I’m a big fan of Freakonomics. I read the book, I’ve listened to just about every episode, and I’ve been consistently subscribed to it longer than any other podcast that isn’t about math or house music. So I was jazzed when they decided to take on math curriculum. Based on earlier episodes about our political parties, the life of a CEO, and behavioral economics, I was really expecting something amazing. After listening to this episode I came away a little underwhelmed as it went to too little depth so they could support a pretty unoriginal, pre-determined solution.

There is a typical line of reasoning proffered by potential education reforms that support their innovations which seems to be used here. It goes like this:

- Our education system is pictured as old and outdated.
- The outdated system could be immediately fixed by the new solution.
- The only thing stopping us from bathing in the revolution are those stodgy old educators, who need to adopt the solution nationwide.

If you look around you’ll notice this idea sandwich everywhere. It’s surprising to see it used here as it violates the principles of basic research e.g. choosing your conclusion before you understand the problem. I won’t go into too much detail about the episode, you can listen to it here. In the episode there was a frustration with the Algebra II homework that host Steven Levitt was helping his 10th grader finish. He then does the whole idea sandwich to suggest swapping out data science for algebra 2 in high school math. There was a question for bringing this to school as a whole. Then a historical summary about math education’s origins. There also interviews with Jo Boaler, and the college board CEO, and Levitt’s cousin who taught a few years. All were ostensibly asked a version of two questions “High school math sucks, right?” and “How cool would data science be?” It seems like stacking the deck for data science, which is fine, as data science is cool, but there is more to what’s wrong with math than just the lack of regression models.

Later in the show they review research done with listeners of the show. They were asked what kind of math they use in their everyday life, and the results imply that data science would have brought more day to day utility. If your audience is full of people who earned high school diplomas, and higher ed degrees, accepting that premise is a bit premature. Everyday math benefits these people regardless of how much they’ve used it. Their career would be inaccessible without the education that their math scores allowed. Their knowledge of math made them competitive at colleges providing them a privilege to ignore math the rest of their life while keeping their benefits in tact. Many people don’t know how to parallel park, and don’t do so regularly, but their knowledge of parallel parking on their driving exam allows them the privilege of a driver’s license. Contrast all of this with someone whose struggles in math prevented them from attaining any of those levels of education. Perhaps they were in a school that didn’t offer advanced math classes, or only offered them to students on a higher track. Perhaps the student was in a class, but the teacher did not teach for equity, leaving many traditionally underrepresented students and special needs students behind. For many, math isn’t just a boring chore. It’s a glass ceiling, locking them into lower income classes while bestowing privilege on others.

I am not arguing for continuing the focus on algebra 2 so that students can take AP exams, I am arguing that math should be decoupled from the privilege society gives it. Earning high math scores is as important for your daughter to compete for scarce seats in colleges as it is for providing day-to-day value. This sucks. Math could be a subject of beauty and meaning for people’s day to day life like art or poetry, if it wasn’t militarized to help people jockey for position. However, competitiveness in education has made math appear solely as a measuring stick for students. Algebra 2 is a class his 10th grade daughter is taking when many take it senior year. This means she must have had algebra in the 8th grade or earlier, and must be in line for AP calculus or Stats, or both senior year. These other classes are pushed into lower and lower grades so that students appear more prepared for college. These students will beat out students from schools without that math preparation. It’s easy to imagine that if his daughter were taking a data science course right now, she would lose out on her competitive edge and face a similarly small pool of options.

Unless dozens of parents start an opt-out campaign, the idea for adopting the class that he proposes would be to talk with college admissions counselors about how to make it interesting, or talk to to current teachers about how to integrate data science into what schools are currently doing. This would be a really interesting route to explore and lead to an interesting episode. The show could pick up with part 2 where they continue the analysis of how math curriculum could change. The first step of that, would be to talk to the National Council of Teachers of Mathematics who wrote a whole book about changing high school math, that is fully in line with the changes proposed in the show and could use the amplification Freakonomics could provide.

There are plenty of other avenues that Freakonomics could take with math education outside of the well worn “Idea sandwich.” There are so many good economics ideas to be discussed around high school math. Scarcity, opportunity cost, competition, etc. Freakonomics is also in a position to learn a great deal of these things. It would have been interesting to hear what the people at University of Chicago Lab school, as a high school, would think about replacing algebra 2, and what the anticipated parent response might be. It also might be interesting to talk to your University of Chicago admissions, and see how they would interpret a data science course on a students transcript who doesn’t go on to take any AP math courses. It would be really interesting to also talk to current teachers who are teaching data science and describe how different the classroom experience is with a current on-the-ground perspective especially considering all of the new stats and data tools that are becoming available (Desmos, CODAP, etc).