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I see this as a memorize-vs-understand fallacy many repeat.

It is really a combination: you need to memorize a large corpus of information to operationalize knowledge — understanding a bunch of theorems in mathematics does not help much (even if you are able to prove them when you see them) if you can't remember the boundary conditions they hold under.

Or having good understanding of foreign language grammar won't help you if you do not memorize words that you need to express your thoughts.

Good literature will show you some of life's challenges and potentially let you think through them in a non-stressful situation (other than "I've got to finish the last 200 pages by Monday" ;)).

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> if you can't remember the boundary conditions they hold under.

At the outskirts of one's knowledge this is inevitably the case. My impression it is still useful to know that a certain implication is possible - and one can look up the exact conditions.

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Maybe. As the nature of assistive tools changes, so does pedagogy. Calculators are the easy example since most of us are (still) familiar. But there are others that were just as pronounced -- e.g. log tables and slide rules were transformational and instrumental at one time, and you've (probably) never used them. If you had used slide rules to solve your homework problems then were excluded from using them on exams, you'd see a similar effect.

AI is a big change; pedagogy is going to change too.

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> As the nature of assistive tools changes

I mean, does it? The way I see it, the best LLMs have to offer is infinite patience (until they inevitably and unpredictably start to confabulate, which should be a gigantic red flag, anyhow), I don't see how LLMs can be used to explore teaching paradigms that haven't been explored before. We know pretty well from centuries of empirical experimentation how children's brains develop under different stimuli. It's not exactly something the software industry needed to "hack".

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I wish that was the main way countries understood education
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