Learning to Fail: Higher Education’s Broken Ladder

Work hard, play by the rules, and success surely will follow. This well-known promise has kept generations of students obediently studying and fretting over grades. But conventional knowledge hides a downside. This meritocratic parable advances individual will as democracy’s great social leveler, with talent and effort overriding bias or disadvantage. In the already-achieved equality of the U.S.,  anyone with enough drive can rise to society’s highest tier. Colleges have enthusiastically adopted this philosophy and present themselves as impartial judges of ability and determination. They use GPA’s as moral scorecards, standardized tests as scales of human worth, and class rankings predictors of future success. This merit machine functions so effectively that few question what is being measured or how the process began.

Only now are colleges and universities starting to see the problem. Students meeting every academic benchmark increasingly find achievements unreal and lacking practical benefit. Many feel scammed by promises that effort pays off, only to hit structural barriers from the start. The premise of fair and equal opportunity works like a shell game, held in place by invisible rules and roadblocks institutions pretend aren’t there. And while bad for nearly every student, the effects have been catastrophic in the highly charged post-DEI atmosphere of reverse discrimination, “racial exhaustion,” and the rollback of civil rights advances on nearly front.[i]

These contradictions now undermine the foundations of higher ed. While students may arrive on campus with a genuine desire to learn, the atmosphere around them quickly shifts from a common pursuit of knowledge into a zero sum game of individual achievement. The psychological effects of this are documented in a growing body of research showing spiking levels of anxiety, depression, and disengagement among students who otherwise should be thriving. Meanwhile, first-gen students, working learners, and those historically minoritized are overlooked by a system designed (and increasingly politicized) to support others with social and economic capital. The dichotomy is stark and relentless. Just as schools have developed metrics to quantify student outcomes, many conceal and often inadvertently intensify the inequities they claim to alleviate.

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Flipping the Script: Using AI to Motivate and Inspire

David Trend

Every new information technology has sparked fresh panic about the future of teaching.  Plato warned that writing itself would destroy memory and learning. The printing press set off fears that books would undermine scholarly authority. Thomas Edison said that motion pictures would replace schoolbooks. Radio, television, and personal computers each drew the same anxious forecasts, followed in the 2000s by a wave of predictions that online courses would empty out campuses. None of it happened. Each technology reshaped instruction while leaving the teacher-student relationship intact. 

Generative AI has now joined the parade, and once again the loudest voices are asking the wrong question. The issue isn’t whether AI will replace faculty. It’s how instruction must adapt so that the human work stays at the center of teaching.

A good place to start is a recent Forbes interview with Ben Gomes, Google’s Chief Technologist for Learning and Sustainability, in which he made one simple point.  The hardest problem in education is motivation. And it’s a problem AI will never solve. “Technology can improve how you learn and the details of it,” Gomes put it, “but the why you learn is a very human thing.”[1] That sentence should sit at the heart of every conversation about reforming college instruction. AI can deliver content, flag errors, generate practice exercises, and personalize feedback faster than any human. None of that addresses the prior question of why a student would bother engaging in the first place.

Gomes grounded the point in a lifetime of watching learners. He observed that high-achieving people almost never credit a book or a tool for unlocking their potential. They credit a person. A teacher who said something, who treated them differently, who made them feel that the work of learning mattered. Once that feeling took hold, the student could run forward on their own, and the tools became accelerators. But the ignition was always human. Decades of educational research echo the finding, with thousands of studies placing teacher-student relationships and instructor clarity among the strongest predictors of learning, well ahead of any technology.[2] If motivation comes from relationships rather than from content delivery, then any reform that pushes instructors further from their students is moving the wrong direction.

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