III: Small: Algorithms and Practical Applications for Team Formation and Change

几十年来，社会学、心理学、组织行为学和其他社会科学的研究人员一直在进行定量数据分析研究，以了解和建模个人如何形成团队以及不同因素（如多样性或同质性）如何影响团队绩效。最近，用于教育、外包、协作学习、软件开发和解决问题的在线平台的激增也促使计算机科学家致力于开发团队组建算法。这项工作闭合了团队形成研究的理论和实践之间的循环。这是通过将社会科学的研究成果整合到新的计算问题的开发和团队工程的新算法的设计中来实现的，团队工程是一个用来包括团队的形成和现有团队的修改的术语。此外，这项工作开发了必要的计算概念以及软件，使团队推荐算法能够应用于各种教育场景，包括黑客马拉松，学生创业团队，以及在课程和课外项目为基础的学习机会的团队组建。该研究将具有强大的算法，实验和工程组件，并将包括以下研究重点。受社会科学研究的推动，该项目的第一个重点是开发计算概念，使团队的形成具有低断层线潜力。在第二个方向，该项目将专注于修改现有团队的算法，以改善其功能;在这个方向上，将再次使用社会科学研究中存在的概念，通过计算透镜进行观察。在最后的推力中，该项目还将考虑在线团队工程问题，其中团队按需组建，由核心成员和临时雇用的非成员组成，以帮助完成特定任务;在这种情况下，重点将放在与成本优化策略相关的算法问题上。除了这些问题外，该项目还将考虑教育环境中出现的问题（例如，该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

For decades, researchers in sociology, psychology, organizational behavior, and other social sciences have been conducting quantitative data-analysis studies in order to understand and model how individuals form teams and how different factors (like diversity or homogeneity) affect team performance. Recently, the proliferation of online platforms for education, outsourcing, collaborative learning, software development and problem solving has also motivated computer scientists to work on the development of algorithms for team formation. This work closes the loop between the theory and practice of team-formation research. This is done by integrating social-science findings in the development of new computational problems and the design of new algorithms for team engineering, which is a term used to encompass the formation of teams and the modification of existing teams. Moreover, this work develops the necessary computational concepts as well as the software that enables the application of the team-recommendation algorithms to a variety of educational scenarios including hackathons, student entrepreneurship teams, as well as team formation in curricular and extracurricular project-based learning opportunities.The research will have strong algorithmic, experimental and engineering components and will consist of the following research thrusts. Motivated by research in social sciences, in the first thrust the project will develop computational concepts enabling the formation of teams with low faultline potential. In the second thrust the project will focus on algorithms that modify existing teams in order to improve their functionality; in this thrust concepts that exist in social science research will again be used, viewed through computational lenses. In the final thrust the project will also consider the online team engineering problem where teams are formed on demand and consist both of core members and non-members that are temporarily hired in order to help with a particular task; in this scenario, the focus will be on algorithmic questions related to cost-optimizing strategies. In addition to these problems, the project will also consider problems arising in educational settings (e.g., hackathons, student entrepreneurship teams) and the development of a software platform to implement team-formation algorithms in such practical settings.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.