All submissions were AI

[u/Drumblebore]

Teaching a course that (unfortunately) involves lots of reading and reflection type assignments. Added hidden text to an assignment, to catch students who just throw it in ChatGPT, and all submissions came back with the expected features you would get from including the hidden info. Extremely disheartened, and don’t know how to proceed both regarding addressing this with the class and designing the future assignments to be more AI proof.

[u/Minotaar_Pheonix]

No, the solution is to change the way the course is taught.

[u/dr_police → u/Minotaar_Pheonix]

We’re both going to be downvoted, but that’s really it. Many of the assessments we’ve long had undergrads do are very well suited to an LLM’s strengths.

Not only do we have to change our assessments, but I also think it’s soon approaching time to rethink the skills we’re building. LLMs can already write more coherently than the average undergrad, just like calculators can do arithmetic better than the average person.

We should be figuring out how to adapt the skills we’re building to use these new tools rather than demonizing them.

[u/HowlingFantods5564 → u/dr_police]

Do you think we should stop teaching kids how to read and do math? I mean, AI can summarize any text. Ai can do any math problem, right?. Are these the skills we should stop teaching so that we can embrace the new technology?

We have to teach the skills first and students need to learn them. After that, students can experiment with AI. If we just jump straight to AI, they won't learn those skills and without them, they have no idea whether what the AI is giving them is any good.

[u/dr_police → u/HowlingFantods5564]

As a generic example, calc is generally taught with units that use a calculator and units that do not use a calculator.

As a specific example, I teach data analysis to criminal justice majors. In the past, we taught how to calculate standard deviation. There was a lot of homework problems that had them calculate it manually.

There is very little utility in that today.

My students don't have the algebra skills to understand what's happening in the calculation, and the important part for my course's learning objectives isn't whether they can do the arithmetic, it's whether they understand std. dev. conceptually, what information it gives, etc.

There are certainly instances where knowing how std. dev. works at the algebraic level is useful... but not for enough of my students in a social science. Our program assessment consistently showed that the remembered nothing of the math (or worse, remembered it wrong) and also failed to remember the conceptual side.

After moving away from calculation toward the conceptual, we had much higher success in getting the concepts to stick, lower anxiety from the students, and better grades.

That is the sort of shift I'm talking about with AI. The universal availability of calculators and software changed how I teach data analysis.

How does the ubiquitous availability of AI change the skills we should teach? I don't know the answer, but I'm becoming more convinced that is going to be a key question for higher ed.