[kuschku]

> The other two groups also used LLM but in a high-level and architectural way.

Sounds more like the score is 3/3 (100%)

Would you have accepted them cooy-pasting code from libraries together to build their project? If not, why is using LLM generated code different?

[newswangerd]

Using AI to inform architecture doesn’t seem so different from googling architecture in this case. Architectural patterns are mostly well understood and well documented these days and are something that you could piece together via Google search pre AI. The thing that AI brings to the table that wasn’t google able in the past is code generation. Previously you had to understand the architecture patterns to implement them yourself, but now the AI can just do it for you.

[jventura]

> Would you have accepted them cooy-pasting code from libraries together to build their project?

Yes, if they are "responsible" for the code delivered, where responsible means they understand the code, the architecture, the decisions made, etc.

In this case, the students had to invent multiple strategies to solve a specific problem. The "successful" groups did a mix of generated and hand-crafted code (don't know percentages), implemented different strategies and knew their plus and minuses, could change the code in a timely manner to accommodate some of my requests, etc. The "unsuccessful" group couldn't do any of that.

I'm not anti-AI (and really, what could I do if I were?) since I use it myself, I'm just anti-slop, especially from my students.

But in reality I've been slowly transitioning from group projects (for a subset of the grade) to "practical tests", where they must implement a significant subset of a larger project in a 2h class. Still experimenting though.

[cushychicken]

> Yes, if they are "responsible" for the code delivered, where responsible means they understand the code, the architecture, the decisions made, etc.

This is a good principle to maintain, I think.

I'm not a professor, but I manage a team of about a dozen people. The maxim I have is: "You're responsible for anything that hits git."

Don't care if the LLM generated it, or the LLM told you if it's a good idea. If you commit it, you are endorsing it as a good idea - so you're the one I'm going to ask about it. I see the same principle at work in your pedagogy.

> I'm not anti-AI (and really, what could I do if I were?) since I use it myself, I'm just anti-slop, especially from my students.

This hits. Especially this part:

> and really, what could I do if I were?

My completely unsolicited opinion: you're doing a responsible thing by teaching these students how to use AI as a reference, and keeping them honest about not using it as a substitute for their own critical thinking.

[lokar]

I'd say most of my CS classes (in the 90s) had us write out code by hand, on paper, during in-class exams.

It was fine.

[dysoco]

Usually you get both kind of assignments, short exercises in paper without any help whatsoever and more open, larger take-home assignments where you can usually use external help.

[archagon]

> and really, what could I do if I were?

I’m not sure what you mean. Have a no-AI policy and fail those who ignore it. If students lie, discipline them appropriately for cheating.

[jventura]

How could I realistically enforce it? These are projects students do at home..

[archagon]

Same as other instances of cheating? A lot of students copy from each other and don't get caught. If anything, LLM-isms seem a lot more obvious, especially if the students are trying to avoid thinking or doing work.

Anyway, I'm not a CS professor, so I'm just venting.

[yubblegum]

He explains why in his comment. Read it again, carefully. Or ask an LLM for an "explainer"..