I’ve said it before, and I’ll say it again — data is cool. It can help us answer questions and help us see connections we never noticed before. But data analysis is something that many students (and some teachers) never fully understand. That’s alarming, considering that our democracy depends on citizens being able to understand and analyze data — from environmental issues to crime statistics. Most companies and schools make major decisions based on data. And recent advances in technology mean that there’s a lot more data out there. Ninety percent of the world’s data was generated in the past two years. Much of that — like the information captured by activity trackers like FitBits and connected home devices like Nest — is also relevant to our daily lives. Data analysis is a skill all of our students need in this century.
But in the classroom, data analysis can sometimes be coma-inducing. My 6th-grade science students were always required to create a graph to help explain the results of their lab investigations. Usually, students created a bar graph for every lab, whether it was the best way to share the data or not. And whenever I questioned them, leading them to the conclusion that their graph might not have been the best, I was met with a deep sigh and a groaning, “I have to draw a new graph?”
That was at least partly because my students would spend hours hunched over graph paper, with rulers and colored pencils, making their graphs. I would stand at the front of the classroom and smile, convinced that they were learning important data lessons. But even when these carefully-created graphs had egregious errors, the students often couldn’t point them out. And several students couldn’t tell me what patterns their graphs suggested.
All that is why I’m really excited about the free website Tuva. Tuva (formerly Tuva Labs) was released a little more than a year ago, and it has one of the simplest graphing interfaces I’ve ever seen. Students can use an existing set of data from the website’s database, or they can upload their own data. Then — using a computer, Chromebook, or iPad — they can use the site’s graphing interface to select which variable(s) should go on the x-axis and the y-axis and how to display the data (bar graph, line graph, scatter plot, etc.). They can even visualize functions, like the line of best fit or the mean. This video briefly demonstrates the website’s graphing tool:
I love Tuva because it finally allows us to teach students about data analysis the way we know students learn best — with ABC (Activity Before Content). What do I mean by that? I’ll be working with 5th graders on data analysis this school year, and Tuva allows me to start them off with no direct instruction about graphing. I can send them all to Tuva and have them open the “Ocean Animals” dataset. Then I can briefly mention the graphing interface (I show them little more than the click-and-drag function and the reset button) and ask, what can you learn from this data?
I can then give students time to explore. They can try putting different variables on the x and y axes. They can visualize the data in various ways. They can talk to their partners and table groups about what they’re finding out. And, after 20 or 30 minutes of exploration, as a class, we can start coming up with some general rules — what works best on the x axis? Why? What works best on the y axis? Why? What information did you learn from different types of graphs?
As a class, we can repeat this procedure with different types of datasets — ideally, most of the data sets would be those collected by my students. (Research tells us that students are far more engaged in data analysis, and understand the process better, when they analyze their own data.)
Rather than telling students which graph is best for what type of data, they can discover it. They can discover why it’s best to put the independent variable on the x axis. And as we know, when students create their own understanding, they are far more likely to retain it.
Tuva is currently totally free — teachers can create accounts for themselves as well as students, and can create classes on the site. Users can upload their own data sets and can make them public. Teachers can also add specific activities or question sets to data sets and then assign them to students. However, Tuva is set to become a Freemium service in the near future. It will still have many free features, but some of the features (uploading multiple data sets, requesting data sets from the site) will require a subscription fee. Tuva is also hoping to create a viable business model by offering web-based and in-person data analysis trainings for teachers.
Take a look at Tuva, and make a plan for using it this school year. Add a comment to share how it worked!