Disciplining Play: Digital Youth Culture as Capital at School

Abstract

Adults may still be catching up to digital age, but digital youth bring to school digital skills they learn from each other. Comparative ethnographic analysis of three middle schools that vary by student class and race reveals that students’ similar digital skills are differently transformed by teachers into cultural capital for achievement. Teachers effectively discipline students’ digital play but in different ways. At a school serving working-class Latino youth, students are told their digital expressions are irrelevant to learning; at a school with mostly middle-class Asian American youth, students’ digital expressions are seen as threats to their ability to succeed academically; and at a private school with mainly wealthy white youth, students’ digital skills are positioned as essential to school success. Insofar as digital competency represents a kind of cultural capital, the minority and working-class students also have that capital. But theirs is not translated into teacher-supported opportunities for achievement.

Avoiding Us versus Them: How Schools’ Dependence on Privileged “Helicopter” Parents Influences Enforcement of Rules

“…Families consider many factors in choosing schools for their children, and some schools are seen as “higher quality” than others (Lareau and Goyette 2014). Perceptions of “quality” are often closely linked to schools’ socioeconomic and racial composition (Bourdieu 1984; Krysan, Crowder, and Bader 2014; Sikkink and Emerson 2008; Weininger 2014), and they reflect the fact that schools with larger proportions of higher-SES White students typically have higher standardized test scores and more amenities (e.g., smaller class sizes, more experienced teachers, more course offerings, more technology) than do other schools (Condron and Roscigno 2003; Duke 2000; Klugman 2013; Logan et al 2012; Rafalow 2018; Shedd 2015; Wenglinsky 1997). Because of the perceived benefits, families (especially higher-SES White families) are willing to pay more to live in neighborhoods with “high-quality” schools (Barrow 2002; Hasan and Kumar 2019).…”

A life course framework for understanding digital technology use in the transition to adulthood

“…The sociodemographic characteristics that shape an individual’s life course should also be explored more fully in future work. Intersecting identities (e.g., race and social class) and levels of analysis (e.g., neighborhood- or school-level characteristics and individual characteristics) likely shape young people’s technology use in ways that should be explored in future research ( Rafalow, 2018 ). Gender was related to young adult technology use in complex ways that should be further investigated.…”

“…Time diary and survey data document that watching television and video content remains the most frequent primary screen time activity among US children and adolescents (author 2019a,b; Rideout & Robb, 2019 ), but stationary and portable digital devices are also used for school, work, producing content, communication, gaming, and entertainment, sometimes at the same time ( Ito et al, 2019 ). These diverse activities make it harder to understand the benefits and drawbacks of time spent using technology because it is simultaneously (among other things) a sedentary health behavior, a powerful educational tool, and a cultural symbol infused with classed meaning ( Rafalow, 2018 ). Despite these complexities, rapid changes are fostering a “moral panic” focused disproportionately on the dangers of digital technologies for young people, as did the emergence of earlier technologies like radio, film, and television ( Wartella & Jennings, 2000 ).…”

“…At the same time, computers and internet access are perceived as fundamental for educational success, and technological competencies can lead to well-compensated careers ( Rafalow, 2018 ; Russ et al, 2009 ). But not all forms of screen time foster such competencies.…”

The New Structural Transformation of the Public Sphere

“…Raced, classed, aged, and gendered distinctions in how individuals learn to use the internet to garner social capital suggest that this stratified access to the internet affects civil society not only by determining who can participate online but also by structuring how people learn to use these technologies. Resulting differences in communicative styles and social-linguistic norms can bolster racialized and gendered constraints on civic inclusion (Rafalow 2018; Warschauer 2004; Zillien and Hargittai 2009).…”