Higher Education Needs Its Own Version of Moneyball

This spring, Major League Baseball banned the defensive shift, a tactic that lets teams respond instantly to batters’ tendencies by loading up one side of the infield to prevent hits. It’s a change that’s seeking to respond to a greater issue in the game—how to sort through an enormous trove of baseball data to gain a competitive edge.

Until recently, baseball traditionally has been ruled by so-called counting statistics. Players who led the league in home runs and strikeouts were seen as stars. But building analytics muscle has allowed teams to compile and analyze enormous amounts of data. Sophisticated calculations have created a wealth of situational information that helps managers decide which players to play and what adjustments to make.

Known as sabermetrics or “moneyball”—a term that comes from a book and movie of that name—empirical statistical modeling gives a much more complete and accurate picture of in-game success in baseball. It’s data that can be used in real time to affect the outcome of a single moment or even an entire game. This type of data has changed baseball—but is still too often missing from higher education.

That’s because higher ed professionals measure student success with traditional counting statistics such as persistence and completion rates. These cumulative metrics are usually examined long after the end of the academic year and offer little chance to improve a learner’s likelihood of staying in school and graduating.

Higher education needs its own version of moneyball—a set of active, predictive and creative measures that can be deployed to improve student outcomes and fulfill their promise of student success. Postsecondary institutions must be able to collect and instantaneously analyze student progress data and have intentional plans for adjusting in the moment to the needs of their learners.

Every institutional leader would agree that going from matriculation to completion is critical, yet there are data indicating that colleges are moving in the opposite direction. A recent Ad Astra report reveals that college students took nearly 15 percent fewer credit hours in the fall 2021 semester than they did just two years earlier. Full-time students at the nation’s four-year public institutions are taking an average of 14.75 credit hours each semester. That means the typical student won’t be able to graduate in four years and will have to spend more time and money to finish a degree.

A Complete College America policy brief published in 2022 shows that the credential attainment of part-time learners lags far behind that of their full-time counterparts. Most institutions are ill equipped to serve part-time students, who make up 40 percent of the nation’s college enrollment. That presents significant equity challenges because part-time students are disproportionately students of color, ages 25 and older, and community college students.

To see trends as they develop, institutional leaders should:

• Use active measurements to augment existing data so they can understand what’s working and implement change at the learner level. They should focus on using data around course schedules and productive credit hours—classes that count toward an intended credential—to compare a learner’s actual progress toward a degree with their expected progress. When the metrics reveal students who aren’t making timely progress toward graduation, institutions can adjust course offerings quickly to improve student retention and degree completions.

A new Ad Astra research project that examined degree progress and completion data from four-year regional public institutions contains some promising findings. One university found that having students take one extra course per term that counts toward their degree increased graduation rates by 11 percent and retained students on average for 22 more credit hours.

• Commit to new advanced planning frameworks so institutions are prepared to address trends as they develop. This planning starts with insights that enable institutions to identify opportunities for accelerating student progress and predict the efficacy of those interventions on retention and graduation rates. By adopting predictive metrics, administrators will be able to determine the effectiveness of their forecasts and take further action to address any gaps that remain.
• Envision an ideal world where they have access to all relevant data and more precise measurements on which to base decisions. This creative mind-set encourages the identification of measures that align with an institution’s mission, measure progress on reform efforts that prioritize equitable student attainment and strive for a deep understanding of student success—much like the moneyball strategy that values a broader range of player skills that can be counted and rated. Adopting a sabermetrics approach enables institutions to measure exactly what matters so they can do more to help students achieve their full potential.

Postsecondary institutions will never be called on to decide whether to intentionally walk a hot hitter. But they do have access to significant amounts of data that can help more students graduate on time and reach their personal and career goals.

Higher education should augment existing statistics with new metrics that more objectively understand what works for their learners. A moneyball approach doesn’t change the goal of the game—institutions should still be measured by completion—but it creates more room for strategies that will make more learners into winners.