Yea, struggling, is one way, but there are others like optimizing for spaced reptition, visualization, etc.
The shift should be from "grind these problems so the pain sticks with you", to "create a mini logic board in minecraft to blow up that mountain". Or, "build mini simulations to show how forces work, and tie them to an interactive applet".
The discourse surrounding education is mostly a discourse of spectators. The voices who actually do the work of teaching are the quietest.
So, I don't think that struggle-based learning is the only way of learning or even the most efficient way of learning.
I think that this idea is more of a social ritual, than an actually useful method.
One can travel from one end to the other.
I was talking about being curious, how something works and figuring it out and being curious why something is done one way and not the other and figuring it out.
You can implement a full HTTP server from scratch without learning one bit of the HTTP spec by just asking the AI tool you’re using to correct itself until tests pass. At the end you have an HTTP server, you didn’t grow doing so.
HN front page has a story about Bun being rewritten to Rust. How much of rust did the author of that PR learn by doing that process? I would say very little. If they were doing that process without AI they would very likely be Rust expert once done given the complexity and size of the codebase
Yeah this has been my experience too.
I have read and heard takes similar to OP's probably 50+ times from different people in the last few months (and years, now), and I agree mostly.
But I can't get over the myopic nature of this perspective. Technological advances often change the nature of work, and therefore change the nature (or location) of the "struggle".
I can imagine some hunter-gatherers probably admonishing early farmers at the dawn of agriculture for losing the "struggle" of hunting and foraging for their own food. It's much easier to drive a car than tame, train, and ride a horse. And so on throughout time.
So now with AI, some things that were hard before are now easy. So we move on to the next hard thing that maybe before was impossible or unimaginable. There is still hard work to be done.