Collaborative Research: New Insights into STEM Pathways: The Role of Peers, Networks, and Demand.

该项目是纽约大学、俄亥俄州立大学和密歇根大学安娜堡分校的研究人员共同参与的，他们正在扩展之前一个项目的工作，该项目将多个数据集连接起来，对STEM学生的结果进行纵向分析。目前的项目利用之前奖项支持的研究基础设施来研究同行效应、网络联系和雇主需求如何影响博士生的职业结果。它整合了11.3万名博士生的全面管理数据、UMETRICS研究数据、关于学位论文的ProQuest数据与学习和研究领域的信息，以及受限的人口普查局关于收入和就业结果的数据。DARA的整合将在创新与科学研究所(IRIS)的保护伞下进行。该项目将通过阐述和测试STEM职业选择的新概念模型的关键方面来提供新的知识。这项理论和实证工作将确立有关需求和培训条件如何影响早期STEM职业选择的基本事实，这些选择只能通过整合单独的数据集来确定。该项目得到了教育和人力资源核心研究计划的支持，该计划为STEM学习和学习环境中的基础研究、扩大STEM的参与和STEM劳动力发展提供资金。研究设计结合了三种方法-基于同行、基于网络和需求。在他们的基于同伴的方法中，研究人员建议将进入研究生队列的同伴的组成视为准随机的，并估计同行的组成如何与他们自己的特征相互作用。第二组分析涉及从数据中识别实验室，并估计实验室中人员的组成与结果的关系。基于网络的方法将被用来研究社会资本的个体差异如何影响博士生的结果。需求将回答实际和感知的劳动力市场需求对职业选择的影响的分析问题。分析将首先描述从本科生辍学到大学毕业生，从硕士到博士辍学再到博士生的早期职业成果。除了加强基础设施以进行强有力的劳动力发展研究外，该项目还将对同行网络对STEM劳动力发展的作用和影响进行更全面的分析。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The project is a collaborative effort involving researchers from New York University, Ohio State University, and University of Michigan Ann Arbor who are extending work on a previous project that links multiple data sets to conduct longitudinal analyses of STEM student outcomes. The current project leverages the research infrastructure that was supported by prior awards to examine how peer effects, network connections, and employer demand shape career outcomes for doctoral students. It integrates comprehensive administrative data for 113,000 doctoral students, UMETRICS research data, Proquest data on dissertations with information on fields of study and research, and restricted Census Bureau data on earnings and employment outcomes. Dara integration will occur under the umbrella of the Institute for Research on Innovation and Science (IRIS). The project will contribute new knowledge by articulating and testing key aspects of a novel conceptual model of STEM career choices. This theoretical and empirical work will establish basic facts about how demand and training conditions shape early STEM career choices that can be determine only through the integration of separate datasets. The project is supported by the Education and Human Resources Core Research Program, which funds fundamental research in STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.The research design integrates three approaches - peer-based, network-based, and demand. In their peer-based approach, the researchers propose to take the composition of peers in entering graduate cohorts to be quasi-random and estimate how the composition of peers interacts with their own characteristics. A second set of analyses involves identifying labs from the data and estimating how the composition of the persons in a lab relate to outcomes. The network-based approach will be used to examine how individual differences in social capital shape doctoral student outcomes. The demand will answer the analytical question of the effect of actual and perceived labor market demand on the choice of careers. The analysis will begin with a description of the early career outcomes of students from undergraduate dropouts to college graduates, from master's students to Ph.D. dropouts to doctoral recipients. In addition to enhancing the infrastructure to conduct robust workforce development research, the project will provide a more comprehensive analysis of the role and impact of peer networks on STEM workforce developmentThis 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.