Welcome back to our August blog series on high school data science.
We’re nearing the end of our monthlong series and this week present to you our penultimate debunking of common claims against high school data science education.
In the first three blogs, we introduced the series and explained the problems with several common arguments against teaching data science in high school.
This week we look at another common claim we hear when people say high schools don’t need data science courses:
CLAIM: High school math has existed without data science for decades; it doesn’t need it now.
FACTS: All disciplines are updated to reflect changes in knowledge, culture, and technology. The calculator has replaced the slide rule, Latin is rarely taught, and diagramming sentences is no longer part of the English curriculum. To teach math as it was taught 50 years ago, before computers were ubiquitous, deprives students of the opportunity to acquire the most relevant and up-to-date quantitative reasoning skills.
But still there are questions. Is data science mathematical enough? Is it really math? Shouldn’t it be taught as an elective or in a social science class? Doesn’t introducing students to data science interfere with them learning the mathematical canon?
What is important to note is that arguing for the inclusion of data science in high school shouldn’t be misconstrued as an attack on mathematics itself.
The National Council of Teachers of Mathematics says the purpose of school mathematics is “to expand professional opportunity, understand and critique the world, and experience wonder, joy, and beauty.” Reuben Hersch, a mathematician and philosopher of mathematics, has also posited that mathematics is “a human activity” where mathematical objects are “created by humans, not arbitrarily, but from activity with existing mathematical objects, and from the needs of science and daily life.”
High school data science fulfills these purposes and gives students the opportunity to engage creatively, socially, and rigorously with the world around them and critique it using data. There is no need to look for ways to apply data science to the real world, as it is already a tool for understanding it! For example, a data science course framework developed by the Charles A. Dana Center emphasizes that students develop the ability to contextualize data, collaborate with fellow students, and learn programming and data visualization technologies.
This framework also reflects many of the Common Core mathematical practices, teaching students to use tools strategically and helping them “apply the mathematics they know to solve problems arising in everyday life, society, and the workplace” by modeling with mathematics.
Data science courses can also give students a greater sense of mathematical confidence. Erica Heinzman of UC San Diego reports that high school students who took the Introduction to Data Science class developed by UCLA “derived a sense of competence or self-efficacy from the purposefulness of coding.” In interviews, students described the subject matter as fun and accessible, in contrast to prior experiences with mathematics and statistics associated with detachment and failure. As noted in the second blog in this series, a course can be both rigorous and engaging.
The success and confidence these students experienced reflect the mathematics outcomes we strive toward as educators. Unfortunately, the current approach to math education has not been providing such outcomes for all students. This has contributed to a huge underrepresentation problem in STEM fields, particularly among women and students from minoritized communities. Certain mathematics pathways today are essential to a STEM career and a barrier to them as well. With more than half of California high school seniors taking no advanced math courses at all, innovative and rigorous secondary math courses in subjects such as data science are needed for developing more equity and opportunity for students.
In the end, there are many reasons why high school mathematics education exists. One of these is for the continued transfer of mathematical know-how. But high school math education should exist, first and foremost, for students. Our goal should not be to aim for an either-or stance on math education. We can both adequately prepare students for formative experiences in their college-level STEM classes and provide mathematical avenues that better reflect our society’s changing needs, purposefulness in math learning, and collaboration among students. We must recognize that mathematics as we know it today is founded equally on principles such as logicism and humanism. The teaching of mathematics must strive for the same.
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