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

AI Article Synopsis

  • - Graduate schools in the U.S. are trying to enhance access to STEM fields, focusing on improving admissions processes that may limit diversity.
  • - Research at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences compared metrics-based and holistic review models to see how GRE scores influenced admissions and applicant demographics.
  • - Findings revealed that metrics-based reviews disproportionately excluded historically underrepresented minorities, while holistic reviews showed that GRE scores did not bias assessments by gender, race, or citizenship, offering a data-driven model for improving applicant evaluations.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6757224PMC
http://dx.doi.org/10.1187/cbe.18-06-0103DOI Listing

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