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Comment by Retr0id | Hacker News Reader

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 anyway. I think if I had access to AI from a younger age, I'd have used it to skip learning the things I didn't care about, which would not have done me any favours.

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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 wanted to work with computer graphics, computational stuff, or similar.

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.

Back in the university, I took both math and CS courses and a significant percentage of students seemed interested in neither math nor programming but rather in the jobs they would get afterwards. I didn't notice the same thing with math majors.

Well, that’s because for math majors any monetary incentive is nonexistent (modulo some rather specific careers). Just about nobody majors in math for any reason other than math itself.

Personally, I do believe that math as a discipline has this huge issue of being mostly incomprehensible garbage.

Not because the actual truth encoded in it would be this complex, but because the encoding scheme just sucks.

I see it as a packaging problem that has so far not been painful enough to trigger any meaningful change.

With this LLM-driven collapse, that might finally change.

Idk I'm hopeful.

Math is literally the law of the universe. It makes zero sense that the way that it is taught needs some special brain wiring only found in small chunks of the population to truly click.

If you have a problem with the math notation, you should open a law book, and look at the terminology mess they have going on. I like math notation, because it can be simply converted into natural language, thus removing the notation from the equation and leaving pure logic. Once you have that, thinking about it and working out what the original notation actually meant should be on you, that's how you build an understanding of math.

Compelling argument.

Counterpoint: no

> Math is literally the law of the universe. It makes zero sense that the way that it is taught needs some special brain wiring

Ok, I'm all for overhauling math notation and teaching but this doesn't follow. Most animals can't do Math, even if they can do arithmetic. Clearly living in the universe doesn't guarantee you can learn how it works. There's no reason to believe we slightly smarter animals are universally entitled to understand it either.

There's some discussion of math skills in the article, but the headline courses with huge jumps in failing grades (CS10 and 61A) are pretty math-light. The former is "CS for poets," the latter is the first CS class for majors - lots of work on scopes, recursion, basic data structures, and, at the end, a simple Scheme implementation.

Understanding math well might help a bit, but they're the least mathy classes in the core Berkeley CS curriculum IMO.

Can confirm- I took both of those classes and don't remember any math beyond big O, which only technically counts.

And even that is much heavier in 61B IIRC (speaking as someone who did as well!).

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