McCusker remembers one girl who appeared to find the whole exercise tedious—“it was just another lesson on not drinking”—and so he sat down and helped to work through the interface.
“Do your teachers tell you not to drink,” he asked, do they tell you it’s a bad thing to drink?”
“Yeah,” she replied.
“Does it do any good?”
“Do you think your teachers think it does any good?”
“If your teachers think it is pointless and you think it is pointless, why are you still doing this?”
At which point, he says, she sat up and started looking at the data to see if it really was pointless. “From this, she saw that those criticizing her generation for drinking too much actually drank the same [amount] when they were her age.”
“The data,” he says, “empowered her to say, ‘yes, I know these are pointless as lessons because, basically, you do what your friends do, and here’s some evidence.’ It’s a powerful thing for people to have a voice in their own lives. They can use data to make decisions over right and wrong contextualized to their behavior. Are they more at risk, as portrayed by the media, or are things as they have always been?”
This sense of empowerment was general—even for 13 and 14-year-olds around the 75th to the 80th percentile of the academic spectrum, says Nicholson. “They weren’t using sophisticated language like ‘interactions,’ but they were quite clearly identifying changes in behavior—and critically for us, they were quite comfortable doing that.” Technology, the interface, had unlocked their “natural” statistical reasoning; they were using big statistical concepts—interactions and effect sizes—without realizing it.
There were several reasons for this.
First, the exercise didn’t start with a closed, direct question that demanded the binary thinking of “I must find the right answer to this.” For kids whose normal experience of math was that of mostly getting things wrong, says Nicholson, this was psychologically freeing. “They were much more open to having a go at interpretation.”
Second, they connected with the data. “Their friends are part of the data,” says Nicholson, “they are part of the data. They know the older kids drink more than the younger kids, so they have something matching their experience, and therefore they have a language to talk about the data. Not having a language to talk about data is, I think, a big obstacle.”
We’ve shown, through access to large and relevant data sets that kids “can do things we thought were too hard for them,” says Ridgway via email. “Children need to see that there is a point in investing effort in learning things—and/or that it is fun. Content needs to be relevant to them—or they can see it is relevant to someone. A problem with math classrooms has always been the triumph of technique over meaning and usefulness. Interactive displays let kids see real stuff.”
The implications for educational inequities are not lost on the researchers, both in terms of getting people to ‘see’ that such inequities exist, and then to start doing something about them. In this, good interactive displays also give overburdened teachers a chance to improve their skills in posing questions.
Inexorably, this leads to the role of data and reasoning from evidence in sustaining democracy. The more kids (and citizens) have access to data through interactive displays, “the more they will be empowered to think about how the world is organized and should be organized,” says Ridgway. “A disadvantaged underclass, where people don’t value knowledge, is a threat to democracy.”
McCusker, who also uses Lego to get people to build physical models of ideas in order to extract how people see problems, is even more expansive: We have to think of statistical literacy as a democratizing skill that must be open to everyone, and not just experts. “If you want to understand complex social phenomena,” he says, “there is a small group of people who decide how they are analyzed and presented, and what is valid. I’d like to see recognition that new conventions are acceptable and to open up the scope of data interpretation to a much wider population. Then we can argue what it all means and what’s right and what’s not right.”