I agree students should learn how to be efficient with their time to learn the concepts they need to learn and pass the courses they choose to take in the school they’re choosing to attend, knowing the lessons are going to help them in their future careers. If a student thinks learning how floats work isn’t valuable, Computer Science might not be their thing.
It’s not the professor’s job to minimize the student’s effort, it’s the student’s job. The arrangement is the opposite of your implication. The professor’s job is to get lazy students to confront and learn these concepts and have them practice enough to understand the concepts. Having to analyze carefully is the whole point.
I also agree about the first place you should go is to use all the tricks you have to make writing code faster… at least in business. I’m not sure that applies in school. But either way, this is precisely why school should have students practice things like floating point analysis and low-memory programming until they are part of the students’ bag of tricks, until they can do high quality engineering fluently.
BTW, just using doubles in the name of not having to analyze is not particularly great outside of school either. That does not fly where I work now (on GPU ray tracing), and would not have been acceptable when I worked in CG films or video games either. You might be underestimating how expensive doubles are. If you don’t know whether you need doubles, you probably don’t. If you have a problem that needs more than floats, and accuracy is that important, then you’ll need to justify why doubles are enough, so in practice you’ll have to analyze carefully anyway.
Maybe you’re just teasing me with the BigFloat suggestion, I can’t tell. Since they might be orders of magnitude slower than floats, they’re rarely justifiable as a robustness replacement, especially by someone who hasn’t analyzed carefully. That might be a firing offense at some jobs if done more than once. :P