America’s Math Curriculum Doesn’t Add Up

Stephen LEVITT: I’m up in northern Minnesota with my family on vacation right now, so this week’s episode is a little different. It’s an episode I initially created for Freakonomics Radio. And actually, not just any episode, my very first try at hosting. 

Welcome to People I (Mostly) Admire, with Steve Levitt.

LEVITT: If you’re a regular listener, then you know how frustrated I am with the current educational system. Today’s episode, which first aired about two years ago, marked my transition from someone who only complains about a problem to someone who’s trying to do something about it. So here’s my question to you: Try to guess what was the reaction when it first aired. Did it spur people into action, make people angry, or was it just completely ignored? I’ll tell you the answer at the end. 

*      *      *

Sophie LEVITT: Rationalize the denominator in the equation: 3 over the square root of X minus 7. 

LEVITT: That’s my daughter, Sophie Levitt. 

Sophie LEVITT: I’m gonna be a sophomore in high school at the University of Chicago Lab Schools. 

LEVITT: These are the kinds of questions she’s working on in her math classes — the questions that I’m responsible for helping her with. 

Sophie LEVITT: Rationalize the denominator in the equation: 3 over the square root of X minus 7. Find the imaginary zeros of the equation: f of x equals 4x to the fourth, plus 35 x squared, minus 9.

Steven LEVITT: Can you tell us what an imaginary zero is?

Sophie LEVITT: No. 

LEVITT: I have four teenagers. I’ve spent a lot of time working with them on their math homework. More often than not, after helping them answer whatever questions are assigned that day, I’m left with questions of my own — questions that I can’t find good answers to. Like, why are we teaching kids these things? Does anyone actually use the math we are teaching in their daily life? Is there any benefit at all to learning this stuff? And are there not more interesting and useful things we could be teaching them? Don’t get me wrong. I’m not anti-math. I use mathematical thinking, statistics, and data analysis constantly, whether I’m writing economics papers, trying to get better at golf, or hoping to pick winners at the race track. But here is the thing: 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. Which makes me think that we must be able to better for our children when it comes to teaching them math. So, after years of idle complaining, I finally decided to try to do something about it. I wrote up a grant proposal, and I convinced the philanthropy Schmidt Futures to give me some resources to put together a small team to explore modernizing high school math. The first step on my journey was to talk to someone who has thought about this subject much longer, and more deeply, than I have. 

Jo BOALER: My name is Jo Boaler. I’m a professor of mathematics education at Stanford University.

LEVITT: So, you’ve written a number of books and mountains of research on reforming mathematics education. Let’s just say that someone made you the math czar tomorrow.

BOALER: I would love that.

LEVITT: What would be some of your first reforms?

BOALER: The curriculum that we teach in maths classrooms was really designed in days that are long past. It was a long time ago that somebody in the U.S. decided to teach what I think of as the geometry sandwich — a course of algebra for a whole year, followed by a course of geometry for a whole year, and then another course of algebra. I don’t know any other country that does that, and it’s part of the problem. So, I would change the curriculum to really reflect real mathematics, and I would also change it to reflect the 21st century, because maths still looks in classrooms pretty much as it did in Victorian days.

LEVITT: In the United States, it was the elite universities that spurred the teaching of higher-level math. In 1820, for instance, Harvard began requiring knowledge of algebra to gain admittance. As a result, secondary schools started teaching algebra. Fifty years later, Harvard added geometry to its requirements, and the secondary schools followed suit. After the Soviet Union launched Sputnik in October 1957, math education became a matter of national security. The math curriculum was overhauled with two very different goals in mind. The first goal was to increase the number of engineers, mathematicians, and scientists. This led to the introduction of higher-level, more abstract math in the high school curriculum. The second goal was to develop a workforce that could do the complex calculations required to support the military and space efforts. Remember, this predates the age of modern computers. 

BOALER: It’s funny, really. When I was in school and many years ago, the joke of maths teachers used to be, you’ve got to be able to do all these calculations because you’re never going to be walking around with a calculator in your hand. Well, turns out that everybody’s walking around with a calculator in their hand. I think of it, in a way, that we’re teaching kids to be computers, and they’re learning to do what computers do. So, high school in particular has lots of antiquated methods that students sit and work out by hand. They will never do that again in their lives. What kids can be doing that computers cannot be doing is creative, flexible thinking.

LEVITT: Has the American approach to teaching math been successful? In terms of how U.S. students perform relative to students from other countries, the answer is “no.” On the most recent Program for International Student Assessment test (known as PISA), a standardized test administered in 70 countries, the U.S. placed 39th in math, just behind Hungary and Slovakia. American math performance is substantially worse than on either science (25th place) or reading (24th). Jo Boaler has devoted her academic career to developing new ways of teaching math that generate creative, flexible thinking. Her work has had a massive impact. A website she helped develop called youcubed.com translates academic research into actionable ideas for teachers to use in their classrooms. Youcubed has tallied 32 million page views over the last three years. 

LEVITT: Could you give me an example, a more specific example, of 21st century math taught in a way that students would find inspiring. 

BOALER: Let’s think about algebra, for example. Many people see algebra as, you know, as methods and rules, but you can take any algebraic expression and see it visually. So, I love to show people a visual of a growing pattern. So, it starts off as a little collection of squares and then a bigger collection of squares and then a bigger collection again. And what I ask people is, “How do you see this? How do you see it growing?” And people see it in many, many different ways. Some people will say to me, “Oh, it’s like raindrops falling as the shape gets bigger. It’s like a layer of extra rain on top of the shape.” And other people will say, “Oh, I see, it’s like a volcano erupting. The top goes up and then the sides come out.” And so, there are probably 12 different ways people will talk about seeing the growth. Now, it turns out that you could describe all of these 12 ways algebraically, and we would have a room full of algebraic expressions, all of them equivalent to each other, which is a really nice discussion. You can do this with any mathematics at all. I mean, we always say at our center at Stanford you can give us any boring, most procedural maths that you teach, and we will make it creative and visual for you. And when maths is creative and visual, people see connections and different ways of thinking are valued. And so, all sorts of lovely things happen. 

LEVITT: To me, 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. Could you talk a little about that? 

BOALER: Yeah, absolutely. And so — you’re right. When we look at the world out there and the jobs students are going to have, many students will be working with big data sets. So, we haven’t adapted to help students in the most important job many people will do, which is to work with datasets in different ways. So, 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.

LEVITT: So, it seems to me pretty obvious that we need a radical transformation in the math curriculum, and I think it seems obvious to you as well. Why do you think this struggle has been so difficult and the existing approaches have proven so resilient to reform?

BOALER: So, 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. Well, maths teachers do anyway. And when people have tried to change, they’ve really received aggressive pushback, which has caused some of them to sort of withdraw and go back into teaching the way that they were. 

LEVITT: Boaler knows firsthand what this pushback is like. During the early 2000s, she found herself caught up in what’s known as the “Math Wars,” a debate over the math curriculum between reformists and traditionalists. And if you think “wars” is an exaggeration… 

BOALER: People went to extreme lengths to try and stop reforms. I think somebody went on a hunger strike, even, in LA. Yeah, it was really a battleground. 

LEVITT: At the time, Boaler was working on implementing a new curriculum. 

BOALER: I interviewed some of the parents working to stop the new curriculum, and I remember one of the mothers saying to me, “You know, I’m not traditional about anything else, but if you can change math, anything can change.”

Sally SADOFF: I actually had the students doing regressions.

LEVITT: That’s Sally Sadoff, an economist at the University of California-San Diego and a former ninth-grade math teacher. 

SADOFF: I asked them to go out into the world and collect data on two variables they thought were related — like height and shoe size — and then to plot those points on an x-y plot, and then find a best-fit line in those data, and calculate the slope of that line. So, that was actually a really interesting project, because students that were really disengaged from my class — actually, it sort of sparked some creativity in them. I remember I had one student, this girl Jamie, who had no interest in my class. Jamie’s main interest was offering to give me a makeover. And the interesting thing about the project was, my high-achieving students chose kind of boring projects, like height and shoe size, or age and height, or something like that. Jamie, actually, her project was on the relationship between hairspray use and hair damage, which was a topic that was close to her heart, and it kind of showed that she could bring some of her own interests into math, which I think, until that moment, she thought was just completely boring and had no relation to anything she would be interested in life.

LEVITT: In addition to being an economist and teacher, Sally Sadoff also happens to be my cousin. If you’ve seen the Freakonomics documentary, Sally is the tireless redhead running an education experiment in Chicago Heights in which we paid kids to do well in school. Since then, she has earned her Ph.D. in Economics, gotten tenure at U.C. San Diego, and become one of the leading voices on the economics of education. 

SADOFF: When I graduated from college, I was really interested in education and educational achievement gaps. And so, I wanted to start off by teaching school. I started off in a large public high school. I went from there to a charter school in East Palo Alto. Unfortunately, I wasn’t a very successful teacher. They didn’t say I was fired; I was not rehired. I think a lot of the reasons that they let me go had to do with things like classroom management. My class seemed a bit out of control. Part of that was just that I was young and I didn’t know how to manage the students. They weren’t scared enough of me. Part of it I think was, to some extent, that I was doing some non-traditional teaching. On Fridays, I would do something called Function Fridays. I would play this song “Bring Out The Funk”, and I would have this little box where I put candies in, and they had to try to predict how many candies would come out based on how many candies had gone in and out on prior demonstrations, and if they correctly predicted the function, they got the candy.

LEVITT: The school seemed to think your teaching style was — hmm, hurting these kids. Do you have any idea whether that actually turned out to be true?

SADOFF: What was interesting is, after I left the school, I heard from a colleague of mine that when the scores came in, in the summer, my students had actually done really well and everyone was shocked that my students had performed so well on the test. And there were some saying, “Oh, so I guess Sally wasn’t as bad of a teacher as we thought she was.” 

LEVITT: The rate at which data are being created is mind-blowing. Every second of every day, enough data are created to fill 50 Libraries of Congress. Ninety percent of the data ever created by humanity was produced in the last two years. The labor market is having a hard time keeping up. According to LinkedIn’s 2018 Jobs Report, seven of the ten fastest-growing job categories in the United States are data-centered: machine-learning engineer, data scientist, big-data engineer, full-stack developer, to name just a few. And these are well-paying, exciting, challenging jobs. And other in-demand jobs like software engineer or finance analyst — these jobs require data fluency as well.

LEVITT: Do you think that the students we are graduating from high school are well-equipped to thrive in a data-intensive world?

SADOFF: I teach business-school students now, and I spend a lot of time, for example, trying to explain to them that even though there’s big data — and they — often in their work, they work with big data — they struggle to understand, for instance, the difference between correlation and causation. Understanding that basic idea, I think, is something that if it was started earlier for students, they would be able to understand all this data that is coming at them. And they have to understand — it’s, you know, in the newspaper, it’s in their lives. They think because they live with it, they understand it, but I think there’s some really important concepts that are missing. 

LEVITT: My own personal opinion is that there are few things more valuable in the modern world than “data fluency.” By that, I mean a basic comfort with data; an understanding of the difference between correlation and causality; the ability to evaluate claims that others make with data and maybe even to take a pile of data and to make some sense out of it. Yet, most high-school students are barely exposed to data. Only 10 percent of high school students take a statistics class — and even most statistics courses are primarily theoretical rather than requiring students to get their hands dirty with data. Mostly, if students are exposed to data, it is only because of enterprising teachers like Sally. It seems to me that the years we now devote to topics like geometry and trigonometry would be better spent focusing on achieving data fluency. But even if everyone shared my opinion — and I’m sure many people don’t — it is not at all clear how we could ever transform a high-school math curriculum that has proven quite resistant to change. A natural place to start is by changing the incentives faced by teachers and schools. One of the strongest incentives is the high-stakes testing done in almost every state. How students perform on these tests can determine school funding, teacher bonuses, whether a principal is fired, and even whether a school will be shut down. Here is Sally Sadoff again, talking about high-stakes tests.

SADOFF: Well, certainly, if you put different concepts on the test, schools will reorient how they teach to those tests. We always think of teaching to the test as a bad thing, but we want people to teach to the test. We put those concepts on the test because that’s what we want students to learn.

LEVITT: But do you think if we could give the teachers the right set of tools for teaching data — you think the teachers would make the investments to make that work?

SADOFF: I can imagine especially math teachers would be open to this idea.

David COLEMAN: What I wanted most to do was to be a schoolteacher.

LEVITT: That’s David Coleman.

COLEMAN: I’m the C.E.O. of the College Board.

LEVITT: The College Board, for those who don’t know, is the non-profit that administers the SAT, PSAT, and Advanced Placement exams. It was founded in 1899, then called the College Entrance Examination Board, by 12 elite East Coast schools in an attempt to standardize the college-admissions process. David Coleman didn’t plan on getting involved with the College Board. After graduating from Yale and completing a Rhodes Scholarship, he found himself looking for a job.

COLEMAN: And so I went back to New York City, where I grew up, and talked to principals of high schools. And the problem was, they were making layoffs. So, they told me that I could be a substitute if I wanted. And the other side of the coin is that McKinsey had been interviewing me for a job and it offered me a job at a management-consulting firm, and I turned them down because I said I would prefer to be a public high-school teacher.

LEVITT: I’m surprised — I know you eventually went to McKinsey — I’m surprised they would have you back, because I would have thought that saying you wanted to be a public high-school teacher would have completely convinced them that you were not right for the job at McKinsey.

COLEMAN: In candor, I think I may have had the most interviews ever for the job, because they so wanted to scrutinize me after that decision. They did indeed find it strange. 

LEVITT: While at McKinsey, Coleman devoted much of his time to pro bono education projects, first with the New York City Public Schools, then later with school superintendents across the country. He left McKinsey in 1999, after five years, and launched an education start-up which analyzed state test-score data and that was eventually bought by McGraw-Hill. Just prior to joining the College Board, he played a key role in the National Governors Association’s Common Core Standards. Coleman was responsible for the English Language Arts portion of the standards. In 2012, with the standards now in the hands of states, Coleman was hired as CEO of the College Board. Under his stewardship, the SAT has been radically overhauled.

COLEMAN: Let’s talk about why it began. So, the reason the SAT was developed is, in a remarkable moment of self-criticism and idealism, colleges recognized that they were recruiting from a very small part of America, from largely white men from a set of a small, select set of private schools and they actually saw this and saw that it was wrong, and said our democracy is in jeopardy if we don’t let a wider set of merit in.

LEVITT: That was in 1926. In the spirit Coleman describes, the original goal of the SAT was not to measure what you had learned in high school, but rather to identify people’s intrinsic ability or aptitude; thus the name Scholastic Aptitude Test. The original SAT was styled after the recently invented IQ test, which saw its first widespread application in the screening of military recruits in World War I. The original SAT looks nothing like the more recent versions. One section involved the College Board inventing an artificial language, giving the test taker rules for how to create the past and future tense; how to transform verbs into nouns, adverbs, or adjectives; and how to distinguish singular or plural. Then, armed with the definitions of 10 words in this artificial language, the test-taker had to craft sentences and translate from the artificial language into English. In another section, the student was given six words and had to say which three of those words had the most in common. For instance, “Columbus, Beethoven, Socrates, Wagner, Verdi, Corneille,” The answer here would be the three composers Beethoven, Wagner, and Verdi. If the goal of the SAT was to broaden the pool of applicants from a narrow set of elites, however, this particular question hardly seems likely to accomplish the goal! Notably, out of 310 questions on the original SAT, only 10 tested math skills, and these focused exclusively on arithmetic and simple algebra. My favorite question, which shows just how much both social norms and prices have changed over time, is this one: “If a package containing twenty cigarettes costs fifteen cents, how many cigarettes can be bought for ninety cents?” By 2012, the SAT looked very, very different. It also was facing a great deal of criticism. 

COLEMAN: When I became president of the College Board, very few people saw the College Board as opening up new areas of merit. They saw us as certifying the inequalities that exist. And so, the first question to ask is, is there something about the test itself that was unfair, that was either perceived to be or actually was deeply unfair. And it was our view that there are at least two things: the SAT came to be dominated by a kind of obscurity. So for example, what is the definition of an SAT word is a word you have likely not seen before and won’t see again. And candidly, what does that have to do with succeeding in college? And then moving on to mathematics in the redesign, we got rid of all those problems that used to be called “tricky.” The really big new idea of the SAT is the only thing you’re allowed to put on it is that which is most widely used. So, we survey first-year math teachers and first-year college professors not only in math but outside of math, and we analyze which math is most used in their courses. That’s a knowable question. At the same time, we ask high-school teachers what math is the most important for use in college and compare those two data sets. Any guess as to what we see?

LEVITT: My guess is that the high-school teachers say something that’s orthogonal to what the college teachers say.

COLEMAN: It will break your heart. The college teachers say, “Very few things matter and matter a lot.” The high school teachers say, “Everything matters.” Think of the stress of that. They must do everything, or they are betraying their kids, which forced them to race through the curriculum lest their kids are not ready. What the college teachers say but is not heard is, “If your students can do these core set of things, we can do the rest.” But if those are shaky and they’re merely faintly aware of them and aware of a lot of other mathematics, we’re stuck.

LEVITT: And what are the core math concepts?

COLEMAN: The first is the most humble, but it’s powerful, is arithmetic. The command of the four operations, you know: subtraction, multiplication, division, and addition — but crucially, fractions. The next area of math that’s hugely predictive of your future success is what I would call data analysis and problem- solving, including rates, ratio, proportion, designing quantities that interact with one another in that way, and watching their growth over time and development. The third area of math that’s extremely widely used is what I would call the heart of algebra, which is linear equations. That portion of algebra is then very widely used in other disciplines to open up many other problems.

LEVITT: So, what I find really compelling about what you just said, David, is that you are using data analysis to really understand what students need, and the outcome is that what students need in math, among other things, is data-analysis skills.

COLEMAN: That’s exactly right. And it’s demonstrable. I’ll tell you another interesting thing, Steve, that we haven’t talked about. Do you know how when we grew up, students would call themselves proudly, like, verbal kids or math kids, so you could get an 800 on the verbal section even though you didn’t like numbers and you never had to encounter them. And there were a lot of kids like that. And then there were math kids, you know. The new SAT disrupts that picture in what’s called now not verbal, but evidence-based reading and writing. There are five passages, two of them always are a passage from science that includes numbers, data, and a passage from social science, like economics, that includes data. And so you can no longer be perfectly verbal without being able to read and analyze data from charts, tables, and graphs. Because what was so silly was that people call themselves highly verbal and wide readers, when in fact they’re illiterate when they reach science or the social sciences if they can’t evaluate numbers.

LEVITT: Honestly, when David Coleman told me how heavily the new SAT emphasizes data, I didn’t really believe him. I knew that he knew that I am on a mission to make data fluency an integral component of high-school math. I thought he was just telling me what I wanted to hear. But I analyzed the new SAT, and everything he says is true. Twenty percent of the SAT math questions test data fluency; and, amazingly, 10 percent of the questions on what used to be the verbal section are data questions also. A decade ago, those numbers would have been close to zero. The College Board has quietly been leading the charge on data fluency. And that matters, because the SAT is becoming an even more powerful force for change in the education system. Students have, of course, always cared deeply about their SAT scores. But what you might not know is that the SAT is starting to be adopted by a few states as their high-stakes test for teachers and principals as well. I suspect that will become increasingly common. And if David Coleman has his way, there will be a lot of teaching to the test going on. Coming up after the break, I’ll get into more of my own data sets.

Daphne MARTSCHENKO: About 2 percent said that they use calculus on a daily basis.

LEVITT: And we’ll visit a school in California where the data revolution is already underway.

SAYLEE: And that’s what I like about this class, because it shows me how to detect, like my teacher would say, like, liars. 

*      *      *

LEVITT: A few months ago, my team used the Freakonomics Twitter account to gather some data on my hypothesis that most of what we are teaching kids right now in high-school math is pretty useless. 

LEVITT: Daphne, we’re here recording, and so will you just start by saying your name and what your job is?

Daphne MARTSCHENKO: My name’s Daphne Martschenko and I’m a research analyst at the University of Chicago.

LEVITT: Daphne recently earned her Ph.D. in Education at Cambridge in the U.K. Before that she was a Stanford undergrad majoring in Russian language and medical anthropology. She also was a world-class rower, representing the U.S. twice on the under-23 national team. 

MARTSCHENKO: So, we’ve been putting together a survey that we sent out to Freakonomics listeners. We asked our survey respondents which subjects they use in their daily life, traditional math and data-related. So trigonometry, geometry, calculus, versus more data-related skills like analyzing and interpreting data and visualizing it.

LEVITT: So, what percent of people, say, use calculus on a daily basis? 

MARTSCHENKO: About 2 percent said that they use calculus on a daily basis and almost 80 percent say they never use it.

LEVITT: Okay. I would think calculus would get used more than trigonometry and geometry, although that would be hard if only 2 percent are using it. But what percent use trigonometry and geometry? 

MARTSCHENKO: Yeah. Less than 2 percent of respondents said that they use trigonometry in their daily life, but over 70 percent of them said that they never use it. 

LEVITT: And how about geometry? 

MARTSCHENKO: Geometry was a little bit better. There were about 4 percent of respondents who said that they use geometry daily, but again, over 50 percent said that they never use it. 

LEVITT: So, it’s a pretty sad day when we’re celebrating the use of geometry because 4 percent of the people report using it. And if you think about it, who’s responding to our survey, right? So these are people who love Freakonomics and listen to the podcast. If there’s anybody who might actually — you expect to use math on a daily basis, you might think it was the Freakonomics podcast listener. I can’t imagine if you took a random subset of the U.S. population, how vanishingly small all of these numbers would turn out to be. So that’s really disappointing — not disappointing, because we knew it’s going to be true. But it’s, it’s embarrassing — it’s embarrassing that we teach a math curriculum that nobody, pretty much, is using. Now, what do we find when we asked about some of the data-related tools? Like what about simple things like — I’ve always thought we should teach Excel in the schools. Do people actually use Excel, or is that just my imagination? 

MARTSCHENKO: Yeah. Close to 70 percent of people said that they use Excel or Google Spreadsheets on a daily basis. We ask people how often they visualize and present data to make an argument. So, if you include those who say they visualize data, daily, weekly, and monthly, you’re gonna get over 70 percent — close to 75 percent of people. 

LEVITT: Okay, great. So — but we didn’t just ask them what they used. We also asked them what they wished they had learned more of, right? So tell me, which of the traditional math topics were people hoping that they had gotten more of in high school? 

MARTSCHENKO: None. Virtually. 

LEVITT: So, how about the data skills? I mean, we hardly teach data skills, so my guess is, people are going to want more of that. That’s what our premise was. Is that what the data tell us?

MARTSCHENKO: Yes, on every single one of the data-related questions we asked, over 40 percent of people said that they wish they had learned more. But the ones that really stood out were how to analyze and interpret data to discover hidden insights. We had close to 65 percent of people say that they wished they learned more about that. 

LEVITT: I wish I’d learned more about that. That’s the most valuable skill in the world. 

MARTSCHENKO: Yeah. And on top of that, we had 60 percent who said that they wish they’d learned more about how to visualize and present data to make an argument. So those two definitely go together. 

LEVITT: Okay, great. So this is reassuring, because here we are off on this wild goose chase of trying to change the minds of decision-makers or Americans about math. But the data support us, which is good. If you make an argument that you need more data in an education, it would be good to be able to say that the data support what we’re trying to do. 

MARTSCHENKO: Yeah, it is. It’s overwhelmingly convincing that people believe data-related skills are important to get by in work today. 

LEVITT: So, we have compiled a set of data that will allow us to not just — I think it’s really important when you’re trying to convince people, not just to assert something to them, but to really show them. But what you also need is, you need to really understand the institutions and the incentives. And that’s not something I know very much about, but that’s something I think you know a lot more about. So tell me, who makes the decisions? How does curriculum get set in the U.S., in education systems? 

MARTSCHENKO: In public education, the people with power are those on the State Boards of Education. So each state will have a State Board of Education. There are typically six to 10 people on the board, and they’re the ones who make those decisions about the curriculum, what gets taught, how testing is done. 

LEVITT: So, literally this set of six to 10 people have the power to set the guidelines, say, for whether or not data courses are required. 

MARTSCHENKO: That’s correct. 

LEVITT: So, what you’re implying is that each state sets its own standards. 

MARTSCHENKO: There is the Common Core curriculum, which are a set of standards set out for all states to adopt if they wish to. Most states have. But again, it’s up to the state to decide which standards to adopt, how they adopt them, how it gets taught. 

LEVITT: And is the Common Core — is that a friend or foe when we’re trying to push data? 

MARTSCHENKO: The Common Core does have a set of standards around statistics and probability. They do recognize that we’re in a changing world. But they’re continuing to focus or place more emphasis on those traditional math subjects. 

LEVITT: Okay, so there are these State Boards of Education who have all the power, and so it seems to me what you’re saying is, if we can get in front of those boards, and we can convince, say, even one of them of the wisdom of what we’re doing, they can flip a switch, although that’s probably way too simple, and put into motion a whole series of events which will lead in that state to the teaching of data being part of the math curriculum. 

MARTSCHENKO: I think taking a step back, state boards are always inundated with requests for changes that they should be making to the curriculum, to the testing. And a common response is, “Well, what am I supposed to take out to make room for this?” One thing state boards of education could do is to implement a data proficiency course instead of Algebra II. We see that Algebra II has become a chokehold for a lot of students that’s preventing them from continuing on and meeting those graduation requirements. And a number of states have even put in waivers to allow students to opt out of Algebra II and take other courses. 

LEVITT: Is there something out there that schools could use that could actually teach kids data in the way we’re imagining? 

MARTSCHENKO: There is a curriculum out there. It’s called Introduction to Data Science. It was created by academics at the University of California Los Angeles, in partnership with the L.A. Unified School District. 

Suyen MACHADO: So, Los Angeles Unified School District is, I believe, the second-largest school district in the country.

LEVITT: That’s Suyen Machado. She’s the program director for the Introduction to Data Science Project, or IDS for short. In 2010, UCLA in partnership with the Los Angeles Unified School District, received a National Science Foundation grant to design a high-school course that would teach statistical thinking. It was piloted in the 2014-15 school year with ten teachers in ten different high schools. The Introduction to Data Science class covers just about everything you might want to do with data: creating a data set, cleaning the data, visualizing it, and analyzing it. The course even teaches how to design randomized experiments.

MARCHADO: The students use a mix of large data sets and data sets generated by themselves through something called participatory sensing, which puts data collecting at the hands of students. As part of the initial grant, we developed an app where students go and they collect data about their lives. 

LEVITT: Machado allowed us to talk with some of the kids taking the class.

SONIA: My name is Sonia. A project that I’m doing is about California wildfires and how they have been spreading over the years. 

SAYLEE: I’m Saylee Garcia, 12th grade. I’m studying about crime rates in Los Angeles. And I’ve noticed how on the news, they keep on talking about crime. This is bad. It’s all negative. So most people are going to think Los Angeles is really unsafe. South Central is really unsafe. They don’t really show you crime rates have gone down in the last five years. And that’s what I like about this class because it shows me how to detect, like my teacher would say, like liars. 

LEVITT: This school year, there will be 125 IDS classes taught. That’s an amazing accomplishment. But to fundamentally change things, that number of classes needs to be multiplied by 100 or even 1,000. It is hard work building to that scale from scratch. It struck me that the College Board, which is responsible for the Advanced Placement (AP) tests, might be able to use its enormous reach to jump-start this process. So I asked David Coleman whether the College Board had given any thought to an AP data-science test.

COLEMAN: We have, but I think the more profound thing we’ve done, in candor, and I’ll explain why, is to include data science in the core exams we give like biology, like AP Government, is to make data analysis something you encounter over and over again. I want to again push back slightly against the most powerful picture of data science as isolating it as a discipline all by itself. It often comes alive in its actual application to situations, and I would just be careful of that. And the reason why I’d be careful of making an AP data-science course is not because we don’t love it and think it’s valuable, but we find our courses spread much more quickly for all kids when they’re not an elective or a special course. That is, if I weave data analysis into AP biology that’s widely given, or if we weave it into AP Government and Politics, which 400,000 kids take, that will touch kids in public schools in all levels of our society. If I create a kind of elective data-science course, that might only be taken by a few who choose to take it. 

LEVITT: But will teachers in AP Biology or AP Government have the skills to teach the data-fluency parts of their courses? 

COLEMAN: One magnificent thing about teaching is, it’s often the most lively when the teacher himself or herself is learning something. I think the model of practiced expertise being the only way that teaching is exciting is false. And so I think what’s more interesting is, can we create environments for teachers and students where together the data comes alive and fascinates them. And so, I think the question is not to kind of try to suddenly retrain the American teaching force to be data analysts, but instead design superb data experiences, superb courses, where the hunt for data and the experimentation is so lively that it excites them as well as their students. And then they together might be surprised at the outcomes.

LEVITT: I believe that we owe it to our children to prepare them for the world that they will encounter — a world driven by data. Basic data fluency is a requirement not just for most good jobs, but also for navigating life more generally. Whether it is in terms of financial literacy, making good choices about our own health, or knowing who and what to believe. Math class isn’t the only place to teach data skills, but it seems like a good place to start. The current math curriculum isn’t preparing students well for either the workforce or the classes they will take in college. It isn’t even helping them do well on the new SAT! There is every reason to think that with a bit of retooling, the current batch of high-school math teachers could be outstanding teachers of new data-focused courses. Radical change is never easy. We have heard today from a few of those on the front lines of this battle; there are thousands more like them. If you want to join the cause, visit freakonomics.com/math, where you can find more information, useful links, ways to contact policy makers in your state, and even a petition. Otherwise, be prepared to hear a lot more of this from future generations…

Sophie LEVITT: Oh God. Let the line from the origin to A and the origin to B, 2 perpendicular radii of a circle centered at the origin…

LEVITT: I posed the question to you, the listeners, at the top of the show, what was the reaction to the episode when we first released it? Well, the response was, shockingly, positive. The students and parents and teachers who wrote us overwhelmingly agreed with our arguments. But most importantly, it turned out that there were already a bunch of nonprofits working in the area, but they were working independently and not having the impact they wanted. And over the last two years, we’ve come together and we’ve just this summer formed a consortium. It’s called Data Science for Everyone, and we’re willing to do whatever it takes to give every child a chance to achieve data fluency. It’s a hard problem though, and we’re just getting started. So, if you have great ideas in this area, send them our way. Now, it probably won’t surprise you that one of the first schools on board is Sal Khan’s Lab School. That’s one of the topics we talked about in Episode 22. And if I hadn’t had Sal Khan on the show, none of this would have happened. If you want to learn more about what we’re doing. Visit our website at datascience4everyone.org. That’s the words “data science,” the number four and the word “everyone.” Datascience4everyone.org. Thanks for listening. And we’ll be back next week with a regular episode. 

*      *      *

People I (Mostly) Admire is part of the Freakonomics Radio Network, which also includes Freakonomics Radio, No Stupid Questions, and Freakonomics M.D. This show is produced by Freakonomics Radio and Stitcher. This episode was produced by Zack Lapinski. Jasmin Klinger is our engineer. Our staff also includes Stephen Dubner, Alison Craiglow, Greg Rippin, Joel Meyer, Tricia Bobeda, Morgan Levey, Emma Tyrrell, Lyric Bowditch, and Jacob Clemente. Theme music composed by Luis Guerra. To listen ad-free, subscribe to Stitcher Premium. Thanks for listening.

LEVITT: I know that when he read the book, our audiobook. He did it in like one take. And I did like a thousand. I was like, f*ck. Why didn’t Dubner read the whole damn thing?