Dive Brief:
- Incorporating data analysis into subjects like social studies can make math and data science more approachable for students, according to experts.
- “Anytime we can cross over disciplinary lines without abandoning the core principles and practices of the disciplines, learning becomes more engaging, especially when it's relevant,” said Tina Ellsworth, president of the National Council for the Social Studies.
- Zarek Drozda, executive director of Data Science 4 Everyone, said data skills and data analysis are an emerging fundamental basic that every student needs by the time they graduate from high school. However, the vast majority of K-12 students in the U.S. are not receiving data science education.
Dive Insight:
Data Science 4 Everyone is partnering with different national organizations, among them the National Council for Social Studies, to explore how to incorporate data science across disciplines.
According to Drozda, creating these connections between data science and various academic subjects is especially important during middle and high school, where subjects tend to be siloed. The interdisciplinary approach helps students understand the real-world implications and applications of math.
“Most kids despise rules for the sake of rules without any connection to their background or what they're passionate about,” said Drozda. “What data science offers for the school subject of mathematics is that connective tissue to show why quantitative analysis is important and what it can do if you're excited about history or economics or ecosystems in biology.”
For educators interested in incorporating a data analysis component into their curricula, Drozda recommends starting by looking at the state standards that already need to be covered. Instead of relying on a textbook chapter, he suggests finding one of many readily available data sets online that cover that topic.
For example, the history of World War II, the cycle of economic booms and busts, and the growth of certain species in an ecosystem can all be explored through data sets, he said.
Teaching students how to grapple with data allows them to discover the subject matter themselves, which makes learning more engaging and more likely to be retained, said Drozda.
“It's incumbent upon us as social studies professionals to include data literacy, because of all of the data our students are engaging with on a daily basis that they may not yet know how to make sense of,” said Ellsworth.
While data analysis can strengthen social studies curricula, social studies also bolsters data literacy because it teaches students to question the data and its source to assess different biases.
“We don't want to abandon the stories and the qualitative things that we can learn from history for more statistics and mathematical models,” said Ellsworth.
To support this cross-curriculum collaboration, administrators and principals can best support educators through effective professional development, said Drozda.
Drozda highlighted that Data Science 4 Everyone has a network of curriculum and professional development teams available as a resource that can partner with schools or districts to host workshops on teaching strategies. This, he said, makes data analysis integration easier and more feasible, as they help cover the content educators already have.
Administrators and principals should also ensure that teachers have access to classroom-appropriate data analysis software, such as Excel spreadsheets and other education-specific tools, which exist to help build lesson plans, Drozda suggested.
Drozda also recommends that principals allow time for shared instructional planning across school subjects.
“We've seen again and again the power of giving the math and the science teacher a couple of hours to sit down together and really plan out a couple of units jointly, or think about where they see an intersection between their content at a particular grade level,” he said.
A challenge that Data Science 4 Everyone has encountered while working with state standards, according to Drozda, is that there is often not a perfect alignment between math standards and social studies or science standards, something the organization hopes to help improve over time.
“Mathematics is an obvious home base for data science, but we would lose a major opportunity if we didn't make clear connections to other school subjects where we know it can be a beneficial teaching strategy,” he said.