Random internet people explaining math better then math teacher
Random internet people explaining math better then math teacher
I mean you've just translated from a language most people don't speak to a different language most people don't speak
A simpler language many people know (math) to one of the imfinite dialect of a language most people don't speak.
Left representation is definitely more readable and understanded by more people
I don't know about that, I know a lot of successful programmers who never took calculus.
The barrier to entry for programming is considerably lower today than it was even 15 years ago. Lots of kids, myself included back in the day, were learning basic control flow in languages like C, Python, or JavaScript long before taking advanced math courses in high school.
Left representation is definitely more readable
Hard disagree. The right can be read linearly. You know, the way humans read.
I sucked balls at precalc, but I'm pretty decent at programming. I suppose, with enough practice, one becomes "fluent" in mathematical notation, but the C-style language definitely reads more naturally. The mathematical notation is what I'd call "too much abstraction."
and understanded by more people
I don't know the stats, but I have to imagine, by this point, there are more programmers than mathematicians.
Part of what's going on here is that math notation is ... not good. Not for understanding, readability or explanation. Add in the prestige that surrounds being "good at math" and "being able to read that stuff?" and you get an unhealthy amount of gate keeping.
Whenever I've been able to find someone breakdown a set of equations into computer code has been a wonderful clarifying experience. And I think it goes beyond just being better at code or something. Computer code, more often, is less forgiving about what exactly is going on in the system. Maths, IME, often leaves some ambiguity or makes some presumption in the style of "oh, of course you'd need to do that". While if you going to write a program, it all needs to be there, explicitly.
I recommend Brett Victor's stuff on this: Kill Math
That's absolutely the opposite for me. Math language is extremely good in summarizing extremely complex logic in few lines. We have huge ML projects with a looot of logic, that can be summarized with either 10 lines of math or 100 lines on English overwhelming cognitive complex.
Math is the best language we have for logic.
This meme is the proof, left representation is more concise and clearer than the for loop, and therefore allows for easily represent much more complex logic, while for loops become quickly unreadable (map and reduce are for instance more readable)
It's funny, with the increase in use of numerical models, so much math has been turned into computer code. Derivatives and integrals as well are defined by finite difference formulas that serve as the basis for the notations. The point of them isn't to explain, it's just to simplify writing and reading it. I agree it can be a bit obtuse but if you had to write out a for loop to solve a math equation every time it would take forever lol
Well this is where the computing perspective comes in.
Programming culture has generally learnt over time that the ability to read code is important and that the speed/convenience of writing ought to be traded off, to some extent, for readability. Opinions will vary from programmer to programmer and paradigm/language etc. But the idea is still there, even for a system whose purpose is to run on a computer and work.
In the case of mathematical notation, how much is maths read for the purposes of learning and understanding? Quite a lot I'd say. So why not write it out as a for loop for a text/book/paper that is going to be read my many people potentially many times?!
If mathematicians etc need a quick short hand, I think human history has shown that short hands are easily invented when needed and that we ought not worry about such a thing ... it will come when needed.
Than
Haha, touché. I just used the xpost function on the original though. I hold myself blameless.
You can edit it I think (not sure if it works for crossposts)
Yeah, cool, except that the first time you encounter these (probably in high school) you'd be a minority if you somehow already know programming.
Edit: and if you somehow already know programming, chances are you've encountered some math in the process.
I learned basic programming skills around the time I was taking algebra in middle school. This was in the '00s.
For me, code was a lot easier to understand and going forward I would write programs that implemented the concepts I was learning in math classes in order to better comprehend them (and make my homework easier). I demonstrated enough aptitude here that I was allowed to take two years of AP Computer Science in high school despite lacking the math prerequisites.
I know a lot of programmers who think they are "bad at math" but really, they struggle with mathematical notation. I think a big reason for this disconnect is that mathematical notation prioritizes density, while modern programming languages and styles prioritize readability.
These different priorities make sense, since math historically needed to be fast to write in a limited amount of space. Mathematicians use a lot of old Greek symbols, and single-letter variable identifiers. The learning curve and cognitive load associated with these features is high, but once mastered you can quickly express your complex idea on a single chalkboard.
In programming, we don't need to fit everything on a chalkboard. Modern IDEs make wrangling verbose identifiers trivial. The programming languages themselves make use of plain English words rather than arcane Greek letters. This results in code that, when well written, can often be somewhat understood even by lay people
Maybe it's the order that you learn it in. For me the left side is the easy to read and understand one.
I am with you
Single-letter constant/variable names are strongly discouraged in programming but standard in math.
Math standard practices were created at a time when everyone was doing them by hand. Absolutely no one would write out “coefficient of gravity” or whatever 20 times by hand while trying to solve a physics equation.
Single letter variable names were common in early programming for basically the same reason, only with typing.
Ever since the proliferation of autocomplete and intellisense in programming IDE’s, typing a 4-word-long variable name has become a few key letters and then hitting tab. Ever since then, code readability has trumped the desire to type out fewer letters.
Complicated math generally contains a lot more explicit definitions of the variables involved, either in English or with previously established notation. Writing proofs is more about communicating the result than it is proving it. In that sense it is similar to programming with an emphasis on maintainability.
Sure, the variables have explicit definitions somewhere, but it still requires you to go back and reference them every time you forget what y stood for.
With more verbose identifiers like in code, you don't need these reminders. The cognitive load is reduced, because you no longer need to hold a table in your head that correlates these random letters with their definitions.
I mean Freya Holmer is a pretty great teacher, so not surprising. I learned vector math watching her videos.
One of my math teachers explained it exactly like this. ‘For the people who know how to program: this is the same as using a for loop’.
Math is a language, code is instruction. The language of math is geared toward efficiency and viability for abstractions a layer higher (ad infinitum). Once you are familiar with the language, the symbols take a life of their own, and their manipulation becomes almost mechnical, which reduces the cognitive cost for your mind to operate at the current level of abstraction, so you can focus your mental power on the next level of abstraction, and try to figure out something novel. You can of course unpack the compact language of math into the more plain -- in a sense more "flat" -- form of code instructions; the purpose is different: its more about implementing ideas than creating the ideas in the first place.
I love this!
I struggled with higher math in high school until I started learning how to code. I was lucky and had math teachers that encouraged me to learn this way.
I would love to see a full calculus course that teaches you in code before teaching you the proper notation.
One of the worst things is a teacher who knows his material so well that he can't dumb it down enough to explain it to someone who literally has never seen that notation ever before.
A teacher without empathy is a terrible, awful thing that can turn students off so fast.
I went to get my degree later in life and I would butt heads with this one particular math teacher all the time who admitted was extremely intelligent, but the entire class was lost because he could just would not break from his predetermined notes and lesson plans. Everyone else in that class was 18, 19 or 20 years old and too naive or timid to voice their concerns. I was considerably older and paying dearly for these classes, so you better believe I refused to just let issues slide. I'm sure some teachers would think I was a nightmare student, but I wasn't trying to be disruptive - I was simply trying to learn and this guy was just bad at it with 3/4 of the class dropping out eventually.
Ohhhhhhhhh
Meta: I love this thread. It gives me hope that Lemmy has the critical mass required already. I can imagine this discussion taking place in r/math, and there being many times more comments, but the substantial points are all hit here. :)
tbh, I am not sure what's more scary, the LHS or the RHS
Check out Eddie Woo on YouTube.
Freya is awesome. Nearly everything I know about shader code I learned from her YouTube channel
A maths major could point out edges cases where the maths terminology works but the computer code break, but for broad-strokes purposes they’re the same.
what? they're just
forloops (actually they're better described as reduce operators, but those are not so friendly either). if you mean infinite bounds, it's just not finitely terminatingIf the bounds are infinite then it's defined by a limit of partial sums, which isn't the same as a non-terminating algorithm. It would be pretty tough if we couldn't evaluate limits. It's also important to understand limits as being a precisely defined operation as opposed to a way of saying "and so on."