It was already discussed on HN.
Could you explain?
From the current article
In addition to overreliance on AI, Garcia also pointed out that many students are underprepared mathematically, a concern echoed by campus associate teaching professor Gireeja Ranade.
From the article discussed the other week:
Over three years — from fall 2021 to fall 2023 — the letter said, at least 20% of Berkeley first-semester calculus students who took a diagnostic exam showed deficits. “Basic mathematical fluency is analogous to literacy; without it, success in university-level STEM becomes structurally unattainable for students,” faculty wrote.
It's been steadily getting worse. The current article only looks at F's which conveniently hides if there has been a slope down. Additionally, kids entering HS in 2021/2022 would just now be hitting college.
A sudden materialization is what's depicted by the data.
> It's been steadily getting worse.
I don't believe this is accurate. Failing grades are what the observation entails, and the data clearly depict an abrupt change; not a gradual one.
In the section titled "Failing grades in 3 CS classes skyrocket in spring 2026 ", there's a clear jump in failing grades for all cited courses between 2025 and 2026. Failing grades for every course jump by multiples of the previous year.
"Ranade said students are expected to enter the course having taken classes on linear algebra, vector calculus and mathematical proofs. However, she found out in office hours that many students struggled with linear algebra, and was even more shocked when one student told her the linear algebra class they took at UC Berkeley had an “open-internet, open-AI policy” for homework and exams."
Also, this professor doesn't grade on curves? Could be very specific to this teacher. I don't know. Would be great to have more data but it is a big jump and could be very specific to this professor or perhaps this class.
FWIW I did a little digging, and EECS 127 indeed has explicit prerequisites of:
* Math 53 - Multivariable Calculus
* Math 54 - Linear Algebra & Differential Equations
* CS 70 - Discrete Mathematics and Probability Theory
This suggests the students are either taking those classes or have provided some kind of AP/test-taking credential to skip them.
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 and you'll get promotions much quicker than in a high performing team doing challenging (but fun) work.
It was right. I had 2 "dream" jobs where I did cool, challenging stuff, but where everyone was more than competent. They turned out to be career killers. The promotions I got were all in the other 2 jobs where I did boring business logic coding, and where my peers were barely competent (one had trouble navigating directories using the command line).
That's what happens when you grade on a curve. Smart people begin to work on boring stuff, and not the real challenges.
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 rapidly.
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?
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.
I repeatedly said "standard course", which implies it is a commonly taught course (be it upper or lower division). In my undergrad, Analysis I, II and Abstract Algebra I, II were upper division courses. In the engineering departments, stuff like Electromagnetics I, II were upper division.
Anything that is not an elective (and even some popular electives) were standard courses.
Now I'll grant that in CS, some material like machine learning changes rapidly. But in most engineering, very little in the undergrad material changes. Even my semiconductor courses in undergrad haven't changed much in decades.
So yes - for most of those classes (and that means the vast majority of undergrad engineering) classes, the curriculum is relatively standard.
> 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?
First: In my very average undergrad university, professors were always careful not to reuse old homeworks/exams. It wasn't a huge burden. Professors who don't do this (e.g. most professors in top universities) signal very clearly their lack of interest in pedagogy.
Second: You want to do a curve on <= 15 students? Are you aware of basic statistics and the problems you get with small N? Are they using a normal distribution or one that is more appropriate for small N?
And as I already said, for a lot of electives where the material isn't standardized, professors lean towards lenient grading. They offer those classes because they want people to take it, and grading via a curve discourages it.
> since you mentioned an Intro to Analysis course
That was an upper division course. Yes, I know some universities have it as a lower division, but many (most in the US?) treat it as upper division.
> 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.
It was not a weed out course. Neither my undergrad nor grad math departments had weed out classes. I saw that concept only in the engineering departments. My EE department had only Circuits I, Circuits II and digital logic as "lower division". Circuits II was the weed out course, and you were not allowed to take anything else (e.g. E&M, Electronics, etc) unless you got a B or higher.
So assume 4 years of high school and someone that just came in. They are still preparing for SAT like tests in their first year of high school. Someone in final year of high school is well trained in it. So even though the benefits do not carry, enough portion of incoming students are still reaping benefits of standardized tests. The decay only shows later when batches without any benefits of standardized tests are coming through.
Pardon? Is that a normal thing in the USA? I don't think I've ever started preparing for a test more than a week and a half ahead, a month if you count graduation exams. Not sure they ever determined more than a year in advance (more commonly: a bit less than a semester) what tests we'd be given in the first place
I think we will make a major mistake if we think math preparation fixes this - especially in CS classes where AI literally calls out to be used for projects. And it certainly doesn't explain me hearing the same problems are happening at MIT -- they just are being a bit wiser about "catching students" (or rather not doing so).
The kids who saw the removal of standardized testing 3 years out from going to college never bothered.
Also some children who excel write their SATs sometimes 2-3 years before college and then re-write if need be.
Works the other way too - if you introduce something positive in grade 1, you'll only see the results a few years later.
"Failure to complete the qualification" is the prediction.