How California’s ‘math wars’ hurt black and Latino students

California’s math wars are shaking the state’s education system, with contentious debates over high school curriculum.

The question is whether a “data science” course should be available as a replacement for Algebra 2. The University of California and California State University systems previously accepted data science as an advanced math requirement in place of Algebra 2. But both UC and CSU recently reversed that decision.

Data science proponents cite the high failure rates of Black and Latino students, even in Algebra 1. They point to real-world, real-world applications of data science as a great motivator for students over boring subjects and theoretical algebra such as the quadratic formula, arguing that the substitute offers more vital knowledge for our data-driven society. Two popular data science degree programs have emerged: UCLA’s Introduction to Data Science and Stanford’s Youcubed.

But as a longtime data science teacher, I am dismayed by the implications and consequences of allowing data science to substitute for Algebra 2. Among other concerns, it would harm Black and Latino students , the very group that data science proponents claim to help, in teaching they have virtually no practical or conceptual skills.

Opponents of data science programs like myself believe that the courses, while effective at engaging students, are so superficial that they amount to “data science appreciation” courses at best. Any substitute for Algebra 2 should be of comparable mathematical sophistication. Even the author of Introduction to Data Science admitted that his course contained “only a hint of math.”

Most Black data science professors at UC oppose dropping the Algebra 2 requirement for UC admission. Data science risks becoming known as the “Black and Latino math class” among students, parents, and teachers. As of March 2023, according to numbers I obtained through the state’s Public Records Act, 936 of 1,091 data science students in the Los Angeles Unified School District were Hispanic. Where is the outrage over certain populations being diverted to a lower course?

Real data science, unlike most courses, is more than just drawing a few graphs and bar charts. This is a deep and sophisticated area in which even we specialists can make subtle but very serious mistakes. Students with weak math skills simply don’t have the foundation to understand the nuances of applications of the subject.

In particular, the field requires strong skills in basic mathematical topics such as the slope of a line, functions, etc. — in other words, Algebra 2. Some college and K-12 teachers have suggested a compromise: teaching data science alongside Algebra 2 topics, thereby challenging students while developing their math skills. This could be a great solution, but the options available are not yet well developed.

An integrated course should not only include logarithms and exponentials, but should actively connect these ideas to data science applications, where they are widely used. The method known as logistic regression uses exponentials to help predict whether an event might occur, and it has a log-based interpretation. Did you know that the famous “bell curve” uses both exponential and quadratic functions? Data science also uses matrix algebra, which can be used to determine the probability of a player going bankrupt. All of these concepts would fit nicely into the R programming language already used in data science courses.