One of the great things about math is that it lets us surpass our own intuition. The spatial intuition we evolved in the wild doesn't work well for a number of things, which is why symbols and abstraction are so useful in the first place.
We don't need mathematics to figure out how a swinging pendulum works; we can do that intuitively. (Actually, this isn't completely true, but we can at least get the general idea.) Simple problems like that are worked out in classes so that students can get used to the mathematics. In domains where our intuition fails us - e.g. quantum mechanics, high-energy physics, statistical mechanics, not to mention 11+ dimensional formulations of string theory, infinite or fractional dimensional spaces, and more esoteric theoretical mathematics and physics - we rely on mathematical symbols and abstraction to guide us, because our finely honed physical intuition is useless (and sometimes worse than useless).
I'm interested in seeing what the author does with concepts like superposition and n-dimensional spaces. Replacing them with graphs and animations is not going to cut it.
We don't need mathematics to figure out how a swinging pendulum works; we can do that intuitively. (Actually, this isn't completely true, but we can at least get the general idea.) Simple problems like that are worked out in classes so that students can get used to the mathematics. In domains where our intuition fails us - e.g. quantum mechanics, high-energy physics, statistical mechanics, not to mention 11+ dimensional formulations of string theory, infinite or fractional dimensional spaces, and more esoteric theoretical mathematics and physics - we rely on mathematical symbols and abstraction to guide us, because our finely honed physical intuition is useless (and sometimes worse than useless).
I'm interested in seeing what the author does with concepts like superposition and n-dimensional spaces. Replacing them with graphs and animations is not going to cut it.