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Embracing AI’s Disruption in Higher Education

It won’t do higher education any good to resist AI. Rather, institutions should focus on using it to free up faculty time for more humanistic purposes.

Now that AI can create assignments, complete the assignments and grade them too, what’s left for us? I’d suggest we finally get on with pursuing Western education’s oldest goal: the good life. But it will take extraordinary teaching and, if we’re being honest, of a quality that higher education has never really seen.

Some context: America’s 1.5 million professors were never taught how to teach. They are world-class scholars and researchers; they are dedicated educators. But pedagogical best practices aren’t part of most PhD programs. Instead, faculty teach the way they were taught. Think: lecturing, Socratic questioning and high-stakes grading.

Sounds overdrawn? A landmark study of 700 classes summarized the quality of college instruction as only “middling.” Some of the best universities remain “stuck in time.” Others sustain practices that border on discrimination. Taking the long view, UPenn historian Jonathan Zimmerman observes“College teaching has probably seen less change than almost any other American institutional practice since the days of Henry Adams.” 

Nor do colleges and universities have much incentive to care. As scholar Corbin Campbell explains, the sector is driven by status, but U.S. News and World Report rankings don’t include a single instructional metric. The Carnegie Classification system recognizes R1 and R2 institutions for research productivity, but no comparable T1 or T2 system yet exists to incentivize great teaching.

Journalist Bill Deresiewicz makes the consequences plain:

The dearth of effective instruction “ … matters because people are paying a lot, or borrowing a lot, to go to college … because a huge proportion of them are not finishing—60 percent of undergraduates fail to complete their degree in four years … and a major reason is that they are disengaged. Their professors are remote; their classes leave them cold … the students who drop out are disproportionately poor and working-class, Black and Latino, and members of the first generation in their family to go to college. The quality of undergraduate instruction, in other words, isn’t just a value-for-your-money issue. It is also an equity issue, a democracy issue.”

With a situation this bad, one can almost forgive the technofuturists who want to replace educators entirely. But let’s not get ahead of ourselves; the path to enlightenment is cluttered with overhyped tech. MOOCs anyone?

Instead, let’s embrace AI as a liberating opportunity, to do what only people can do, together. First, we should welcome AI’s disruption of 200-year-old practices that ought to have been retired long ago. Second, let’s not try to preserve old approaches as AI-proof or AI-compatible; that’s just new wine in old skins. Instead and third, let’s fill our newfound instructional void with practices that engender curiosity, stimulate deeper learning and lead to greater human understanding. Such practices draw on experience to create relevance, correct misunderstandings in motivating ways and build an appreciation for the social nature of knowledge and epistemological norms. They are as applicable to small seminars as large classes, to the humanities and the sciences.

Decades of higher education’s own research have identified these kinds of technical moves. They are codified, too, by groups like the Association of College and University Educators (ACUE) in its Effective Practice Framework. And, importantly, they take a human hand. Only well-prepared professors bring these practices together in just the right mix, mindful of learning goals and students’ context. It’s the human element, what experts Anna Neumann and Aaron Pallas call, “Targeting, surfacing, and navigating” for meaningful learning.

Such teaching is decidedly not speaking at lecterns for 50 minutes or judging students solely on end-of-term papers. And despite higher ed’s “ruinous resistance to change,” as Harvard professor and past Macalester president Brian Rosenberg laments, making the shift may not be as hard as assumed. 

New mindset research from ACUE finds that faculty are more open to change, more confident in their teaching skills and think more positively about their students when they experience world-class professional development of the kind ACUE certification offers. Most faculty want to teach well. When given a meaningful opportunity to hone their craft, by administrators who emphasize that teaching matters, the rest takes care of itself. To date, ACUE has supported over 38,000 professors across all 50 states, D.C., Puerto Rico, and Canada. Studies of their impact show that student engagement, learning and retention are all up with equity gaps closed or narrowed. 

This new mindset paper involved thousands of professors and students nationwide, and it was commissioned by the Bill & Melinda Gates Foundation. It also disrupts some unhelpful conventional wisdom—that professors need to think differently before they’ll do differently. Rather, the analysis shows that change is iterative. Learning and using proven approaches creates a virtuous cycle of changed practice and belief. It means that students shouldn’t have to wait until professors change their minds to get a better education. Plus, with chronic headlines like “The Public Is Giving Up on Higher Education,” presidents and provosts ignore instructional quality at their peril.

As for the good life? Great teaching, of the sort that AI can spur by disrupting out-of-date pedagogy, puts us in conversation with one another. It asks us to question assumptions and assume some fallibility. It requires careful listening, close analysis, clear communication, collaboration and creativity. Not coincidentally, these are precisely the skills employers have long said they need in 21st-century workers. They are the same skills that democracy requires in citizens. They’re what neighbors need to get along and what the planet demands if we’re to be good stewards. 

Such an education is fundamentally humanistic and much more interesting than the tiresome instrumentality of merely getting a degree to get a job. It pursues what Aristotle called eudaimonia, understood as an individual’s happiness and humanity’s flourishing. We surely could use more of both. And, if confronted with AI, I suspect the great philosopher would happily give the machine work to the machines and keep the good stuff for himself.