I think you're overlooking that whys and whens are still knowledge leading to understanding of a concept, and they tend to come before the hows. You want to understand why you're using the algorithm before you begin working on how to implement the algorithm. As an extreme example, consider us teaching the Quicksort and the Bogosort as pure implementation but without explanation on usage. Granted, this is unlikely to ever happen, but it serves to illustrate that this kind of knowledge is part of the understanding of any algorithm, or even further, any concept.

Now the context you're referring to regarding your "implementing ols" example seems to be largely assorted trivia to be honest. They don't know the answer, they're filling in something, and have done so through highschool and then college because something might get mercy marks. I'd like to disagree on giving that the moniker meta-knowledge, it's losely tied factoids at best.

I completely agree that deep understanding of concepts is incredibly important, but i think it's unlikely we'll see large scale change in that attitude. The way I see incentive structures for students, making that shift unconsciously is disincentivised, since moving from a cramming schedule to a more thourough approach puts you even further behind temporarily which hurts your grades. The fact that any kind of disaster or holdup could push you into the former style of learning is what I think causes the entire thing to tilt.

Whilst there are a couple more points I'd love to adress, I kinda want to question your assertion that this is a current generation thing. That is an awfully easy assertion to make, can usually be said about the asserters generation as well and all generations before that. Unless there's more concrete data to back that part up, i think it does the present generation plenty of injustice.