Educators of all sorts have been suddenly thrust into online teaching amidst the global pandemic. But who might be left behind as we adapt online? Digital inequality research points to three questions that help us understand the current landscape for K-12 students: How robust is the global technological infrastructure? How ready are educators and students? And how might students be unequally rewarded as classes go online? We address each of these questions in turn below, including implications for policy and practice, and show how they overlap with the central concerns of sociology of education.
How Robust Is the Global Technological Infrastructure?
Unequal access to technology, the “first” level of the digital divide, is the most commonly known since the dawn of the digital age. While access gaps have shrunk over time, at least 15 percent of U.S. households with children in school lack high-speed internet at home and among low-income families one in three lacks internet access (Anderson and Perrin 2018). Internationally, this picture is bleaker; only 36 percent of citizens in lower-middle income countries have internet access (Vegas 2020). Further, there are ongoing access issues related to stability and maintenance (Gonzales 2016).
Under-resourced students and families need greater support to make technology access (both devices and internet) more equitable.
This is directly connected to longstanding similar concerns that prompted decades of national debate and federal lawsuits about access to quality education (Patterson 2001; Powers 2007; Reardon and Owens 2014). Reframing technology as a public good for public advantage is necessary, rather than allowing the continued privatization and unequal allocation of fundamentally public resources.
How Ready Are Educators and Students For Technology Learning?
Digital inequality scholars identify a “second level” digital divide in readiness, skills, and literacies that shape how students can use technology resources. Schools are underprepared in terms of technology education, particularly lower-performing schools. Further, many assume kids born into the digital age are naturally skillful with technology. Yet, research shows many students are still underprepared for technology-based learning, even in districts that demand students demonstrate technological skill to graduate from high school (Bennett, Maton and Kervin 2009; Palfrey and Gasser 2008; Prensky 2001; Puckett 2019). Moreover, students from working-class families may be less likely to ask for help due to technology issues than students from wealthier families.
Make technology learning for both teachers and students a more central feature of schooling.
In much the same way students are not assumed to “automatically” know how to use a book to gather information, they do not “naturally” know how to learn from technological resources. Just as literacy is critical to a democratic society, technological competence is an equally critical feature with so much of our civic and economic activity now online (Mihailidis 2013). Media literacy scholars have long made this argument; it’s all the more urgent that we do something about this now.
Policy and practice should focus on this goal. Teacher training should be better supported with sustained funding and technology instruction should be integrated in partnership with school members at all levels of the institution; technology expectations should be made transparent to students; and tech-savvy students should be utilized as valued peer mentors.
How Might Students Be Unequally Rewarded?
The third level of the digital divide focuses on unequal reward from technological use. For example, teachers may only reward affluent students who demand extensions on assignments due to technology issues (Gonzales, Calarco, and Lynch 2018). We also know that teachers differently validate the same digital skills depending on the race and class of their student populations.
In terms of how this translates to online learning, we expect inequities along statuses, like social class, race-ethnicity, and gender, may be exacerbated. For example, teachers reward technology use among white, affluent students (or allow them to opt out of some online activities) and police technology use among less affluent students of color, even as their families face more challenges during the pandemic (Rafalow 2018; Sims 2014). These “digital distinctions” operate in much the same way long-documented educational distinctions are made among students by social class and race, where lower-income and minoritized students are more heavily policed in schools (Shedd 2015).
Offer support to meet students’ needs without requiring them to ask for help. Recognize and amplify the efforts students make. Monitor outcomes in instructional use of technology and achievement to identify gaps along race, gender, and class.
We understand the seriousness of these problems offline, but they have yet to be effectively addressed and are a continuing concern among researchers and policy advocates (Gonzalez 2018; Ruha 2019). The same problems may be amplified online, where disadvantaged students may be held accountable for online learning in ways more affluent students may not.
While the issues that have been raised in the rush to online learning due to COVID-19 may seem like new concerns, these issues are central not only to digital inequality research but are connected to research and policy on educational equity. We encourage sociologists of education to take up this call to see with fresh eyes how these two bodies of scholarship are fundamentally intertwined.