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While data science isn’t a new subject, there’s been growing interest recently in helping students — in both K-12 and higher ed — gain data science skills.
One reason is the shifting job market, said Zarek Drozda, director of Data Science 4 Everyone, a national initiative based at the University of Chicago. “The top skills in demand today are data analysis, data interpretation, being able to communicate about data,” Drozda said. “It’s hard to find a career or a sector of the economy where data skills are not important.”
With the rise of artificial intelligence tools such as ChatGPT that rely on data sets, students also need to understand how to use AI in a responsible way, he added.
The adoption of data science education hasn’t been without controversy. In 2020, some of California’s public universities allowed applicants to skip Algebra II and substitute data science. The universities walked back the effort this year after experts argued that students were taking less challenging coursework that limited their post-secondary opportunities.
No state is currently getting rid of algebra courses in favor of data science, Drozda said. Rather, some are introducing the subject as an additional option for students. In the last three years, 17 states have added some sort of data science education course to their K-12 offerings, Drozda said.
“There are opportunities to make the barrier to entry low, but the benefit high so that students are able to see the existing school subjects in a context that is relevant to their daily life.”
Zarek Drozda, director of Data Science 4 Everyone, a national initiative based at the University of Chicago
In higher ed, data science is often housed in a particular school or limited to one field of study, such as a mathematics or computer engineering. But North Carolina State University is taking a different approach to teaching the subject, said Rachel Levy, executive director of the school’s new Data Science Academy. N.C. State launched the academy two years ago to introduce the use of the subject across disciplines, from biology and art to English and history.
To help all 10 of its colleges introduce courses incorporating data science, available to students at different levels, the university adopted the All-campus Data science through Accessible Project-based Teaching and learning model, or ADAPT. Examples of interdisciplinary classes available to students in any college include “Introduction to Data Visualization,” “Introduction to R/Python for Data Science” and “R for Biological Research.” The classes are project-based, and history or English major might choose to focus their class project on applying the use of data science to a topic within their major. Students are also encouraged to apply the skills they learn in these classes to other non-data science courses as well.
The university’s College of Education is also using the ADAPT model to prepare future K-12 teachers for the classroom. Using federal grants, N.C. State researchers are studying the model and its impact on teaching and learning. Meanwhile, the Data Science Academy is collaborating with the state’s Department of Public Instruction, hoping to roll out data science education in schools across the state, according to Levy.
Taryn Shelton, the academy’s K-12 data science coordinator, said the goal isn’t to add yet another thing to teachers’ plates, but to help them use data to enrich their lesson plans and expose students to data science skills early on. Her team is working with school districts outside of the tech and research-heavy Raleigh-Durham-Chapel Hill Triangle area, as well as with more rural and underserved districts, to help educators build data science concepts into their curriculum. ‘Shelton’s team also hosts events like mini hackathons where high schoolers can work with data.
“There are lots and lots of ways across the disciplines that teachers can bring in data,” said Levy, the academy’s director. Social studies teachers can help students explore data about people, places, events and cultures, she said, while English teachers might have their students identify and count words or phrases that help create a particular mood in a piece of writing.
If educators introduce data science in authentic ways that connect to students’ interests, Levy said, their comfort with the topic will grow. “People of all ages can engage data in ways that are useful and meaningful and challenging,” she said.
The challenge right now, said Data Science 4 Everyone’s Drozda, is that most students don’t encounter data science until they take AP Statistics or Intro to Data Science toward the end of high school, if they encounter it at all. But it doesn’t have to be that way. Drozda and Levy envision data science being integrated into the elementary and middle school curriculum, with teachers using data sets in biology units about ecosystems, or to analyze economic booms and busts in social studies.
“It’ll be really important for students to build a comfort and familiarity with the data science way of thinking, as well as the computational and technology tools,” said Drozda. “There are opportunities to make the barrier to entry low, but the benefit high so that students are able to see the existing school subjects in a context that is relevant to their daily life.”
This story about data science was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the Hechinger newsletter.
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