Episode
What should kids study? How should AI help? Khan Academy's learning chief on productive struggle
- Podcast
- Future Around & Find Out
- Published
- Mar 24, 2026
- Duration seconds
- 2818
- Processing state
not_requested- Canonical source
- https://share.transistor.fm/s/722d3bc7
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Summary
So what the heck should kids be studying today!? That's my opening question to Khan Academy's Chief Learning Officer, Kristen DiCerbo , a learning and AI expert who is back for her second appearance on the show. We discuss: Kristen's advice for what to study today: fundamentals, AI literacy, and critical thinking How helpful should AI be? Why the productive struggle is critical to learning, but also why we shouldn't "fetishize" struggle When should AI be Socratic — "and why do you think that?" — and when should it just give you the answer? The "5% problem" — why edtech that's proven to work still barely gets used How Khan Academy overhauled its classroom platform and evolved Khanmigo from a standalone chatbot into something woven into the whole learning experience Personalization that actually works How Khan Academy uses LLMs as judges to evaluate 20,000 student interactions a day The scenario planning report that imagines deepfakes of school principals and AI going underground in schools What parents should be asking their kids' schools about AI right now What it looks like when a school implements AI well — and what it looks like when they don't Chapters: (01:44) - What the heck should kids be studying right now? (03:55) - Teaching critical thinking in the age of AI (06:37) - What successful schools are doing differently (08:37) - The real risk: not that kids use AI too much, but that they don't use it enough (10:52) - My 13-year-old has to check five apps just to find his homework (11:52) - "Beyond the AI inflection point" — three scenarios, none of them great (16:30) - Should we just make every school a trade school? (19:41) - What should parents be asking their kids' schools? (22:27) - Khan Academy's Winchester Mystery House problem (26:28) - Personalized learning…