“America’s math curriculum doesn’t add up,” observes Steve Levitt.

Please listen to (or read) this week’s Freakonomics podcast. I will wait.

No, actually, I’m going to discuss it without making any prior assumptions that you have listened to it or read it:

If you’ve been reading this blog for awhile, the Freakonomics podcast will remind you of some of my previous posts, such as the one about Dan Meyer, or the one titled “When am I ever going to use this?” Steve Levitt — and especially his guest, the great Jo Boaler — make many legitimate points in the podcast.

I also have some reservations about them.

First, four legitimate points (imho), two from each contributor:

  1. Levitt says “the math tools I actually use, and the math tools I see people around me actually using, seem to have nothing to do with what my kids are learning in school.”
  2. Boaler says “maths still looks in classrooms pretty much as it did in Victorian days.”
  3. Levitt says “the biggest change in the world over the last 50 years has been the emergence of data and computing, and it strikes me that the math curriculum hasn’t kept up with that at all, both in terms of thinking about what students need to succeed in the world, but even, maybe more broadly than that, about what role humans play.”
  4. Boaler says “statistics is really important, as a course, but is under-played. This is a fifth of the curriculum in England and has been for decades. But here in the U.S., it’s sort of a poor cousin to calculus… Teaching is always very hard to change because people learn it from their own school days, and then they want to become the maths teacher they had.”

Every one of those points is worth thinking about. And they’re valid. But they’re not the whole story. In particular, they seem to suggest that the knowledge and skills taught in middle school and high school will be retained ten years later, and we know that that isn’t so. Unless you’re in a vocational program — and there’s certainly nothing wrong with that — in fact, more students should be in such programs, but that’s just not the topic of this post — unless you’re in a vocational program, you’re not learning specific job-related skills in math or English or history or biology or whatever; you’re learning ways of thinking, you’re learning general approaches to learning how to learnThat’s what will be retained. That said, we do need to include more statistics and have a more data-oriented approach, especially for students who will soon turn 18 and will become voters!

I recently wrote about the four units that students learn in their Quantitative Reasoning course at the Crimson Summer Academy. As this course was designed to be both interdisciplinary and applied, it will be instructive to see how it addresses Levitt’s and Boaler’s concerns. And we may need to have a cold dose of reality splashed in our faces. The original conception of the course, in 2004, included six units rather than the current four: three have been (reluctantly) dropped, and one added. As pointed out in the podcast, the reality is that an ideal curriculum runs into the constraints of calendars, college board tests, and expectations of subsequent teachers. Now none of those will be as rigid as you might assume, but still they can’t be ignored. So here’s what we did: we reluctantly dropped the units on probability, statistics (though we incorporated a bit of statistics into the voting models and demographics), and game theory — not that we thought they were unimportant, but we simply didn’t have enough days to do justice to them. And we added a unit on trigonometric models, because of advice from Harvard math professors (and our alumni) concerning our students’ weak points when they took calculus later on.

At CSA, I have to concede, we have the luxury of supplementing our students’s regular math experiences rather than being their entire experiences.


Categories: Math, Teaching & Learning