Tell me about your dog.
What type is it? What color is it? How much does it weigh? If you’ve got a cat, same questions apply. What’s the dog-to-cat ratio in your classroom (or office or home)?
If you’re able to answer these, that’s how you teach data science to third graders—taking what seem like complex or abstract concepts and applying them to tangible elements in students’ lives.
That was the approach that Claire Bowen and her team took when organized a week-long series of data science programming back in 2020, when the pandemic first forced students and teachers to hunker down into remote learning. Bowen, a principal research associate at the Urban Institute, wanted to fill the dearth of accessible teaching resources with sessions on coding, cartography, and—of course—Bowen’s pet-prolific workshop on data collection and visualization.
“There were some kids who were like, ‘Dogs, dogs, dogs,’ all the time, and that was an example of when you have oversampling,” Bowen says with a laugh. In all, about 200 students participated. “It just showed how much kids wanted to learn about this.”
Fast forward a couple years and the Urban Institute has transformed their original idea into Data4Kids, a series of “data stories” that educators can use to teach data science concepts in their classrooms. The project was released in December in partnership with seven K-12 organizations and a $10,000 grant from the National Science Foundation’s South Big Data Hub.
“We wanted to collaborate with educators and figure out what is it that they need, what have they learned in the last year about being in this remote environment and the best ways to engage students [in data science],” Bowen says, and the data stories concept was born. “We wanted to make sure it is as flexible as possible for instructors. Maybe they want to do something a little more advanced, or maybe they just want to get their kids’ toes wet into data and start with something a little more basic.”
Each data story toolkit comes complete with an instructor’s guide, data, and slidedeck. They include activities based on students’ grade level–third grade up to high school seniors—that explore topics like health equity, food insecurity and national parks. Each is designed for teachers to start using it without a lot of extra legwork.
Jonathan Schwabish, an Urban Institute senior fellow, says the students of today will be the data consumers of tomorrow, grappling with all of the security and privacy issues that come with it. Being able to discern data that’s truthful from data that’s not is going to be part of being a responsible citizen, he adds.
“It’s not like we’re born as human beings knowing how to read a bar chart,” Schwabish says. “It’s not in our DNA; we have to learn it. I think that education can’t come early enough, and we’re hoping the materials are low enough hanging fruit so educators can use them.”
Data4Kids is about connecting students with data science in ways that feel familiar to them. That means drawing and coloring data visualizations by hand, or gathering data like height and weight.
“Third graders are not doing multivariate analysis, but they can make some simple observations about the data,” Schwabish says. “One of the questions the team wrote was, ‘Count how many parks are in your state.’ That’s a very personal thing that kids can do.”
The project isn’t done yet, Schwabish says, and he’s hopeful that the templates provided by the initial set of Data4Kids stories will encourage educators and data professionals to become contributors to the collection of data stories. He’s already found a few people interested in creating data stories around topics in sports and test scores.
“Our hope is that we’ll be able to add more and more of these over time,” Schwabish says.
As the demand for data scientists and related professionals remains high, Bowen hopes Data4Kids will help get more students interested in data science careers. She says that collaborators have even talked about ditching the typical professional headshots that would go on the website in favor shots of them taking part in hobbies—an effort to better connect with kids who might see them.
It’s part of a broader effort “to show that you don’t have to be a certain type of person to work with data,” Bowen explains. “I’m a first generation college student and grew up in an area where traditionally women do not pursue a career at all. Having role models makes it so much more accessible and easier to believe it’s achievable.”