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Comment by soultrees | Hacker News Reader

The thing about LLMs as a teacher is that the feedback loop is so short that progress can be made quite fast. Being able to ask a question, regardless of how stupid or trivial it may seem, without fear of judgement is a huge learning hurdle that is overcome. Not only that but reverse engineering other code “if I have this code and wanted it to do this instead - what and how would we change? Etc”, and a short feedback loop for errors where you might have to copy and paste something a lot before it works, makes LLMs the ultimate teachers.

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I agree about short feedback loops, but this was there long before LLMs, and got me into programming initially.

I love that I could compile my program and try it without needing to check it with a teacher or superior. It cost literally nothing to try, and if it failed the computer would tell you it was wrong.

In a sense you are constantly bouncing off of reality (or the limits of the compiler) and that allows you to learn really quickly by experiment. LLMs with their tendency to hallucinate or just provide you with the solution seem like they could be both a blessing and a curse (for learning).

Providing the solution is one thing, but being able to tell you more about the solution, why it is a certain way, what other examples are, what to look out for, etc. having an infinite dialog about the problem space, that's where it really shines. Banging my head against compiler output and combing through Google to figure out _why_ it failed isn't nearly as productive, imo. Otherwise yes, hallucinations are an issue, though I find them not nearly as detrimental as I thought I would, then again I'm not learning to program, I'm merely learning new frameworks or techniques, I already have the underlying foundation and can sniff out hallucinations probably better than a total novice.

I don't know about this take. A lot of what you say makes sense but your conclusion seems like a bit of a stretch.

LLMs could be very useful for learning and probably are, but they also allow you to ask the wrong questions and circumvent the learning you were supposed to be doing.

I wouldn't be surprised to see people using it to simply solve exercises for them, and those people will have a hard time trying to do things on their own.

It's actually worse than that because although LLMs are capable of a lot, they still hallucinate quite frequently and sometimes are just plain stupid.

Recently I was trying to manipulate data in Google Sheets and was using ChatGPT to help. In the beginning is was fantastic, I was very productive because I didn't have to stop and think about formulas, read crappy documentation, or analyze data transformation. ChatGPT just gave me the right answer in a split second, as long as I kept asking the right questions.

Then I stumbled upon a particular issue that wasn't really too complicated but ChatGPT could not give me a correct answer. Unknowingly I spent 3 days trying to fix problems with the solution and every time I got an answer that was slightly wrong, not in subtle ways.

I have 20 years experience as a software engineer and still, I continued to waste time in this loop. After 3 days I decided to apply my engineering skills and solved the matter in 30 min. Now I know the solution and it was way simpler than I thought.

What surprised me was how dumb the whole process was. My questions certainly weren't the problem - as bad as they possibly were, the solution wasn't too far off. Not only ChatGPT had become a crutch but it put me in a situation that no human-tutor would ever put me.

So removing the pain of quick interactions with a tutor has benefits but the technology is not quite ready to be considered as true guidance in forming (or even helping) someone's understanding of a subject.

I've been using ChatGPT a lot for general language but when it requires logical thinking it falls pretty flat.

I'm skeptical of this takeaway.

"I spent days trying to solve X by doing Y, then it turned out I could have solved it by doing Z instead" is an experience I've had countless times before LLMs were a thing. Sometimes you really do need these three days of stumbling before you can build up the confidence to do the easy solution.

(Then again, I don't know the specifics of your case.)

In addition, I feel like you build a sort of intuition after a while and detect when the conversation with the LLM has hit a dead end. When to stop and take a step back, think what it is you're trying to do and try to go down a different path. The LLM can even support with that, it's on the human to kick that off, at least at this point in time.

I can't really disagree with you. Although I want to believe this problem is more exacerbated with LLMs than with human-tutors.

I have no evidence other than hundreds of hours using ChatGPT.

> Although I want to believe this problem is more exacerbated with LLMs than with human-tutors.

Well, yeah, but the central insight here is that LLMs enable a worse-is-better approach with a tighter feedback loop. They're not as good as a regular tutor, but a regular tutor costs money, gets impatient, is only available at set hours, etc.

Part of the appeal of learning-by-LLM is that you can get a flash of motivation at 2 AM and go "hey, I should totally learn about X, that would be cool!", open up ChatGPT, ask some very naive questions, and get just enough to get started.

(It's funny, when I wrote this yesterday I thought "this is an unrealistic example", and yet here I am, at 1 AM, asking ChatGPT a bunch of questions about Google's XLS. I'm pretty sure the answers I got were hallucinations, but at least it helped me formulate the questions for when I go to the mailing list.)

I've experienced this exact frustration loop before, but I've also got a major counter-example.

I've been using GPT4 as a tool to interrogate lesson transcripts for a language I'm learning and mention in the prompt to specifically focus on things mentioned in the transcript, if it's not in the transcript, check the helper script I update as I move on through the process (which does sadly take up more and more context window) and figure out if my answer is in one of those previous lessons, and to not guess. Hallucinations are quite rare, I don't think I can name an egregious instance of it in the 25 lesson I've done of approximately 20 minutes in length each, though I'm sure it's happened.

It's also pretty good at suggesting drills based on the contents of the lesson, there are probably a whole bunch of lesson plans in the training data.

The end result has been progress at a pace I could only dream of previously, and it doesn't matter if a question is too basic because I'm asking a computer. There is zero concern of any question being embarrassing because it's only between me, GPT4, and the OAI engineer who happens across the conversaiton.

I absolutely have the same overall feeling, when the task at hand is related to text processing (including understanding and spinning off new takes or ideas from it).

But when the task at hand involves logical thinking, that's when I believe the LLMs of today are still a very much work in progress.

So I'm skeptical of trying to use them as tutors for now. I'm sure things will evolve quite quickly from now.

They should be smart enough to know when you ask the wrong questions. Perhaps they aren't there yet, but that's likely where they are going.

Which is also an interesting problem isn't it? The majority of people will only be doing what the LLM suggests...

The LLM's best role is this context is as a trusted, knowledgeable advisor/teacher. It works so well because there's no negative psychology that can be introduced, because you know the LLM isn't a human.

Like the commenter for this thread was saying, there's no fear of asking a stupid question. Or going to slowly or too quickly.

> I wouldn't be surprised to see people using it to simply solve exercises for them, and those people will have a hard time trying to do things on their own.

This is a more recent version of the argument against most machines and similar automation tools. There is usually some validity to it, but we saw the same arguments against MOOCs, calculators, computers, type writers, smart phones, spell checkers, etc.

Absolutely. Fail fast, fail often. It makes it very easy to quickly try out ideas before you go down a rabbit hole. However I think for people that are completely new to programming it could quickly become a crutch.

Seconded. And it's not just programming. Any subject that is easy to moderately verifiable like most Math and Science in school can also benefit from this. We're one step closer to personal tutors and autodidactism for everyone. The other half of the learning journey would be arranging the curriculum for yourself.

If only more people would focus on cultivating learning instead of locking down tech like this because they're afraid (and perhaps lazy to create new teaching methods).

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