New developments that help prepare students for tomorrow’s careers require a fresh approach, as well as more teachers who can transmit the knowledge.
By Elisha Smith Arrillaga
Elisha Smith Arrillaga is the managing director of the Charles A. Dana Center at the University of Texas at Austin, firstname.lastname@example.org.
Pamela Burdman, Special to CalMatters
Pamela Burdman is the executive director of Just Equations, a Berkeley policy institute, email@example.com.
Awash with data and powered by computers, our lives look very different than they did a few decades ago, as do the ways we research and learn about the world. Whether the topic is political polling, COVID-19 epidemiology, police shootings or sports statistics, understanding data is key to making sense of our social and natural environments.
College education is shifting in light of this reality, with California universities leading a transformation in the definition of quantitative literacy, and in designing math courses and pathways to better prepare students for 21st-century careers. This shift offers promising new ways of teaching math before college — but only if our K-12 system seizes the opportunity.
Consider a course titled Foundations of Data Science pioneered at the University of California at Berkeley six years ago to teach undergraduates statistical analysis and computer programming. Developed in response to rapidly rising interest in statistics and computer science classes, the course quickly became the fastest-growing class in campus history.
Around that time, UCLA biology faculty developed a new introductory math class designed for life sciences majors, a course that incorporates computational thinking and modeling of biological systems, along with calculus concepts. Today, all life sciences majors take the course, rather than traditional calculus.
Recognizing the importance of these modernized pathways, UC noted in a 2016 statement that high school students needn’t take calculus to be eligible for admission. Last year, it went further, broadening the options it accepts for students’ third and fourth year of math.
Students seeking to attend California universities can still opt for such traditional courses as Algebra 2, precalculus and calculus, particularly if they’ve decided to pursue a major like physics or engineering. But now they can also choose to learn programming, explore data science and use mathematics to model real-life problems through certain computer science, data science or discrete math courses that are relevant preparation for a wide array of majors, including science majors. The new admissions policies also apply to the California State University system, which previously signaled its interest in broadening quantitative reasoning requirements.
Still, too few high schools offer these 21st-century courses, and because of the longstanding emphasis on traditional calculus-path courses, not enough students, counselors and families recognize that there can be valid options for college-bound students. New developments promise to build the capacity of K-12 schools to prime students in areas like data literacy. They mustn’t be thwarted by the misperception that they will weaken the math curriculum.
Following the lead of key math societies, the California Department of Education’s newly proposed California Math Frameworks recommends incorporating data science into the curriculum beginning in elementary school, with free-standing course options in high school. UCLA faculty already have piloted the Introduction to Data Science course, which is now being offered in 52 high schools across 17 California districts. It is one of five courses funded by the state to broaden the range of math curriculum and pedagogy available to high school juniors and seniors.
Still, a barrier to implementing such new options — one that recently introduced federal legislation (S 1839/HR 3588) seeks to address — is the dearth of K-12 math instructors prepared to teach them. The bipartisan bill would support more training for teachers to teach statistics, data science and mathematical modeling.
Because the traditional sequence of algebra courses leading to calculus has been the norm for decades, it’s not surprising that anything different would be perceived as suspicious or strange to many students, families and even teachers. That’s why it’s important to support the math frameworks’ emphasis on data science and spread the word that, outside of specific technical programs, almost no university in the country requires calculus for admission.
The math sequences of the past were based on tradition and differentiated by perceived difficulty. The evidence-based math pathways of the future offer rigorous and relevant preparation for college and lucrative careers, differentiated by students’ areas of interest. Math classes should be used to propel students forward, not hold them back.