📚 Don't miss the Spanish-language launch of @GEEAP_'s report, Effective Reading Instruction in Low- and Middle-Income Countries.
Join education experts to discuss what works to help children learn to read.
📅 15 June | ⏰ 11 AM EDT
Register here: https://t.co/D8WsNJy6zx
Robert Pondiscio: 19 reasons that knowledge-rich curricula have not been broadly adopted in the US, despite strong research support. I'd add this one: "educators underestimate what young children can learn, and the joy with which they will learn it." https://t.co/NQPakMfP3B
I have slightly updated my new blogpost on education's problematic history with evidence,
(https://t.co/dcIrv2gtcU) to include a point I meant to include at the outset, as per below.
NEW ISSUE: when retrieval practice stops working, why mixed feedback backfires, what the OECD found when students lost GPT-4 access, and the phonics message that still hasn't landed. The Learning Dispatch, June 2026 ⤵️
This super myth buster from Steplab about evidence-informed approaches to SEN/ additional needs provision. Summary: lots of things we sometimes think are useful, have no evidence to back them up, or weak evidence. In some cases they may even harm. Fidget spinners, Zones of Regulation, Mindfulness…just because we want something to work doesn’t mean that it does.
Anyone wanting a deeper dive on myth busting regarding interventions for children and adolescents with additional needs might be interested in this 2026 text by Dr Caroline Bowen (@speechwoman) and yours truly:
https://t.co/MAHhcbBHct
MIT's Nobel Prize-winning economist proved that AI is mathematically guaranteed to destroy human knowledge.
They published a massive NBER paper modeling the long-term impact of AI on human cognition.
And they found the most alarming conclusion in the AI literature so far.
It’s called "Knowledge Collapse."
Here is how human progress actually works.
When you struggle to solve a complex problem, you generate two things:
General knowledge about how the world works, and context-specific knowledge about your exact problem.
Normally, humans acquire both at the same time. You do the hard work to solve your specific problem, and in the process, you learn a general principle.
You share that principle. That is how human knowledge grows.
Then comes Agentic AI.
AI is incredibly good at giving you the exact, context-specific answer you need right now. It hands the solution to you on a silver platter.
So you stop doing the hard work.
And because you stop doing the work, you stop generating the "general knowledge" that society relies on.
Acemoglu calls it the "knowledge-collapse equilibrium."
When AI reaches a certain accuracy threshold, the incentive for humans to learn drops to zero.
Nobody verifies. Nobody explores. Nobody discovers new fundamental truths.
Society gets increasingly sophisticated automated outputs, while our actual capacity to generate new knowledge quietly erodes.
But here is the most terrifying finding in the paper.
Welfare is "non-monotone" to AI accuracy.
That means as AI gets more accurate, society actually gets worse off.
Why does anyone even question the science of reading? The Community Connections podcast teaches us why, with yours truly, @markseidenberg who wrote the brilliant "Language at the Speed of Sight," and others.
https://t.co/m3vTbcds4M via @YouTube
I’d love to quote this entire piece. I’ll admit that not too long ago, I was a “progressive” teacher myself. The problem I encountered time and time again was an ongoing focus on so many things that had little to do with improving actual pedagogy. The furniture, pronouns, wall displays, flexible seating, grading practices, homework bans, learning styles, makerspaces, SEL initiatives, classroom aesthetics, care carts, student choice in everything, and countless other debates often took center stage.
What made it frustrating was that these issues generally had little to no impact on student learning. Meanwhile, while so much energy was being spent debating and defending these ideas, students were missing out because there wasn’t a deliberate focus on improving the quality of instruction itself. Discussions about curriculum coherence, explicit instruction, retrieval practice, prior knowledge, and cognitive load were non-existent.
The most meaningful gains in student learning come from refining our teaching methods and deepening our understanding of how learning works and not from constantly revisiting the peripheral details of the classroom.
"Observers found the project method to be the least effective mode of pedagogy...but the terminology shifted and the practice remained in different forms under different names such as 'discovery learning', 'hands-on learning',..."
Education isn't just about years in school—it's about what students learn.
A review of 73 studies in 41 countries finds that a 1 SD gain in cognitive skills is associated with ~15% higher earnings. Better learning, better livelihoods.
https://t.co/kFKFu0T7H4 #EducationPolicy #Skills #EconomicGrowth
Basic mathematical fluency is analogous to literacy; without it, success in university-level STEM becomes structurally unattainable for students”
https://t.co/n2FDGbiGYT