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Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

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Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#541

Post by girfan »

camelmel wrote: post #35

I have some sympathy for these kids. If LLMs were around when I was a student, I would've also used them to "speed up" my homework assignments then proceed to fail all my tests. Now I work mostly with PhDs who were at the top of every academic environment they've ever been in. And yet I can see their thinking skills rapidly declining as well; many of them can no longer brainstorm, code, think deeply, or write without…

I broadly agree with the premise. As a PhD student in Computer Science, I feel there are some significant upsides to my work routine. LLM access has made many new domains more "accessible" to me which I otherwise would be too hesitant in investing my time in. For example, my area of research is computer systems which involves operating systems, distributed systems and more recently systems for AI. Within these, there is a wide breadth of topics/techniques one can employ and up until now, I have not gone deep into theoretical aspects of things like scheduling etc. But with access to LLMs, I feel like I can at least brainstorm from a high-level about these sub-areas that I am not well-versed in and the responses give me some relevant pieces to start exploring on my own, depending on what interests me more or the amount of time I want to spend on that sub-branch of a larger tree of ideas. However, the one thing I do have skepticism is the lack of awareness of blind-spots when dabbling into areas that I am not an expert in, and taking the LLM's lead in applying such techniques to some systems problems that I am working on. I often feel that I am not aware of what alternatives exist that the LLM has not explored for me, or if the directions it has proposed really do apply or have corner cases/assumptions that break in what I am doing. On the other hand, when working on something I have good intuitions about, I am often correcting the model's assumptions and it back-tracks what it told me. Unfortunately, I cannot do that comfortably with topics I don't have good intuition about which limits my confidence in "if this is the right direction to pursue."

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#542

Post by visarga »

Hasz wrote: post #498
greenavocado wrote: post #475

Earlier quoted context omitted.

> If you treat the model like an excellent bluffer, it has never been more fun to challenge a model. To me, there is something deeply intellectually satisfying about "proving" it incorrect, and I like being deeply critical of what the model spits back out. I find that refinement process (with the constant sycophancy turned down in the system prompt) creates a really good loop of critical evaluation that would be hard…

new session. It's easy to lead a model into getting the response you want, deliberately or accidently. The point is not to literally win an argument (it doesn't matter), it is to use the model like a partner to poke holes in your own understanding. Once it's poked a hole, it has served its purpose. Plus, you eventually run out of context or the model trails off into babbble.

That is how I use models too. Sometimes I have them role play the supporters of the idea I am arguing against.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#543

Post by feoren »

TuringNYC wrote: post #461

How do we know this is due to AI usage? Perhaps it is because the students missed key in-person learning at the tail end of high school due to the pandemic lock-downs? I cant imagine learning calculus / linear algebra on my own in high school.

Absolutely: missing in-person learning due to COVID. Less attention span due to growing up in a distracting environment. A lower bar to entry due to removal of standardized testing and indirectly from No Child Left Behind. Changes in parent or student attitudes. It could be any number of things, and it's lazy to just say "with AI usage" as something that has increased at the same time.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#544

Post by Ekaros »

forlorn_mammoth wrote: post #497
ap99 wrote: post #266

Earlier quoted context omitted.

This goes with calculator to do basic math, contacts apps to store phone numbers instead of remembering them, and watches to tell time imo. Sure we could use our brain power with old techniques to do these, but why? I don't want to do any of these. I'd rather use that brain power for other problems. Same with maps. I don't want to have to store a bunch of location or routing data in my head. I think what you're point…

> I don't want to have to store a bunch of location or routing data in my head. hmmm, given how closely memory is linked to spatial navigation sense, and not just in humans, but in evolutionary terms-- think squirrels remembering where they buried nuts, birds and fish remembering migration routes, ... suggests the ability to store location/routing is foundational to much of intelligence. Even simple tasks, typing, fo…

I thought that it was discovered that squirrels don't remember where nuts were stored. They just kinda guess and enough of them doing storing and then some make it work on average.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#545

Post by keeda »

camelmel wrote: post #35

I have some sympathy for these kids. If LLMs were around when I was a student, I would've also used them to "speed up" my homework assignments then proceed to fail all my tests. Now I work mostly with PhDs who were at the top of every academic environment they've ever been in. And yet I can see their thinking skills rapidly declining as well; many of them can no longer brainstorm, code, think deeply, or write without…

> Many of them can no longer sit quietly for even 30 minutes just thinking on their own

Plummeting attention spans has been a trend for much, much longer than LLMs and is more the result of constant digital interruptions and these days overwhelmingly social media and doomscrolling: https://www.apa.org/news/podcasts/speaking-of-psychology/att...

The effects on children have gotten most of the, err, attention, but the effects on adults are no less deleterious.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#546

Post by lokar »

TrackerFF wrote: post #235
Retr0id wrote: post #116

It's interesting that it's specifically math-within-CS being discussed here. I can imagine a lot of students "just want to learn programming" (or similar), and see the math as a tedious distraction. As a naturally curious person, nothing will stop me from learning about the topics that interest me. But school also taught me a lot of things that didn't interest me, and a lot of those things turned out to be useful any…

I also think that's one reason. Where I'm from (Norway), the majority of computer science and software engineering studies do not have the same math requirements as, say, engineering or math/physics/etc. - nor do they have the same amount of math as the latter ones. When I did my CS classes as an engineering student, I did meet a bunch of students that viewed math as some niche subject only relevant to those that wan…

My (UC) CS (pure software) program required a bunch of math, but not for the math. You could talk almost anything (I did set theory and meta-logic), it was required to ensure a certain level of mathematical formalism and reasoning. Which is very helpful in CS.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#547

Post by lokar »

Sharlin wrote: post #221
PeterStuer wrote: post #205

A famous MIT professor did a sabatical at our AI lab. He said it was "a joy to teach here, as you can rely on students being proficient in basic math as opposed to the US where you have to teach those explicitly or lose the class completely". That was in the 1980s. My first math exam as a CS undergraduate, 123 out of 129 students failed. The math department professors refused to dumb down their classes for CS student…

To be honest, there’s approximately zero reasons to teach major-grade math to just about anyone but math majors. None of the applied math disciplines need go that deep, and what they do need depends on the field (physics is all about analysis, CS is about algebra and discrete math, and so on).

My CS program required one year of upper division math. But you could take anything (I took set theory and meta-logic from the philosophy department, it was actually pretty hard!). They did not care about the specific math skills, they wanted us to have a level of mathematical formalism and reasoning, which was in fact important for the CS classes.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#548

Post by welshwelsh »

sndgndgndgndy wrote: post #78
0xDEAFBEAD wrote: post #71

>In addition, the guidelines state that “a typical GPA for a lower division course will fall in the range 2.8 – 3.3.” In spring 2026, both classes’ average grades were C-pluses, according to Berkeleytime, corresponding to a 2.3 GPA. As a Cal alum, I am actually really glad to see they are holding the line on grade inflation. I worked my butt off to achieve the GPA I did, and it would really suck to see my labor deval…

Unpopular opinion: turning public universities into an academic hunger games is diametrically opposed to their purpose for existing, which is to create an educated populace. Intentionally lowering the quality of instruction, as well as deliberately trying to trip students up on exams, is not improving educational outcomes for anyone. People who complain about "grade inflation" have completely lost sight of why public…

Even more unpopular opinion: universities don't exist to create an educated populace. People don't need universities to learn, they can read textbooks on their own.

Universities exist as gatekeepers and credentialing bodies. Their purpose is to certify that a person has studied some topic in depth and is an expert in it. They promote education indirectly, by giving people an incentive to study.

A good university is one where anyone with a degree is guaranteed to be highly knowledgeable in their field of study. This makes it easier for anyone who might want to employ or do research with graduates, as there is no need to test their knowledge.

By this metric, universities have failed spectacularly. This is particularly obvious in computer science. Employers routinely ask CS graduates to solve data structure/algorithm problems in interviews, because a degree is not enough to prove that somebody knows this stuff.

Re: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes

#549

Post by ndriscoll »

aleph_minus_one wrote: post #363
techblueberry wrote: post #348

Earlier quoted context omitted.

What a delightful fantasy world you live in. Doesn’t sound very predictive of actual human behavior though.

> What a delightful fantasy world you live in. I can really certify that this was my lived experience. In the math degree course, basically everyone who was not incredibly passionate about mathematics (NB: "passionate" does not necessary imply "great academic achievements") changed their major or decided for a different kind of tertiary education. Former co-students who attended the same university and degree course…

Another factor might just be that math pretty much is the extra depth behind a bunch of STEM fields, so people studying math specifically are more likely to be interested in that depth.

That said I generally think the take that it's somehow privileged to find school interesting to be sad. Over the last couple decades one could do pretty well with pretty much any STEM degree. Is the majority feeling among people studying engineering that they just have no interest in any facet of how the world around them works? They have no desire to understand how to create (and alter to their liking) the things they see? No interest in the fundamentals of how the universe works? How different materials come to act the way they do? How living beings work? Nothing?

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