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Learn Your Way: Reimagining Textbooks with Generative AI

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Re: Learn Your Way: Reimagining Textbooks with Generative AI

#101

Post by janalsncm »

Ray20 wrote: post #82
janalsncm wrote: post #47

Earlier quoted context omitted.

> EdTech has the worst returns of any industry in venture capital. Why? I think this one is fairly simple. Half of consumer spending comes from the top 10% of earners, whose kids we can assume have generally pretty decent educations already. The people who need education help the most don’t have money to spend on it. The parents who do have money to spend want to invest in tailored education from a human teacher, not…

> So if you want to make money, you need to focus on things like enrichment and test/college prep for the top 10% But there's no potential market in the top 10%. I mean, these people just hire a good teacher and that's it. There's no room for improvement; there's nothing that can beat a good teacher. > Helping inner city kids who are 3 grades behind in reading doesn’t print money This is a political problem. Politica…

Getting into an elite college is an arms race. Anything you can sell to a parent which will give them a leg up over other parents is a viable product. To put a finer point on it, a teacher + your product beats a teacher.

> Helping inner city kids who are 3 grades behind in reading doesn’t print money

100% and this is broadly why ed tech doesn’t move the needle.

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#102

Post by e-khadem »

bigfishrunning wrote: post #29
criddell wrote: post #21

Earlier quoted context omitted.

> explain a textbook I've had very good luck using LLMs to do this. I paste the part of the book that I don't understand and ask questions about it.

But the problem is, you don't understand the passage, so therefore how will you vet the answers? Seems like hallucinations would be very very damaging in this use-case

Depends on the subject. For example in maths (assuming that one has a good background) you can verify the proofs yourself (and this isn't a given for highschool students).

I have also found another use for this. For example in studying modulation techniques in communication systems, I went back and forth between Monte-Carlo simulations and theoretical approximations to see how accurate each one is. And then added some more realistic error scenarios to do an end-to-end validation. In this case the LLM was used as a shortcut to write repetitive code that was verified manually, and this was complementary to the text-book, and made reading the topic more engaging, enjoyable, and comprehensive.

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#103

Post by aDyslecticCrow »

lacy_tinpot wrote: post #42
bigfishrunning wrote: post #29

Earlier quoted context omitted.

But the problem is, you don't understand the passage, so therefore how will you vet the answers? Seems like hallucinations would be very very damaging in this use-case

If you can't discern what good answers look like to the questions you're asking, you're not asking the right kind of questions. Asking the right kind of questions is a genuine skill. It applies to every domain of life where you are at the mercy of a "professional" or at the mercy of some knowledge differential. So you need to be a good judge of whether the answers you're getting are good answers or bad answers.

> Asking the right kind of questions is a genuine skill.

A skill we cannot rely kids to have, and which i think takes years of training and learning for even adults to really acquire. (to be clear, i'm not thinking about AI prompting. I 'm thinking about assumption breaking and understanding prodding questions the learner asks themselves and seeks answers for, to build and refine their mental models of something they learn)

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#104

Post by squigz »

lacy_tinpot wrote: post #42
bigfishrunning wrote: post #29

Earlier quoted context omitted.

But the problem is, you don't understand the passage, so therefore how will you vet the answers? Seems like hallucinations would be very very damaging in this use-case

If you can't discern what good answers look like to the questions you're asking, you're not asking the right kind of questions. Asking the right kind of questions is a genuine skill. It applies to every domain of life where you are at the mercy of a "professional" or at the mercy of some knowledge differential. So you need to be a good judge of whether the answers you're getting are good answers or bad answers.

> If you can't discern what good answers look like to the questions you're asking, you're not asking the right kind of questions.

Whaaaaat? How does this work? If you're trying to learn a new topic, how are you supposed to recognize a good (and truthful) answer, whether it's from an LLM or instructor?

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#105

Post by aDyslecticCrow »

janalsncm wrote: post #32
mossTechnician wrote: post #20

I wonder how this will contribute to our current declining literacy rates in a social climate that's already rife with anti-intellectualism and isolation. Even if this worked well, it appears to be to be a step backwards. Call me pessimistic, but this technology looks more poised to replace teachers in schools than supplement them.

In that case the problem isn’t what technology we do or do not introduce. A society that values literacy isn’t going to be duped by a demo and a blog post. However a society which does not value understanding, expertise, or teachers will take every opportunity to shortcut them.

Going by the atrocious salary expectation for teaching (which i firmly place as one of, if not the most, fundamentally important jobs in modern society) i think we've already established where we land on this.

And note how i didn't mention a country; i think this is a widespread issue beyond country borders currently.

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#106

Post by doctorpangloss »

Ray20 wrote: post #82
janalsncm wrote: post #47

Earlier quoted context omitted.

> EdTech has the worst returns of any industry in venture capital. Why? I think this one is fairly simple. Half of consumer spending comes from the top 10% of earners, whose kids we can assume have generally pretty decent educations already. The people who need education help the most don’t have money to spend on it. The parents who do have money to spend want to invest in tailored education from a human teacher, not…

> So if you want to make money, you need to focus on things like enrichment and test/college prep for the top 10% But there's no potential market in the top 10%. I mean, these people just hire a good teacher and that's it. There's no room for improvement; there's nothing that can beat a good teacher. > Helping inner city kids who are 3 grades behind in reading doesn’t print money This is a political problem. Politica…

> This is a political problem. Political problems cannot be solved by technological means. So there is no market here either.

Another POV is: pick your disruption.

AI stuff has definitely disrupted education... for the worse. It happened within a political and economic status quo. The AI stuff did not need to wait for the movement of any levers of power to happen at all.

If you are seeking a way to fix low returns in ed tech (and for that matter, Health IT, which is like, #2 worst performing sector): attack Enterprise Sales. Destroy it. Make stuff that destroys the monetization system where districts buy exactly what they ask for. It isn't complicated.

Scratch and early Khan Academy provide a template for good ed tech targeting the learner directly.

Whether you make $1 million or $1 billion doing this, I don't know.

Chegg got to, and fell from, great heights by delivering cheating, which ChatGPT does for free now. Cheating ALSO worked within a political and economic status quo, that 30% of students cheat, and that the cheating is a necessity, apparently, for the survival and thriving of a vast number of people, all around the world.

There are markets. Lots of them. You can do good or bad. Paul Graham doesn't invest in Cluely, even if it makes money, it's kind of evil (A16z doesn't care about cheating, the people who run it are the ones who cheated in school). So there are even opportunities that are missed by the very best seed fund.

To me, a big opportunity lies in things the government education cannot do. Some things good, some evil, some complicated. For example, no matter how hard it seems to try, the government cannot functionally collect on a trillion bucks of student loans. What does that mean for education? I don't know, but I think if you are looking for $1b+ opportunities, they're there.

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#107

Post by golem14 »

rhetocj23 wrote: post #92
apwell23 wrote: post #17

Earlier quoted context omitted.

yea this is stupid . agreed. I don't know when these dorks will understand that education isn't a technical problem. Its a social and emotional problem. existing material is clear enough to learn from.

Theres a reason why theres a grave yard of Google's dead projects. Its annoying that software is such a high gross margin industry - I would love to see Googles cash get taken away so they cant take these vanity projects.

There's a _huge_ cottage industry of edu apps and programs that are both hugely expensive and not better at teaching, consuming a lot VC and end user $$$. As a first step, this seems not bad at all.

I do agree that it would be better to dial in on a pupil's interest than the grade level (my kid may be 7th grade in English but 9th grade in Chemistry, for instance.)

[Edit: fix typo]

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#108

Post by lacy_tinpot »

aDyslecticCrow wrote: post #103
lacy_tinpot wrote: post #42

Earlier quoted context omitted.

If you can't discern what good answers look like to the questions you're asking, you're not asking the right kind of questions. Asking the right kind of questions is a genuine skill. It applies to every domain of life where you are at the mercy of a "professional" or at the mercy of some knowledge differential. So you need to be a good judge of whether the answers you're getting are good answers or bad answers.

> Asking the right kind of questions is a genuine skill. A skill we cannot rely kids to have, and which i think takes years of training and learning for even adults to really acquire. (to be clear, i'm not thinking about AI prompting. I 'm thinking about assumption breaking and understanding prodding questions the learner asks themselves and seeks answers for, to build and refine their mental models of something they…

That's absolutely not true. Kids get trained how to ask questions very quickly from a very young age. Good responses to those questions fundamentally shape the entire developmental journey for kids and extends to their academic abilities in school.

Because questions are fundamentally about knowledge differentials, which will always exist for individual human beings. We can't at any point know everything.

Know how to know what you don't know and get a good grasp of what it means to know in the first place.

Knowledge isn't absolute.

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#109

Post by clusterhacks »

non_aligned wrote: post #86
clusterhacks wrote: post #18

Isn't this just showing the effects of actively engaging the learner by placing a topic in contexts familiar/favored by learner versus just reading about a topic? Like, if you had made the text pdf readers do some manual thinking by working on trying to place the topic into the same type of familiar/favored context, wouldn't that have been the better comparison? I think using GenAI for learning is cool and exciting (…

> I think using GenAI for learning is cool and exciting (especially for autodidacts) I don't know. I've been trying, but I think there are two fundamental issues. First, I don't think it's all that useful for "out-of-order" learning and for explaining concepts in non-conventional ways. To give you a practical example, there's a certain order in which we teach math, and every subsequent step builds on the previous one…

"Out-of-order" and non-conventional explanations are interesting to consider. For both, I would expect LLMs to do poorly when there isn't much (or any) material for those approaches in the training data. My intuition would be the learner is going to have to be more exploratory via prompt engineering and still struggle against the tendency of the model to lean into classic or conventional explanations.

I don't particularly expect models to be dependable in responses, but I see how that presents a much larger problem in a learning context. I'm ok with bad responses that I can fight back against, but I also wouldn't reach for an LLM for a new field by default either.

For me, I do like using an LLM as a supplemental learning aid along with other traditional resources. I haven't tackled a deeper, new-to-me field yet with one. Maybe it's time for that . . .

Re: Learn Your Way: Reimagining Textbooks with Generative AI

#110

Post by lacy_tinpot »

squigz wrote: post #104
lacy_tinpot wrote: post #42

Earlier quoted context omitted.

If you can't discern what good answers look like to the questions you're asking, you're not asking the right kind of questions. Asking the right kind of questions is a genuine skill. It applies to every domain of life where you are at the mercy of a "professional" or at the mercy of some knowledge differential. So you need to be a good judge of whether the answers you're getting are good answers or bad answers.

> If you can't discern what good answers look like to the questions you're asking, you're not asking the right kind of questions. Whaaaaat? How does this work? If you're trying to learn a new topic, how are you supposed to recognize a good (and truthful) answer, whether it's from an LLM or instructor?

I would argue you're doing it right now.

By being skeptical of the answers, testing the answers, corroborating with other sources, etc.

This isn't new. This is literally how we've been exploring this knowledge game for thousands of years.

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