So, they don't realize that there's kind of another level of understanding beyond that (when to optimize vs. how to optimize)
There's also the fact that some people just like optimizing shit for selfish or even slightly nefarious reasons. Some just like doing it because it's fun. Others like it because it gives them visible and easily quantified "wins." On the rarer and more nefarious side of things, they may enjoy now having "ownership" over a piece of complex code that only they can understand....
It's also rigid by design and (probably) necessity: students don't typically encounter unknown, unchanging, and evolving constraints and requirements throughout the project. Lastly they are not typically maintaining a medium/large codebase in conjunction with other engineers.
So you tend to get these smart kids don't know when to optimize. They can make a 15-line function "faster" but they don't have a sense of the impact this has on a larger project and they don't know how to weigh the impact of an optimization vs. the effort involved and future complexity it might incur.
The lack of knowledge would be fine on its own, but back to the Dunning-Kruger effect: they typically don't know that they don't know this stuff.
Not sure how you change that at the CS education level, honestly. At the very least you could stress to the kids that in the real world you have conditions and goals much different than in CS classrooms...
