At this point, any frequent consumer of higher education news is well aware of the controversial remarks Justice Antonin Scalia made during oral arguments in Fisher v. University of Texas at Austin. Many are also likely familiar with the subsequent debates about affirmative action and “mismatched students” that these remarks provoked. In speculating whether black students preferentially admitted to UT Austin might be better off attending “a slower-track school where they do well,” Justice Scalia prompted numerous articles, analyses, and opinion pieces regarding the reasoning behind his remarks as well as their validity.

Justice Scalia’s comments were grounded in a critique of affirmative action called “mismatch theory.” This theory posits that preferential admissions hinders the progress of those it aims to assist by placing them into institutions for which they are not academically prepared. Those who believe that the theory has validity have pointed to academic research by scholars like Richard Sander of UCLA and Peter Arcidiacono of Duke, who argue that preferentially admitted minority students would increase their chances of success by attending less selective schools. Critics of mismatch theory, like Matt Chingos of the Urban Institute, have convincingly argued that the concept lacks strong evidence. Chingos cites studies that show that, if two students with similar academic credentials go to differentially selective colleges, the student that enrolls at the more selective institution has a better chance of graduating. This parity holds true for students of all backgrounds, including underrepresented minorities.

One thing that seems missing—or at least problematically implicit—in recent debates about mismatch theory is the role of the institution in helping underprepared students succeed. In his advocacy of mismatch theory, Reihan Salam refers to a proverbial “pecking order” of students at selective institutions, in which preferentially admitted students are at the bottom. His language, which evokes a “survival of the fittest” hierarchy, is directly at odds with what institutions should be—and increasingly are—doing to support struggling students: designing interventions to help these students succeed. Too often, proponents of mismatch theory, like Salam, imagine the institution, faculty, support staff, and other stakeholders as relatively powerless in determining outcomes—especially for at-risk students. An approach that truly embraces increased access and opportunity would ask what institutions can do to help more qualified but underprepared students graduate and succeed, especially at selective schools and in difficult majors.

To their credit, some proponents of mismatch theory have advocated that institutions provide admits with information about their chances of success, typically based on the outcomes of previous students with similar academic credentials. However, this scenario still imagines institutions as relatively passive. Many institutions—both selective and broad access—have developed much more sophisticated and proactive ways to use information about students and their predicated outcomes.

In fact, UT Austin, the defendant in Fisher’s suit and the target of Justice Scalia’s comment, is a leader in this area. As Texas’s Top Ten Percent Law altered the demographics and range of preparedness of UT Austin students, the institution developed an innovative predictive analytics system to determine which students have the highest risk dropping out. Rather than deter these students from the school or from difficult majors, UT Austin offers them a suite of rigorous yet supportive programs and services, such as the University Leadership Network. UT Austin does not disclose the selection criteria for these programs to students, and is careful to ensure that enrolled students feel a sense of belonging at the institution—a stark contrast to the imagined “transparency” scenario that mismatch theory advocates propose. The University Leadership Network has realized early successes in improving grades and persistence rates for at-risk students, and is a crucial part of the UT Austin’s plans to reach a 70% graduation rate by 2017.

As technologies for collecting and analyzing student data become more advanced, and as the national movement to increase degree completion grows stronger, there is no reason we should settle for students struggling at selective institutions, or conclude that they would simply be better off elsewhere. Instead, we should use the new tools at our disposal to design interventions that remove barriers to success.