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by ToucanLoucan
360 days ago
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> Evaluation should primarily be done in the classroom without access to AI. I grant that I have no evidence for this claim but: I don't see how it's reasonable to teach a subject with access to such a powerful tool and then to remove that tool to assess what the student has learned. My primary uses for LLM, limited as they may be, are explicitly about things I do not care to know, and I find it difficult to hold in my head how ChatGPT is going to help me learn anything in such a way where my understanding of it and use of that knowledge is not hinging directly on continuing to have access to it. And, more broadly, there's reason to suspect that the student will have access to it after that class ends, so it runs up against that old axiom of school meaning to prepare you for working life. My math classes never interested me, I did the work on calculators whenever possible, and sure I have decent mental math skills, but I still pull out a calculator (app) for everything because... my meat brain just isn't as good at this task as this silicon one, and not only does every smartphone in existence have one, if you really don't want a touchscreen version, they can be had at any retailer in America for like $5-10. |
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AI can be used in ways that lead to deeper understanding. If a student wants AI to give them practice problems, or essay feedback, or a different explanation of something that they struggle with, all of those methods of learning should translate to actual knowledge that can be the foundation of future learning or work and can be evaluated without access to AI.
That actual knowledge is really important. Literacy and numeracy are not the same thing as mental arithmetic. Someone who can't read literature in their field (whether that's a Nature paper or a business proposal or a marketing tweet) shouldn't rely on AI to think for them, and certainly universities shouldn't be encouraging that and endorsing it through a degree.
I think the most important thing about that kind of deeper knowledge is that it's "frictional", as the original essay says. The highest-rated professors aren't necessarily the ones I've learned the most from, because deep learning is hard and exhausting. Students, by definition, don't know what's important and what isn't. If someone has done that intellectual labor and then finds AI works well enough, great. But that's a far cry from being reliant on AI output and incapable of understanding its limitations.