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Data science now a mandatory subject for all students
The world we live in is fueled by data. Every commercial, civic, or social interaction generates data, and this data is collected and stored in enormous server “farms” around the globe. Data scientists and statisticians are among the most sought-after professionals. Algorithms play a significant role in various aspects of our lives, from determining prison sentences to detecting potential suspects in crimes and influencing decisions related to loans, college admissions, and job interviews.
However, there are challenges that need to be addressed. When algorithms are trained using data that poorly represents specific populations, certain groups may be at a higher risk of wrongful incarceration. Moreover, data models developed without input from contextual experts can reinforce existing patterns of racism and sexism. Data breaches also pose a threat, as stolen data can be used for identity theft and other malicious activities. Privacy is at risk, with companies potentially knowing more about your medical conditions than your own family.
Surprisingly, statistics and data science are not mandatory subjects for high school students. Despite this, over the past decade, an increasing number of California high schools have offered statistics courses. In 2013, data science courses were also introduced to meet the admissions requirements of the University of California and the California State University systems. However, the future of these courses is currently under review by the University of California academic senate, which could make it even more challenging for students to acquire relevant skills needed for the 21st century.
I, along with other statisticians, believe that data science is an essential evolution of the current statistics curriculum. To address this need for modernization, I collaborated with high school teachers, UCLA statisticians, computer scientists, and education researchers to develop the Introduction to Data Science (IDS) course. Supported by the National Science Foundation, this yearlong high school data course aims to reflect the modern practice of statistics, which heavily relies on computers, algorithms, and various modeling techniques.
The Introduction to Data Science course was approved as a statistics course by UC’s High School Articulation Unit in 2013. The course aligned with the guidelines established by the American Statistical Association, the National Council of Teachers of Mathematics, and the Common Core state standards. Statistics courses have been approved as high school math courses without the requirement of teaching Algebra II standards.
However, recently, the long-standing practice of offering data science courses has faced controversy. Critics argue that these courses lack the necessary algebraic rigor. The real issue, however, is the purpose of high school mathematics education. Should it only cater to STEM majors, or should it serve the needs of all students? Moreover, if it is intended for future STEM students, is Algebra II the only starting point? The focus should be on providing rigorous courses that prepare students for the data-driven world, rather than categorizing them as “weak” or “strong” math.
This is not just my opinion as one of the developers; it is backed by high school leaders. The demand for data science courses has been widespread. Since the initial pilot in 2014-15, Introduction to Data Science is now offered in 189 high schools nationwide, with over 400 high schools in California offering one of the available data science courses. Research has also shown that these courses improve college preparation and matriculation.
Universities like UC Berkeley have recognized the importance of data science and established introductory data science courses. They emphasize that the instructional approach should not be viewed as “going soft on the math” and that hands-on experience and computational actions are crucial for developing conceptual understanding.
While it is true that high school students shouldn’t be forced into making major decisions, the reality is that for many students, the decision to take Algebra II and pursue a STEM path is already made for them. A study of over 450,000 California high school students found that only 40% of those who passed Algebra I continued to Algebra II. Courses like Introduction to Data Science provide additional opportunities for students to develop mathematical skills and prepare for college.
Statistics and data science courses equip students with essential skills to address major issues of our time. Even STEM students need to deepen their understanding of data science to avoid scandals and controversies arising from the misuse of statistical concepts. In a data-driven world, all students should learn data science, and for some students, Algebra II may also be necessary.
Robert Gould is a teaching professor at the UCLA Department of Statistics and Data Science, a fellow of the American Statistical Association, founder of the ASA DataFest competition, and co-author of a college introductory statistics textbook: Exploring the World through Data.