Teachers have used signals technology – radio, film, television, computers, internet, mobile devices, and more – in classrooms for over a century. Researchers have investigated these cycles, both contemporaneously and in retrospect, and two important patterns stand out.
First, when teachers have access to new technologies, they primarily use them to extend existing practices. Smartboards replace acetate overheads, teachers distribute recitation worksheets through learning management systems, and traditional grades are entered into digital gradebooks. Most educational technologies leave a minimal imprint on classroom practice. Despite this overall trend, there are many examples of innovative practice that happen in classrooms across America, pockets of excellence where students use technology as producers rather than consumers to develop and demonstrate their understanding in innovative ways.
The second crucial pattern in education technology research is that this innovative practice with technology is concentrated among affluent schools and families. Students attending schools serving affluent neighborhoods are more likely to use technology for deep learning and creative, production-oriented applications with the support of adults and mentors, and students attending schools serving poor neighborhoods are more likely to use technology for drill and practice with less adult support. When we look within schools, we see similar patterns. Interview teachers about who they do the most interesting education technology work with, and many will tell you that they reserve their most innovative practices for students in their honors and advanced classes. These tracking practices class map onto within-school divides of race and class.
The sociologist Paul Attewell in 2000 called this the “Second Digital Divide.” The first digital divide concerns access: affluent youth have more access to signals technology than their less affluent peers. The second digital divide is one of usage: students from affluent families have better access to richer technology-mediated learning experiences with more support from adult mentors.
In Attewell’s time, researchers investigated these differences using anthropological observations and nationally representative surveys. New online technologies give us important new datasets to investigate these phenomenon: we can look at the clickstream records of what people do and combine them with demographic data to understand how people from different circumstances use technology differently.
In the last ten years I’ve worked on two major studies about the second digital divide. In the late ‘00s, I studied how teachers and students used social media and peer production tools like blogs and wikis. At the time, there was a real optimism that the tools would be as transformative in education as they had been in journalism, business, social relationships, and information management. Moreover, since so many tools were free, the hope was the low-income students would particularly benefit from access to these learning tools. I looked at data from hundreds of thousands of wikis used in K-12 education settings, and found that wikis were more likely to be created in affluent schools, and the wikis created in those affluent schools were used for longer periods of time with greater opportunities for student involvement. Wikis created in schools serving low-income families were more likely to be used for teacher-centered content delivery.
After the passing surge of interest in social media and peer production in education, MOOCs became the next participant in the edtech hype cycle, with advocates declaring that free online courses would democratize education. With my colleague Dr. John Hansen, we connected MOOC registration and participation data from edX with demographic data from the census, and we found that people living in more affluent neighborhoods were more likely to sign up for MOOCs. Moreover, markers of socioeconomic status—like having a parent with a college degree or living in a more affluent neighborhood—were positively correlated with course completion. MOOCs opened a door of opportunity, and there are incredible stories of learners from very difficult circumstances who took advantages of these new opportunities, but the majority of people who walk through that door of opportunity were already educated, and already affluent.
Learners with more social, financial, and technological capital are better able to take advantage of new education technology advantages, even when those technologies are free. By default, we should expect that most education technology initiatives—including those made available for free online—will disproportionately benefit the affluent.
With my colleague Mimi Ito, I recent published a report laying out this arguments in greater detail: From Good Intentions to Real Outcomes, Equity by Design in Learning Technologies. In the report, we extend the short argument presented here about the second Digital Divide, and we begin to explore what might be done about it. All around the world, there are researchers, designers, and practitioners who are deliberately experimenting with applications of education technology in order to serve the learners furthest from opportunities. What unites these diverse efforts is that they acknowledge that issues of cost and access are only one dimension of digital inequality: social and cultural exclusions are powerful barriers that are subtle to understand and essential to address.