This sounds like a good strategy for mastering and memorizing a pattern of behavior, which is the demand in most grade school and college math courses. It's nothing like what higher mathematics demands, which is much less about rote memorization and much more about deep understanding of the intricate interconnections between a comparatively small number of concepts.
Put another way: math isn't really about memorization, either of behavior patterns or of facts. That's why I've been confused and somewhat skeptical about the utility of flash cards for learning higher mathematics.
> Put another way: math isn't really about memorization, either of behavior patterns or of facts.
I mean, on the surface level that's true. But obviously we could reductio ad absurdum this claim - would a mathematician be able to work if they lost all their memories every day? Clearly not!
It's something of a matter of how good is your memory, plus how actively you use it. How many people who complete PHDs can still prove the PHD 10 years later? Not many. Which is not to say that you can or should use Anki to learn something as complicated as a PHD dissertation, that clearly won't work. But when learning a new topic, it's a very helpful tool, and it makes sure that even if you now focus only on linear algebra, you'll still recall at least the basics of, say, set theory, which most mathematicians who don't actively study probably don't use much.
> It's nothing like what higher mathematics demands, which is much less about rote memorization and much more about deep understanding of the intricate interconnections between a comparatively small number of concepts.
Well Anki certainly won't help you actually do higher math :) But I find it is surprisingly good at making these weird connections, because in the middle of learning say modern algebra, you'll suddenly need to recall things from linear algebra, and suddenly see interesting new connections. Or things from real analysis, which will make you go "hmmm, so that's why a field is defined this way" or something.
Well, I'm not trying to pitch it or anything. I haven't tried it either for this. I do have a PhD in Materials Science, but it sounds like your experience is different than mine. For me, my experience is like this:
Step 1: Read about stuff people are doing.
Step 2: Read between the lines to understand how it fits into other things I already know about.
Step 3: Evaluate based on my intuition whether the fit is reasonable. Since the data is presumed real, if the fit is bad it usually means I didn't understand the details of what they did. See if I can make the fit with other things I know coherent.
Step 4: If I can explain the fit coherently, consider what problems might be solved by using that connection.
Step 5: Research how that problem is normally solved and why.
Step 6: Go back to Step 1 and keep going until I find something that is actually solved better using my weird idea than it is solved currently.
I am terrible at memorizing, and if I am in Step 3 or Step 4 or Step 5 it's a real roadblock if I'm trying to understand why I can't harmonize the reported data and my understanding and it's because I've forgotten which sites are interstitials in a fluorite lattice. I know the information I need, but now I have to go look it up. Of course this is why people have reference materials, but it's definitely a speed bump.
The important aspects of the work up there clearly aren't about memorization, but it sure helps me actually do it in practice. I really wish I were better at it.
Another thing that this made me think of was using it to remember student/coworker names. Remembering my unreasonably numerous cousins' kids' names would also be nice.
Put another way: math isn't really about memorization, either of behavior patterns or of facts. That's why I've been confused and somewhat skeptical about the utility of flash cards for learning higher mathematics.