2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Nationally, engineering PhD ten-year completion rates hover around 76% for men and 65% for women, and below 50% for PhD students from marginalized groups; however, the most recent census-level data were collected in 2008 from the Council of Graduate Schools following students from the ten years prior. Since then, it has been difficult to ascertain any dominant trends, given that there are no centralized data collected from institutions, and each institution is left to collect and track their own students. It is unclear if and how these data, if collected, are used, leaving the research and graduate administration communities with an incomplete understanding of the extent and landscape of attrition and persistence. Given the persistent gaps in recruitment and retention of graduate engineering students from marginalized racial/ethnic and gender backgrounds, the purpose of this presentation is to introduce a novel dashboard initialized by the College of Engineering at Penn State to understand 10-year completion and attrition statistics, able to disaggregate between a wide range student profiles, identities, and trajectories. This ability to disaggregate data separates and provides a utility differently than other publicly available data; often, data are grouped either by gender or race; and master’s and PhD students are often lumped together. Further, our dashboard offers the opportunity to map degree completion from intended program, capturing trajectories of students who changed from a PhD to a Master’s degree, and those who completed degrees in programs different than their original programs of study. These are nuanced forms of departure and attrition in graduate school that are rarely captured. Formed over six years of conceptualization, this paper will demonstrate features of the dashboard that may be able to be utilized by other Colleges interested in attempting their own dashboard concepts for graduate student retention tracking; and will interpret some of the dominant trends in comparison to recent publicly available statistics as well as through relevant theory and literature specific to graduate-level engineering education.