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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

#591

Post by djeastm »

bko wrote: post #308
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…

What does this have to do with LLMs? They stopped requiring SAT and ACTs in order to get a student population more representative of the population in general. This obviously allowed students that were not prepared for college into the system. If you do well in your math SATs you'll likely do well in math college. SAT scores and college GPA are highly correlated. No idea why anyone thought it was good to ignore proba…

Isn't GP talking about PhDs here? If they're PhDs I imagine they've already had good enough GPAs/were smart enough to be selected for the program.

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

#592

Post by MengerSponge »

alephnerd wrote: post #22
MengerSponge wrote: post #19

Earlier quoted context omitted.

Spring 2026 saw a marked shift in student performance. We saw it in intro physics courses on the East coast too. I bet anyone who cared to look saw it.

I'm not denying that. I'm just wondering if anyone measured if there is a correlation effect being induced by CS major declaration requirements. Barely over a decade ago, CS tended to be a large but not too large major by enrollment in most universities yet nowadays it is the most in-demand major in most universities. You can see this at Stanford [0], but most other programs as well. [0] - https://stanforddaily.com/2…

The failure rate tripled. So no, it’s not CS major declaration requirements.

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

#593

Post by BeetleB »

seanmcdirmid wrote: post #508
BeetleB wrote: post #450

Earlier quoted context omitted.

Actually, when I read they usually graded on a curve, I lost all interest. I don't respect teachers that grade on curves. You should be graded by how well you know the material - not how well your peers don't know it. I'm always grateful both my undergrad and grad professors didn't curve on a grade. In my first company, I had 4 different jobs. It was a common adage: Go into a low performing team that does simple work…

For failing grades sure, there must be some sort of minimum competence. For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable. If you wanted to grade purely off a curve, you would be stuck with old test problems that were thoroughly vetted and calibrated, an impossible task for smaller classes where the material changes r…

> For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable.

I'm still not getting it. For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers. You have a syllabus, and a set of abilities for each grade level. If you hit those targets, you get the grade. If half the class gets an A, then it means they're pretty smart, or you did a great job in teaching. Of course, there's the chance the class was too easy, but you can always fix that.

No, I don't see why you're stuck with old test problems. For standard engineering classes, there's a huge (almost infinite) set of problems one can create.

For smaller classes, grading on a curve is even sillier, as the variance is always higher when the population size is small. For example, a lot of my small classes consisted of highly motivated students (all "A material"), because they're usually obscure electives where the content is challenging. You then pointlessly penalize students who sign up (just like they do at work). In fact, my professors were usually much more lenient on small classes for this very reason (i.e. lowering the standard needed to get an A).

I once took an Intro to Analysis course. It was moderately challenging. I got the highest score in the class, and my grade was A-. Everyone else got B+, B, or lower. A friend of mine (who didn't take the course) got really upset that I didn't get an A (or A+) given that I was the top scoring student.

But I knew my level of understanding/performance. It wasn't that great. I felt even an A- was too high a grade for me. And the teacher did a pretty good job in teaching. Why should I get a higher grade just because the other students were worse?

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

#594

Post by yawnxyz »

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…

before AI was around we blamed Covid for doing this to us, and now we blame LLMs... and before that we blamed social media. I'm pretty sure this downtrend has been happening for decades.

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

#595

Post by reaperducer »

conductr wrote: post #140
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’m not noticing the decline in my own abilities any more than I had before using them. I finished undergrad 20 years ago and my once sharp math skills had been severely diminished within only 5-10 years. Just simple arithmetic and percentages that I could rapidly do in my head became dependent on calculators/spreadsheets. For all other trivia type knowledge, my brain has offloaded it to the internet RAM in my pocket…

I’m not noticing the decline in my own abilities

…said every drunk person ever.

That you don't notice it doesn't mean it isn't happening. By the time you notice it, it's too late.

That's why elderly people who are worried about their brains play chess and do puzzles like mad.

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

#596

Post by djeastm »

SirMaster wrote: post #518
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 don't understand why people take shortcuts in school. You pay a LOT of money to be there to learn. Taking shortcuts seems completely counterintuitive to me.

- Time is a scarce resource. Students do what they can to learn what they can, but if they're under the gun, they'll take the path of least resistance to make it to the next day (totally not like the business world, right?)

- In the interest of having well-rounded students, a lot of degree programs include subjects the student didn't want to sign up for, but have to. Even in something like CS, I knew a lot of people who liked the hardware side of it, but didn't like the software side and vice versa. So I can imagine a student justifying taking shortcuts that way.

- Psychological reasons like wanting to protect their ego. Maybe they had always done well in school and are now struggling, but don't want to ask for help, so they think why not just take a shortcut here and promise to do better next time, etc., etc.

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

#597

Post by alephnerd »

MengerSponge wrote: post #592
alephnerd wrote: post #22

Earlier quoted context omitted.

I'm not denying that. I'm just wondering if anyone measured if there is a correlation effect being induced by CS major declaration requirements. Barely over a decade ago, CS tended to be a large but not too large major by enrollment in most universities yet nowadays it is the most in-demand major in most universities. You can see this at Stanford [0], but most other programs as well. [0] - https://stanforddaily.com/2…

The failure rate tripled. So no, it’s not CS major declaration requirements.

> The failure rate tripled

And did the rate of students attempting to declare CS also triple?

> So no, it’s not CS major declaration requirements

Are intending CS majors in your university required to take that specific physics class before declaring the degree?

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

#598

Post by seanmcdirmid »

BeetleB wrote: post #593
seanmcdirmid wrote: post #508

Earlier quoted context omitted.

For failing grades sure, there must be some sort of minimum competence. For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable. If you wanted to grade purely off a curve, you would be stuck with old test problems that were thoroughly vetted and calibrated, an impossible task for smaller classes where the material changes r…

> For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable. I'm still not getting it. For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers. You have a syllabus, and a set of abilities for each grade level. If you hit those targets, you get the gr…

> For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers.

Do you think upper division college classes are somehow like high school classes with well developed curriculum and teaching professors who teach the same thing every quarter? Now you expect the professor to not only come up with new test material, but also extensively calibrate it before students take it, maybe for a 15-hour per week class (3 hours of teaching + 12 hours of studying), with maybe 15 students? Well, thank God we have AI for these kinds of things now.

Ok, let's exclude upper devision classes and just focus on lower division courses (since you mentioned an Intro to Analysis course). Here you have a relatively better chance of a well understood enough curriculum and testing material to actually not grade on a curve. BUT these are also usually weed out classes, with the idea that they only have N spots for students to proceed on to the upper division course, so curving serves an actual purpose that is aligned with the intended result.

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

#599

Post by jawilson2 »

faidit wrote: post #510
everforward wrote: post #445

Earlier quoted context omitted.

I think some people are okay with communication that’s less involved. Like meme-y BSing where everyone involved knows everyone else is putting like 12% of their thinking power into sending a response. I don’t really enjoy that, so I find having that many threads stressful and annoying. I just take a hard line and will unilaterally downgrade communications (while politely letting the other party know). I have all my f…

We have to normalize being on silent all the time and making people wait hours for a response. Return to the primordial monkey of 1800s-era high-latency comms. At first, some people will be offended. "Why didn't you let me ping and buzz you and interrupt you all day? You didn't respond immediately each time :'((". Some people with unrealistic expectations may even stop talking to you entirely. But eventually (years m…

I've told people this for years. The mode of communication reflects the urgency. If you text me, expect a response on the order of 3+ days. If you call, and I recognize the number, it will be more urgent. If I DON'T recognize it, it goes to voicemail and back in the 3+ days queue. If you show up at my door, it is immediate. Even with my wife, she will text while I'm at the grocery to pick up some extra food items, and it doesn't necessarily come through or I'm on silent. I'll get home, and she'll ask where the food is, and I ask why she didn't call if it was timely. I just do NOT check my texts that often, it isn't because I'm deliberately ignoring anyone.

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

#600

Post by e-topy »

jventura wrote: post #589
LovelyButterfly wrote: post #573

Earlier quoted context omitted.

As a professor, what's you opinion regard the Socratic method with LLMs? Would that be preferable over simply "give me the answer" prompt?

Everything that provides students with a workflow to think and to try to find solutions to a problem is much better than giving the answer directly! Unfortunately there will always be students that prefer to take the shortcut.. How could we "force" the students to use an LLM that confronted their doubts with more questions? We could tell them to start each chat with a specific prompt (to use the socratic method, etc)…

I'm curious on your opinion, as a professor, how should universities (not individual professors) adapt to LLMs?

As an undergrad, I hope schools move to educating students to use LLMs in a more responsible way. You can't put the genie back in the bottle, and resisting progress is futile, might as well use the tool we now have to help students learn even faster and better (e.g., making feedback instant and not answers, helping digest or split up material, checking answers).

I know opinions about AI at (not only at) my faculty are very mixed, but I think the answer is going to be in the rational mean, just like how technorealism reacted to the internet[0].

In our last program board sitting, some teachers said that they think programming as a job will be completely irrelevant in two years, while other pushed for more adoption. And meanwhile I know of some students that are basically only passing because of LLMs, and it's bad, like "leaving claude output in markdown files and finished source code on the faculty server in /tmp because opencode did so" bad. And our first year classes completely prohibit even sharing tests or talking about the solutions, which in my opinion a) makes people extremely asocial and atomized b) doesn't prepare students for real life c) promotes dishonesty.

Still, I think our university's thinking is in a stalemate, not wanting pure AI output and useless students, while also wanting to move with the times, and I doubt it's the only one.

[0]: https://web.archive.org/web/20081009111415/https://artefaktu... (absolutely amazing read, recommend it)

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