The art and science of selecting graduate students in the biomedical sciences: Performance in doctoral study of the foundational sciences

The impact of holistic review on correlations between doctoral student outcomes, and GPA and GRE scores in the biomedical sciences

Graduate admissions committees throughout the United States examine both quantitative and qualitative data from applicants to make admissions determinations. A number of recent studies have examined the ability of commonly used quantitative metrics such as the GRE and undergraduate GPA to predict the likelihood of applicant success in graduate programs. We examined whether an admissions committee could predict applicant success at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences based on quantitative metrics. We analyzed the predictive validity of admissions scores, undergraduate GPA, and the GRE for student success. We observed nuanced differences based on gender, ethnicity, race, and citizenship status. The scores assigned to applicants by the admissions committee could not predict time to degree in PhD students regardless of demographic group. Undergraduate GPA was correlated with time to degree in some instances. Interestingly, while GRE scores could predict time to degree, GRE percentile scores could predict both time to degree and PhD candidacy examination results. These findings suggest that there is a level of nuance that is required for interpretation of these quantitative metrics by admissions committees.

Undergraduate GPA Predicts Biochemistry PhD Completion and Is Associated with Time to Degree

There is interest in admission criteria that predict future success in biomedical graduate school programs, but identifying predictors of PhD attainment is inherently complex. In particular, high noncompletion rates of PhD programs have long been recognized as a major crisis. Here, we present a quantitative analysis of the PhD students enrolled in the Department of Biochemistry and Biophysics at Texas A&M University between 1980 and 2010. The input variables included sex, country of citizenship, undergraduate grade point average (GPA), and Graduate Record Examination (GRE) scores (Verbal and Quantitative Reasoning). Only GPA was a significant predictor of PhD completion based on logistic regression. We also examined associations involving nonbinary measures of success (PhD duration, first author, and total number of publications) among students who completed a PhD. GPA was again associated with the PhD duration. No enrollment variable was strongly associated with publication output. Despite potential limitations, this analysis is the first to suggest an undergraduate GPA association with PhD completion in life sciences. These results from a large state university in a predominantly rural area expand the range of programs from which such analyses have been reported.

Postbaccalaureate and graduate applicants to dental school: An analysis of holistic review

Although they are valued for their perceived maturity, resiliency, and diverse insight into dentistry, postbaccalaureate and graduate (PBGR) applicants face significant challenges in the admissions process. This study looks at how PBGR applicants are evaluated during the selection process at a US dental school. An analysis of metrics associated with PBGR applicants was performed, focusing on the demographic makeup, academic performance, and total experience hours compared to traditional applicants. Our results suggest that PBGR applicants who are successful in their postbaccalaureate/graduate course of study are also more likely to be admitted if they have a history of strong undergraduate performance. Our results also suggest that PBGR applicants with high self-disclosed employment hours are strongly considered. Taken together, these results suggest that holistic review has helped PBGR applicants in the admissions process but that further adjustments need to be implemented.

Predicting professional school performance with a unique lens: are there other cognitive predictors?

BACKGROUND

We investigated the associations between admissions criteria and performance in four cohorts of pre-dental MS in Oral Health Sciences (OHS) program at Boston University Schools of Medicine and Dental Medicine. Previously we have reported that OHS serves as a successful pre-dental pipeline program for students from underrepresented groups.

METHODS

We evaluated academic variables that further affect overall graduate GPA and grades in the first year dental school courses taken by OHS students at Boston University between 2012 and 2016 as part of the MS curriculum. Demographic data, region of residency, undergraduate grade point average, number of science and math credits, major of study, dental admissions test scores and undergraduate institution were collected. The competitiveness of the undergraduate institution was scored based on Barron's Profiles of American Colleges. OHS-GPA was assessed and individual grades in two first year dental school courses taken as part of the OHS curriculum were collected. Analysis of variance, the Chi-square test and Fisher's Exact test were utilized to assess associations between academic performance parameters, successful program completion and matriculation to dental school.

RESULTS

Results indicate that undergraduate major, age and number of science course credits taken had no impact on MS performance in the Boston University MS in Oral Health Sciences program; however, students who took an undergraduate course in Physiology performed better than those who did not (p = 0.034). This was not the case with courses in Cell Biology and Biochemistry. Students with DAT scores over 20 academic average (p = 0.001), 18 total science average (p = 0.001) and 22 reading comprehension (p = 0.004) performed better in dental school courses taken in OHS.

CONCLUSION

We report that strong test scores, attending a mid or highly rigorous undergraduate institution and completion of an undergraduate Physiology course are positive predictors. We hope these findings will guide admission's decisions and improve recruitment to, and future success of, graduate student's pursuit of professional school. Understanding alternative predictors of success may help to reduce the intrinsic bias among applicants from underrepresented groups and continue to look beyond the DATs (or MCATs) to decrease the gap between professionals from underrepresented groups and those they serve.

The GRE over the entire range of scores lacks predictive ability for PhD outcomes in the biomedical sciences

The association between GRE scores and academic success in graduate programs is currently of national interest. GRE scores are often assumed to be predictive of student success in graduate school. However, we found no such association in admission data from Vanderbilt's Initiative for Maximizing Student Diversity (IMSD), which recruited historically underrepresented students for graduate study in the biomedical sciences at Vanderbilt University spanning a wide range of GRE scores. This study avoids the typical biases of most GRE investigations of performance where primarily high-achievers on the GRE were admitted. GRE scores, while collected at admission, were not used or consulted for admission decisions and comprise the full range of percentiles, from 1% to 91%. We report on the 32 students recruited to the Vanderbilt IMSD from 2007-2011, of which 28 completed the PhD to date. While the data set is not large, the predictive trends between GRE and long-term graduate outcomes (publications, first author publications, time to degree, predoctoral fellowship awards, and faculty evaluations) are remarkably null and there is sufficient precision to rule out even mild relationships between GRE and these outcomes. Career outcomes are encouraging; many students are in postdocs, and the rest are in regular stage-appropriate career environments for such a cohort, including tenure track faculty, biotech and entrepreneurship careers.

A Model for Holistic Review in Graduate Admissions That Decouples the GRE from Race, Ethnicity, and Gender

Graduate schools around the United States are working to improve access to science, technology, engineering, and mathematics (STEM) in a manner that reflects local and national demographics. The admissions process has been the focus of examination, as it is a potential bottleneck for entry into STEM. Standardized tests are widely used as part of the decision-making process; thus, we examined the Graduate Record Examination (GRE) in two models of applicant review: metrics-based applicant review and holistic applicant review to understand whether it affected applicant demographics at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences. We measured the relationship between GRE scores of doctoral applicants and admissions committee scores. Metrics-based review of applicants excluded twice the number of applicants who identified as a historically underrepresented minority compared with their peers. Efforts to implement holistic applicant review resulted in an unexpected result: the GRE could be used as a tool in a manner that did not reflect its reported bias. Applicant assessments in our holistic review process were independent of gender, racial, and citizenship status. Importantly, our recommendations provide a blueprint for institutions that want to implement a data-driven approach to assess applicants in a manner that uses the GRE as part of the review process.