I mean, in this context I agree. But most people doing math in high school or university are graded on their working of a problem, with the final result usually equating to a small proportion of the total marks received.
This depends on the grader and the context. Outside of an academic setting, sometimes being close to the right answer is better than nothing, and sometimes it is much worse. You can expect a human to understand which contexts require absolute precision and which do not, but that seems like a stretch for an LLM.
I think current LLMs suffer from something similar to the Dunning-Kruger effect when it comes to reasoning - in order to judge correctly that you don't understand something, you first need to understand it at least a bit.
Not only do LLMs not know some things, they don't know that they don't know because of a lack of true reasoning ability, so they inevitably end up like Peter Zeihan, confidently spouting nonsense
But most people doing math in high school or university are graded on their working of a problem, with the final result usually equating to a small proportion of the total marks received
That heavily depends on the individual grader/instructor. A good grader will take into account the amount of progress toward the solution. Restating trivial facts of the problem (in slightly different ways) or pursuing an invalid solution to a dead end should not be awarded any marks.