> "But I do think it has become increasingly difficult to struggle for prolonged periods of time on a problem, now that we know the answer is often a few keystrokes away."
We need to seriously (or at least try to) make changes to our pedagogical processes.
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".
Education isn't just the acquisition of facts or problem-solving skills. There are fundamental skills like reading that have their own specific pedagogies that must be used, because those skills are taught so early on.
The discourse surrounding education is mostly a discourse of spectators. The voices who actually do the work of teaching are the quietest.
> grind these problems so the pain sticks with you
The reason you grind on a problem is because it is difficult and requires you to learn and bridge knowledge. You're not grinding through many problems for the sake of it you're doing it because they're challenging and slightly different each time.
Think ‘all is well’ now while ‘struggling’ generations are still alive and working. When they go away I’m more concerned. We may have to intentionally suppress tool access in education eg like certain levels of calculators being permitted for math classes, limit llm assistance similarly.
As an ancient one (graduated college 1981), my use of AI is very conservative: look things up. Generate code I can read and understand in less than 30 minutes. This is working well for me, because when the AI botches the answer, I know quickly. It either works or fails fast: there's no importable function by that name, that keyword isn't in the language, that only works in a different version of the OS. I never ask it to do something I couldn't do myself in 10x the time (spent fixing typos or missing punctuation). If I ask it to do something I don't know how to do, I create tests - usually informal - to ensure that I understand what the code is doing. If the syntax is unfamiliar, I make it explain what it's doing, and then I informally test that explanation (usually toy examples at the command line). You must learn to do these things regardless of where the answers come from - the Internet, a journal, a book, a colleague. Otherwise >>when<< it fails, you will not be able to reason about the causes for the failure and how to find a correction.
I personally refuse to not heavily use any revolutionary technology as it comes out - the old man who says he never touches AI because it cannot be trusted is not the vision of who I want to be! Use it heavily. Understand it. Or lest be confused by its take over and success.
My experience as well (30+ years developing software for a living).
I have tried everything from generating a complete, detailed spec using AI and then one-shot generating the code, to generating code one step at a time with me reviewing each result.
The speed is pretty much the same. But generating code one step at a time is IMHO vastly superior because I deeply understand the code and can easily fix issues that the AI get stuck trying to fix.
For me personally, most of skills that I managed to acquire (including coding) came from satisfying my curiosity and messing around with things to see how they work.
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.
There's always struggle. Technology just moves the point at where it starts. Your decision is if you want to venture into those areas or are you content in staying in areas that are comfortable. But that has always been the case. Most people didn't struggle with differential equations, because they never decided to go there.
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[ 0.67 ms ] story [ 922 ms ] threadYeah this has been my experience too.
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.
The reason you grind on a problem is because it is difficult and requires you to learn and bridge knowledge. You're not grinding through many problems for the sake of it you're doing it because they're challenging and slightly different each time.
I have tried everything from generating a complete, detailed spec using AI and then one-shot generating the code, to generating code one step at a time with me reviewing each result.
The speed is pretty much the same. But generating code one step at a time is IMHO vastly superior because I deeply understand the code and can easily fix issues that the AI get stuck trying to fix.
https://en.wikipedia.org/wiki/Slow_movement_(culture)
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.
"I wrestled with package installation" / "nerfed my operating system"
This is not struggle. It's toil.