Real discourse was not carefully crafted to test you.
So, when something is off in real discourse you can usually dismiss it or apply a correction yourself, but when you find it in a test you have to understand the person writing the test and what their intention was.
I hate academic problems because too often the answer depends on how you interpret that intention. Granted, the majority of questions can be guessed pretty easily, but then you lose sooo much time on the ones that aren't.
And/or end up arguing with the writer afterwards, and it takes a day or two before they admit that indeed they made a mistake in their question. Since those mistakes in questions are possibel too you have to decide what they want.
Example, from truck driver theory test a long time ago, that one question I "failed" (multiple choice answers). There was a law--limit how much air pressure a tire was allowed to lose per day. I knew that limit. Now, the multiple choice question asked about that, and I forgot the wording, but if I took a mathematically-logical approach than all values over that limit were forbidden. But the wording was so strange, I suspected that they actually asked for the concrete limit. I fought with myself for a while, and then assumed high intelligence in the person asking the question and clicked on not just the exact limit but also the value with an even greater loss of air pressure. Too bad, I guessed wrong. I will be mad about this until the end of my life, even if it had no impact.
There is also the problem that those academic questions want to steer you down some narrow corridor. The more you know about the problem and its complexities the harder it is to answer some of those questions! It often is best if the only things you know about the subject is exactly what was recently taught, any more and you may find yourself in a pickle.
Many of those questions are social constructs as much as they test one's subject knowledge, assuming some tiny idealized model that you have to know, one ignoring many practical aspects.
There are some contexts, academic or professional, where questions are posed carefully and specifically, but these are narrow contexts.
A useful general purpose assistant needs to be able to find what's relevant among what's irrelevant.
Excellence at just solving math problems that are especially well specified can be a useful domain assistant (no small win!), but is not the same thing.
That said, if you've got a hundred billion dollars betting on your AI project achieving AGI, you benefit a lot by conflating those contexts. In that case, grinding on formal SAT, LSAT, GRE, etc problems amounts to tuning for microbenchmarks rather than real world use cases.