Teaching data science and statistical reasoning in addition to traditional algebra ensures that California students will be better prepared than ever.
By Pamela Burdman, Berkeley
Pamela Burdman is the executive director of Just Equations, a Berkeley policy institute, firstname.lastname@example.org.
Re “California’s proposed new math curriculum defies logic”; Commentary, Aug. 19, 2021
Though it is possible that learning the quadratic formula “made you a clearer thinker,” as Svetlana Jitomirskaya tells readers, many students, myself included, learned it as a rote procedure.
And to the extent that quadratics confer critical thinking, the implication that they somehow uniquely do so is absurd. Why not also teach randomization, confidence intervals and linear regressions — key statistical concepts that also support understanding of everyday phenomena? These topics are taught in new courses — such as CourseKata and Introduction to Data Science — offered at some California high schools. Both were developed by UCLA faculty (including Jim Stigler, whose research underscores how U.S. math teaching falls short of that of Asian countries).
Another canard is that teaching data science somehow jeopardizes the opportunity for future California students to learn algebra. Data science builds on algebra and uses functions to model real-world data, with value in preparing students for college and careers. The current 6th- through 11th-grade standards are also algebra-based. But data science, despite being a rapidly growing field at universities, is virtually ignored by most K-12 schools. That status quo has defenders, but it’s not good enough for the 21st century. Teaching data science and statistical reasoning in addition to traditional algebra ensures that California students will be better prepared than ever.
That’s probably why the committee of math teachers and administrators that developed the state’s draft math frameworks (despite Jitomirskaya’s claim that the “math community” was never consulted) chose to include them.