When educators are researching and comparing edtech tools, they’re not just looking for a solution to a problem. They’re looking for a solution to their problem—suited to the unique needs of their students.
So what’s the best way to choose edtech when what worked for a small district in the Midwest might not have the same outcome for, say, an urban district in New England?
That’s what a new partnership between the EdTech Evidence Exchange and the National Council of Teachers of Mathematics aims to work out. The goal is to pay thousands of math educators—who work from early childhood education through high school—to give in-depth feedback on the edtech products they’ve used, information that will help their colleagues around the country make better-informed decisions about edtech for their own classrooms.
Through the partnership, called EdTech Evidence Exchange Platform, about 1,500 math teachers have participated in detailed surveys and interviews, says Bart Epstein, CEO and founder of the EdTech Evidence Exchange. Participants are paid $50 per hour to share their experiences with edtech.
Epstein and his collaborators are trying to bring a semblance of order to an edtech landscape he says is deeply fragmented. Educators are flooded with edtech marketing, he says, but the country’s thousands of schools have no way to effectively learn from each other’s experiences with edtech products.
“Every school wants to know what other schools are doing, what worked, what didn’t, what would they do differently,” Epstein says. “That takes time to document in a way that’s standardized. We want to know about their environments. How did it operate with your LMS? Some products may only thrive if teachers have sufficient planning time.”
The idea is that through the EdTech Evidence Exchange Platform, information about edtech products will be able to flow freely. Educators can move away from reliance on Google searches, social media and word-of-mouth to find the edtech they need, Epstein says.
Without the stipend, there would still be some population of teachers who would participate, he surmises.
“But they’d probably be the super nerds who love tech and love to evangelize, teachers who have relatively more free time, maybe they don’t have school-aged kids of their own. It would not be a representative sample,” Epstein says.
Rather, it’s those educators who feel like their experiences are valued the least that are needed the most, he adds.
“What works for teachers who are facing the most challenges, the most technology struggles?” Epstein says. “If we can figure out which tools work for them, we can have a tremendous collective impact on their students, which is of course the goal.”
Among the program’s first 1,000 participants, 83 percent of educators said they are never, almost never or only occasionally involved in the edtech selection process.
Math teachers are recruited through partnerships in Alabama, Nevada and Utah and with members of the National Council of Teachers of Mathematics. Epstein says the University of Virginia’s School of Data Science is working on an algorithm that will match users to schools that are similar to their own, helping them efficiently sort through the information.
“Just because my and your school are across the river from each other doesn’t mean we’re anything alike,” Epstein says. “In schools that are dysfunctional in the way that mine is dysfunctional, what worked?”