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We were left to figure how that part ourselves, on our own. And we did, confusedly, awkwardly. From direct experience, through trial & error. It was horribly inefficient. Because, naturally, the meta is a science. It can, and should be taught.
Of course, it is learning "how to learn" and "how to solve problems" that really matters (or even the more specialized "how to prove theorems"). The content -- specific pieces of knowledge -- is unimportant. I've already forgotten all of the theorems. Only the meta remains.
Agreed François! Is there a specific resource that you feel covers the meta well?
Hopefully this will change, in part thanks to @StanDehaene and his latest book which I highly recommend (plus Consciousness and the brain)https://www.penguinrandomhouse.com/books/579922/how-we-learn-by-stanislas-dehaene/ …
Generally those things come through practice. Someone can understand something yet be incapable of implementing it, I’d much prefer a more targeted coaching style with relation to exams over time spent explaining how one should think.
Why do you get resentful then when we call deep learning neither deep nor learning?
Would you kindly be able to provide a link to a sample of these type of Putnam-style exams
But does the meta remain because that is the part you taught yourself? That was the part you learnt through trial and error, and gaining experience. Maybe that is what learning really entails.
Required reading from my high school calculus teacher: “How to Solve It,” by George Pólya
you are not taliking about flash and the other metas right? 
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