GoKawiilThis piece was also cross-posted on the Civics of Technology blog. This piece also has a followup post that you can find at Three Questions on Questions: On Asking, Knowing and Noticing
Two pieces crossed my feed recently, both about Sal Khan and the AI tutoring revolution that wasn’t. The first was Matt Barnum’s reported piece in Chalkbeat, where Khan himself acknowledged that Khanmigo, the AI chatbot tutor he launched three years ago with world-changing ambitions, was “a non-event” for most students. “They just didn’t use it much,” Khan said. His own Chief Learning Officer, Kristen DiCerbo, put it even more plainly: “So far I am not seeing the revolution in education.”
The second was Dan Meyer’s sharp obituary on LinkedIn, titled “RIP Khanmigo & Edtech Industry Dreams of AI Tutors.” Meyer traced the whole arc: the TED talk predictions, the philanthropic subsidies, the increasingly aggressive way Khanmigo inserted itself into the student experience (because students wouldn’t seek it out voluntarily), and the steadily shrinking user projections. His conclusion was blunt: if Khanmigo died with every advantage in the world (early OpenAI access, Microsoft backing, government subsidies, Sal Khan’s Rolodex), what hope should the rest of the edtech industry place in chatbot tutors?
These are important pieces, and I’d recommend reading both. But reading them, I found myself thinking about a deeper question. Not whether the revolution failed (it clearly did) but why it was never going to work in the first place.
To explain I have to go back a bit in time, back during my days at MSU, when I was out there giving talks about technology integration and the critical role played by the teacher in this entire process. And further about the significance of students actively constructing representations of their understanding.
So in these talks I used to show a clip from the Charlie Rose show (see below). It’s an interview where Khan describes how he prepares to teach a new topic. And it’s wonderful. Here’s Khan on learning about, say, Napoleon and the French Revolution:
“I approach it from what my brain would like to see… I like to see a scaffold, I like to see a map… what is the Holy Roman Empire, like where, what is that now?”
He reads Wikipedia first, “just to get the scaffold.” He draws timelines. He copies maps and pastes them onto his digital blackboard. And then he does something genuinely important: he pushes past the surface until he hits the questions that textbooks skip. Here’s Khan on the neuron:
“A biology book will tell you okay the signal goes across because there’s a myelin sheath and I’m like yeah but how does putting a little tissue around a neuron, how does it make the signal go faster? And no biology book will tell you that answer.”
So what does he do? He ponders. He thinks it through by analogy (fiber optics, signal amplification). And then he calls up friends who are biologists or communications engineers and asks: “Does this make sense?” Sometimes they confirm his intuition. And sometimes, beautifully, they say: “You know what, we don’t know.” Khan’s response to that is perfect: “Why didn’t the book tell me that?”
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