Data is now everywhere in our lives, informing our decisions about which new show to watch, what path to take or whether to grab an umbrella. But it’s practically absent from the way our kids learn.
Our approach to teaching data science and data literacy has hardly evolved since I started my teaching career in 1995. Yet now more than ever, K-12 students need basic modern data science skills.
Nearly 1 in 4 job postings in the United States require data science skills. These aren’t just tech jobs — they span industries from manufacturing to agriculture to transportation. The ability to capture, sort and analyze data is as important for small business owners as it is for computer scientists.
Now is the time to reprioritize curricular emphases to reflect the importance of data science and data literacy. With data talent in high demand globally, other countries are investing billions in data education.
But American K-12 education still underemphasizes data science and data literacy skills — including the ability to understand qualitative and quantitative data, assess claims based on data and make data-driven predictions.
How do we know? Look at the data.
According to the most recent NAEP results, between 2019 and 2022, student performance in data analysis, statistics and probability fell by a full 10 points for eighth grade students, representing what some experts consider a full grade level in lack of progress.
Data science education is typically reserved for higher education, but only slightly more than a third of Americans have a college degree. The opportunity to learn basic data skills should not be reserved for a select group of students.
Every student needs a chance to practice these vital skills from kindergarten through high school. That’s why I am excited for the National Council of Teachers of Mathematics to be a part of Data Science 4 Everyone’s national Chart the Course initiative, exploring the integration of data literacy and science across our most important school subjects. It will build upon NCTM’s work to reimagine, revitalize and increase math’s relevance for high schoolers.
As president of NCTM, I’ve had the honor of helping to lead the mathematics education community through a time of profound technological change, which has included developing a position statement on AI.
Additionally, in partnership with the National Science Teaching Association, the Computer Science Teachers Association, the National Council for the Social Studies and the American Statistical Association, we made an unprecedented joint call to build data science as an interdisciplinary subject across K-12 education.
Early in my teaching career, we focused on teaching students how to use a dataset to create a bar graph or scatter plot. Now, students need to know how to formulate the question that will generate the data, how to collect the data and how to interpret the data.
Students are eager to make sense of the world around them, but many don’t see how classroom instruction is related to the problems they will face as adults.
Data — in the form of numbers, graphics and videos — can provide the hook that pulls students into lessons with real-world examples and applications.
While a math teacher might look at a graph and observe that a certain variable decreased, a social studies teacher might say, “Of course there was a decrease, look at what was happening at that moment in history.”
If we want students to think with and use data analysis skills in their everyday lives during and after high school, we need to create relevant data-learning experiences that engage students in using statistics to make sense of the world around them. This will also result in better test scores because students will understand the material and be able to apply what they know.
We are now joining with Data Science 4 Everyone in an even broader effort to create the first-ever national K-12 data learning progression that stretches across school subjects. It will shape how generations of students study data.
Educator voices are vital to this process. We need input from the people who are closest to students and who will be rolling out data science lessons in their classrooms, so we’re asking them to weigh in. We need to engage our educators in order to effect change.
Data Science 4 Everyone’s Chart the Course voting platform is open through October 31, and we are encouraging teachers to vote for the learning outcomes they believe are the most important for K-12 students to learn by the time they graduate from high school.
The selection of the learning outcome options in Chart the Course was informed by 11 focus groups made up of students, educators, higher education leaders, policymakers, researchers, curriculum designers and industry professionals.
The collaborative approach was designed to create a framework that meets the needs of students and reflects the cross-disciplinary potential of data science. We hope to equip students with the skills they need to understand data and think critically and carefully as they interact with AI tools and draw their own conclusions about the world around them.
Engaging with data is a way to make education relevant for all our students and bring our many subjects together in unique ways. It’s time to chart a course that connects classroom learning to the lives of students. That should be our goal for all teachers.
Kevin Dykema is president of the National Council of Teachers of Mathematics (NCTM), an international mathematics education organization with more than 30,000 members. He has taught eighth grade mathematics for over 25 years in southwest Michigan.
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