Review of Digital Divisions: How Schools Create Inequality in the Tech Era

Sorting Machines: Digital Technology and Categorical Inequality in Education

“…We argue that there is purchase in analyzing how K-12 school contexts categorize software, and student data collected through these tools, and in ways that ultimately match students to different educational experiences. For example, we find that schools' software selection, and thus the data teachers collect about students and use for different purposes, is matched to assumptions about their student demographic (Rafalow, 2020).…”

“…Educational resources, like digital technologies, are also sorted by schools. Drawing on scholarship from both education research and science and technology studies, we show how educational institutions have long played a role in constructing the value of technologies to different ends, by constructing hierarchies of technological activity, like "vocational" and "academic" computer use, even when strikingly similar (Rafalow, 2020). This lens can help education scholars to view technologies as part of school sorting processes and with implications for inequality within and beyond the classroom.…”

“…For example, some schools might view technology use as connected to power and prestige and therefore encourage advantaged students to leverage it to maintain their social position. Other schools, in contrast, might see technology use as necessary for entry-level jobs and encourage less advantaged students to secure vocational roles (Rafalow, 2020). Categories of activity and students are also mutually constituted, where activity may be defined by who participates in it (i.e., technology classes are vocational because lower SES students are assigned to them).…”

“…At a school for primarily wealthy, White children, digital technologies, like iPads, were seen as "portals," or means to bridge students' lives at home with their live at school, as part of a learning process. Instead, at a school for primarily working class, Latinx children, teachers saw similar types of digital technologies instead as a means for students to learn "basic skills," like typing, to help someday get a job at a digitized version of the factory shop floor (Rafalow, 2020). Teachers categorize students as "needing" different types of education depending on their demographic and match them to different interpretations of similar technologies.…”

“…Educators are similarly adapting student data to fit their organizational culture, pedagogical, and disciplinary approaches. For example, schools with a punitive bent categorize student data as a means to surveil student activity and use it as evidence to punish students (Kumar et al, 2019;Rafalow, 2020;Selwyn & Facer, 2013). Teachers construct the value of student data through a disciplinary lens, sometimes even printing out text messages between students as evidence of misbehavior ("talking" during class).…”