Moneyshot: "The results are eye-opening. After six months, pupils using ai saw their average homework score rise by 18% across all subjects. The time they took to complete each assignment fell from an average of 64 minutes to 45. But come exam time, the same students scored 20% below their classmates who had not called on ai’s help. Homework scores once predicted exam performance; now those who score highest are, perversely, more likely to do worse in exams."
Study design: "David Stromberg of Stockholm University and Victor Lei and Wu Yanhui of the University of Hong Kong set out to fill the gap. They tracked 27,000 pupils aged 12-18 in China, where ai adoption has been fast. Around 80% reported using models such as Doubao and DeepSeek; the other 20% formed the control group."
As with most training the journey is the point, not the destination.
That said, I think smart use of AI could help. It could explain concepts in a way that might help you understand better, it could probe your knowledge in a more dynamic way by tailoring questions, and so on. This requires the AI be restrained by some harness, not free to write down the answers for you.
AI seems like an amplifier of bad and good. One fundamental difficulty for using it for good is unless you’re primarily using it to find parts of primary source documentation and canonical references, which requires conscious effort, you end up using it as a secondary source reference. This means you’ve fundamentally added another step (if you have to know what’s in the textbook to pass the class, you’ve now added additional labor to your process).
I would like an AI system which adds as little of its interpretation as possible until I ask, for which the main behavior is bringing up exactly the part of the primary reference which has the information I want.
(I think this is probably slightly heterodox to the degree I prefer this though.)
I'm way beyond homework, but I do appreciate the compliment on seeming young!
I meant: what's going to stop the average lazy student from ignoring whatever harness the university recommends and instead use an unrestricted LLM, thus learning nothing?
> what's going to stop the average lazy student from ignoring whatever harness the university recommends and instead use an unrestricted LLM, thus learning nothing?
Nothing until they start failing exams and maybe seeing the error of their ways. My suggestions wasn't for you, it was for the smart student who wants to use AI to enhance their learning but not have it do all the work.
But cheating isn't new. People have been cheating in school for centuries. It's easier now, but the consequences were always the same. At some point the chickens come home to roost and you pay the piper.
> But cheating isn't new. People have been cheating in school for centuries. It's easier now, but the consequences were always the same. At some point the chickens come home to roost and you pay the piper.
My concern is that with LLMs and above average bullshitting abilities, the chickens might never come home to roost.
I think that is fine, certain things are becoming less important to learn and certain things more important. With the pace of change it is likely to continue shifting.
I really don't see how anything but social skills are rising in prominence. Perhaps twenty years from now everything will depend on your connections as any "hard" problems will be readily solved by AI (seeing as few problems are ever really novel).
Back when I was studying there were topics which I had a really hard time grasping. Having a personal tutor that I could ask specific questions and have a back and forth with would have helped a lot I think. At least the few times I did have such an opportunity that was definitely the case.
Kids are, by and large, lazy however. Hell, adults are lazy, this isn't even an indictment on kids or even people in general, I think our bodies & brains are simply wired to seek the path of least resistance from an evolutionary POV.
Kids won't be using LLM tooling as a personal tutor following some sort of Socratic method, they'll ask it to solve their home/coursework for them and blindly copy/paste the answer. Hell, they'll just manually copy down what's on their screen if copy/pasting isn't possible for whatever reason.
Obviously exceptions exist, but I'd wager from being an ex-kid myself the type of kid who would genuinely use these tools for actual proper self-tutoring would be an extreme rarity.
When I was in college, we had office hours with the prof and the TAs, we had group study sessions, and private tutors. Or you could ask your friends. All of those required going somewhere at a specific place and time and asking someone else to give up their time for you.
AI gives you a way to get the same help without asking another human. Say of that what you will, but not everyone was comfortable asking other humans for help even back then.
You also have your book and a wealth of online resources, which also don't require interacting with someone, and which have the same information the AI is trained on. Fundamentally nothing is different. We don't see positive outcomes from students using AI as an aid even if hypothetically it could be possible.
The kids who used AI and studied for a similar amount of time as the non-AI high performers apparently had similar (slightly higher) performance. The kids who used AI and did poorly used the AI to do the homework for them (this is what the article says).
I believe AI is basically an amplifier of bad and good. I’m cynical about the world and assume it will be used more for bad than good, but I don’t doubt some of the best people in every field will be using AI to amplify their work in good ways.
I dunno, concentrating the environmental impact of 20GW of gas based power generation would be the equivalent of 6-9 Million cars running... All in the space of a corner of a small city
Just one 20 GW AI data center which is being built with gas powered turbine generator power plant, will be the largest fossil fuel power plant in the world... How exactly is that the same as one coal mine
It helps smart people be barely more effective and helps dumb (more importantly, people who do not value effort, people who are lazy, people who are self absorbed) people shit out endless streams of worthless tokens that can swamp out everything.
Raising the noise floor like this only makes it that much harder to find "Smart" people, which we were already doing terrible at.
I use Claude every single day, but this is such a bad tradeoff. Maybe it will help me standup a quick fix when that is needed. Maybe it can help me dig through documentation to find relevant bits and figure out the unstated assumptions underlying it. Maybe it helps me generate test cases.
Meanwhile, my day to day life is now noise. All social media is noise. All content is noise. Slop pours onto me from all directions. Writing more test cases isn't helping me.
Am I smart? Am I dumb? I don't care, right now I'm deafened
All I've noticed is AI creating a perverse incentive to make everything as complicated and bureaucratic as possible, so only the people that know how to leverage AI to cut through it ever succeed.
I'm using Claude at work myself and am impressed with the product, but notice that this is the only reason I need to use it at all. Our product pages were shit to begin with, now they're AI-generated and somehow even worse. Our procedures are incomprehensible spaghetti with enough arbitrary context switching to give a sadistic Soviet municipal administrator an erection at the thought of watching anyone try to actually follow them.
Use AI to create inefficiencies, then use AI to bypass them. Those who can't do the latter will struggle to survive.
> Raising the noise floor like this only makes it that much harder to find "Smart" people,
It does give us a new heuristic, though: people who are willing to completely cut generative AI out of their lives (cold-turkey, if you ever started using it) are a much smaller group of, predominantly thoughtful, people. You do have to give up Claude to be part of this group, but from what you say, that's no great loss, and no longer being deafened is worth it.
This has considerable advantages over conventional elitism, because the barrier-to-entry is negative in almost all cases.
The one exception I've found is assistive tech, where the state-of-the-art is so poor that vibecoded slop is genuinely an improvement over the state-of-the-art, and in many cases the tooling simply isn't available to make your own assistive tech (unless you want to bootstrap an entire networked computing environment, which isn't very helpful when you want to do your online banking and do not, in fact, work at your bank).
But there are not many principled exceptions where you could seriously argue that the trade-off is worth it. Take mathematics, for example, which we often see touted as a "good use-case" of generative AI. The primary advantage of generative AI in mathematics is being able to search though a vast corpus of ivory towers and inconsistent terminology (without proper attribution) to locate and connect ideas that can help solve problems. The deficiency this is addressing is elitism, inadequate communication, and inadequate indexing within academic mathematics. This problem is entirely created by the academic mathematicians, and has been known for nearly a century (per https://en.wikipedia.org/w/index.php?title=Nicolas_Bourbaki&...):
> Bourbaki was founded in response to the effects of the First World War which caused the death of a generation of French mathematicians; as a result, young university instructors were forced to use dated texts. While teaching at the University of Strasbourg, Henri Cartan complained to his colleague André Weil of the inadequacy of available course material, which prompted Weil to propose a meeting with others in Paris to collectively write a modern analysis textbook.
To my knowledge, this is the only organised project to clean up and improve mathematical communication. Everything else (Metamath, Mizar, AFP, Lean) is yet another ivory tower. The Wikipedia article on this topic (https://en.wikipedia.org/wiki/Mathematical_knowledge_managem...) risks deletion as non-notable, that's how little anyone's actually trying. They made their own bed, and generative AI will only provide a brief respite from having to lie in it. (I was surprised how many other "compelling" use-cases evaporated when I applied this razor to them: the sibling comment https://news.ycombinator.com/item?id=49392265 points out one such.)
Vibe-coding assistive tech which doesn't yet exist, as a temporary scaffold to improve the quality-of-life of yourself and others in a social world dominated by non-essential access barriers is, to my knowledge, the only exception to this principle that can be justified. If you treat people who make other excuses, or who don't even bother with excuses, as not worth listening to, you lose little – and doubly-so, if you make your stance clear, so that others know the "cost" of gaining your attention.
> It helps smart people be barely more effective and helps dumb (more importantly, people who do not value effort, people who are lazy, people who are self absorbed) people shit out endless streams of worthless tokens that can swamp out everything.
... including ultimately stuff needed to make the smart people.
LLMs make significant mistakes frequently and smart people have no way of judging those mistakes outside their domain expertise. They are also sycophantic and great at being an echo chamber which makes people feel smart even if they are not.
So I think the burden of proof is on you to prove that they somehow amplify intelligence, it seems highly unlikely.
Smart people know LLMs confabulate and tell them they’re Absolutely Right! Smart people don’t want to be embarrassed by trusting the hallucination machine and revealing their gullibility to others.
Smart people are handsome, charming, and always make the right decisions even on things they don’t know about. And if they ever are deceived, well I guess they were no true smart person.
Really widely reported in normie news and on reddit, hallucinations and sycophancy. Stand by that whether you’re a petroleum engineer or a bartender, if you’re clever you were probably either well informed or curious enough not to blindly trust the plagiarism machines.
Why would a smart person go to an LLM for an answer they cannot judge or test, be succeptible to flattery and sycophancy rather than picking up on the emotional manipulation and being suspicious/sceptical of the interaction, or looking for support from an echo chamber target than a Socratic opponent?
All of those sound like flaws and defects of dumb people?
> Why would a smart person go to an LLM for an answer they cannot judge or test, be succeptible to flattery and sycophancy rather than picking up on the emotional manipulation and being suspicious/sceptical of the interaction, or looking for support from an echo chamber rather than a Socratic opponent?
Great summary of the flaws with LLM "research"/"reasoning". It's always trying to con you, and I question the literacy and intelligence of the people who can't see this.
Many people think they are smart and are taken in by LLMs. Also many genuinely smart people are unable to judge their competence in other areas (eg Nobel Laureates making pronouncements in fields they know nothing about).
AI does not make me "smarter" in the important thing I am working on.
In software particularly, what AI does do is give me back my time from the drudge work that I don't care about. Keeping my build system configured and my tests up to date and my documentation synchronized is a good use of AI because I mostly don't care about how crummy the result is as long as it "works".
You aren’t being cynical, you’re arguing with disingenuous entities with money on the line. We already know it’s used primarily for the negative case. Everyone who ever intended High School or College knows this.
Definitely had a sheltered public school experience, took AP stats my senior year and realized all the top students were sharing answers from an earlier period through text messages. After figuring this out I too joined in on the action, then shortly after I quickly deskilled.
Suppose it's good to learn how elastic the brain is, in both directions, at a young age where it doesn't matter.
Not really. I would rather not find out later in life, with way more responsibilities, that when you purposely neglect mental skills they atrophy quite fast. People already have a hard time noticing that they age, being able to truly self asses is a skill that few, including myself here, possess.
The scary thing is that 81% of AI users in this study were determined to be "outsourcing" their homework to the LLMs - and the rate increases the more exposure they had to LLMs.
I thought that it was generally accepted by now that homework in the volumes that it is being assigned in the modern day was not found to be beneficial in any significant way in the first place? Maybe once all students start outsourcing it to AI it might finally die like it deserves to. People these days grow up with almost no free time for themselves, it's all school, sports/extracurriculars or homework nonstop. All worker drone and no play makes for an increasingly dysfunctional society.
All play and no work makes for an even more dysfunctional society. Kids need to do their homework, both to train their minds but also to develop integrity and work ethic. Being able to work toward a distant goal is not something you're born with.
But I keep reading here on HN about the brave future where everyone carries around a little box that you put coins in whenever you need to know how to compose a song, solve a problem, write some code, etc, and it will give you your answer you can take credit for without actually wasting time on learning or work ethic.
I think there are better ways to teach this particular skill than homework. But I agree that practicing is very important. In hindsight I think that the concept of TD (classes where you only do exercises and have a teacher guide you if needed) in France is really good. (This is not the same thing as lab classes)
> I thought that it was generally accepted by now that homework in the volumes that it is being assigned in the modern day was not found to be beneficial in any significant way in the first place?
Citation needed? I have no clue where you got this from. I hadn't even heard of it as a conjecture, let alone as something anyone accepted, let alone as gene rally accepted...
Before I dive into the paper: the claim was that some effect was generally accepted, not that a study was performed on it and that it drew a particular conclusion. Is this actually going to establish the former or are we just assuming that the existence of a study implies general acceptance of its conclusion?
How do you expect students to learn anything when:
1. They don't do any homework.
2. All the in-class time is split between the teacher babysitting and playing social worker to problem students, and lecturing, with little to no opportunity to actually practice what they've learned?
I understand that some students don't have home environments that are conductive to doing homework well. I understand that some students are enrolled in five hours a day of extracurricular university-application-padding activities. I understand that some students have incredibly poor screen discipline and impulse control.
But I don't understand that anyone has magically figured out how to teach complicated things to students, and have it stick without them spending a lot of time practicing what they are learning.
As anyone who has tried to do something hard knows, the first step to being good at something is to spend a lot of time being pretty shit at it.
I suppose I could always place my phone that's playing Rachmaninoff somewhere under a pile of sheet music, while I mash the keys on an unplugged electric piano.
You don't have to do a lot of repetitive, boring exercises to learn piano. Once you learn how to hold your hands a little, read music, and learn where the notes are, you can simply try songs you like, and switch songs when you please. On other instruments, you might not need to read music (I've met many guitarists and drummers that cannot read music, nor do they use printed music to play - and blind folks can play instruments too)
Art is similar. You can look up skills as necessary to try to make the piece you want. Adult art learners often just start with the type of art they want to make.
In both cases, the finished piece might not be the quality you want, but in neither case are you necessarily doing repetitive stuff to learn (playing scales over and over or sketching the same bits over and over). You can retry a piece or move on - the skills will still carry over.
None of these reflect homework in school. Now, I know I graduated school decades ago, but math homework was repetitive with seemingly no real-world application and absolutely no help if I needed it. I took a math course online some years later and it was much better: Instant feedback if I got the problem wrong and instant help to walk through the problem if I needed it - then a different but similar problem was given for the homework. This was actual practice in ways traditional homework wasn't. Homework in the traditional sense isn't practice - they are all miniature tests that affect your grade.
I didn't have to practice writing - I just did the papers assigned and rushed through them. You can grade papers for other subjects on prose and grammar instead of just doing it for language courses. You don't have to read classics to read better if you just read a variety of things you are interested in. You'll read plenty of boring things for other subjects and get that sort of practice.
With most of this stuff, having actual homework isn't necessary as long as students are given time for practice. Practice is what makes you good at something, not homework, and practice can take many forms.
Are there a lot of concert pianists who got to the level that they did by just playing random songs they liked, without deliberately practicing the mechanics? And then, one day, woke up with the ability to quickly learn and perform unfamiliar pieces of music at the level expected of one?
You can absolutely learn to play some piano by just noodling. Your learning will be much slower, and you'll miss important fundamentals that are present in any piano method.
That's perfectly fine for learning things that you do for enjoyment, or things that don't really matter. It's a lot less fine for learning things that... do.
What I remember hearing is that exercises and practice are needed to transform words on the page to something you know and master.
What I remember being questioned is does it make sense to do those exercises as homework or would they be better in school.
Or on the flip side should school get out early like 11 or noon, like I think the german gymnasium does and have all the exercises as homework.
The US system where children get out of school at 15:30 and still have a bunch of homework seems a little lopsided someplace.
The 3 month break in-between school years is definitely questionable.
I think the answer is a complex one because it intersects with personality and neurodivergence.
Depending on who you are and your family situation any form of homework can be a real challenge. Not because of what you are studying but because of how difficult it is to sit down and do anything you aren't passionate about. Certainly anyone with an executive function disability will have that challenge.
The problem was never the volume of homework, it is the targeting and specificity. Learning happens through repetitive deliberate practice, full stop. You can’t learn through osmosis; effort is required.
Industrialized mass education has always suffered from a unit economics problem: the labor required to assign individually-tailored problem sets and manually grade them in the volume needed for most students to actually learn the material is prohibitively expensive.
It's not so clear that AI is an amplifier.. The paper has some fascinating analysis on this topic:
"At the other end of the distribution, AI students who spend more than 65 minutes on their homework receive homework and exam scores similar to those of non-AI students, suggesting that these students do not use generative AI for homework assignments. However, this group consists entirely of students who adopted generative AI no more than Öve months. Six months after adoption, no AI student spends more than 65 minutes completing their homework (see Figure A5). This is consistent with the gradual process of learning how to use AI tools. It also suggests that AI crowds out the highest level of e§ort."
"Interestingly, in the range of 50-65 minutes, the median and the interquartile range
of exam scores of AI and non-AI students are similar. This implies that, in the range
where AI students and non-AI students have overlapping homework times, students
who spend the same amount of time completing homework on average receive similar
exam scores."
"This pattern shows that students who spend the same amount of time on homework
learn similarly, with or without generative AI. In other words, generative AI reduces
time spent learning for the majority of AI students but not learning efficiency for those who spend the same time studying as the non-AI students."
well most university exams are designed to measure how much you study. so we didn't really need a study to tell us, "Exams continue to measure what they are designed to measure."
they're not designed to measure general aptitude, or function as admissions criteria, or screen for job applications, or any other numerous things they are used for.
there can be many questions of pedagogy. one of them is, what do our exams measure and how do we use them? professors who say, "My exam is designed to measure who studies, not be used for all these other purposes that they are actually used for" - I don't buy it. It's the same as late night comedians saying they are not responsible for solutions, even when spending 90% of their air time making political jokes.
THIS is the pedagogical issue, that pedagogy has NEVER caught up with the scope of responsibilities. This is acute in STEM - I mean, the humanities departments are generally pretty well run, all things considered, in this regard. Generative AI is accelerating that pre-existing crisis.
at least in my experience in university - i didn't really ask this question, since it is obvious to me, but some students have asked it during lecture, or some instructors have volunteered the answer ahead of time - if you ask how to perform better on the exam, usually the instructors say, "here's what you should study." they never say, "know more." the thing i am talking about is consistent with the paper. really, your takeaway should be, exams can't see how much you know!
I would usually say something along the lines of “everything we covered is on the table” or “everything we covered since the last exam is on the table” depending on the nature of the test. That’s the same message as “know more” but I think it sounds politer.
The fact that exam scores are correlated with how much you study is not the same as exams only reflect how much you study. Two students who study the same amount could have very different exam scores. The reason that there still is a strong correlation between exam score and time of study is because if all other things being equal, students who studies more have higher exam scores.
i'm not saying they reflect how much you study. they reflect a lot of things, including that. but you ask the people who write the tests, they're going to say, how much you know or how much you study, but nonetheless, they are limited. i agree with you. that's part of my point.
let's imagine a different study. we instead compare AI-users and non-users on a Wechsler (IQ-adjacent) test.
overall, it would be surprising if AI usage impacted your Wechsler scores. someone has done this study and the impact is quite quite small. BUT. do we care? We don't use Wechsler scores for admissions, we don't use them for jobs, we don't use them for... are you getting it now? A Wechsler family test is measuring something real, just like a university exam measures something. But what do we USE them for? Wechsler and a typical university exam are, in some senses, EQUALLY vague in terms of their fitness for purpose for answering a question like, "should we hire this guy?"
Like there is an association between IQ and earnings but it is actually surprisingly small! There is an association with math education and earnings and it is also surprisingly small. And consider how many people get by just fine without using a single piece of math education once they have finished school - like what if maximizing your earnings isn't all that it is about? Are you getting it now?
The issue isn't the AI usage. I can find tests that are immune to AI usage. The issue is using tests for things that they are not designed for. We pick and choose, for some subtle but nonetheless pervasive cultural reasons, which tests we use for which purpose, and very frequently, not because they are calibrated for the chosen purpose. This is coming from someone who scores very well on all these tests, and have kids, so I have a very strong incentive to buy into the status quo, and I'm telling you: academic testing has been fucked up for a long, long time.
You're right that academic exams also measure something along the lines of instruction following / obedience / willingness to jump over hoops for no good reason etc. and that's often a good signal for most kinds of jobs.
I just started teaching undergrad CS courses after ~20 years of various non-academic jobs and it took me about two semesters to realize that almost nothing matters except how I assess students.
Two weeks of ADHD-fueled research later, I concluded that academia is actively resistant to implementing assessment reform because it would expose the utter pointlessness of most of what happens in university classrooms.
The reality is that we have no idea what most university exams measure because they are ad hoc, written by amateurs (yes, most professors are untrained in pedagogical methods) with zero psychometric validity analysis.
> almost nothing matters except how I assess students
This is a reasonable opinion after two semesters.
IMO, with more experience you should have modified your stance.
If all classes were pointless, students would leave at the same point they entered. Since we observe that is not the case, something is happening in class. Do more of that.
The explicitly stated goal of most courses is mastery of a well-defined set of domain-specific knowledge and skills. The only way to objectively determine if the course achieved that goal for a given student is comprehensive assessment. Bad assessment design, much like bad experiment design in science, is worse than useless—it actively misleads and confuses.
A well-designed, repeatable, reliable assessment is a prerequisite before one can even consider the effects of particular pedagogical methods inside or outside of the classroom itself.
Education is a complex topic. I don't claim to understand it, nor do I think we can sort this out in a hacker news thread. What I reject is the simplistic claims like "exams don't mean anything". There are certainly exams that are badly designed, but there are also exams that are well designed. A well designed exam can look very badly to different people, based on what they know and where they come from. It's a bad idea to think exam scores as the single metric of education quality, it is equally bad to reject them completely, because chances are any alternative measurement people come up with are going to be worse.
I think this deviates from the original topic. The article's intent is to argue that AI helps with learning itself, while you question whether this sample can serve as a reference. But what if the target of this sample is a group of serious college students? The article questions AI's enhancement of learning ability, not whether that exam has a real purpose.
I never studied in university and yet I acheived good exam scores. If you understand a topic and ave a reasonable memory and ability to apply my our understanding not much studying is required in my experience. If you don't understand the big picture then you got to laboriously keep track of and manipulate a bunch of disparate pieces.
Well you must be the top 1% of the top 1% of students (although somehow your grammar sucks ass?).
I didn’t study in school, but university definitely required it. I was able to pass some classes without studying, but in those cases I scored in the 60-80 range, not 90+. Admittedly all my peers in uni were way brighter than me, so maybe I’m a bad example.
In any case, your advice is not applicable in any way. “Don’t study, just understand the topic” is not a strategy to master anything. Sure, if you’re so smart that you don’t need to study, then don’t. Most people aren’t like that, but are still perfectly capable of acquiring the required knowledge with some extra work in the form of studying. If you’re so bright, you surely must understand that.
I’m sure you can detect the snark in my comment, because you’re so clever, but I pointed it out just in case anyway.
It would be good to see the effect of access to AI during preparation on those who previously achieved top 10% points in exams of similar topics before. I suspect they would benefit further.
My apologies for coming off as over-enthusiastic, I am currently obsessed with this study. Here is another quote:
"The negative learning effects are larger for students with higher initial achievement. The differences in the estimated full (6-10 month average) effects are substantial, with a 50% gap between the most negative effect (-24 percent) for the highest tercile and the least negative (-16 percent) for the lowest tercile. "
Not top 10% as you asked, but the closest to what you asked. My working hypothesis is that top performance is highly correlated with willingness to work hard, and AI decreases the motivation to work hard.
Interesting. Top academic performance is mostly correlated with conscientiousness (willingness to work hard and keeping track of things) and intelligence. And I'd add motivation and interest to that too.
I think if you take a physics class where the student is intelligent and intrinsically motivated through their own interest (I admit this is rare) then AI probably helps.
I think if they are intelligent, intrinsically motivated, and willing to pursue knowledge beyond what the class requires, it probably helps.
That last part is key. Intrinsic motivation doesn't mean you pursue it outside normal bounds. My kid loves soccer, its her second favorite thing in the world, she has an absurdly high tolerance for physical discomfort while playing, but she doesn't play it at home. There's other things she's rather do, such as play with her toys.
When you move the bar to something even less interesting to most kids like science, you're going to have a pretty huge falloff. You're basically selecting for kids who choose to do it in their spare time. I know a lot of smart kids (I run a boyscout troop, my wife a girlscout troop, both with lots of high achievers), and none of them do this.
I think a substantial minority of students like subjects beyond what the class requires. They go to extracurriculars to learn more interesting math and science, or are history buffs who read about it on their own time etc. These are the people who as adults move things forward and solve novel challenges so it is important to equip them well.
Depends who's using it. Like many tools the force multiplier depends on the operator.
I'm confident it's an amplifier for people who know how learning works and already do a lot of it, successfully. However the level of "learning fluency" I'm talking about isn't reached for many until late college or grad school, and sometimes not at all. So I'm not surprised by the quoted results for 12-18 year olds.
And people who want to learn. Most teenagers lack agency in their studies. They aren't in high school because they love it but because they have no choice.
> Sometimes things are just common sense pure and simple.
The discussion is about "AI", so common sense is out the window. These people's professional reputations depend on addict-level "AI" usage remaining socially acceptable.
It's a fair question. In theory you could do an experiment where the subjects were grad students or professors, or top performing college students. Give them some fixed amount of time to understand some new subject on which they'll be tested, only 1 group has access to an LLM with appropriate context for the learning task, etc. That's just one idea...
This experimental setup would only tell you whether this demographic (grad students or professors, or top performing college students) benefits from access to LLMs for acquiring a new knowledge or skill.
It would not prove that "the results depend on the operator". To prove this (and figure out the traits that make a proficient operator) you would either need a massive dataset to which you'd apply some machine learning to figure out the correlations, or at least you'd need a hypothesis on the traits you want to test.
Do left-handed people perform better with LLMs? Analytical thinkers? Dyslexic people?
It's not enough to just claim "some individuals will perform better with these tools" without any notion of who does, and whether it's possible to become one of these people, and what is the expected gain in this group.
Otherwise, sure, we could sell unsecured chainsaws as a tool for making ice sculptures and observe that "some people" are indeed more proficient at not getting their face cut off ; but if the tool is being marketed to schools, such a vague statement is not helpful in making a case for it.
Yes, I'm using "high-performing college students" or "phd students" or whatever as a proxy for "people skilled at learning". It's not perfect but I think it'd be good enough. You could do lots of refinements on the idea. You could try to do some kind of "pre-test" that more directly tested "meta-learning skills".
My only point was I think it's possible to do. I personally think it's pretty clear. And there's nothing special about AI. In rural places, you could replace it with "access to books" or "access to a good tutor" and so on.
I also think you'd see the same effect with "motivation" (if you could test it), with performance on standardized tests, and with grades. AI will boost the better (by these metrics) students more.
My understanding of this study is that it disproves your assumption: "The negative learning effects are larger for students with higher initial achievement."
It seems that the students who had the most skill and motivation from the start, have the most to lose.
Personally in my own work it's pretty obvious how it's an amplifier. You waste far less time trying to find an answer to something that confuses you.
You might say "it's good to learn research skills" and that's true to an extent, but tutors have always made people better students. And AI is a tutor you can message at any time, day or night, for free.
the difference in the vast majority of cases is that people go to a tutor with an intentional stance of cultivating a particular kind of practice, not merely to get an answer to a question. It's not technically impossible to do this with a chatbot but far less likely given that, unlike an even half decent tutor, a chatbot will never cultivate that attitude in you. The elimination of that friction is exactly why people talk to bots.
The good thing about a tutor is that he or she isn't always available and knows they won't be in the future, so they instill good habits and independence in you.
> a chatbot will never cultivate that attitude in you
Hence the whole "AI is basically an amplifier of bad and good" argument made earlier. The ones who do this because they want to understand, don't need to cultivate this at all, it naturally happens with chatbots. They don't just ask for the answer to a question, but then dig into why it's like that and what not. But the ones that don't care, now have to do even less to get the fast answer without understanding.
I wouldn’t be surprised if you did and still had the same issue, but if you relied on the training data recall alone, you definitely shortchanged yourself.
I’ve had decent results with tasking a model to run pre-research and summarization as a checklist, then have a second instance of the model(s) review and then develop my learning plan learn, versus the times I just asked Claude of ChatGPT to explain something to me “from memory.”
The knowledge AI has is vast. Communicating it to you is slow and narrow baud. The chat interface itself as a medium is lacking and will need to be replaced without another medium.
"AI is a tutor you can message at any time, day or night, for free"
which makes it not a tutor. if it is true that tutors have always made people better students, then those tutors are definitely imposing some limits on how many answers they give you and requiring you to do some thinking. I think you could have premised your same argument by, "copying a smart kid's answers has always made people better students...."
Nothing stopping kids from asking AI to give you responses like this, it is more than capable. There is always going to be the temptation to take short cuts though.
That's why you see the split in outcomes. The fraction of kids who value self improvement are going to get smarter, and the ones who just want to slide by will fall behind.
Finding an answer isn't always an objective, though. I agree it often has been too much in baseline schooling.
First, there's a certain amount of baseline knowledge we'd like students to possess. Without a certain prerequisite amount of underlying information committed to memory, it gets far more difficult to achieve fluency in a topic.
But more than that, there's other skills we're trying to build: frustration tolerance, processing contradictory information, disciplined problem solving. You only really develop these skills through productive struggle. If you find a way to shortcut the productive struggle, students truggle.
> but tutors have always made people better students.
Sure. Bloom showed us that students taught with a combination of tutorial and mastery methods, one-on-one, outperform students in a normal classroom by roughly 2 sigma.
The paradox has always been-- why hasn't technology unlocked these gains for students in normal classrooms? If we could boost everyone's performance by this amount, it would be huge for society-- but society can't afford to teach everyone with tutorial methods.
Since the 1970s, we've invested in edtech towards trying to make this happen, but most of it has actually had net-negative effects as best as we can measure. AI, so far, looks to be much worse.
I think part of the answer is that a big part of what makes a conventional classroom work are social pressures. So far, it looks like AI (and edtech in general) does more to dismantle conventional pedagogy and to break down the social fabric of the classroom, than it has improved differentiation or unlocked this tutorial effect more broadly.
Social stigma against just juices people to stick to socially desirable answers; no doubt a whole bunch who self reported as non-AI users actually used AI
Sounds like the opposite of the social stigma in tech companies, where most people are under pressure to self-report as AI users when they are actually just using normal methods to get the same result (and spending the time saved however they like) (nothing against genAI for making work take more time, it's still good for business as long as the extra work can be moved around)
I wondered the same. ff and fi are common ligature letter pairs, maybe the original is in an encoding where those are represented with separate characters, which then correspond to § and Ö in whatever encoding we find here?
It was copied from a pdf, maybe LaTeX generated. All the ligatures are wrong -- not sure where the problem lies, the pdf itself, pdf reader, or the clipboard on Linux.
PDF is a render-only format with optional hidden metadata for semantics.
The PDF file they created knows how to paint the ligatures they used, like "fi" and "ff", but doesn't contain the `/ToUnicode` metadata for what those symbols meant.
The generated PDF happened to put the "fi" ligature at an index that is normally used "Ö", and didn't provide more information.
The dangerous thing about amplifying is that bad people are often more willing to amplify their activities, because they don't care about the negative effects. We are seeing this now as AI companies (and large companies of all kinds) rush to secure whatever advantages they can, regardless of the negative externalities. Meanwhile people who actually care about doing the right thing get trampled.
We need to shift the incentives by adding ruinous penalties for things that are currently quite commonplace if they are done by large players. Some dude training his own AI on his own computer can scrape and train. The fine for OpenAI or Meta using a single copyrighted book without permission should be in the tens or hundreds of millions.
What we're seeing currently in our society is a "loophole inversion" where the rules have an effect mainly via their loopholes. The most profitable activity is to find loopholes and exploit them as frenetically as possible to gain as much advantage as you can before the loophole is closed, or get people hooked on the loophole so it's retroactively legalized. Entities that are big enough to do this are big enough because they have lots of money behind them. Entities doing the same kinds of things without lots of money are not really doing much harm. So the best approach is to adopt a "sliding scale" in which even tiny violations by wealthy actors result in penalties enormously greater than fairly large violations by small players.
> they don't care about the negative effects [...] rush to secure whatever advantages they can, regardless of the negative externalities
I think we don't yet know the long term view - what is harmful or damaging in the long run. Too early to tell and pass judgements. Every new technology from writing to internet had its detractors and they all pointed out negative externalities, as they seemed to appear at the moment.
It's a familiar story. If you copy/paste Wikipedia and turn it in, you learn nothing. If you skim Wikipedia, hit up the references, the consult other sources, then synthesize your own thought, you probably get farther faster than you would without it.
We could probably cook up thousands of examples of the same problem (YouTube DIY tutorials, GPS navigation, etc.)
This is kind of damning, isn't it? "Similar or slightly higher" for spending the _same time_ means it's not, in fact, helping. At the same time as being extremely damaging to a significant number of students who, of course, use the AI to cheat. Because everything about it makes cheating easy.
Yes, it strongly suggests that AI as a learning tool is at best pretty much useless, but on average its strongly detrimental to most people exposed to it as it makes it too easy to cheat
Intelligence and perseverance are two different traits. Smart + hard working kids will be fine. The problem is smart and lazy kids will find the easiest path, which in a world of AI leads to little actual learning. Maybe it was ever thus, but I fear the currently dwindling endangered book + teacher approach was better at getting slack asses to learn and eventually gain skills and knowledge for themselves.
That’s why I said it will be used more for bad than good. Maybe I should have said, “it will be used for far more bad than good for the purpose of human intellectual flourishing”.
It can be used for good for this purpose. You can use it to find primary source information. You can use it to generate challenges for you. You can use it to critique your work when there’s nobody else available. Etc etc.
What AI definitely is as an amplifier (in my interpretation of the article) is an amplifier of "laziness": students spending less time studying, getting by with the homework with the less possible effort, and finally achieving worse results. And the longer one uses AI for, the "lazier" they get (the more they rely on it for homework, and study less).
If it is an amplifier of "good" vs "bad", I don't know, and I do not know what that means exactly. I do not think some students are just "bad" or "lazy" by character and that explains all. I think that their environment has a big role in shaping their actions. I don't think that AI cannot be used beneficially (and the articles talks about some attempts that maybe worked well), but it requires careful considerations, guidance and intentionality from educational institutions themselves. The same goes with all kinds of technology, and AI is nothing new in that sense, but often new technologies are introduced in education without careful considerations or evidence based policies. Which is why imo articles like this are very important.
I know this study is focused in China but one thing I'd like to understand is the nuance in what kind of student is likely to always reach for ai for homework help as I think (especially in the US, can't speak for other countries) the varying powers that be that can determine the quality and type of education you can receive (does your country have means to buy textbooks per student or shared, do you have funds to give students ipads to take home or no, what sets the bar on how far curriculums can go, are teacher and faculty pay and incentives simply tied to student pass rates, etc.) and those do more in shaping what "use AI responsibly" will look like and why it's so different.
Using the forklift as a spotter and to assist in loading weights increased gains. Then again, a human can do all those things, and provide real human connection.
If you structure learning in such a way that makes learning just a means to some end, and overindex on that end being the ultimate goal, that's what you get.
This is a pedagogical problem that AI merely exposed. Educators need to figure out How to make students choose the scenic route instead of having them optimize for the most efficient completion of a task.
All AI did here is exposed an old problem in education. Kids are expected to get everything perfectly for the first time but a lot of them don't so the class gets easier next year to keep up pass rates.
We need to restructure the system to treat failure as a signal instead of a disaster. Grades should come from hard randomized exams with unlimited retakes so one bad day won't hurt you. Homework should be optional material for self study, evaluated by teachers if you choose to do it but never forced.
Hold back students for individual classes instead of a whole grade so failing one can't ruin your social life and teachers are more willing to do it. F students will realize they have to study, start actually learning and then pass on the second time. No big deal. It happened to my friends in college, no reason they can't do it in high schools.
Discipline is a skill and it's one you have to get from experience. If you try and force kids to study when they don't want to "for their own good" you're not actually helping them. Everyone needs to find their own path. Let people fail.
> If you try and force kids to study when they don't want to "for their own good" you're not actually helping them. Everyone needs to find their own path. Let people fail.
this rhetoric is pretending to be an alternative to coercion. IMO the ideas you are talking about are well trodden and are still coercion nonetheless.
I could be mistaken but my interpretation is that "studying for your own good" is being contrasted with "studying so you don't fail". If you actually fail students, they'll have a second motivation beyond trusting some authority figure's advice. Namely consequences.
You are missing the point. Getting a certificate for all of the programs you passed and still graduating could completely change the course of a person’s life. Community college has certificates and associates degrees to let people start working when they reach a practical limit in their general education.
> Homework should be optional material for self study
At Caltech, homework was assigned but had no bearing on your grade. The grades were based on the midterm and final exams.
But not mastering the homework usually resulted in flunking the exams. There were "retch" sessions after each homework assignment that was staffed by a grad student, and the purpose was to help the students understand the homework problems. I knew only one person (Hal Finney) who was so smart he didn't need to do the homework.
I learned the hard way that the path to success was:
1. never miss a lecture, no matter what
2. take notes by hand during lecture
3. do the homework on time, and make sure you understand every problem. Take advantage of the retch sessions.
As a student of a top-tier French Master's degree, I consulted with a teacher to deal with exhaustion and to ask for a class rescheduling for my case. Explaining my situation, the teacher looks at me and interjected:
—Waitwaitwait. You... you went to all lectures!?
And he was right. Rather than following the curriculum, I should have developed my taste for various engineering topics and only used the classes as entertainment.
I think the first semester, or at least half of that, you should go to every lecture until you develop taste for what's useful. By the time you do your master's you should have a good sense for what classes are serious and have useful lectures and where you can just cram last minute because it's a bullshit class and where you're better off studying from a textbook.
When I was there, a long time ago, exams were timed and were usually open book open note. Blue books were filled in. You were trusted to adhere by those rules, and most students did their exams in their dorm rooms.
The evidence that the students honored the rules was some exams resulted in a 50% failure rate.
As for me, I went there because I wanted to learn the material. I did not care about getting a diploma. (Mine is in the basement somewhere.) I did not take any "easy A" classes, because I wanted a return on my time and tuition investment. (Though, easy A classes were hard to find at Caltech.) I wasn't even going to attend graduation, but my parents showed up and I attended to please them.
The classes, year by year, were dependent on mastering the previous year's classes. So if you cheat with AI, you're digging yourself into a bigger and bigger hole. Caltech rewires your brain. If you don't learn the stuff, you're going to be one of those EEs who carries around a card with V=A*R, V/A=R, V/R=A printed on it.
That only works with competent lecturers. I can speak for my experience at a more mid university, where that would apply to about two thirds of the classes. For the remaining third, going to the lectures felt genuinely counterproductive and you could actually feel yourself losing braincells listening to the confused nonsense or classes held in English for Erasmus students by someone who could barely speak it coherently. It was just a complete waste of already little available time.
So the endgame was figuring out what the tests in previous years looked like (cause it was likely gonna be a copy paste affair), do a targeted study run for those exercises and 9/10 you would pass.
Naval Nuclear Power School had (maybe still does) this model 20 years ago as well. Pass rate for my class cohort was 28% over the entire 2 year pipeline.
We didn't call them retch sessions, and they were taught by the instructors though. We also were encouraged to peer tutor and since we were all restricted to one building the homework was always group work allowed.
Also had badges to track time spent in the building for required study hours, though some people gave up and just slept at their desks when they started sliding down the grade scale and the hours racked up.
Generally I think I did 30 hours of studying/homework (went up and down depending on what was being taught, but was around that) a week (for 12-15 hours of actual lecturing), with some of my friends putting in 50% more. Generally the only day we weren't there was Saturdays. Most of the day Sunday was usually spent in class preparing for the next week.
I think only a third or so of my class wound up graduating. Caltech doesn't flunk people out. What happens is students will transfer to easier schools, or drop out, or decide driving a truck is more to their liking.
Likewise at Oxford - only the final exams counted (though you had to pass first year exams to continue to the second year).
But you had tutorials each week, and if your tutors thought you weren't doing enough work they could set you exams mid-course called 'penal collections' and if you failed them you could be thrown out. They were rare but definitely not unknown.
It's all cute but naively glances over what this all boils to - competition.
Education system, contrary to popular belief/name, isn't tailored to educate but to select winners and losers which then will be picked on the job market.
It does fail at it ultimately because interpersonal relationships matter much more than pure skills in practice.
That's why it seems absurd when you think about it as an institution that aims to educate. That's because that isn't the real purpose of it. The purpose is to stratify and classify early.
> compliance, endurance of boredom, and social maneuvering
Compliance and endurance of boredom I can somewhat agree with (thought not to a great extent), but social manoeuvring? As long as a student completes their classwork and homework, and does well in their exams (none of which mandate any social interaction apart from team projects), they easily pass through the school system. In fact, I used to hear about how the school system disproportionately benefited studious, shut-in students over street-wise, socially-savvy ones.
Yeah but if you get bullied due to lack of social skills then you won’t have mental energy nor drive for passing exams or any learning.
Socially savvy students on the other hand will get plenty of help from teachers and other students even if they are not so good themselves.
This is why the so called “intelligence” where I will define it as skill of acquiring skills right now, is not so important for success. You can be very good at learning but if your social aptitude and charisma sucks then you will just end up as depressed, miserable and poor and probably alone too.
It’s honestly very important and way more important if you have a kid, to care about its social development and how you can help so your kid gains social confidence and never loses it at crucial moments
The study was done in China, where making the class easier to improve pass rates isn't really a thing, as the Gaokao operates more like a stack ranking where it doesn't matter much how well you did in an absolute sense, only that not too many others who did better than you are competing for the same spot. Unlimited retakes are possible in theory, except each costs you a year of your life and except for some extreme cases of repeat test-takers, most people are going to give up after just one or two bad results. Homework is definitely not optional, but going home from school is. I don't see how holding back for individual classes is supposed to work considering scheduling conflicts.
Unlimited retakes would be an enormous amount of work for professors/TAs/teachers.
Optional homework is often a disaster. At best, students would do it right before an exam and the goal of education is not to just pass exams. They’d probably still get a lower score than if they did the homework when they were supposed to.
What I think is better is to have a due date, but just make the maximum 10% each day it is late. So after 2 days, the highest score you could receive would be 80%.
I liked that system because it gave some flexibility with deadlines while still encouraging you to turn things in on time.
Late work policies like this can be a logistical nightmare at scale. Rather than play the penalty-over-time game, have hard deadlines that are inflexible. Students don't have to engage in mental gymnastics with their scores and instructors don't need to track this stuff.
My view is this: a student can turn in an incomplete assignment. Work they completed get evaluated and graded. Anything not completed gets zero credit. Homework should be an investment in effort over time anyway. Unfortunately, procrastination is a deeply rooted problem that usually kills this.
What you described about exams is like how I approach most certification exams: go through a test bank of questions until I get 80% then take the real test.
You put way too much faith in kids' desire to learn and their ability to make responsible choices.
> Homework should be optional material for self study, evaluated by teachers if you choose to do it but never forced.
My wife is a teacher and her school does this. The result is that nobody does homework. The kids who need the extra practice don't get it and they fall into a spiral of failure and apathy. This is especially bad for subjects like math that build on themselves.
IMO the better solution is to require and grade shorter homework and provide students with optional, supplementary assignments that can be used to make up for missed credit on homework for the same material. That way students who grasp the material quickly can demonstrate and move on while others who need practice are naturally encouraged to get it without being permanently punished for struggling initially.
Homework is no longer useful in the era of AI. Options are: treat kids like they are able to make responsible choices, and accept that much more of them will fail; or, keep the charade of grading AI-"assisted" homework and push kids farther along the track, even though they definitely don't know enough.
I much prefer the first.
School shouldn't be impossible, but you shouldn't have a charade of schooling.
It's not necessarily useless. If you make assignmentd short, provide some time in school to work on it, and do not allow students to use devices with access to general-purpose "AI", then there is a good chance most students will do the work like they're supposed to. Some will still cheat, but it's foolish to reorganize everything around the few who stubbornly refuse to learn.
It's "homework" in the sense that it is not bound to the class. It is not due during class and if you can't finish it in class, you'll have to complete it out of class.
And I mean setting aside some time during the class itself, not a separate "study hall" period. Obviously class time is precious, so I don't expect there to always be enough in-class time to finish assignments. But even having a little in-class time for students to get started - and when the teacher is available for help those in need - would go a long way towards encouraging students to do the work themselves and not cheat.
And of course part of my strategy is to make "homework" shorter (5-15 min). That should also reduce the temptation to cheat and increase the likelihood students can even complete them in class.
> If you try and force kids to study when they don't want to "for their own good" you're not actually helping them. Everyone needs to find their own path. Let people fail.
This simply does not work for most, as pupils are too immature. You put sunscreen on children, keep them away from the street and brush their teeth. Having everyone re-learn the same stupid lesson is wasteful, it's better to institutionalize this knowledge in the form of mandatory participation.
I used to skip homework in high school because it was boring and cut into my personal life outside of school (including my job) but I would always do very well on tests.
Then I stopped caring about tests too.
I did the same thing through college. The only reason they passed me and I got a degree is that I built the school’s website and I built personal ecommerce sites for the head of art and his wife to sell their paintings.
I haven’t done shit since like 7th grade.
Worked at Facebook, Apple, Microsoft, same behavior there - did basically nothing for them while making thousands off my games on App Store.
When you get out into the real world, what will matter is how effectively you use AI. When you are done with school, you can take the "exam" using AI. The problem is that teaching is trying to teach skills that are no longer relevant and is always behind what the latest going on in the industry. Every time without fail you got interns, who after two years at stanford would learn more in the 3 months on a google internship than in those two years at stanford. They learn useless shit.
My own experience is that college is fun. You can spend the time wisely, but school stuff, is not what makes you money.
Make student loans dischargeable in bankruptcy and make colleges under write them. The problem will get solved quickly.
Way before AI, the problem was very similar - universities do not teach practically useful stuff. Its been a permanent complaint about the education system, really, at least for the last 50 years.
AI just gave the students a way to dodge the slog.
But university was never intended to teach the bleeding edge. That would really be impossible in practice. Pre-phd, it is supposed to teach ways to efficiently attack a problem. you can take a bunch of "play courses", and succeeding at any of those requires pretty much only that one skill.
Nowadays, the challenge they face, is to keep teaching "problem attack methods" in a way that can't be trivialized by AI.
Though fundamentally, if you go to university, and evade learning the one thing you can learn there - thats your loss.
I am waiting for AI Viva Voce (“AVV”). I am really surprised we aren’t hearing more about this idea?
Try it for yourself by making a prompt like this (adapt as needed):
Pretend I am an undergraduate student of Computer Science. I am learning about early microprocessors from the 1970s. I want you to ask me an examination question as if you were doing a viva voce exam with me, to test my understanding of concepts. I want you to receive my answer and then based on what I said I want you to ask me a more specific question to probe my understanding. Repeat this interaction up to 5 times. Then grade my understanding so far, by giving me a pass, merit, credit, or distinction. Can you explain how you arrive at the grade based on my answers and your expectation of undergraduate knowledge of microprocessor theory?
I've tried stuff like this, but the problem is that you don't know if it's answers are correct, and more importantly, you don't know if its questions are on base or not. Plus its too easy to go off on tangents, especially when you ask it questions to clarify.
You can get some more success by writing down a framework beforehand, but openended dialog is still not a good way to learn with AI, from my experience.
Good points.
I’ve tried this a few times and I’ve been impressed by the dialogue. Given this was a very simple prompt, I am convinced a more precise version could be developed, including a rubric, a library of course content, starter questions and other guidance to the AI. I haven’t seen anything like this and schools / universities seem to be “struggling” with AI, which has me wondering why not embrace LLMs for learning and assessment, like this?
I mean, everyone I know has been using socratic dialogue for months to aid understanding, this seems like a variation of that. The issue is that if the answer is too easy to obtain it's hard to have the discipline not to cheat.
Honestly I wouldn't demonize AI in education. When we were students we were forbidden from using calculators, then the internet and now it's become the norm. It's the same with AI, I think. AI has already become a part of our lives. The important thing is just teaching children how to use it correctly.
Unlike AI, calculator use has been studied and shown to be useful for math education. Our understanding of these things evolved over time, however the results of this study are concerning.
Glad to have scientific results on this, though in my view you could get this from first principles. Homework is onerous but it forces you to learn the material and get it into a configuration that works in your head, which you then validate with the exam.
If others studies tend toward this result, a question comes to my mind: it is a problem with AI or our educational system? or both? I would like to have some comments...
I know someone who pasted all their six sigma certification questions directly into an AI tool and they got a 98% on their exam. Seems like it would help their exam score too if they were allowed to use it on both the homework and exams /s
AI itself is not the problem imo. The core issue is basically outsourcing your entire brain to the LLM and never trying to solve a problem yourself
When I was in school there were multiple instances where I would be stuck on a problem for nearly an hr but I always learnt something from it. They key I think is to accurately identify when to and when not to use AI
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[ 1.6 ms ] story [ 18.0 ms ] threadStudy design: "David Stromberg of Stockholm University and Victor Lei and Wu Yanhui of the University of Hong Kong set out to fill the gap. They tracked 27,000 pupils aged 12-18 in China, where ai adoption has been fast. Around 80% reported using models such as Doubao and DeepSeek; the other 20% formed the control group."
As with most training the journey is the point, not the destination.
That said, I think smart use of AI could help. It could explain concepts in a way that might help you understand better, it could probe your knowledge in a more dynamic way by tailoring questions, and so on. This requires the AI be restrained by some harness, not free to write down the answers for you.
I would like an AI system which adds as little of its interpretation as possible until I ask, for which the main behavior is bringing up exactly the part of the primary reference which has the information I want.
(I think this is probably slightly heterodox to the degree I prefer this though.)
How would this magic harness look like and why would anyone use it?
Put that in your agents.md.
I meant: what's going to stop the average lazy student from ignoring whatever harness the university recommends and instead use an unrestricted LLM, thus learning nothing?
Nothing until they start failing exams and maybe seeing the error of their ways. My suggestions wasn't for you, it was for the smart student who wants to use AI to enhance their learning but not have it do all the work.
But cheating isn't new. People have been cheating in school for centuries. It's easier now, but the consequences were always the same. At some point the chickens come home to roost and you pay the piper.
My concern is that with LLMs and above average bullshitting abilities, the chickens might never come home to roost.
People say that all the time, but does anyone really think a lack of good explanations for things is a limiting factor in 2026? Or even 2010?
Kids won't be using LLM tooling as a personal tutor following some sort of Socratic method, they'll ask it to solve their home/coursework for them and blindly copy/paste the answer. Hell, they'll just manually copy down what's on their screen if copy/pasting isn't possible for whatever reason.
Obviously exceptions exist, but I'd wager from being an ex-kid myself the type of kid who would genuinely use these tools for actual proper self-tutoring would be an extreme rarity.
AI gives you a way to get the same help without asking another human. Say of that what you will, but not everyone was comfortable asking other humans for help even back then.
The act of building the mental muscle is what creates education.
I believe AI is basically an amplifier of bad and good. I’m cynical about the world and assume it will be used more for bad than good, but I don’t doubt some of the best people in every field will be using AI to amplify their work in good ways.
It's good to think about second order impacts but this is not useful.
Just one 20 GW AI data center which is being built with gas powered turbine generator power plant, will be the largest fossil fuel power plant in the world... How exactly is that the same as one coal mine
Raising the noise floor like this only makes it that much harder to find "Smart" people, which we were already doing terrible at.
I use Claude every single day, but this is such a bad tradeoff. Maybe it will help me standup a quick fix when that is needed. Maybe it can help me dig through documentation to find relevant bits and figure out the unstated assumptions underlying it. Maybe it helps me generate test cases.
Meanwhile, my day to day life is now noise. All social media is noise. All content is noise. Slop pours onto me from all directions. Writing more test cases isn't helping me.
Am I smart? Am I dumb? I don't care, right now I'm deafened
I'm using Claude at work myself and am impressed with the product, but notice that this is the only reason I need to use it at all. Our product pages were shit to begin with, now they're AI-generated and somehow even worse. Our procedures are incomprehensible spaghetti with enough arbitrary context switching to give a sadistic Soviet municipal administrator an erection at the thought of watching anyone try to actually follow them.
Use AI to create inefficiencies, then use AI to bypass them. Those who can't do the latter will struggle to survive.
Clarification: to value “smart” people, which we were already doing terrible at.
It does give us a new heuristic, though: people who are willing to completely cut generative AI out of their lives (cold-turkey, if you ever started using it) are a much smaller group of, predominantly thoughtful, people. You do have to give up Claude to be part of this group, but from what you say, that's no great loss, and no longer being deafened is worth it.
This has considerable advantages over conventional elitism, because the barrier-to-entry is negative in almost all cases.
The one exception I've found is assistive tech, where the state-of-the-art is so poor that vibecoded slop is genuinely an improvement over the state-of-the-art, and in many cases the tooling simply isn't available to make your own assistive tech (unless you want to bootstrap an entire networked computing environment, which isn't very helpful when you want to do your online banking and do not, in fact, work at your bank).
But there are not many principled exceptions where you could seriously argue that the trade-off is worth it. Take mathematics, for example, which we often see touted as a "good use-case" of generative AI. The primary advantage of generative AI in mathematics is being able to search though a vast corpus of ivory towers and inconsistent terminology (without proper attribution) to locate and connect ideas that can help solve problems. The deficiency this is addressing is elitism, inadequate communication, and inadequate indexing within academic mathematics. This problem is entirely created by the academic mathematicians, and has been known for nearly a century (per https://en.wikipedia.org/w/index.php?title=Nicolas_Bourbaki&...):
> Bourbaki was founded in response to the effects of the First World War which caused the death of a generation of French mathematicians; as a result, young university instructors were forced to use dated texts. While teaching at the University of Strasbourg, Henri Cartan complained to his colleague André Weil of the inadequacy of available course material, which prompted Weil to propose a meeting with others in Paris to collectively write a modern analysis textbook.
To my knowledge, this is the only organised project to clean up and improve mathematical communication. Everything else (Metamath, Mizar, AFP, Lean) is yet another ivory tower. The Wikipedia article on this topic (https://en.wikipedia.org/wiki/Mathematical_knowledge_managem...) risks deletion as non-notable, that's how little anyone's actually trying. They made their own bed, and generative AI will only provide a brief respite from having to lie in it. (I was surprised how many other "compelling" use-cases evaporated when I applied this razor to them: the sibling comment https://news.ycombinator.com/item?id=49392265 points out one such.)
Vibe-coding assistive tech which doesn't yet exist, as a temporary scaffold to improve the quality-of-life of yourself and others in a social world dominated by non-essential access barriers is, to my knowledge, the only exception to this principle that can be justified. If you treat people who make other excuses, or who don't even bother with excuses, as not worth listening to, you lose little – and doubly-so, if you make your stance clear, so that others know the "cost" of gaining your attention.
... including ultimately stuff needed to make the smart people.
LLMs make significant mistakes frequently and smart people have no way of judging those mistakes outside their domain expertise. They are also sycophantic and great at being an echo chamber which makes people feel smart even if they are not.
So I think the burden of proof is on you to prove that they somehow amplify intelligence, it seems highly unlikely.
Smart people know LLMs confabulate and tell them they’re Absolutely Right! Smart people don’t want to be embarrassed by trusting the hallucination machine and revealing their gullibility to others.
All of those sound like flaws and defects of dumb people?
Great summary of the flaws with LLM "research"/"reasoning". It's always trying to con you, and I question the literacy and intelligence of the people who can't see this.
In software particularly, what AI does do is give me back my time from the drudge work that I don't care about. Keeping my build system configured and my tests up to date and my documentation synchronized is a good use of AI because I mostly don't care about how crummy the result is as long as it "works".
Suppose it's good to learn how elastic the brain is, in both directions, at a young age where it doesn't matter.
Doesn't it matter the most at a young age?
The "slightly higher" performance is based on statistically insignificant samples (between 4 and 20 students, depending on the context, out of the total population of 26,000): https://bsky.app/profile/benjaminjriley.bsky.social/post/3mt...
Citation needed? I have no clue where you got this from. I hadn't even heard of it as a conjecture, let alone as something anyone accepted, let alone as gene rally accepted...
1. They don't do any homework.
2. All the in-class time is split between the teacher babysitting and playing social worker to problem students, and lecturing, with little to no opportunity to actually practice what they've learned?
I understand that some students don't have home environments that are conductive to doing homework well. I understand that some students are enrolled in five hours a day of extracurricular university-application-padding activities. I understand that some students have incredibly poor screen discipline and impulse control.
But I don't understand that anyone has magically figured out how to teach complicated things to students, and have it stick without them spending a lot of time practicing what they are learning.
As anyone who has tried to do something hard knows, the first step to being good at something is to spend a lot of time being pretty shit at it.
I'm pretty sure there is a way to fine-tune this [0] to auto-complete away any of your hesitations or mistakes :)
[0] https://news.ycombinator.com/item?id=49373456
Art is similar. You can look up skills as necessary to try to make the piece you want. Adult art learners often just start with the type of art they want to make.
In both cases, the finished piece might not be the quality you want, but in neither case are you necessarily doing repetitive stuff to learn (playing scales over and over or sketching the same bits over and over). You can retry a piece or move on - the skills will still carry over.
None of these reflect homework in school. Now, I know I graduated school decades ago, but math homework was repetitive with seemingly no real-world application and absolutely no help if I needed it. I took a math course online some years later and it was much better: Instant feedback if I got the problem wrong and instant help to walk through the problem if I needed it - then a different but similar problem was given for the homework. This was actual practice in ways traditional homework wasn't. Homework in the traditional sense isn't practice - they are all miniature tests that affect your grade.
I didn't have to practice writing - I just did the papers assigned and rushed through them. You can grade papers for other subjects on prose and grammar instead of just doing it for language courses. You don't have to read classics to read better if you just read a variety of things you are interested in. You'll read plenty of boring things for other subjects and get that sort of practice.
With most of this stuff, having actual homework isn't necessary as long as students are given time for practice. Practice is what makes you good at something, not homework, and practice can take many forms.
You can absolutely learn to play some piano by just noodling. Your learning will be much slower, and you'll miss important fundamentals that are present in any piano method.
That's perfectly fine for learning things that you do for enjoyment, or things that don't really matter. It's a lot less fine for learning things that... do.
What I remember being questioned is does it make sense to do those exercises as homework or would they be better in school.
Or on the flip side should school get out early like 11 or noon, like I think the german gymnasium does and have all the exercises as homework.
The US system where children get out of school at 15:30 and still have a bunch of homework seems a little lopsided someplace.
The 3 month break in-between school years is definitely questionable.
I think the answer is a complex one because it intersects with personality and neurodivergence.
Depending on who you are and your family situation any form of homework can be a real challenge. Not because of what you are studying but because of how difficult it is to sit down and do anything you aren't passionate about. Certainly anyone with an executive function disability will have that challenge.
Industrialized mass education has always suffered from a unit economics problem: the labor required to assign individually-tailored problem sets and manually grade them in the volume needed for most students to actually learn the material is prohibitively expensive.
"At the other end of the distribution, AI students who spend more than 65 minutes on their homework receive homework and exam scores similar to those of non-AI students, suggesting that these students do not use generative AI for homework assignments. However, this group consists entirely of students who adopted generative AI no more than Öve months. Six months after adoption, no AI student spends more than 65 minutes completing their homework (see Figure A5). This is consistent with the gradual process of learning how to use AI tools. It also suggests that AI crowds out the highest level of e§ort."
"Interestingly, in the range of 50-65 minutes, the median and the interquartile range of exam scores of AI and non-AI students are similar. This implies that, in the range where AI students and non-AI students have overlapping homework times, students who spend the same amount of time completing homework on average receive similar exam scores."
"This pattern shows that students who spend the same amount of time on homework learn similarly, with or without generative AI. In other words, generative AI reduces time spent learning for the majority of AI students but not learning efficiency for those who spend the same time studying as the non-AI students."
they're not designed to measure general aptitude, or function as admissions criteria, or screen for job applications, or any other numerous things they are used for.
there can be many questions of pedagogy. one of them is, what do our exams measure and how do we use them? professors who say, "My exam is designed to measure who studies, not be used for all these other purposes that they are actually used for" - I don't buy it. It's the same as late night comedians saying they are not responsible for solutions, even when spending 90% of their air time making political jokes.
THIS is the pedagogical issue, that pedagogy has NEVER caught up with the scope of responsibilities. This is acute in STEM - I mean, the humanities departments are generally pretty well run, all things considered, in this regard. Generative AI is accelerating that pre-existing crisis.
Huh? They're designed to measure how much you know. They can't see how much you study, nor would they have reason to be interested.
let's imagine a different study. we instead compare AI-users and non-users on a Wechsler (IQ-adjacent) test.
overall, it would be surprising if AI usage impacted your Wechsler scores. someone has done this study and the impact is quite quite small. BUT. do we care? We don't use Wechsler scores for admissions, we don't use them for jobs, we don't use them for... are you getting it now? A Wechsler family test is measuring something real, just like a university exam measures something. But what do we USE them for? Wechsler and a typical university exam are, in some senses, EQUALLY vague in terms of their fitness for purpose for answering a question like, "should we hire this guy?"
Like there is an association between IQ and earnings but it is actually surprisingly small! There is an association with math education and earnings and it is also surprisingly small. And consider how many people get by just fine without using a single piece of math education once they have finished school - like what if maximizing your earnings isn't all that it is about? Are you getting it now?
The issue isn't the AI usage. I can find tests that are immune to AI usage. The issue is using tests for things that they are not designed for. We pick and choose, for some subtle but nonetheless pervasive cultural reasons, which tests we use for which purpose, and very frequently, not because they are calibrated for the chosen purpose. This is coming from someone who scores very well on all these tests, and have kids, so I have a very strong incentive to buy into the status quo, and I'm telling you: academic testing has been fucked up for a long, long time.
Two weeks of ADHD-fueled research later, I concluded that academia is actively resistant to implementing assessment reform because it would expose the utter pointlessness of most of what happens in university classrooms.
The reality is that we have no idea what most university exams measure because they are ad hoc, written by amateurs (yes, most professors are untrained in pedagogical methods) with zero psychometric validity analysis.
This is a reasonable opinion after two semesters.
IMO, with more experience you should have modified your stance.
If all classes were pointless, students would leave at the same point they entered. Since we observe that is not the case, something is happening in class. Do more of that.
The explicitly stated goal of most courses is mastery of a well-defined set of domain-specific knowledge and skills. The only way to objectively determine if the course achieved that goal for a given student is comprehensive assessment. Bad assessment design, much like bad experiment design in science, is worse than useless—it actively misleads and confuses.
A well-designed, repeatable, reliable assessment is a prerequisite before one can even consider the effects of particular pedagogical methods inside or outside of the classroom itself.
I didn’t study in school, but university definitely required it. I was able to pass some classes without studying, but in those cases I scored in the 60-80 range, not 90+. Admittedly all my peers in uni were way brighter than me, so maybe I’m a bad example.
In any case, your advice is not applicable in any way. “Don’t study, just understand the topic” is not a strategy to master anything. Sure, if you’re so smart that you don’t need to study, then don’t. Most people aren’t like that, but are still perfectly capable of acquiring the required knowledge with some extra work in the form of studying. If you’re so bright, you surely must understand that.
I’m sure you can detect the snark in my comment, because you’re so clever, but I pointed it out just in case anyway.
"The negative learning effects are larger for students with higher initial achievement. The differences in the estimated full (6-10 month average) effects are substantial, with a 50% gap between the most negative effect (-24 percent) for the highest tercile and the least negative (-16 percent) for the lowest tercile. "
Not top 10% as you asked, but the closest to what you asked. My working hypothesis is that top performance is highly correlated with willingness to work hard, and AI decreases the motivation to work hard.
I think if you take a physics class where the student is intelligent and intrinsically motivated through their own interest (I admit this is rare) then AI probably helps.
That last part is key. Intrinsic motivation doesn't mean you pursue it outside normal bounds. My kid loves soccer, its her second favorite thing in the world, she has an absurdly high tolerance for physical discomfort while playing, but she doesn't play it at home. There's other things she's rather do, such as play with her toys.
When you move the bar to something even less interesting to most kids like science, you're going to have a pretty huge falloff. You're basically selecting for kids who choose to do it in their spare time. I know a lot of smart kids (I run a boyscout troop, my wife a girlscout troop, both with lots of high achievers), and none of them do this.
I'm confident it's an amplifier for people who know how learning works and already do a lot of it, successfully. However the level of "learning fluency" I'm talking about isn't reached for many until late college or grad school, and sometimes not at all. So I'm not surprised by the quoted results for 12-18 year olds.
The discussion is about "AI", so common sense is out the window. These people's professional reputations depend on addict-level "AI" usage remaining socially acceptable.
How would you prove/disprove this assumption without falling into a True Scotsman fallacy?
It would not prove that "the results depend on the operator". To prove this (and figure out the traits that make a proficient operator) you would either need a massive dataset to which you'd apply some machine learning to figure out the correlations, or at least you'd need a hypothesis on the traits you want to test.
Do left-handed people perform better with LLMs? Analytical thinkers? Dyslexic people?
It's not enough to just claim "some individuals will perform better with these tools" without any notion of who does, and whether it's possible to become one of these people, and what is the expected gain in this group.
Otherwise, sure, we could sell unsecured chainsaws as a tool for making ice sculptures and observe that "some people" are indeed more proficient at not getting their face cut off ; but if the tool is being marketed to schools, such a vague statement is not helpful in making a case for it.
My only point was I think it's possible to do. I personally think it's pretty clear. And there's nothing special about AI. In rural places, you could replace it with "access to books" or "access to a good tutor" and so on.
I also think you'd see the same effect with "motivation" (if you could test it), with performance on standardized tests, and with grades. AI will boost the better (by these metrics) students more.
It seems that the students who had the most skill and motivation from the start, have the most to lose.
You might say "it's good to learn research skills" and that's true to an extent, but tutors have always made people better students. And AI is a tutor you can message at any time, day or night, for free.
The good thing about a tutor is that he or she isn't always available and knows they won't be in the future, so they instill good habits and independence in you.
Hence the whole "AI is basically an amplifier of bad and good" argument made earlier. The ones who do this because they want to understand, don't need to cultivate this at all, it naturally happens with chatbots. They don't just ask for the answer to a question, but then dig into why it's like that and what not. But the ones that don't care, now have to do even less to get the fast answer without understanding.
I wasted several days trying to have AI teach me containers. I would have been much better off just reading the docs.
I wouldn’t be surprised if you did and still had the same issue, but if you relied on the training data recall alone, you definitely shortchanged yourself.
I’ve had decent results with tasking a model to run pre-research and summarization as a checklist, then have a second instance of the model(s) review and then develop my learning plan learn, versus the times I just asked Claude of ChatGPT to explain something to me “from memory.”
which makes it not a tutor. if it is true that tutors have always made people better students, then those tutors are definitely imposing some limits on how many answers they give you and requiring you to do some thinking. I think you could have premised your same argument by, "copying a smart kid's answers has always made people better students...."
First, there's a certain amount of baseline knowledge we'd like students to possess. Without a certain prerequisite amount of underlying information committed to memory, it gets far more difficult to achieve fluency in a topic.
But more than that, there's other skills we're trying to build: frustration tolerance, processing contradictory information, disciplined problem solving. You only really develop these skills through productive struggle. If you find a way to shortcut the productive struggle, students truggle.
> but tutors have always made people better students.
Sure. Bloom showed us that students taught with a combination of tutorial and mastery methods, one-on-one, outperform students in a normal classroom by roughly 2 sigma.
The paradox has always been-- why hasn't technology unlocked these gains for students in normal classrooms? If we could boost everyone's performance by this amount, it would be huge for society-- but society can't afford to teach everyone with tutorial methods.
Since the 1970s, we've invested in edtech towards trying to make this happen, but most of it has actually had net-negative effects as best as we can measure. AI, so far, looks to be much worse.
I think part of the answer is that a big part of what makes a conventional classroom work are social pressures. So far, it looks like AI (and edtech in general) does more to dismantle conventional pedagogy and to break down the social fabric of the classroom, than it has improved differentiation or unlocked this tutorial effect more broadly.
I was assuming this was a typo and was thinking about making a joke about it, but it does appear to be slang that fits the context:
https://www.urbandictionary.com/define.php?term=Truggle
> 1. the standard of perpetual intellectual failure made by an individual.
> Truggle; the standard defenintion of a person who is a failureat everything.
Was it a typo or did you actually mean this?
The answer is obvious: you're doing homework type activity (learning is not a goal), not exam type activity (learning is the goal).
Social stigma against just juices people to stick to socially desirable answers; no doubt a whole bunch who self reported as non-AI users actually used AI
"e§ort" == effort
"Öve" == not sure. Maybe "over five"?
The PDF file they created knows how to paint the ligatures they used, like "fi" and "ff", but doesn't contain the `/ToUnicode` metadata for what those symbols meant.
The generated PDF happened to put the "fi" ligature at an index that is normally used "Ö", and didn't provide more information.
We need to shift the incentives by adding ruinous penalties for things that are currently quite commonplace if they are done by large players. Some dude training his own AI on his own computer can scrape and train. The fine for OpenAI or Meta using a single copyrighted book without permission should be in the tens or hundreds of millions.
What we're seeing currently in our society is a "loophole inversion" where the rules have an effect mainly via their loopholes. The most profitable activity is to find loopholes and exploit them as frenetically as possible to gain as much advantage as you can before the loophole is closed, or get people hooked on the loophole so it's retroactively legalized. Entities that are big enough to do this are big enough because they have lots of money behind them. Entities doing the same kinds of things without lots of money are not really doing much harm. So the best approach is to adopt a "sliding scale" in which even tiny violations by wealthy actors result in penalties enormously greater than fairly large violations by small players.
I think we don't yet know the long term view - what is harmful or damaging in the long run. Too early to tell and pass judgements. Every new technology from writing to internet had its detractors and they all pointed out negative externalities, as they seemed to appear at the moment.
Same can be said of technology in general tbh.
We could probably cook up thousands of examples of the same problem (YouTube DIY tutorials, GPS navigation, etc.)
It’s alarming how near universally AI has been a cataclysm in class rooms.
On homework the short answer is is that we give kids home work exercises.
AI helps learners reduce the effort expended to exercise and get results. This is making homework moot.
The data point around 80 minutes seems like noise to me. Looks like there isn't enough data/students who spend that much time and also used AI.
It would be nice if AI was a force for good as well as bad, but the data here doesn't support it
A huge proportion of people who use AI use it to outsource their thinking.
It can be used for good for this purpose. You can use it to find primary source information. You can use it to generate challenges for you. You can use it to critique your work when there’s nobody else available. Etc etc.
Evidently the AI users think hard things are beneath them. They want to win without doing any work. Sympathy, I have not.
If it is an amplifier of "good" vs "bad", I don't know, and I do not know what that means exactly. I do not think some students are just "bad" or "lazy" by character and that explains all. I think that their environment has a big role in shaping their actions. I don't think that AI cannot be used beneficially (and the articles talks about some attempts that maybe worked well), but it requires careful considerations, guidance and intentionality from educational institutions themselves. The same goes with all kinds of technology, and AI is nothing new in that sense, but often new technologies are introduced in education without careful considerations or evidence based policies. Which is why imo articles like this are very important.
Using the forklift as a spotter and to assist in loading weights increased gains. Then again, a human can do all those things, and provide real human connection.
In the case of some management, is causing them to unlearn, forgetting about proper review and maintenance practices.
This is a pedagogical problem that AI merely exposed. Educators need to figure out How to make students choose the scenic route instead of having them optimize for the most efficient completion of a task.
We need to restructure the system to treat failure as a signal instead of a disaster. Grades should come from hard randomized exams with unlimited retakes so one bad day won't hurt you. Homework should be optional material for self study, evaluated by teachers if you choose to do it but never forced.
Hold back students for individual classes instead of a whole grade so failing one can't ruin your social life and teachers are more willing to do it. F students will realize they have to study, start actually learning and then pass on the second time. No big deal. It happened to my friends in college, no reason they can't do it in high schools.
Discipline is a skill and it's one you have to get from experience. If you try and force kids to study when they don't want to "for their own good" you're not actually helping them. Everyone needs to find their own path. Let people fail.
this rhetoric is pretending to be an alternative to coercion. IMO the ideas you are talking about are well trodden and are still coercion nonetheless.
Do you have evidence for this beyond your friends (who were accepted into college)?
At Caltech, homework was assigned but had no bearing on your grade. The grades were based on the midterm and final exams.
But not mastering the homework usually resulted in flunking the exams. There were "retch" sessions after each homework assignment that was staffed by a grad student, and the purpose was to help the students understand the homework problems. I knew only one person (Hal Finney) who was so smart he didn't need to do the homework.
I learned the hard way that the path to success was:
1. never miss a lecture, no matter what
2. take notes by hand during lecture
3. do the homework on time, and make sure you understand every problem. Take advantage of the retch sessions.
And that worked for me.
As a student of a top-tier French Master's degree, I consulted with a teacher to deal with exhaustion and to ask for a class rescheduling for my case. Explaining my situation, the teacher looks at me and interjected:
—Waitwaitwait. You... you went to all lectures!?
And he was right. Rather than following the curriculum, I should have developed my taste for various engineering topics and only used the classes as entertainment.
When I was there, a long time ago, exams were timed and were usually open book open note. Blue books were filled in. You were trusted to adhere by those rules, and most students did their exams in their dorm rooms.
The evidence that the students honored the rules was some exams resulted in a 50% failure rate.
As for me, I went there because I wanted to learn the material. I did not care about getting a diploma. (Mine is in the basement somewhere.) I did not take any "easy A" classes, because I wanted a return on my time and tuition investment. (Though, easy A classes were hard to find at Caltech.) I wasn't even going to attend graduation, but my parents showed up and I attended to please them.
The classes, year by year, were dependent on mastering the previous year's classes. So if you cheat with AI, you're digging yourself into a bigger and bigger hole. Caltech rewires your brain. If you don't learn the stuff, you're going to be one of those EEs who carries around a card with V=A*R, V/A=R, V/R=A printed on it.
So the endgame was figuring out what the tests in previous years looked like (cause it was likely gonna be a copy paste affair), do a targeted study run for those exercises and 9/10 you would pass.
We didn't call them retch sessions, and they were taught by the instructors though. We also were encouraged to peer tutor and since we were all restricted to one building the homework was always group work allowed.
Also had badges to track time spent in the building for required study hours, though some people gave up and just slept at their desks when they started sliding down the grade scale and the hours racked up.
Generally I think I did 30 hours of studying/homework (went up and down depending on what was being taught, but was around that) a week (for 12-15 hours of actual lecturing), with some of my friends putting in 50% more. Generally the only day we weren't there was Saturdays. Most of the day Sunday was usually spent in class preparing for the next week.
But you had tutorials each week, and if your tutors thought you weren't doing enough work they could set you exams mid-course called 'penal collections' and if you failed them you could be thrown out. They were rare but definitely not unknown.
Education system, contrary to popular belief/name, isn't tailored to educate but to select winners and losers which then will be picked on the job market.
It does fail at it ultimately because interpersonal relationships matter much more than pure skills in practice.
That's why it seems absurd when you think about it as an institution that aims to educate. That's because that isn't the real purpose of it. The purpose is to stratify and classify early.
Compliance and endurance of boredom I can somewhat agree with (thought not to a great extent), but social manoeuvring? As long as a student completes their classwork and homework, and does well in their exams (none of which mandate any social interaction apart from team projects), they easily pass through the school system. In fact, I used to hear about how the school system disproportionately benefited studious, shut-in students over street-wise, socially-savvy ones.
Socially savvy students on the other hand will get plenty of help from teachers and other students even if they are not so good themselves.
This is why the so called “intelligence” where I will define it as skill of acquiring skills right now, is not so important for success. You can be very good at learning but if your social aptitude and charisma sucks then you will just end up as depressed, miserable and poor and probably alone too.
It’s honestly very important and way more important if you have a kid, to care about its social development and how you can help so your kid gains social confidence and never loses it at crucial moments
Optional homework is often a disaster. At best, students would do it right before an exam and the goal of education is not to just pass exams. They’d probably still get a lower score than if they did the homework when they were supposed to.
What I think is better is to have a due date, but just make the maximum 10% each day it is late. So after 2 days, the highest score you could receive would be 80%.
I liked that system because it gave some flexibility with deadlines while still encouraging you to turn things in on time.
My view is this: a student can turn in an incomplete assignment. Work they completed get evaluated and graded. Anything not completed gets zero credit. Homework should be an investment in effort over time anyway. Unfortunately, procrastination is a deeply rooted problem that usually kills this.
> Homework should be optional material for self study, evaluated by teachers if you choose to do it but never forced.
My wife is a teacher and her school does this. The result is that nobody does homework. The kids who need the extra practice don't get it and they fall into a spiral of failure and apathy. This is especially bad for subjects like math that build on themselves.
IMO the better solution is to require and grade shorter homework and provide students with optional, supplementary assignments that can be used to make up for missed credit on homework for the same material. That way students who grasp the material quickly can demonstrate and move on while others who need practice are naturally encouraged to get it without being permanently punished for struggling initially.
I much prefer the first.
School shouldn't be impossible, but you shouldn't have a charade of schooling.
Obviously, extra practice is a good idea.
And I mean setting aside some time during the class itself, not a separate "study hall" period. Obviously class time is precious, so I don't expect there to always be enough in-class time to finish assignments. But even having a little in-class time for students to get started - and when the teacher is available for help those in need - would go a long way towards encouraging students to do the work themselves and not cheat.
And of course part of my strategy is to make "homework" shorter (5-15 min). That should also reduce the temptation to cheat and increase the likelihood students can even complete them in class.
Exams will have to be a lot longer if you allow unlimited retakes. Generally exams work on a sample principle, but this breaks with retakes.
This simply does not work for most, as pupils are too immature. You put sunscreen on children, keep them away from the street and brush their teeth. Having everyone re-learn the same stupid lesson is wasteful, it's better to institutionalize this knowledge in the form of mandatory participation.
Then I stopped caring about tests too.
I did the same thing through college. The only reason they passed me and I got a degree is that I built the school’s website and I built personal ecommerce sites for the head of art and his wife to sell their paintings.
I haven’t done shit since like 7th grade.
Worked at Facebook, Apple, Microsoft, same behavior there - did basically nothing for them while making thousands off my games on App Store.
Fuck authority
When the signal is removed, this is what you get.
My own experience is that college is fun. You can spend the time wisely, but school stuff, is not what makes you money.
Make student loans dischargeable in bankruptcy and make colleges under write them. The problem will get solved quickly.
AI just gave the students a way to dodge the slog.
But university was never intended to teach the bleeding edge. That would really be impossible in practice. Pre-phd, it is supposed to teach ways to efficiently attack a problem. you can take a bunch of "play courses", and succeeding at any of those requires pretty much only that one skill.
Nowadays, the challenge they face, is to keep teaching "problem attack methods" in a way that can't be trivialized by AI.
Though fundamentally, if you go to university, and evade learning the one thing you can learn there - thats your loss.
Try it for yourself by making a prompt like this (adapt as needed):
Pretend I am an undergraduate student of Computer Science. I am learning about early microprocessors from the 1970s. I want you to ask me an examination question as if you were doing a viva voce exam with me, to test my understanding of concepts. I want you to receive my answer and then based on what I said I want you to ask me a more specific question to probe my understanding. Repeat this interaction up to 5 times. Then grade my understanding so far, by giving me a pass, merit, credit, or distinction. Can you explain how you arrive at the grade based on my answers and your expectation of undergraduate knowledge of microprocessor theory?
When I was in school there were multiple instances where I would be stuck on a problem for nearly an hr but I always learnt something from it. They key I think is to accurately identify when to and when not to use AI
AI shouldn't be "helping" with homework. AI should be the homework.
Start with any topic or problem, students should be encouraged interact with AI, and learn stuff using Socratic method.
Teachers should rate the chat session instead.
And iterate the process to high profeciency.