This argument has been beaten to death before AI: Ever since calculators were able to do math, students have been wondering why they need to learn how to do all of this math manually when they could get the same answer from a calculator.

The reasons become more obvious only when you get deeper into a field where the math gets too complex to get a simple answer out of a calculator. If you never learned the basic concepts, you can’t progress to the more difficult topics because you don’t have a good understanding of the foundation.

That’s why changing goals to only look at the output doesn’t work for educating kids. Now that they can have ChatGPT answer every question they might see on a middle school or even high school exam, you could conceivably get all the way through high school graduation never having learned a single thing other than how to copy and paste between the assignment and ChatGPT.

Then what happens in the real world when that student needs to learn something new? It’s obvious: They’re going to try to put the problem into ChatGPT and then give you the result back. They don’t have any foundational tools to do anything else. They haven’t even learned how to learn because there was always an easy way out. Why would anyone hire a person who can only act as an interface to ChatGPT? They won’t. They’ll use ChatGPT themselves.

My unpopular opinion is that some times hard work, memorization, doing work manually, and yes, even testing, are necessary to build up an education and thinking foundation. I don’t believe it can all be replaced by ideas about challenging students to get results and then ignoring how they arrive at the result. I’ve worked with kids enough to know that they are more resourceful about finding lazy ways to pass a test than you could ever imagine.

What is your opinion on using an LLM to provide immediate feedback/grading at scale such that students have to muster their own answers but can check them quickly, compressing the feedback loop and allowing for more iterations?

Students still have to muster their own answers, but the LLM is used to minimize the confusion or uncertainty about the quality of the answer and the time to wait for that clarity.

My understanding is decades of research long before AI has shown the benefit of timely constructive feedback on the learning process. Why aren't all educators tripping over themselves to use LLMs to maximize access to timely constructive feedback?

Great comment! I'm sharing this around my circles.

Analogies with calculators have a big problem. The calculator has no intelligence of its own. A model does. (Yes, it does. You have to be either delusional or willfully ignorant to argue otherwise at this point. Take a calculator to the IMO and see how far you get.)

So there are, or at least there will be, cases where it's actually a good idea to delegate your thinking to an AI model. Students who aren't taught to acknowledge that possibility and keep it in mind are being done a disservice, just as if they were taught to treat today's limited, early-generation LLMs as a first resort.