Expanding Access to Graduate Education and the Advanced STEM Workforce

Increasing the competitiveness of the American STEM workforce depends on recruiting a larger and more diverse group STEM graduate students from across the United States, including those from historically underrepresented groups: racial and ethnic minorities, gender minorities in specific STEM fields, students from U.S. regions with disproportionately low STEM graduate degree attainment, persons with disabilities, first-generation students, low-income students, and veterans. This project will support this goal through the expansion of the National Name Exchange (NNE), a well established program that connects underrepresented undergraduate students with institutions seeking to diversify their graduate programs. Through research and communication activities, the project has the potential to remove barriers to STEM graduate study in three ways. First, it will provide a technological platform for expanding the recruitment of graduate students from underrepresented groups. Second, research using NNE data will be used to understand gaps in student pathways to STEM graduate programs and inform both national and university strategies for recruiting and supporting underrepresented students. Third, the project will design, test and continuously improve resources to support prospective graduate students and universities seeking to recruit them to STEM graduate programs. This project seeks to accelerate the recruitment of graduate students from underrepresented groups. By expanding an existing technological infrastructure for connecting underrepresented graduate students with STEM graduate programs, the project will generate data needed to deepen our understanding of gaps and interruptions in student pathways to graduate school and to remedy these interruptions with information and resources. The data collected from student enrollees in the NNE will be matched with National Student Clearinghouse records to determine whether and on what time frame NNE participants enroll in a graduate program. Using logistic regression, the research team will explore the impact of minoritized status, self-reported undergraduate GPA, undergraduate research experiences, Carnegie classification and other aspects of undergraduate institution type. By exploring the probability of matriculation at different intervals following expected undergraduate degree completion, it will be possible to consider how these demographic and educational factors affect pathways into graduate study. In addition to generating data that will help universities improve their recruitment efforts, the project’s assessment activities will help NSF determine the effectiveness of this technological and data infrastructure for accelerating and scaling the participation of underrepresented students in STEM graduate programs. 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.