Within a single course, the heterogeneity comes from how to actually do things, how to understand what you did, how to understand what other people are doing when they do the same things, how to think about changes to those patterns when the task changes a little, how to write about what you did, how to talk about what you did, how to read/listen to other people talking about what they did, and many other aspects of understanding the material. None of these are actually the same thing; the unifying thread in a given content area is you might have to memorise the same jargon and diagram conventions for each of those different tasks.
A given course may also be somewhat heterogeneous in its content; for instance, a typical AI course might include algorithms and strategies based on discrete probability, others based on highly-architected structural representations of knowledge, and still others based on self-rewriting code. At a lower level (high school), you might consider a biology teacher, who gets to cover cellular biology, taxonomy and cladistics, genetics, anatomy and physiology, and possibly some other things I'm forgetting right now.
Between courses, teaching is heterogeneous because you're teaching a lot of different things. Even if it's all "math", for instance, there's a fair amount of variation between algebra, geometry, logarithms and function analysis, differential calculus, vector calculus, trigonometry, and probability and statistics, and that's just among the courses often taught at the high school level.
And all of that is only talking about the things taught, which speaks directly to the question of evaluation. But on the subject of heterogeneity, classroom dynamics can vary significantly just between semesters at the same school, not to mention between different schools, and within a single classroom you have students with assorted learning disabilities (documented or not) and simply different learning styles—some are more verbal, some need to see it done, some need to do it on their own first, some benefit more from working together, some really need to try it first and crash and then hear the way they were supposed to do it and try again. It's a lot more than just "a few extra geniuses or dunces".
Teaching is pretty damn heterogeneous. The best teachers I know are, and have to be, among the most mentally-agile people I know.
"It makes sense to compare # of students who can integrate in 2012 to # of students who can integrate in 2011. It's a noisy measurement, but it works. How do you compare search engines to quantum mechanics simulations?"
In contrast, my current programming job was to build a visual search engine, my last was to trade stocks. Before that it was research in MRI, before that quantum mechanics simulations. Who knows what my next will be?
It makes sense to compare # of students who can integrate in 2012 to # of students who can integrate in 2011. It's a noisy measurement, but it works. How do you compare search engines to quantum mechanics simulations?
As for my teaching, the data I have suggests I was average. But there was not enough data to get a good picture - I only taught a couple of classes with standardized finals.