In March, the New York Times published a must-read article exploring the relationship between two of the most important recent developments in higher education: the Supreme Court’s ruling on college admissions ending affirmative action and the fast-growing role that data-driven analytics tools are now able to play in helping foster equity in college admissions.
It’s fair to say that the Times article also reinforced the value of the work Liaison Othot does to help colleges and universities accomplish their enrollment and student success goals through technology.
Working with a Stanford professor who studies social and educational inequality as well as a senior researcher from the school, the authors created several different scenarios modeling “alternatives to affirmative action.” Each scenario compared admissions results based solely on SAT scores with results that also accounted for other considerations, including family income, high-poverty schools, and academic outperformance relative to peers with similar characteristics.
Two of the scenarios described in the article — referred to as “finding the outliers” and “casting a wider net” — are particularly illustrative of how Othot helps institutions take advantage of innovative technology and strategies to navigate new pathways to class-building success.
Identifying Overlooked Opportunities
Outliers are the students “who perform better academically than other students with similar backgrounds,” such as those who score significantly higher on the SAT than others with comparable socioeconomic and educational lives. In the wider world of applicants, SAT scores may not necessarily put them at the front of the pack. However, their ability to achieve those results in light of their unique circumstances is noteworthy; admissions professionals are likely to view them favorably as “strivers.”
According to the article, admitting students based in part on their relative overachievement did “the most to produce both economic and racial diversity, compared with admitting students on test scores alone.” The number of admitted Black or Hispanic students in this scenario envisioned by the Times rose from 11% to 25%; the number of low-income students increased from 5% to 17%.
The “wider net” scenario, on the other hand, involves expanding the pool of potential applicants by focusing recruitment efforts on previously overlooked student populations, such as those at predominantly minority high schools. For example, the Times created a model to “pull into the applicant pool all students of any race with SAT scores above 1000 at high schools where at least three-quarters of students are nonwhite.”
Focusing on these variables created the largest shift toward lower-income students and significantly redistributed classroom seats compared with the SAT-only scenario, according to the report. In addition, the authors noted that such a strategy may survive post-SCOTUS affirmative action scrutiny because it involves recruitment initiatives, not admissions policies.
Customizing Your Institution’s Data-Driven Strategies
Regardless of the specific types of students your institution decides to target, AI now needs to be part of the equation in light of the Supreme Court decision on affirmative action in higher education. At Liaison, we use AI responsibly to guide that journey by providing institutions with predictive insights and prescriptive strategies that increase the probability of a given student enrolling. Of course, we do that with the knowledge that data analytics and artificial intelligence in higher education are not necessarily immune to bias. Rather than viewing them as infallible sources of information, you need to evaluate their recommendations the same way you assess contributions from any other well-informed resource.
When you work with Liaison Othot, AI and analytics technology process the data, but your team makes the creative decisions still needed to shape your future classes. That, in turn, has the proven potential to boost equity in college admissions and improve shared outcomes for your students and school alike.