Collaborative Research: STEM Workforce Training: A Quasi-Experimental Approach Using the Effects of Research Funding

这是一个由俄亥俄州立大学（牵头机构）、宾夕法尼亚州立大学、美国研究院、伊利诺伊大学厄巴纳分校和爱荷华大学参与的合作项目。该项目考察了不同的研究经费结构对研究生和博士后培训的影响及其后续成果的影响。这项研究的基本原理是认识到研究团队在组成、规模和对研究生和博士后研究员的依赖方面存在差异。此外，资助机构通过创建鼓励科学研究的项目来改变科学培训的结构。专注于特定研究问题的跨学科小组、多所大学合作或大型研究中心。然而，关于这些因素如何影响STEM专业人员的职业准备的研究很少。pi将首先检查研究资助和培训的不同背景，然后(1)将团队结构的度量与资助结构联系起来，以确定资助机构政策对研究团队的影响程度；(2)捕捉学生和博士后在与团队接触期间和之后的轨迹，以量化团队结构如何影响培训。他们将使用纵向的行政数据，以获取有关参加机构合作委员会的13个主要研究机构的博士和博士后培训和支持资金来源的信息。然后，他们将通过相关文件的文本分析来确定研究培训的性质，并使用准实验设计来估计研究结构和培训长度对学员结果的因果影响。该项目将对整个STEM教育政策和研究领域产生广泛影响。基础算法和工具将提供给学术研究界，并可用于将内部人力资源数据集与外部数据集联系起来。这种新的数据基础设施也将有助于评估研究投资对研究生产力以及本科生和研究生课程发展的影响。

EHR Core ResearchWorkforce DevelopmentThis is a collaborative project involving Ohio State University (lead institution), Pennsylvania State University, American Institutes for Research, University of Illinois-Urbana, and the University of Iowa. The project examines the impact of different research funding structures on the training of graduate students and postdoctoral fellows and the impact of their subsequent outcomes. The rationale for the study is the recognition that research teams are organized differently in composition, size, and reliance of graduate students versus postdoctoral fellows. In addition, funding agencies change the structure of science training by creating programs that ?encourage? interdisciplinary groups, multi-university collaborations, or large research centers that focus on specific research questions. However, little research has been done about how these factors shape the career preparation of STEM professionals. The PIs will begin by examining the different contexts of research funding and training and then (1) relate measures of team structure to the structure of funding to determine the extent to which funding agency policies shape research teams and (2) capture the trajectories of the students and postdoctoral fellows during and after their contact with the teams to quantify how the structure of teams affects training. They will use longitudinal administrative data that to capture information about sources of funding for the training and support of Ph.D.s and Postdocs from 13 major research institutions that participate in the Committee on Institutional Cooperation. They will then identify the nature of the research training through a text analysis of pertinent documents and use a quasi-experimental design to estimate the causal impact of the structure of research and length of training on trainee outcomes. The project will have broad implications for the entire field of STEM education policy and research. The underlying algorithms and tools will be made available to the academic research community and can be leveraged to link internal human resources data sets to external data sets. This new data infrastructure also will facilitate the assessment of the effects of research investments on research productivity as well as undergraduate and graduate curriculum development.