Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes • Hacker News Board

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

#161

Post by johnvanommen » Thu, Jun 04, 2026, 7:31 AM UTC

adamcharnock wrote: post #112

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've been wondering if there would be a benefit to inverting how we teach subjects now. Previously we would teach from the bottom, and build up. Semi-colon goes here, curly brace goes there, and then build up to architecture, systems, etc. But this doesn't seem to make sense when someone comes to a topic with an LLM in-hand. They need to know high-level techniques, architecture, best practice, etc. As they pursue the…

I keep trying to convince people that English majors and Philosophy majors will benefit the most from LLMs. English majors in particular, have been trained to be VERY exact in how they word things.

That awareness of how to structure the English language, it will benefit those who use LLMs.

Then again, maybe someone will just make a LLM that’s built to turn poor English and poor reasoning into excellent English and excellent reasoning. Maybe this is just a technical puzzle that needs solving.

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

#162

Post by ricardobayes » Thu, Jun 04, 2026, 7:33 AM UTC

This tracks, I have read that this generation is the first one since the 1800s that performs worse academically than the previous ones. Experts blamed screens and anything digital in the classroom.

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

#163

Post by lelanthran » Thu, Jun 04, 2026, 7:35 AM UTC

HanayamaTriplet wrote: post #77

lelanthran wrote: post #52

Earlier quoted context omitted.

There's always a lag between cause and effect in education. Works the other way too - if you introduce something positive in grade 1, you'll only see the results a few years later.

If it's a lagging effect, then why is the year-over-year spike in failure rates happening not just in 1st/2nd year classes, but also in a 3rd/4th year class at the same time?

Entrance tests predict academic success , not 1st year success.

"Failure to complete the qualification" is the prediction.

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

#164

Post by schnitzelstoat » Thu, Jun 04, 2026, 7:36 AM UTC

somenameforme wrote: post #39

The likely 'real' reason is hidden in one paragraph within the article and has nothing to do with the implication of the eye-catching title: "Both Garcia and Ranade have joined more than 1,300 UC faculty in signing a petition calling for the reinstatement of ACT and SAT standardized testing scores for STEM admissions in the UC system. The petition and its accompanying open letter detail similar concerns with students…

I'm not American so maybe I am missing some context. But how did admissions work without test scores?

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

#165

Post by xiaoyu2006 » Thu, Jun 04, 2026, 7:36 AM UTC

adamcharnock wrote: post #112

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've been wondering if there would be a benefit to inverting how we teach subjects now. Previously we would teach from the bottom, and build up. Semi-colon goes here, curly brace goes there, and then build up to architecture, systems, etc. But this doesn't seem to make sense when someone comes to a topic with an LLM in-hand. They need to know high-level techniques, architecture, best practice, etc. As they pursue the…

I can't speak for other disciplines, but for math and CS, both with a really heavy focus on abstraction, the final result of learning is to build a nice intuition on top of the abstractions we find useful/expressive. And to build the intuition, the old, usual, and perhaps the only way is to see and practice a lot of concrete examples, after which the motivation of building some abstraction can be understood, and after which the abstraction itself can be fully grasped.

e.g. The "group" abstraction requires one see a lot of int, polynomial, modular arithmetic etc. before knowing why we want such a thing. It's unskippable.

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

#166

Post by ListeningPie » Thu, Jun 04, 2026, 7:37 AM UTC

f311a wrote: post #158

adamcharnock wrote: post #112

Earlier quoted context omitted.

I've been wondering if there would be a benefit to inverting how we teach subjects now. Previously we would teach from the bottom, and build up. Semi-colon goes here, curly brace goes there, and then build up to architecture, systems, etc. But this doesn't seem to make sense when someone comes to a topic with an LLM in-hand. They need to know high-level techniques, architecture, best practice, etc. As they pursue the…

You can ask LLMs about high-level techniques, and their answers will usually be good enough. What you can't get from LLMs is the taste and judgment, which you can only obtain by having a strong CS base and coding manually for years. High-level techniques were never a problem. You could Google tens of articles on this topic. They are useless too, it's like learning how to drive a racing bicycle from reading a book. Su…

taste and judgment, which you can only obtain by having a strong CS base and coding manually for years.

I disagree, the definers of taste; art and food critics, movie and book reviewers, don’t need to have learned the craft by doing. Taste is a separate skill.

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

#167

Post by xiaoyu2006 » Thu, Jun 04, 2026, 7:38 AM UTC

f311a wrote: post #158

adamcharnock wrote: post #112

Earlier quoted context omitted.

I've been wondering if there would be a benefit to inverting how we teach subjects now. Previously we would teach from the bottom, and build up. Semi-colon goes here, curly brace goes there, and then build up to architecture, systems, etc. But this doesn't seem to make sense when someone comes to a topic with an LLM in-hand. They need to know high-level techniques, architecture, best practice, etc. As they pursue the…

You can ask LLMs about high-level techniques, and their answers will usually be good enough. What you can't get from LLMs is the taste and judgment, which you can only obtain by having a strong CS base and coding manually for years. High-level techniques were never a problem. You could Google tens of articles on this topic. They are useless too, it's like learning how to drive a racing bicycle from reading a book. Su…

Exactly. Repeating or rephrasing a definition is trivial, teaching someone is not.

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

#168

Post by amelius » Thu, Jun 04, 2026, 7:38 AM UTC

enoeht wrote: post #118

com2kid wrote: post #12

At this point I would support a ban on generative AI by anyone under 18, or even perhaps 21 years of age. A bunch of science fiction stories had "first connection to cyberspace" as a coming of age event, maybe those authors were on to something.

ban has always been the failing option

Tell that to millions of ex-smokers.

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

#169

Post by coldtea » Thu, Jun 04, 2026, 7:42 AM UTC

qsort wrote: post #74

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 dumb as a rock and I don't have a PhD, but since ~1 year ago I started forcing myself to do small bits of coding and math manually. I'm not noticing a "cognitive decline" per se, but I do see I'm a lot "lazier", even stuff that used to be routine when I started coding now feel heavy.

>I'm not noticing a "cognitive decline" per se

The funny thing is, maybe not noticing one can be the actual sign of it :)

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

#170

Post by curun1r » Thu, Jun 04, 2026, 7:42 AM UTC

dyauspitr wrote: post #26

com2kid wrote: post #12

At this point I would support a ban on generative AI by anyone under 18, or even perhaps 21 years of age. A bunch of science fiction stories had "first connection to cyberspace" as a coming of age event, maybe those authors were on to something.

It’s like the greatest teacher. Plus it’s not toxic like social media. Banning it would be a shame.

This.

It's funny that GP mentioned science fiction as a negative because what immediately springs to mind, for me, is Neal Stephenson's The Diamond Age. We literally have the tools to build his "Young Lady's Illustrated Primer" today. We just have to give today's AI a lesson plan to follow and ensure that it never gives the student the answers, and only keeps explaining the concepts in different ways until they click. Wrap that in an iPad app and you've essentially got the exact self-paced learning tool that Stephenson envisioned changing the world.