To fellow professors, when you're suspicious my suggestion is to appeal to their honesty (like "let's be honest, how much of this code is yours, and how much is ChatGPT's?") and offer some empathy and understanding (like understanding they may had multiple deadlines in the same week, etc.). Nevertheless, don't miss the chance to give them the lesson on how is the correct way of doing things. The way to catch these students is to find the same signs of yesteryear copying from other students (which in essence is what copying from an LLM is, although the number has increased because they found us professors unprepared for the volume).
The other two groups also used LLM but in a high-level and architectural way. They were clearly responsible for the code (even if they didn't wrote it 100% manually) and could explain their reasoning and strategies used to solve the problems.
Me and my colleagues still have a lot of projects to review, and I asked them to keep the score of the number of projects like these, but so far, the score is 1 in 3 (33%).
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?
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.
It was fine.
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.