There are several reasons for this:

1. Cheating in CS is easier to detect. MOSS [2] (authored by CS professor Alex Aiken) is a very effective tool at detecting plagiarism in coding assignments. Personally I witnessed more honor-code violations in math problem sets, but there was no feasible way for professors to detect this.

2. Problems in programming assignments are (usually) very tangibly wrong. I can bullshit my way through an essay with shoddy research, I can hand-wave a proof that is definitely wrong but will probably garner at least some points. But when your program is crashing or not compiling, and the due date is approaching, it produces a very immediate and undeniable sense of failure and pressure to cheat. The thing is, many students would get a decent chunk of credit even for failing code, but this is not immediately obvious.

3. The ability to cheat is more available. Math problem sets tend to change quarter by quarter. It's basically impossible to cheat on a prose essay short of straight up paying someone to write it for you, or fabricating sources. But for CS classes, especially at prominent universities, there are plenty of solutions online. Much of it is people who aren't event at Stanford implementing the assignments for fun or self-learning, and sharing it with their peers. Which, to be clear, isn't unethical or bad - it's the responsibility of Stanford students to refrain from looking at those solutions. But nonetheless, it's a contributing factor.

1. https://stanforddaily.com/2015/03/29/increase-in-cs-106-hono...

2. https://theory.stanford.edu/~aiken/moss/

The whole situation sucks for both students and teachers. Teachers know that the knowledge they're going to great effort to convey isn't going anywhere. Or at least, it's landing in far fewer fertile brains than it used to. Students are squeezed because part of the university experience is being forced to adapt to an academic load, and as a result change yourself in ways that benefit you (or at least produce learning!) There have always been relief valves -- not just forms of cheating, but blowing off a study session by using game theory on your grade or going to a tutor or taking easier classes or extending your stay at the school. But now there's this huge giant relief valve in the form of a shiny LLM that is always available, particular at 3:45am when your project -- the one you've steadfastly refused to use AI on thus far -- is due the next day. The schools have tuned the pressure for the old set of options, and it's not clear that there's a new tuning that maintains anywhere near the old level of learning.

I guess my question is: of those students who were flunked for cheating, how many of them were learning despite their cheating? (And how about the students who were cheating but not caught?) Also, what levers are there to move more students towards learning even with the chatbots present?

I'm sure these questions are being debated. I know Garcia personally, and he is very invested in his students learning. The title of his Joy course is legit. So I'm sure the profs have ideas around this, though clearly not happy ones. Perhaps I'll ask him.