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I've come to the conclusion that my brain's "algorithm"y, rather than "equation"y. My scores on (especially) spatial reasoning tests are excellent so one would
by asark 7y ago
I've come to the conclusion that my brain's "algorithm"y, rather than "equation"y. My scores on (especially) spatial reasoning tests are excellent so one would think I'd have a leg up in mathematics, but trying to read typical "mathy" (equation-heavy) writing makes me feel the way I assume dyslexics do, even when it's something I'm pretty familiar with.
Algorithms, though? No problem. Programming in typical Algol-family languages & similar came easily to me. The "tough" early topics? Pointers, recursion? Not even a bump in the road, totally natural. To this day, though, the ones that look more like mathematical writing (Haskell) are really hard to read, let alone write. I can get all the concepts at play in a piece of Haskell and still not be able to keep the syntax or meaning of the code itself straight. When I do want or have to read mathematics of any complexity whatsoever, I only make headway by converting it to something more algorithmic as I go ("OK, so what does this term or whatever do to any other values passing through, here?")
- new4thaccount 7y agoYou're not alone. The Math symbols are easy once you learn them (at least the subset I know), but it was challenging getting there. My field has a lot of dense math that makes the pyramids look simple (ok I exaggerate, but there is a lot going on). The only way I've been able to really grok it is by writing software to do it. Now that I know what's going on, the math notation is useful in that it explains the problem in a succint way. I think Calculus via Python with nothing but the stdlib and Matplotlib would be a better way for me to learn to be honest.