Data Science Collides with Traditional Math in the Golden State – Datanami

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Is traditional math still important in data science? Or can a new curriculum based on data science replace some of traditional mathematics courses while promoting greater racial equity? These questions are at the heart of a debate that’s heating up in academic circles this month.

The issue of racial disparities in middle school and high school math classes has been a subject of concern for some time. In San Francisco, public school educators have pulled back on the availability of advanced math classes in an attempt to close the performance gap.

San Francisco’s approach is the model for a new math framework proposed by the California Department of Education that has been adopted for K-12 education statewide. Like the San Francisco model, the state framework seeks to alter the traditional pathway that has guided college-bound students for generations, including by encouraging middle schools to drop Algebra 1 (the decision to implement the recommendations is made by individual school districts).

This new framework has been received with some controversy. Yesterday, a group of university professors wrote an open letter on K-12 mathematics, which specifically cites the new California Mathematics Framework.

“We fully agree that mathematics education ‘should not be a gatekeeper but a launchpad,’” the professors write. “However, we are deeply concerned about the unintended consequences of recent well-intentioned approaches to reform mathematics, particularly the California Mathematics Framework.”

Frameworks like the CMF aim to “reduce achievement gaps by limiting the availability of advanced mathematical courses to middle schoolers and beginning high schoolers,” the professors continued. “While such reforms superficially seem ‘successful’ at reducing disparities at the high school level, they are merely kicking the can to college.”

Data science also plays a role in the debate, since the California Math Framework also brings recommendations centered around the use of data science. In fact, it devotes an entire chapter to the data science, which it defines as “the process of uncovering the stories hidden within data.” The framework encourages teachers to use data science techniques to present lessons, as well as teaching some of the basics of data science as well.

A visualization of Kira’s dog’s interactions (California Mathematics Framework)

The CMF also provides examples of how data science and statistics power the investigation process, and describes resources that will be available to students, such as the Common Online Data Analysis Platform (CODAP), which the CMF describes as “a set of databases that will be interesting to school students, such as data on earthquakes, mammals, stars and cities….”

Considering the current shortage of professional data scientists, which are projected to get even worse in the coming years, the decision to prominently position data science in the new math framework could be seen as forward-thinking. To be sure, all sorts of data analysis techniques will be important job skills to have in the future, and getting students familiar with the concepts and terminology can position them for greater success in the future.

However, the university professors take issue with the Gold State’s treatment of data science as a whole, specifically the possibility that the proposed data science education would replace the more traditional approaches to teaching mathematics.

“Another deeply worrisome trend is devaluing essential mathematical tools such as calculus and algebra in favor of seemingly more modern ‘data science,’” the professors write in the Open Letter. “As STEM professionals and educators …….

Source: https://www.datanami.com/2021/12/06/data-science-collides-with-traditional-math-in-the-golden-state/

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