My colleagues say "We must fully embrace AI as a tool". I agree. But how do you teach it? It's a moving target, and you can't even give homework like: "Research <this topic> with an LLM of your choice, and submit the transcript" because they can do that, or they can just copy the task into an LLM and have the LLM do it. It becomes meta quite quickly.
And independent what and how we teach, we have to change how we assess a students learning result:
The first thing we have to change is that homework needs to be completely ungraded. Reviewed and corrected, yes, but not part of the grade. That's the only way to make sure that people who don't want to cheat have to cheat anyway to compete with those that do.
Second, all exams have to be in person. Online, cheating is so trivial it's not even funny (many students are so stupid about it that we have a pretty clear idea what's going on). In person, we have maybe 2-3 years until we have to make sure its proctored and people's glasses are checked. I think in less than 10 years, local mobile AI will be good enough so even a Faraday cage will not help.
Maybe we have to go to oral tests only.
Of course, none of this scales. Some of our intro courses have a thousand students.
Any ideas are much appreciated.
Any ideas are much appreciated.
Oral exams graded by LLMs? Scale with the improving models. Based on GPQA Diamond results they're mostly at PhD level for subject trivia anyway.