Standardized Tests and Affirmative Action: The Role of Bias and Variance

The University of California suspended through 2024 the requirement that applicants from California submit SAT scores, upending the major role standardized testing has played in college admissions. We study the impact of such decisions and its interplay with other policies---such as affirmative action---on admitted class composition.

This paper considers a theoretical framework to study the effect of requiring test scores on academic merit and diversity in college admissions. The model has a college and set of potential students. Each student has observed application components and group membership, as well as an unobserved noisy skill level generated from an observed distribution. The college is Bayesian and maximizes an objective that depends on both diversity and merit. It estimates each applicant's true skill level using the observed features and potentially their group membership, and then admits students with or without affirmative action.

We characterize the trade-off between the (potentially positive) informational role of standardized testing in college admissions and its (negative) exclusionary nature. Dropping test scores may exacerbate disparities by decreasing the amount of information available for each applicant, especially those from non-traditional backgrounds. However, if there are substantial barriers to testing, removing the test improves both academic merit and diversity by increasing the size of the applicant pool.

Finally, using application and transcript data from the University of Texas at Austin, we demonstrate how an admissions committee could measure the trade-off in practice to better decide whether to drop their test scores requirement.

The full paper can be found at https://arxiv.org/abs/2010.04396.