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Every Student Needs 21st-Century Data-Literacy Skills

Steven D. LevittJeffrey Severts 8-9 minutes 7/12/2022

Most educators understand that school curricula must evolve as the world changes. Refusing to adapt would do a terrible disservice to students, leaving them poorly prepared for their futures. Striking the right balance is difficult, but our schools usually find a way to forge ahead, teaching more Spanish and less Latin, more Angelou and less Shelley.

But math instruction seems to resist this needed evolution. Math is viewed by some as an immutable revelation, as if Pythagoras himself chiseled the curriculum into stone tablets and brought them down from the mountaintop. Thou shalt teach synthetic division! Thou shalt master factoring higher degree polynomials!

Why this perception persists is a mystery. High school math instruction has changed before. The current gauntlet of algebra through calculus was set in the 1960s in response to Russia’s Sputnik. To win the Space Race and the Cold War, the United States needed more scientists and engineers, and a steady diet of quadratic equations and differentials was considered the best way to cultivate them. Before this abrupt shift, high school math had been evolving slowly to include algebra and Euclidean geometry, in response to changing admissions standards at selective universities. In 1926, only 10 of the 310 questions on the SAT were about math, and those questions were limited to arithmetic and basic algebra.

Today, we could be more confident in our current math curriculum if little had changed in the world since the 1960s. But that would be an absurd position to take, of course. Society has been transformed over the past six decades, and in ways that have dramatically affected how we use math in our lives. Nearly every one of us walks around with a powerful computer in our pocket, capable of making billions of calculations per second. Each day, we collectively generate enough data to fill five Libraries of Congress. And the Internet has disrupted almost everything, including our most trusted sources of information. We now must sort fact from fiction for ourselves. Do cosmetics cause cancer? Is Covid-19 a threat to a healthy 5-year-old? Was the last election stolen?

Our lives have been changed by this revolution in so many ways, including the way we work. Seven of the 10 fastest-growing jobs in America are related to data. And while most of those roles are highly technical, computing and data have seeped into everyone’s workplace. Auto mechanics used to turn wrenches. Now they plug cars into computers and interpret the results. Teachers used to give lectures and write on chalkboards. Now they record their lessons on YouTube and analyze their students’ test scores with sophisticated software. Can you imagine how often today’s children will be working with data when they come of age?

In this new world, how useful is the math we are currently teaching in our schools? To get some insight into this question, we conducted a small survey with several hundred Freakonomics podcast listeners. While this sample is far from representative, it’s fair to say the respondents are likely to be biased toward overestimating the value of today’s math, as Freakonomics fans tend to be a pretty geeky crowd. The unscientific results of our poll suggest that educators have much work to do on the current math curriculum. Only 2 percent of respondents report that they use trigonometry in their daily work, while 66 percent say they are constantly building spreadsheets—a tool that is rarely covered in today’s curricula. Furthermore, when asked what math topics they wish they had learned more about in high school, 64 percent named data analysis and interpretation while only 5 percent said geometry.

What should be done? Our proposal, which we call “Merge and Purge,” is simple. We believe the three years that schools currently dedicate to algebra and geometry could be easily distilled down to two, simply by doing away with 1) anachronistic, computation-heavy topics that are no longer relevant in the computer age and 2) elements that do not serve as critical building blocks to higher-level math. This would open up a year of new capacity that could be dedicated to data literacy, statistics, and other forms of applied math. Kids could learn how to analyze, interpret, and visualize data. We could teach them the difference between correlation and causation. And perhaps most importantly, we could help them understand the limits of data, so they would know when to be skeptical of data-based claims.

The true power of data emerges in applications. We recommend that the data-based math course be offered early in the math sequence, so students will have opportunities to integrate data analysis into their social science, humanities, and science courses.

Merge and Purge purposely avoids creating a separate data-math track that would lead to some students choosing the new path and others sticking to the traditional one. Neither students nor parents are well equipped to weigh the tradeoffs between, for example, data proficiency and calculus. If elite colleges maintain a calculus requirement, would a student who chose a data track be disqualifying herself from admission to such institutions? Moreover, every proposal for separate tracks that we have seen positions data science as the last step in a math sequence. As noted above, we believe that data skills should be taught earlier so they can be applied throughout the broader high-school curriculum.

Critics have accused reformers like us of wanting to make math instruction less rigorous, but nothing could be further from the truth. Data science, in many ways, demands more of students. Analyzing and interpreting data requires critical thinking, creativity, and a nuanced understanding of the context within which the data were generated. Furthermore, data science is probabilistic instead of deterministic, presenting challenges not unlike those encountered in the transition from classical to quantum physics.

While we believe that students have much to gain by becoming data literate, we recognize the challenges inherent in curriculum change. Teachers will need extensive professional development to acquire the requisite skills. Reaching consensus on which topics to purge from the curriculum will not be easy. And unlike some who support this change, we are skeptical of the claim that a focus on data literacy will dramatically improve the equity problems we have in education.

Still, data literacy will be a critical skill for living in the 21st century, so we must do all we can to ensure that every kid has the opportunity to acquire it. Some educators recognize this and are already making changes. Sal Khan, the innovator behind Khan Academy, has already adjusted the algebra-through-calculus lineup at his Lab School in Mountain View, California. Students there now spend an entire year learning data science. Forty school districts across the country are following Kahn’s lead, taking the first steps toward introducing data science into their curricula. Data Science for Everyone, a coalition of individuals and organizations launched by our team at the University of Chicago, advocates for policy reform and the expansion of K–12 data-science education. And a dozen states have begun the difficult work of modifying their guidelines and standards, making room for this modernized approach. Virginia is leading the way, with plans to approve a new data-science curriculum framework for implementation in 2023. It is our hope that developments such as these represent the start of a movement to advance data-science education so that every K–12 student in America is equipped with the data-literacy skills needed to succeed in our modern world.

Last updated July 12, 2022