary collaboration. Together, these qualitative and quantitative studies advance the rapidly growing science of team science literature which has relied mostly on descriptive and archival research rather than primary data collection. Students will be involved in all phases of the research.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.