Can we really measure happiness? How does educational attainment vary across ZIP codes? What does math have to do with charity? Which team has the better athletes, Yankees or Red Sox? These are just a few of the wide-ranging questions that students are asking -- and attempting to answer -- by analyzing data.
"Looking at data needs to become part of the conversation across every classroom, not just in math," says Harshil Parikh. He's co-founder of an educational platform called TuVaLabs that connects students with data sets and analytical tools to help them make better sense of their world.
Start with Curiosity
The idea for TuVaLabs emerged when Parikh was tutoring children in the slums of Delhi, India. "I was looking for tools to drive inquiry," he explains. Drawing on his own background as engineer, educator, and social entrepreneur, he knows that curiosity can be a powerful motivator for learning.
But curiosity alone isn't enough to ensure that learning happens. Students often need to do some investigating and critical thinking to arrive at answers that they can trust. That's where TuVaLabs comes in. When students (or teachers) post questions on the site, Parikh and his team get busy scouring sources of publicly available data that relate to the topic. Then they curate data sets to make the information accessible to students. TuVaLabs might provide some context about an issue, offer background about the data source, or suggest specific strategies to represent information visually. The service is provided at no charge for teachers and students.
"We want to be a bridge between schools and the open data movement," Parikh explains. From the World Bank to local government bureaus, organizations are becoming increasingly transparent about the information that they gather. People who know how to analyze and interpret open data (such as Nate Silver of Five Thirty Eight can crunch those numbers to make predictions, explain historical trends, or poke holes in faulty arguments. Students who become data literate are better equipped to make sense of the information that's all around them and support their arguments with reliable evidence.
Leverage Tools and Techniques
What does data analysis look like in a K-12 classroom?
The Global Happiness Project, designed by the New Tech Network, offers an engaging example. The project, still underway, connects students around the world in an investigation of happiness. This collaborative project has attracted more than 240 teachers and thousands of students in 43 states and 11 countries.
Since January, students have been thinking hard about how to measure happiness, exploring existing metrics such as Bhutan's Gross National Happiness Index. They have designed and administered surveys to gather their own data about key indicators of happiness and are communicating their findings in a variety of formats. The project will conclude in May with students proposing action projects that leverage data, creativity, and community to increase the happiness factor in their own communities.
At Tantasqua Regional Junior High in Massachusetts, health teacher Jamie Armin says the project has sparked a variety of student investigations. Some students want to dig deeper into the science of happiness. Others are interviewing family, teachers, friends, and community members about what makes them happy, building on the data with personal stories. An eighth-grade team is exploring laughter therapy. "Happiness is a great topic for middle-school kids," says Armin.
Across a range of grade levels, content areas, and cultures, the Global Happiness Project is teaching students to leverage data to be better investigators and thinkers. To learn more about the project, follow project updates on Twitter with the hashtag #ntnhappy or explore the Global Happiness Project survey data on TuvaLabs. More than 1,400 people have responded so far.
Connect Data to Student Interests
Eleanor Terry, an award-winning math teacher at the High School of Telecommunications Arts and Technology in Brooklyn, New York, is known among her colleagues as the go-to person for any project that involves data. "I try to be vocal about teachers using data in their classrooms," she says.
She started using TuVaLabs last fall and finds the platform useful for connecting math content with student interests. "We might all be working on scatterplots or standard deviation, but students can choose which data set to use," she explains. Some students will gravitate to sports, while others might want to analyze a data set that has to do with education, entertainment, or a social justice issue like human trafficking. They're all learning the same math concepts, "but with more student choice. That's not always easy to do in math," she adds. She teaches statistics, AP statistics, and trigonometry.
When students choose which topic to explore, they're more apt to ask questions that take them deeper. "If they get to choose a data set that interests them, then I can ask, what do you want to know about that? It's a much better entry point for thinking about statistics," she says.
Not surprisingly, students are drawn to data that reveal something about their own lives, such as looking at SAT scores at schools across Brooklyn. To build on local interests, TuVaLabs features hyper-local data sets about specific communities in the U.S. and internationally.
While exploring data sets, Terry says, students also are "training their eyes to look more critically at visual representations. What message do they want to convey with data? What's a reasonable number? Those are all important questions."
Thinking analytically about data can start as early as the elementary grades. Tania Hipple-Lopez, math specialist at the MUSE School in Calabasas, California, helps students connect math with their interest-driven projects. "If doesn't matter if the project is about dogs, skateboarding, or fashion," she says. "We want to infuse it with math."
Once she discovered TuVaLabs, Hipple-Lopez began requesting specific data sets to connect with students' projects. "One boy was doing a project on the U.S. Marines. TuVaLabs found a data set about the various branches of the armed forces and how the size of the military has changed. That led to a rich discussion," she says.
Hipple-Lopez encourages students to consider the source of information as part of their investigation. "We'll talk about, are the numbers trustworthy? What can we learn by looking at the source?" If students want to use data to tell a story, they need to consider the best way to represent information visually. "Which format is most appropriate for which data? They may know about bar graphs, but what else is available? How do you make data understandable and interesting to others? There are lots of teachable moments," she says.
One of the curiosity-inspiring features of TuVaLabs is the "Ask" tab. Students can pose a question they're wondering about and speculate about the type of data they would need to answer it. Eventually, the community will be able to vote for favorite questions, creating a leader board of hot topics. That should generate even more questions, fueling the inquiry cycle.
What do your students wonder about? How do you help them use data to arrive at reliable answers? Please share your thoughts in the comments section below.