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Why Math Needs Data Science Reform Article preview reposted from The Learning Curve. Almost every occupation involves interpreting and analyzing data as well as making decisions based upon that data. The modern business world was built on the spreadsheet. Medical professionals make life and death decisions comparing conflicting data. Natural scientists and social scientists wrangle data by the fistful. Politics, policy, sports, automotive technology, heck, even reading a newspaper requires data analysis skills these days. Nonetheless, data sources are not always ethical and algorithms are not always as transparent as they initially seem. Making decisions driven by data can cause pre-existing biases to persist which leads to a lack of objectivity and can result in poor decision-making. But the prevailing math curriculum does little to support students in developing data science vital skills. Students may make graphs in physics or have to interpret a table on a standardized test. However, they rarely have to clean data sets, make tradeoffs when choosing a data visualization, or resolve conflicting interpretations of the data in order to ensure that the outcomes are fair, accountable, and transparent. Instead, students learn things like L'Hopital's Rule and Integration by Parts, while complaining that math has little relevance to their everyday lives. Is it time for a change? The short answer is yes. Today’s math curriculum is not relevant for students and far more needs to be done to incorporate data science into the curriculum... Read the full article in The Learning Curve

'Freakonomics’ author Steven Levitt, Stanford's Jo Boaler, and other reformers are pushing for more equitable curriculum that better equips students for a data-driven world. By Yoree Koh, reposted from the Wall Street Journal Steven Levitt, like many parents, has spent countless evenings helping his kids with their math homework. Increasingly, his four teenagers’ work on quadratic equations and imaginary zeros has felt like an exercise in futility. “They’ll never use it again,” says Dr. Levitt. It’s an odd thing for someone like Dr. Levitt to say, given his career as an economist at the University of Chicago and his work as co-author of the book “Freakonomics.” But learning math is different from understanding data. He and others contend that the way math is taught in schools is outdated and impractical in preparing students for today’s data-driven world. This frustration has led the economist to moonlight as a math education reformer. Last year, Dr. Levitt and his nonprofit at the University of Chicago, the Center for Radical Innovation for Social Change, teamed up with Stanford University math-education professor Jo Boaler to push the movement to modernize math. Dr. Levitt’s proposal is simple: Condense three years of high-school math—typically Algebra I in ninth grade, Geometry in 10th grade and Algebra II in junior year—to two years. Then, devote the freed up time to more relevant learning, such as data science or financial literacy. Policy makers are beginning to imagine what a modernized math curriculum could look like—one that would acknowledge the prevalence of computers and the importance of data literacy, broaden the pathways to college acceptance, and prepare students for real-life issues, such as understanding the amortization of a mortgage, evaluating the impact of waste on the environment or deciphering infection rates of Covid-19. Dr. Boaler, who has been pressing for change for years, says the movement for reform is gaining momentum, as some higher-education institutions adjust their admissions requirements and the pandemic highlights inequities within education. “We don’t need people to replicate what a computer can do in the 21st century. We need those creative thinkers,” says Dr. Boaler. Conrad Wolfram’s vision is at the extreme end of math reform: His idea is to eliminate hand calculations from the curriculum. Mr. Wolfram, the co-founder of Wolfram Research Europe, the mathematical lab behind the specialized search engine Wolfram Alpha, has campaigned for over a decade to overhaul the way mathematics are taught. Mr. Wolfram, the author of the book “The Math Fix: An Education Blueprint for the AI Age” that was released in June, says the fundamental problem with today’s math curriculum is that it doesn’t acknowledge that computers exist. > Read the full article at the following link: The Movement to Modernize Math (Wall Street Journal)

By Sydney Johnson, article reposted from EdSource Students take notes as teacher, Nick Johnson, writes unfamiliar words on the board in his Algebra 1 math class at Rudsdale Newcomer High School in Oakland, California. High school students planning to apply to the University of California now have a broader set of courses they can take to meet the math requirement for admission to the public university system. As more high schools across California have developed and adopted new college-prep math courses, math education and equity advocates have urged the state’s public universities to allow these courses to count toward admission requirements. Under the new rules adopted in October, students in 11th and 12th grade can take data science, computer science, statistics and other approved quantitative reasoning courses to satisfy the required third year or recommended fourth year of math needed to be eligible for UC. Both the UC and California State University require three years of high school math but recommend four as part of the A-G courses that students must take to be eligible for admission. Historically, that typically includes Algebra 1, Geometry and Algebra 2, which often leads to Calculus. But some students do not reach Algebra 2 or Calculus by their senior year, the courses aren’t offered, or they don’t want to take the courses because they don’t align with their academic pathway, creating barriers to college admission for students. According to UC officials, the decision to accept a variety of quantitative reasoning courses for admission aims to provide more options outside of the traditional Calculus track, which isn’t required for most non-STEM pathways. It will also expose students to other math topics that are increasingly available on college campuses and in-demand in the workforce. “There have been ongoing efforts from high schools to design and implement an expanded range of college-prep math courses, so at its core, this is an opportunity to broaden the range of course options for students to enter UC,” said Eddie Comeaux, chairman of the UC Board of Admission and Relations with Schools, which approved the admission change. Students must still complete three years of math, including a course in geometry or an integrated math course that covers enough geometry to be eligible for UC. Approved math and quantitative reasoning courses must also cover topics included in elementary algebra, two- and three-dimensional geometry and advanced algebra. In recent years, courses such as Introduction to Data Science, a high school course developed by Los Angeles Unified and UCLA, have grown increasingly popular. First offered in Los Angeles Unified in the 2014-15 school year, it has since expanded to 17 California school districts plus other districts in Idaho, New Jersey and Oregon. Phineas Banning High School in Los Angeles was among the first schools to implement the data science course, which was already accepted by UC to meet the required third or optional fourth year of math prior to the recent admissions change. > Read the full article on EdSource

By Pamela Burdman, reposted original op-ed from EdSurge. Over a decade ago, I learned about a pioneering course at Cabrillo College in California. In it, students collected survey data in their neighborhoods on issues such as youth gangs or discrimination against immigrants, learned statistical methods to analyze that data, and presented their findings to their local community. This social justice approach struck me as an effective and relevant way to teach mathematical concepts. The only problem? The community college’s math department didn’t consider it a math course. Although statistics was an accepted general education math course at institutions around the state, and the class used a valid inquiry-based pedagogical strategy, the math faculty nevertheless felt that the course needed to cover more algebra. They weren’t exactly wrong: At the time, state policies required California community college students seeking to transfer to four-year universities to pass a college-level math course with an intermediate algebra (or Algebra 2) prerequisite. This was true regardless of whether they were pursuing an algebra-intensive major like engineering or physics, or a field like communications, counseling, or political science that doesn’t rely on algebra. Fortunately, much has changed since then in California and elsewhere, paving the way to modernizing mathematics education. Instead of the one-size-fits-all math pathway that leads to Calculus and STEM majors, postsecondary education systems around the country are diversifying pathways to include courses—like statistics, data science, and quantitative reasoning—that better align with many students’ fields of interest. And that opens the door for courses that use mathematical concepts to examine public policy and social justice issues, whether policing, access to health care, or political representation. These shifts, in turn, make room for new K-12 math content aimed at building the quantitative skills students need to examine issues relevant to their lives and their communities. The Common Core math standardsincorporate a new emphasis on statistics as well as on using mathematics tomodel real-world problems. But math educators indicate that these topics often get short shrift. Data science courses that teach basic coding along with statistical skills are a novel and engaging way to address those standards. Unlike traditional math courses that focus on formulas and procedures, they are centered on real-world data. In fact, if the ability to “understand and critique the world” is one of the primary purposes of math education, as the National Council of Teachers of Mathematics claims, data science needs to play a central role. And that is exactly what has started to happen: • In higher education, college students are flocking to data science courses. Take Foundations of Data Science, a five-year-old course at the University of California at Berkeley: It’s a mix of inferential thinking (including statistics), computational thinking (computer science), and real-world relevance. And it meets the campus undergraduate math requirement. By its second year, more than 1,000 students were enrolling in the course, making it the fastest-growing course in campus history. Berkeley also offers connector courseslinked to specific disciplines that use real-world data to examine topics like race and policing, child development, and human migration. • Opportunities to teach data science at the high school level are also opening up. In California, for example, 17 school districts have adopted an introduction to data science course that was conceived by faculty at UCLA and initially piloted by Los Angeles Unified School District. Students in the course collect data from their own lives—about their snacking or sleep habits, for example—and learn the programming language R to analyze the patterns. The course’s initial development was supported by the National Science Foundation. It also meets requirements for admission to California public universities, a key explanation for its rapid growth. It is also being replicated by high schools in three other states. In Georgia, mathematics and computer science instructors are also developing a two-course high school data science sequence that they hope to make available in that state by next fall. These developments are helping to reinforce the notion that learning to analyze data to answer real-world questions or address social issues is a rigorous and relevant educational pursuit. And to detractors who worry that it won’t position students for college success, there is evidence to suggest otherwise: Research at the City University of New York found that college students who took introductory statistics courses were just as likely to pass advanced math courses as students who had taken a required algebra course. Other evidence shows the potential for social justice-oriented math curriculum to support math learning. This momentum doesn’t automatically guarantee a place in the curriculum for data science or statistics. High school math sequences, in particular, are already quite crowded. But, as National Council of Teachers of Mathematics leaders have noted, those sequences include a lot of “obsolete legacy content.” And scholars from leading universities blame the traditional emphasis on algebra and geometry content for leaving U.S. students “woefully underprepared for the modern world.” Some of that traditional content might follow the slide rule and the abacus into extinction. That would be a worthy sacrifice for ensuring students understand concepts like correlation and causality and know how to analyze data on spreadsheets. Most importantly, it would help ensure learners become 21st-century critical thinkers. Pamela Burdman is the executive director of Just Equations, a nonprofit focusing on the role of mathematics in ensuring education equity.

By: Daniel Rockmore Many parents relish reliving moments from our childhoods through our children, and doing homework with them is its own kind of madeleine. For Steve Levitt of "Freakonomics" fame — who is, in his own words, "someone who uses a lot of math in my everyday life" — a trip down memory lane vis-a-vis math homework became a moment of frustrated incredulity rather than gauzy reverie. "Perhaps the single most important development over the last 50 years has been the rise of data and computers, and yet the curriculum my children were learning seemed to have been air-dropped directly from my own childhood," he told me. "I couldn't see anything different about what they were learning than what I learned, even though the world had transformed completely. And that didn't make sense." Read more here on how we can modernize mathematics and the origins of Data Science for Everyone.

Stanford Data Science Education Convening Originally published by the Stanford Graduate School of Education. By Carrie Spector. Life in the 21st century is defined by data, tracking everything from our shopping and exercise habits to the spread of disease and the impact of climate change. Some educators are asking how schools can prepare young people to make sense of it all: Should data science become as much a part of the K-12 mathematics curriculum as geometry, algebra and calculus? Intent on elevating data science to a more prominent place in K-12 education, a group of 50 mathematicians, data scientists, teachers and education policy leaders gathered for a daylong summit at Stanford Graduate School of Education (GSE) on Feb. 3. Led by GSE professor Jo Boaler, the event brought participants together to strategize next steps for a burgeoning movement to modernize the K-12 math curriculum for the data age. “The world has changed dramatically in recent years, but our mathematics curriculum has stayed the same,” said Boaler, the Nomellini and Olivier Professor of Education at Stanford and co-founder of youcubed.org, an organization providing resources for math learning. “We urgently need to teach kids what they’re actually going to use in their lives and their work. So we brought together the people we think can make this movement happen.” "This really seems to have the potential to change [mathematics] in school — from a very procedural, meaningless subject for most kids into something they can see is useful in the world." ‘An opportunity to reset’ The gathering grew out of an ongoing collaboration between Boaler and Steven Levitt, a professor of economics at the University of Chicago and co-author of the best-selling Freakonomics books, which apply data science to a variety of topics in contemporary culture. The pair recently co-authored an op-ed in the Los Angeles Times that called for putting data science at the center of high school mathematics. Levitt, a father of four teenagers, became interested in the issue when he saw the mismatch between his own experience of mathematics and what his kids were learning. They came to see math as “voodoo,” said Levitt, who cofounded the nonprofit Center for Radical Innovation for Social Change (RISC) at the University of Chicago. “They were taught by teachers that these sets of things work, without any real understanding of why they’re doing what they’re doing.” Data science, on the other hand, is “literally the expression of what is happening in the world,” he said. It lets students become “the discoverers of knowledge, as opposed to the recipients of the brilliance of past generations dumping knowledge upon them, with the hope that somehow it will stick.” Boaler and Levitt convened the summit for participants to explore questions about the challenges of incorporating data science education into K-12 schools. Where could it fit into existing curriculum? What type of professional development would be most useful to prepare classroom teachers for this shift? How can schools ensure that students of all genders, race and economic background have equal access to the classes? “When we think about computer science or math, the images that most people have in their heads are not of women, they’re not of people of color,” said participant Elena Grewal, PhD ’12, former head of data science at Airbnb. “This is an opportunity to reset. How can we ensure that everyone is included in this new field and feels like they can master these concepts?” A more equitable pathway Citing research demonstrating racial and socioeconomic disparities in access to advanced math courses in U.S. high schools, Boaler said that data science could offer a more equitable pathway. “Calculus sits on this whole system of tracking and racial inequalities,” she said. “Calculus is the only AP class where you need to be advanced in middle school in order to get there.” When students are in sixth grade, it’s decided whether they should be able to go on to calculus, she said. “That is wrong on so many levels. Data science could be different, particularly if we go into this with our eyes open.” Working with real-world data could also be a way to draw students who might otherwise be disinterested or daunted by mathematics, participants said. Studying data science offers kids the chance to see how mathematical ideas “connect to their everyday lives and have consequences,” said Victor Lee, an associate professor of education at the GSE, whose research includes studying ways to engage K-12 students in data analysis. “Kids can look at their own daily activities using wearable activity trackers, examining what sorts of activities are making them more active or are more physically demanding. They can look at air quality sensors and see the quality of the air in their neighborhood. They can look at food and nutrition to see what sorts of resources are made available to some communities and less so for others.” Outdated standards Linda Darling-Hammond, president of the California Board of Education and a professor emerita at the GSE, noted at the summit that the current high school math sequence goes back to 1892, when a group of educators known as the Committee of Ten recommended a standardized curriculum for American schools. “It’s a fairly antiquated approach to teaching,” said Darling-Hammond, who recently appointed Boaler and GSE assistant professor Jennifer Langer-Osuna to a state committee working to revise California’s K-12 mathematics framework. One complication in changing the K-12 math curriculum is the perception that students who don’t follow the traditional pathway will be at a disadvantage in applying to colleges. In California, high school students need to complete a sequence of courses known as the A-G requirements, which include algebra II and geometry, to be admitted to a University of California or California State University campus after graduation. Colleges across the country similarly limit the high school math courses they recommend for successful applicants. Boaler and Levitt are working with college administrators to broaden the scope of mathematics their institutions indicate they value. They are also pushing to expand the options available in high school for all students, including those who aspire to attend elite universities. Preparing students for the data age Beyond emphasizing the importance of preparing young people for a changing job market, participants at the summit spoke to schools’ duty to equip students for the demands of modern citizenship. “It’s a bit like before literacy was common across most of the population—we had a small number of people at the top who could control everything else,” said Conrad Wolfram, co-founder of computerbasedmath.org. “We’re in a similar situation now with data literacy.” As artificial intelligence becomes increasingly omnipresent, the need to understand how to work with data becomes more urgent, Wolfram added. “There’s a question of who’s in charge, the AI or the human,” he said. “We don’t want to compete with the machines we’ve made. We want to go to another level, and that’s got to change in our educational set-up.”

Washington Post Perspectives (Astrid Riecken/for The Washington Post) Reposted from the Washington Post—Perspectives. By Jay Matthews I got an A in algebra II, I think. That was long ago. I do know that I have long since forgotten whatever I learned in that course and have never used it since. That has become a national problem. Algebra II is required for graduation in 20 states and the District. Yet many experts want to discard it in favor of something more fashionable. These days, they say, students need to understand big data, a course often called statistics. Algebra II is frequently combined with trigonometry in the third year of high school math. It covers linear equations, functions, exponential and logarithmic expressions, and other things. It became a regular part of American education after high school math was overhauled in the wake of the Soviet Union’s launch of Sputnik in 1957. It no longer gets much respect. The Freakonomics Radio podcast, in a special episode hosted by University of Chicago economist Steve Levitt, surveyed listeners about math subjects they used in their daily lives. Algebra II wasn’t part of that poll, but 70 percent of respondents said they never used its close cousin trigonometry. That includes me. I use math in my work but only the long division I learned in fourth grade. It helps me prepare my annual list of schools with high rates of college-level test preparation. A calculator I got free in the mail from SPCA International does the actual arithmetic for me. So why, many people ask, do we need algebra II, or any of those upper-level high school math courses? “It’s embarrassing,” Levitt said on his podcast, “that we teach a math curriculum that nobody, pretty much, is using.” In a new report, math education experts Phil Daro and Harold Asturias conclude that the traditional math sequence of which algebra II is a part is more trouble than it’s worth. Its peculiar difficulties frustrate too many students interested in math and science “while simultaneously erecting irrelevant math hurdles for students with other interests,” they said in their paper “Branching Out: Designing High School Math Pathways for Equity” on the Just Equations website. They suggest different pathways after algebra I and geometry that would align with different student goals. This would include “an initial course suitable for 11th grade, in lieu of the traditional Algebra II.” They suggest 11th- and 12th-grade math combinations that would include data science and quantitative reasoning. That meshes with changes in the workplace. Daphne Marts­chenko, a research analyst at the University of Chicago, told Levitt: “It’s overwhelmingly convincing that people believe data-related skills are important to get by in work today.” Robert Q. Berry III, a professor of mathematics education at the University of Virginia, is president of the National Council of Teachers of Mathematics, headquartered in Reston, Va. He told me Levitt’s concerns are warranted. He said his organization wants “significant rethinking of what we are teaching in high school to transform learning from focusing on mindless manipulations in mathematics toward developing conceptual understanding.” NCTM wants "a significant rethinking of what we are teaching in high school to transform learning from focusing on mindless manipulations in mathematics toward developing conceptual understanding" That means more than just dumping algebra II. Berry wants to build what he calls “positive mathematics identity and agency.” He described that as students “seeing themselves as doers of mathematics and engaging in the behaviors of doers of mathematics.” That will be a difficult assignment, at least in high school. Many teens don’t even see themselves as doers of homework. Berry understands that overturning the current math sequence will require cooperation from universities, local school boards, state school boards and others. “The challenges are systemic,” he said. To me, that means I will not live long enough to see it happen. But there are ways to ease algebra II out of high schools. Gregg Robertson, longtime principal of Washington-Liberty High School in Arlington, Va., noted that his math department has courses in probability and statistics, both regular and Advanced Placement, as well as a dual-enrollment quantitative reasoning course through Northern Virginia Community College. School by school and state by state, that is one way to nudge algebra II toward the trash bin. Requiring that students take four math courses — but not saying which ones — can give a boost to the data and statistics courses being advocated by people like Levitt. Robertson said even calculus, despite its lofty reputation, is also unnecessary for most of his students’ future success. I passed calculus, too, but don’t ask me to justify its worth. Even before I completed it in 1963, I knew I would never use it again.

Swap Algebra 2 for Data Science and Get a 1 Point Bump in GDP Engineering class modeling deflection at Liberty High School Reposted from Forbes By Tom Vander Ark (Getting Smart) I visited 20 high schools in the last 20 days. In every case, I saw kids suffering through the arcane symbol manipulation of Algebra 2, an obsolete requirement that keeps some youth out of meaningful employment and serves as a boat anchor on the American economy. Now that everyone has powerful computers (like that smartphone in your hand), we should teach math as if computers existed. Now that everyone is an entrepreneur, we should teach financial literacy (make it a graduation requirement like Missouri). Now that we all use probabilities all day long in life, work, and leisure, we should teach statistics and probability. Now that every field is computational, we should invite youth to attack big problems with big data sets (that’s called data science). What we don’t need to teach is long division and factoring polynomials. The memorization of procedural computation that monopolizes math time in U.S. classrooms trips up most young people and discourages many from attending and completing a degree, and gaining meaningful employment. Really, Kill Algebra 2? OK, Algebra 2 isn’t the only culprit, it’s the anachronistic American math sandwich of Algebra 1, Geometry and Algebra 2. There is some good and widely useful stuff in each course, but we could eradicate half of rule memorization and calculation and add more data science, and the outcome would be less painful and much more beneficial to young people. Really, 1% of GDP? Preparing young people to succeed in the innovation economy with data science, probability and financial literacy has to be worth at least a point of Gross Domestic Product in the long run. Granted, we probably have to fix reading instruction and add some design thinking to fully realize a $200 billion boost to the economy, but I think it’s in the ballpark. A $200 billion boost to the economy... I think it’s in the ballpark. (Leading economist and Stanford researcher Eric Hanushek has studied the correlations between traditional measures of achievement, particularly math, and economic growth. He cites a study that shows that one standard deviation difference on test performance is related to 1% difference in annual growth rates of GDP per capita. He also calculates that GDP growth rate would be boosted by about three-fourths of 1% a year if U.S. test scores in math equal Canadian achievement levels. The point is that getting math right appears to be a big deal for the economy.) Is this really a problem? With the push for more college going, nearly every state has boosted its math graduation requirements to at least three years. Most states provide some flexibility in what comprises those three courses, but because college entrance exams include a lot of Algebra 2, it’s a de facto graduation requirement—at least for youth that want to attempt college. Common Core State Standards was an attempt to update American math standards. While some probability and data science was added, it left nearly all of the traditional symbol manipulation and calculation in place. It did offer an integrated approach that was an improvement over the traditional sequence, but there hasn’t been much of an update. In addition to college entrance tests (ACT and SAT) that still have a lot of symbol manipulation, it’s the pesky placement exams (Accuplacer and Compass) that keep people out of credit-bearing community college math courses and, as a result, out of pathways to meaningful employment. So, it’s a combination of state and local graduation requirements, state and national tests, and a century of tradition that has us stuck in a bad place—bad for kids and for the economy. What the heck do you know? Fair question. I’m a former engineer, public company finance exec, business school instructor, school administrator, venture investor, and policy advocate that has studied this for 25 years while visiting thousands of high schools—arguably miore than most people will in their lifetimes. With apologies for the delay, I’m joining a parade of leaders ready to take on the tired traditions of math in America. “The tragedy of high school math,” said venture investor, education advocate and Forbes contributor Ted Dintersmith (who has a Ph.D. in math modeling), “is that less than 20% of adults ever use algebra. No adult in America still does integrals and derivatives by hand—the calculus that blocks so many from career paths. It remains in the curriculum because it’s easy to test, not important to learn.” “Put data and its analysis at the center of high school mathematics.” That’s the conclusion of Stanford University math professor Jo Boaler and University of Chicago economist Steven Levitt. They recommend that “every high school student should graduate with an understanding of data, spreadsheets, and the difference between correlation and causality.” The Center for Radical Innovation for Social Change (RISC) at the University of Chicago has produced a great presentation making the case for teaching data science in high school. Last month, PISA released a mathematics framework that guides the assessments. Data literacy is central to the framework. Rather than the plug and crank of symbol manipulation in our high school math, we should be teaching computational thinking. As mathematician Conrad Wolfram said, we should be teaching math as if computers existed. He argues that math should be taught as computational thinking and integrated across the curriculum. Branching Out, a new report from nonprofit Just Equations, was a good attempt. They suggest dropping Algebra 2 for most students, while maintaining the traditional path for STEM-focused students. Other than a few math “monks,” the STEM professions don’t require long division or factoring polynomials anymore than book editors. What everyone needs is success in using data to solve problems. Math for making a living—and making a difference High school should be an opportunity to figure out who you are, what you’re good at, and where you want to make a contribution. That should start with problem finding—spotting big tough problems of interest. Next comes understanding the problem and variables associated—that’s algebraic reasoning. But rather than focusing on computation (including factoring those nasty polynomials), students should be building data sets and using computers to do what they’re good at: calculations. Add some finance and probability to guide the investment of time and resources, and you have a new, more compact set of math requirements for making a living and making a difference. Want to join the parade? Boaler and Levitt need to hear from people who would like to see more relevant math instruction—and perhaps a one-point boost in GDP.

Los Angeles Times Opinion Reposted from the Los Angeles Times—Opinion By Jo Boaler and Steve Levitt Thanks to the information revolution, a stunning 90% of the data created by humanity has been generated in just the past two years. Yet the math taught in U.S. schools hasn’t materially changed since Sputnik was sent into orbit in the late 1950s. Our high school students are taught algebra, geometry, a second year of algebra, and calculus (for the most advanced students) because Eisenhower-era policymakers believed this curriculum would produce the best rocket scientists to work on projects during the Cold War. It has been 50 years since the U.S. reached the moon, almost 30 years since the Berlin Wall fell. Technology has advanced to the point that tiny powerful computers are routinely carried around in pockets and purses. Times have changed, and so has the math people use in everyday life. We surveyed 900 “Freakonomics” podcast listeners — a pretty nerdy group, we must admit — and discovered that less than 12% used any algebra, trigonometry or calculus in their daily lives. Only 2% use integrals or derivatives, the foundational building blocks of calculus. In contrast, a whopping 66% work with basic analytical software like Microsoft Excel on a daily basis. When was the last time you divided a polynomial? If you were asked to do so today, would you remember how? For the most part, students are no longer taught to write cursive, how to use a slide rule, or any number of things that were once useful in everyday life. Let’s put working out polynomial division using pencil and paper on the same ash heap as sock darning and shorthand. "When was the last time you divided a polynomial?" What we propose is as obvious as it is radical: to put data and its analysis at the center of high school mathematics. Every high school student should graduate with an understanding of data, spreadsheets, and the difference between correlation and causality. Moreover, teaching students to make data-based arguments will endow them with many of the same critical-thinking skills they are learning today through algebraic proofs, but also give them more practical skills for navigating our newly data-rich world. Data-based math courses allow students to grapple with real-life problems. They might analyze issues about the environment, space travel or nutrition. Students can examine the threat of wildfires or the ways social media is tracking their data, learning how to apply math to real-world issues. Other countries are moving much faster than the U.S. in instituting such a curriculum. Over the last 50 years, statistics and data science have become an integral part of the United Kingdom curriculum. Canada’s educational system, which is ranked highly internationally, also incorporates statistics and data. In addition, the Program for International Student Assessment, or PISA, measures how effectively countries are preparing students for the mathematical demands of the 21st century. Last week, PISA released a mathematics framework that guides the assessments. Data literacy is central to the framework. In contrast, U.S. high school students learn algebra and geometry — and are woefully underprepared for the modern world. The Los Angeles Unified School District is leading the way in updating the way math is taught. In 2013, the LAUSD secured approval from the University of California to recognize data science as a statistics course that students can substitute for Algebra 2 in the college pathway. Over 2,000 students are taking advantage of this option. The classroom we observed was full of critical thinkers who see data everywhere and appear comfortable interpreting, analyzing and questioning it. Modernizing math at a national level will require an intensive effort from educators, policymakers and high school counselors — as well as from students and parents who will need to advocate for it. Some states are already exploring changes to their mathematics frameworks, while a fair number of innovative teachers across the country are independently developing their own data-focused lesson plans. For this revolution to be carried out across the country, decision makers will need to hear from parents and other interested parties who recognize that our children deserve math instruction that is relevant to their lives. Jo Boaler is a professor of mathematics education at Stanford University and author of “Limitless Mind.” Steven D. Levitt is a professor of economics at the University of Chicago and co-author of “Freakonomics.”

In Freakonomics Radio Episode 391, Steve Levitt hosts and investigates whether traditional math instruction is really preparing students for the work of the digital era. By Steve Levitt. Produced by Zack Lapinski. Most high-school math classes are still preparing students for the Sputnik era. Steve Levitt wants to get rid of the “geometry sandwich” and instead have kids learn what they really need in the modern era: data fluency. Listen here on the Freakonomics Episode page, or listen and subscribe to our podcast at Apple Podcasts, Stitcher, or elsewhere. Below is a transcript of the episode, edited for readability. For more information on the people and ideas in the episode, see the links at the bottom of this post. Looking for more? Check out the Freakonomics Extras page dedicated to K-12 Data Literacy.