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.
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.
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.
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.
Doing only interesting things tends to leave students with serious knowledge gaps. Anyone that's an autodidact or has interviewed/trained one will be familiar with this.
Discipline and grit are perhaps the greatest predictors for success. High intelligence and the foresight to know what to work on, per Hamming, will get you much farther, but with discipline and grit alone your chances of failing completely and ending up in the poor house are much reduced.
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.
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.
> "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."
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.
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.
I found a spectrum - starting from copying and not understanding things through to fully internalising them.
One can travel from one end to the other.
I'm not sure what do you mean by copying.
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.
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.
Doing only interesting things tends to leave students with serious knowledge gaps. Anyone that's an autodidact or has interviewed/trained one will be familiar with this.
Discipline and grit are perhaps the greatest predictors for success. High intelligence and the foresight to know what to work on, per Hamming, will get you much farther, but with discipline and grit alone your chances of failing completely and ending up in the poor house are much reduced.
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.
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.
Very realistic and grounded take and I totally agree. And the ride just seems to keep moving faster.
> "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."
Yeah this has been my experience too.
I'd be curious on the author's views of their own child's education. I wonder how "along for the ride" he actually is.