Abstract
Many US biomedical PhD programs receive more applications for admissions than they can accept each year, necessitating a selective admissions process. Typical selection criteria include standardized test scores, undergraduate grade point average, letters of recommendation, a resume and/or personal statement highlighting relevant research or professional experience, and feedback from interviews with training faculty. Admissions decisions are often founded on assumptions that these application components correlate with research success in graduate school, but these assumptions have not been rigorously tested. We sought to determine if any application components were predictive of student productivity measured by first-author student publications and time to degree completion. We collected productivity metrics for graduate students who entered the umbrella first-year biomedical PhD program at the University of North Carolina at Chapel Hill from 2008–2010 and analyzed components of their admissions applications. We found no correlations of test scores, grades, amount of previous research experience, or faculty interview ratings with high or low productivity among those applicants who were admitted and chose to matriculate at UNC. In contrast, ratings from recommendation letter writers were significantly stronger for students who published multiple first-author papers in graduate school than for those who published no first-author papers during the same timeframe. We conclude that the most commonly used standardized test (the general GRE) is a particularly ineffective predictive tool, but that qualitative assessments by previous mentors are more likely to identify students who will succeed in biomedical graduate research. Based on these results, we conclude that admissions committees should avoid over-reliance on any single component of the application and de-emphasize metrics that are minimally predictive of student productivity. We recommend continual tracking of desired training outcomes combined with retrospective analysis of admissions practices to guide both application requirements and holistic application review.
Highlights
The PhD degree is required for advancement to leadership within biomedical research fields
To test for correlations between application components and graduate student productivity, we collected applications for admissions and publication data for the cohort of 280 students who matriculated into the UNC umbrella first-year program, Biological and Biomedical Sciences Program (BBSP), between 2008 and 2010
We found that the quantitative Graduate Record Examination (GRE) scores in our cohort differed by gender and race/ethnicity; males scored higher than females and Asian and white test takers scored higher than those from under-represented minority groups, similar to observations for all science graduate school test takers reported by Miller and Stassun [5]
Summary
The PhD degree is required for advancement to leadership within biomedical research fields. Graduate school admissions acts as a de facto filter for scientific leadership opportunity. PhD programs often receive many more applications from qualified candidates than the number of training slots available, leading to intense competition during the admissions process [1]. To select candidates from a large pool of qualified applicants, committees must look for aspects of the application that differentiate candidates in a meaningful way. With limited information in the graduate application, this can be a difficult process and can lead committees to overly rely on quantitative metrics like standardized test scores or grade point averages for quick comparisons [2]. Despite the importance of the application process, applicant characteristics presumed to predict success in the biomedical sciences are based largely on untested assumptions. It is critical to rigorously examine selection criteria to reduce or eliminate factors that introduce biases that disproportionately limit certain groups’ access to PhD training and the biomedical workforce
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