TOC4Fairness Seminar – Faidra Monachou

Date: Wednesday, March 24th, 2021
9:00 am – 10:00 am Pacific Time
12:00 pm – 1:00 pm Eastern Time

Location: Weekly Seminar, Zoom

Title: Dropping Standardized Testing for Admissions: Differential Variance and Access


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 dropping 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 skill level generated from a known distribution. The college is Bayesian and has a dual objective that depends on 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 informativeness of standardized testing in college admissions and access barriers to testing. 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 can improve 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 these trade-offs in practice. 

This is joint work with Nikhil Garg and Hannah Li.


Faidra Monachou is a Ph.D. candidate in Management Science and Engineering at Stanford University, advised by Professor Itai Ashlagi. She is interested in market design and her work focuses on the role of discrimination, diversity and information design in education, sharing economy, and matching markets. Faidra’s research has been supported by various scholarships and fellowships from Stanford Data Science Institute, Google, and others. She co-chaired the MD4SG’20 workshop and currently co-organizes the Stanford Data Science for Social Good program. Prior to Stanford, she received her undergraduate degree in Electrical and Computer Engineering from National Technical University of Athens in Greece.