{"id":385,"date":"2026-06-23T10:57:49","date_gmt":"2026-06-23T14:57:49","guid":{"rendered":"https:\/\/solutionsreview.com\/edtech\/?p=385"},"modified":"2026-06-23T11:24:07","modified_gmt":"2026-06-23T15:24:07","slug":"engagement-is-not-learning-and-ai-is-widening-the-gap","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/edtech\/2026\/06\/23\/engagement-is-not-learning-and-ai-is-widening-the-gap\/","title":{"rendered":"Engagement Is Not Learning, and AI Is Widening the Gap"},"content":{"rendered":"

\"\"<\/p>\n

Pocket Prep’s Michelle Marlowe offers this commentary on why engagement is not learning and how AI is widening the gap. <\/strong><\/em>This article originally appeared in Insight Jam<\/a>, an enterprise IT community that enables human conversation on AI.<\/span><\/strong><\/em><\/p>\n

\"\"<\/a><\/span><\/p>\n

Ask a learning platform how it is doing, and it will almost always answer the same way, showing you streaks and completion rates. The dashboard glows green, the trend line climbs, and everyone in the room nods in approval. As someone who has spent 12 years in EdTech, I have learned that engagement is the easiest thing to measure and the easiest thing to sell, which is exactly why it has become the industry\u2019s empty vanity metric. AI is supercharging this problem because it is the most persuasive engagement engine we have ever presented to a learner (so far).<\/p>\n

Sure, a streak can prove that a learner showed up, but it says almost nothing about whether that learner can think for themselves. Those are two wildly different claims, while the entire EdTech buying process tends to collapse them into one. Researchers have a name for the gap AI opens between them – the “learning-performance paradox.” Hassan Khosravi and a team of learning scientists\u00a0describe this paradox<\/u><\/a>\u00a0as “the well-documented phenomenon whereby AI tools can enhance short-term task outputs while simultaneously undermining durable learning.” As they put it, “the distinction between performance and learning is not merely semantic.” An AI tool can make your engagement metrics look spectacular while quietly eroding the learning they are supposed to represent.<\/p>\n

We now have peer-reviewed evidence of exactly that. In a\u00a02025 study<\/u><\/a>, Hamsa Bastani and colleagues gave nearly 1,000 high school math students access to AI tutors built on GPT-4 in two differing versions. One, “GPT Base,” behaved like standard ChatGPT and simply handed over answers. While students had access, their performance soared 48%. When the researchers took it away, those students scored 17% worse than their classmates who never used it. Bastani likened the AI tool to a crutch, and the in-session gains proved to be a mirage. This is the vanity metric in a literal sense: the performance number went up, when in reality, the learning went down. The second version, “GPT Tutor,” prompted to give teacher-designed hints instead of full-blown answers, drove even larger in-session gains (127%), yet largely erased the penalty once the tool was gone. Same study, same model, opposite long-term result, decided entirely by design.<\/p>\n

We are uncovering that AI can, at times, remove the effort that learning actually requires. Khosravi points to “metacognitive laziness, in which learners abdicate the cognitive and metacognitive effort required for deep understanding,” essentially a learning penalty from cognitive offloading. A progress bar can only nudge a learner to show up, while a capable AI tool can think\u00a0for<\/em>\u00a0them, leaving them feeling more prepared than they actually are. Remove the struggle, and you remove the learning, even as every engagement metric climbs.<\/p>\n

This is not the first time the field has mistaken engagement for learning. When massive open online courses (MOOCs) arrived around 2011, they were sold as the solution that would bring elite education to anyone with a connection. Engagement was high enough to raise millions of dollars, but learning was not high enough to get most people to the end (completion rates<\/u><\/a>\u00a0still hover around 4%.) Rather than question whether engagement meant learning, the industry doubled down on engagement itself. AI inherits this reflex and amplifies it. But here\u2019s the red flag: where a MOOC could only inflate logins and completions, AI can manufacture the feeling of understanding, handing learners fluent answers and a false sense of mastery.<\/p>\n

I want to be clear that none of this means AI is bad for learning; the research actually says the opposite. In a\u00a02025 Harvard study<\/u><\/a>, Greg Kestin and colleagues built an AI physics tutor around deliberate teaching principles to keep students actively thinking but withholding answers. Students who used it gained more than double what their peers gained in an active-learning classroom, in less time. Time on task did not correlate with their test scores; those who lingered longest did not learn the most. Engagement and learning can rise together when a tool is well-designed, but engagement should not be blindly accepted as evidence that learning has occurred. The problem was never the technology. It was the metric we pointed it at. If we\u2019re optimizing for engagement, AI will manufacture engagement, including the counterfeit kind. Optimize for durable\u00a0understanding<\/em>, and you have to measure something much harder.<\/p>\n

So what should EdTech buyers and learning leaders actually ask for? Start by demanding evidence of retention, not just activity. Henry Roediger and Jeffrey Karpicke\u00a0showed<\/u><\/a>\u00a0that retrieval practice, pulling knowledge out of memory rather than rereading it, is what builds lasting retention. EdTech tools should show how learners perform on a delayed assessment, not how engaged they were during the session.<\/p>\n

Interrogate what the AI does when a learner struggles. Does it withhold the answer to encourage true learning, or does it act like an oracle rather than a tool with a defined role? The same technology can also be aimed at the right target. The Khosravi paper describes “metacognitive calibration,” comparing a learner’s stated confidence against actual performance, \u201cto surface the gap between what they think they know and what they demonstrably know.” That is AI measuring real learning rather than manufacturing the illusion of it.<\/p>\n

Be honest about the incentive you are creating. Whatever you measure becomes what everyone optimizes for, both learners and vendors alike. If you press only on completion rates and minutes per session in a product demo, that is the number the next AI feature will be built to lift. Ask instead to see how learners perform on a delayed test with the tool switched off, and vendors will engineer for that. We get the EdTech we measure for.<\/p>\n

I am not urging anyone to abandon engagement data or fear AI, only to stop confusing motion with learning, especially now that AI has made motion trivially easy to generate. The streak was always a vanity metric; AI has just given it a more convincing voice. While the dashboard keeps glowing green and the room keeps nodding, it\u2019s our job to ask the harder question: when the AI tool is gone, can the learner still think?<\/p>\n","protected":false},"excerpt":{"rendered":"

Pocket Prep’s Michelle Marlowe offers this commentary on why engagement is not learning and how AI is widening the gap. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI. Ask a learning platform how it is doing, and it will almost always answer the same way, showing […]<\/p>\n","protected":false},"author":1451,"featured_media":395,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[14],"tags":[48,47],"acf":[],"yoast_head":"\nEngagement Is Not Learning, and AI Is Widening the Gap<\/title>\n<meta name=\"description\" content=\"Pocket Prep's Michelle Marlowe offers this commentary on why engagement is not learning and how AI is widening the gap.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/solutionsreview.com\/edtech\/2026\/06\/23\/engagement-is-not-learning-and-ai-is-widening-the-gap\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" 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