This article appears as part of a special issue series of CITE English Language Arts Education focused on critical perspectives on digital platforms in ELA teacher education (Volumes 24:4 to 25:3).
ReadingPlus, ReadTheory, Epic!, Accelerated Reader — digital reading platforms are pervasive in today’s literacy classrooms across grade levels and contexts. While exact numbers are elusive, consider that Dreambox Learning (2023), owner of ReadingPlus, reported that six million students use its platforms across multiple countries. ReadTheory (https://readtheory.org) counts 18 million students among its users around the world, while Epic! tallies its global user base at over 60 million students and two million teachers (Yahoo! Finance, 2023). Finally, Renaissance, owner of Accelerated Reader (AR), the focus of this study, reports serving over 17 million students across more than 100 countries (Renaissance, n.d.a). Such figures underscore the significant presence of digital reading platforms in schools around the world, where they shape the reading education experiences of millions of students and their teachers.
If a digital platform is a networked hub that facilitates various kinds of user interactions through digital infrastructures like code, algorithms, and user interface design (Poell et al., 2019), a digital reading platform deploys such infrastructures to provide users with efficient, accessible reading experiences. Digital reading platforms exist both in and out of education. For example, the Amazon Kindle reading platform consists of proprietary hardware, software, and application programming interfaces (APIs) that allow it to interact with other platforms (e.g., smartphones), which together structure the reading experiences of users and create a market for publishers, advertisers, cloud service providers, and so on. Unlike such mainstream digital reading platforms, contemporary digital reading platforms for education (DRPEs) are specialized infrastructures that provide access to reading education materials, including some combination of texts, quizzes, rewards, and algorithmic personalization. These platforms also typically include data dashboards where educators can monitor individual and collective student performance and intervene whenever necessary.
DRPEs represent a subset of the many digital platforms used in education (e.g., Canvas, Flip, ClassDojo, etc.), the pervasiveness of which has garnered the attention of a growing number of scholars affiliated with the emerging subfields of critical edtech studies (Macgilchrist, 2021) and platform studies in education (Nichols & Garcia, 2022), itself an offshoot of the broader field of platform studies.
A key insight from platform studies both in or out of education is that while platforms are perpetually unstable entities — that is, they are constantly being altered through updates to the frontend (e.g., user interface) and backend (e.g., servers) — they are also powered by durable logics that animate these ongoing transformations (Perrotta et al., 2021). By “logics,” we simply mean the underlying principles, values, motivations, and assumptions that directly or indirectly guide the design, development, and operation of digital platforms.
At a basic level, for example, a profit logic animates the ongoing maintenance of commercial platforms like YouTube as they work to remain competitive by offering new features and improving upon existing ones. When YouTube added the “Shorts” feature to its platform in 2020, it did so in response to the growing popularity of TikTok, meaning that YouTube users, even those with no interest in short-form video content à la TikTok, were then fed such content throughout the YouTube platform.
A similar profit logic underpins the design and evolution of platforms in education, which likewise compete for market share by introducing new features, refining their offerings based on user data or outright purchasing potential competitors, such as when Renaissance purchased the AI-powered reading platform Lalilo from a French startup in 2021 (Taylor, 2021). Such economic logic is itself threaded to the logic of datafication — or the commitment to transforming various aspects of life into quantifiable data (van Dijck, 2014) — since platforms like YouTube, TikTok, and DRPEs need to extract and process user data to design and deploy sticky new features that will strengthen their positions in the broader platform economy.
A related insight from platform studies is that when a given domain of human activity is subject to the influence of platforms (i.e., platformized), that activity can be reshaped to reflect the priorities and logics of platforms (Helmond, 2015). This helps explain, for example, the proliferation of digital displays in today’s vehicles, which are increasingly designed according to the logics of platforms like Apple Carplay, Android Automotive, Spotify, and so on (Hind et al., 2022)—this even though analog buttons are generally preferable to and safer for drivers (Blanco, 2022; Gross, 2017). In this way, the practice of driving has been reshaped according to the logics of platforms.
Given the potential for platforms to reshape human life, often in ways that warrant critical attention, we aimed to investigate how the platform logics animating DRPEs might exert a durable influence on students’ reading practices and identities. To do so, we turned to what, at first, may seem an unlikely data source: literacy autobiographies written by preservice English language arts teachers in an undergraduate English Education course focused on adolescent reading difficulties. Struck by the extent to which students wrote, and did so without specific direction, about their use of AR in elementary and middle school, we combined a qualitative content analysis (Bengtsson, 2016) of AR with a thematic analysis (Braun & Clarke, 2006) of preservice teachers’ (PSTs’) reflections to (a) identify the platform logics that may have shaped their reading experiences and (b) consider how those logics may have influenced their attitudes toward reading and literacy education.
Our analysis surfaced three focal logics — competition, speed, and personalization — that structure the AR platform and, thereby, influence participants’ reading practices and identities. Based on these findings, we call for more explicit engagements with digital platforms, DRPEs in particular, in ELA teacher preparation programs. Such engagements have the potential to help PSTs develop a critical attunement to platform logics and their capacity to influence their future students’ literacy practices and identities, helping them make thoughtful decisions about whether, when, and how to integrate DRPEs in their future classrooms.
The Platformization of Literacy
The digitalization of education across ages, contexts, and geographies has prompted literacies scholars to examine how the technologies deployed in classrooms are reshaping teaching and learning in profound, if subtle, ways. This growing body of scholarship, influenced by such fields as media studies, software studies, and science and technology studies, has increasingly organized itself around the concept of the digital platform. As Nichols and Leblanc (2020) explained, the term digital platform speaks both (a) to the infrastructures upon and for which specific programs are built, including hardware like Chromebooks, and (b) to the digital apps and services where so many of today’s social, culture, political, and economic exchanges take place.
To that list, one might also add pedagogical exchanges, given the proliferation of digital platforms in schools: Canvas, Schoology, ClassDojo, ReadingPlus, Accelerated Reader, and so on. Such platforms are not mere tools floating in the digital ether; rather, they are structured by particular social, technical, and political-economic forces that condition pedagogical relations in the learning spaces where they are deployed (Nichols & Garcia, 2022).
Digital platforms are structured by layers of hardware, software, and network protocols that play an active role in shaping the interactions and exchanges they facilitate. Platforms are strata, not monoliths, and these strata give form to the logics that animate platforms, both in terms of what they enable and what they constrain. As Bratton (2016) argued, the layers that compose a given digital platform are tethered to a global infrastructure, “The Stack,” which includes physical hardware like laptops and server arrays, the software running on that hardware, the network protocols that enable communication across systems, and the natural resources that power such computational processes.
A platform’s layers are not neutral technical objects, but rather they inherit particular values, priorities, and assumptions designed into them by people. These forces, in turn, shape the social relations that emerge within and across platforms, producing what van Dijck et al. (2018) termed the platform society, a social order in which platforms play an active role in shaping politics, economics, public values, and education.
The process by which platforms shape social relations is one of platformization (Poell et al., 2019). When, for example, users interact with one another on TikTok, their interactions are mediated by a global array of internet servers, digital advertisers, recommendation algorithms, and user-interface design choices (e.g., swiping). Together, such forces produce a platformized mode of social relations, one that can accelerate the spread of disinformation (Basch et al., 2021), stoke political division (Kubin & von Sikorski, 2021), and further marginalize people from already marginalized communities (Boffone, 2022).
Given that many digital platforms heavily rely on users’ abilities to read, write, speak, listen, and create, the platformization of social relations is likewise the platformization of literacy. In other words, the practice of literacy — whether it is reading a book on a Kindle, writing and publishing an Instagram post, coauthoring an essay on Google Docs, or taking a reading quiz on AR — is shaped by the opportunities and limitations of the digital platforms where literacy happens.
Emerging research on the platformization of literacy has aimed to investigate how platforms are reconfiguring literacy both in and out of schools. Nichols and Johnston (2020), for example, examined how the Google Images algorithm influenced students’ multimodal composing practices, highlighting its uneven effects on students from marginalized communities. In a study of automated writing assessment (e.g., Turnitin), Dixon-Román et al. (2020) described how the data used to train such platforms can diminish the voices of young writers who use nondominant forms of English. For DRPEs, in particular, Apps et al. (2023) found that, according to their teacher participants, the data provided by such platforms presented a limited and inaccurate representation of students’ reading abilities, while still extracting value from the data children produce when they read on the platform. Together, this research shows that literacy is not simply etched on the visible layers of digital platforms, but rather that reading, writing, speaking, listening, and creating on digital platforms are intertwined with the social, technical, and economic forces animating them.
Accelerated Reader: A Protodigital Reading Platform
Concerned that her children were not being provided opportunities to read beloved classics at school, in 1984, Judith Paul, a stay-at-home spouse with a degree in education, created a supplementary reading program for them (Stoflet, 2019). Initially, Paul curated a set of books she wanted her kids to read, assigned points to the texts based on their length and complexity, developed multiple-choice questions for each one, and gave her kids points and rewards based on their performance on the quizzes. Inspired by Judith’s project, her spouse, Terry Paul, a software developer, adapted the program to the computer, and in 1986 the couple established Advantage Learning Systems, which they would sell for $455 million in 2011 (Vitello, 2014). AR began integrating web-based elements in the 2000s and was renamed Renaissance. Today, AR forms just one part of the Renaissance platform suite, which also includes DnA, FastBridge, Nearpod, Lalilo, and others.
While AR still reflects Paul’s reward-based orientation toward reading development, that approach is now augmented by cloud-based algorithmic data practices that track, monitor, and personalize students’ reading engagements. Just as Paul’s children selected a book to read from those she curated — and for which she had created assessments — today’s students also identify a book to read from AR’s catalog of fiction and nonfiction titles, which they go on to read independently. (This, by the way, marks a key difference between AR and many other DRPEs, which often provide access to texts within the platform.)
Unlike Paul’s children, however, the AR platform now deploys recommendation algorithms that suggest books to children based on their “reading history, reading level, and books’ popularity” (Renaissance, 2022a, p. 5). In this way, algorithmic data practices play a key role in shaping the reading practices of AR’s users, whose progress is tracked, measured, and rewarded with points, which are often integrated into various kinds of token economies (Kim et al., 2022) that extrinsically motivate students both to continue reading and, crucially, to continue using the platform.
The evolution of AR from analog to digital to digital platform tracks with the digitalization of education writ large across the 1990s and 2000s. This process fueled debates over the standardization of education, and AR was often at the center of such debates, even as its use was interrogated by scholars in journals like The Reader Teacher (Anderson & Balajthy, 2009; Vitello, 2014). While we are less concerned here with evaluating the efficacy claims made by Renaissance Learning about Accelerated Reader, it is worth noting that the platform’s effect on reading achievement is some permutation of mixed, small, or inconsistent, according to What Works Clearinghouse (WWC, 2016). Indeed, Tischner et al.’s (2023) meta-analytic review of AR’s influence on reading outcomes found that the platform at best exerts a “marginal impact on student reading” (p. 33) across such domains as motivation, achievement, and attitude.
Worth noting, too, is that while Renaissance has in the past reported that AR as being used in more than 37,000 schools (WWC, 2008), independent empirical research on it is actually quite limited, which led Tischner et al. (2023) to include unpublished — and often less methodologically rigorous — doctoral dissertations (n = 35 out of 44 studies total) in their meta-analysis. All to say, whether and how AR positively improves reading skills remains an open question, especially if independent, peer-reviewed, and randomized controlled trial designs are the gold standard for quality, as they are for WWC.
From a platform studies perspective, however, AR’s efficacy is only one piece of the puzzle, the social piece, and the platform’s capacity to shape educational outcomes should be considered alongside its technical and political-economic dimensions, especially how such dimensions interface with teachers’ pedagogical choices and students’ learning experiences. Only then can scholars and educators begin to fully understand the potential tradeoffs at work when a given platform is deployed in educational contexts.
Surfacing Platform Logics: Method of Inquiry
Working with data from an institutional review board approved study into Heidi’s teaching practice, our method involved analyzing both PSTs’ literacy autobiographies and AR itself, the platform’s public-facing documentation, in particular. Because we were examining both the logics of the AR platform and the lived experiences and memories of PSTs who used it as schoolchildren, we combined a qualitative content analysis (Bengtsson, 2016) of AR with a thematic analysis (Braun & Clarke, 2006) of PSTs’ written reflections.
Our content analysis of AR’s website, marketing materials, user guides, and so forth, allowed us to identify the values and imperatives that animate the platform’s design and function, while thematic analysis of PSTs’ written reflections enabled us to discern patterns in their experiences with AR. This dual approach provided complementary insights: The content analysis revealed the underlying logics of the platform, while the thematic analysis illuminated how those logics are taken up, experienced, and remembered by users. In this way, we were able to put two different kinds of data in conversation to more fully understand the logics of the AR platform and how users might experience them.
Context, Participants, and Data Collection
The literacy autobiographies we analyzed were part of PSTs’ teacher preparation coursework at a large regional university in the midwest U.S. in a course on reading assessment and remediation in secondary ELA classrooms. Although most of the 22 students enrolled in the course were English education majors, their reflections on using AR in elementary and middle school can still offer insight into the impact of digital reading platforms on developing readers. Since such platforms are increasingly used across grade levels, including in secondary ELA classrooms (e.g., CommonLit), examining PSTs’ experiences with AR can inform their critical engagement with digital reading platforms in their future teaching contexts.
The autobiographies that make up the data corpus were the result of activities, discussions, and assignments during the first few weeks of the course that encouraged the PSTs to examine their own reading identities. They created and shared slides that showcased their literacy lineages (Muhammad, 2020). They also engaged in critical discussions about how their personal literacy lineages shape their understanding of what counts as reading, how they read, and why they read and what that shaping might mean for them as secondary ELA teachers.
As a prewriting exercise, they completed Ripp’s (2018) reading teaching inventory, which asks questions such as, “What is your earliest memory of reading? How was reading a part of your childhood? What were pleasurable experiences you had with reading in school? What are experiences that you did not like with reading at school?” (pp. 148-151). Finally, PSTs wrote their own literacy autobiographies according to the assignment guidelines. (see Figure 1).
Figure 1
Heidi’s Literacy Lineage and Autobiography Assignment for Preservice ELA Teachers
None of the class instruction, discussion topics, or assignment parameters mentioned AR specifically or DRPEs, in general. Rather, PSTs brought forward their own recollections of their most impactful reading experiences both in and out of school. As Heidi initially read through PSTs’ autobiographies, she was struck by the unprompted omnipresence of AR as one of the most memorable and formative parts of PSTs’ reading experiences in school. In fact, of the 11 PSTs who reported attending a school where AR was used, nine of them wrote about their experience with AR as part of their literacy autobiographies.
Because the narratives described how the use of AR shaped their feelings about reading, changed their reading practices, and influenced peer interactions and classroom cultures around reading, these nine literacy autobiographies became the data corpus for this study. Acknowledging that our data set is small, our goal here is not to argue for blanket generalizability (a debatable outcome even with large data sets; see Kerlinger & Lee, 2000, Polit & Beck, 2010) or replicability of participants’ experiences with the AR platform. Rather, we attempted to follow Polit and Beck’s (2010) urging to qualitative researchers to be reflexive and conceptual throughout the research process, by presenting the collected data, the context of the study, and the conceptual framework in a way that allows readers to make a “reasonable extrapolation” (Patton, 2002, p. 489) of how DRPs might be working to shape the reading identities and practices of the students who use them. Also, while PSTs experienced the AR program a decade ago — a point we will return to later — their accounts nevertheless chimed with emerging research in the field of platform studies in education (Decuypere et al., 2021; Nichols & Garcia, 2022).
Data Analysis
We began our analysis by reading through the pertinent reflections to familiarize ourselves with the data and to form general impressions of how PSTs were talking about AR. In this initial pass through the data, we especially focused on how their reflections suggested their reading practices or perceptions of themselves as readers were influenced by their experiences with the platform.
We then investigated AR through a qualitative content analysis of AR’s website (e.g., blog posts, FAQs, and user manuals), both its current form and, thanks to the Internet Archive, its form in 2010, around the time participants would have used it. Although the website is not identical to the AR platform itself, it can nevertheless be understood as an extension of the platform, serving as a public-facing venue for explaining its aims, features, and underlying values to current and potential subscribers. Further, because the platform itself requires a subscription to access and has evolved significantly since 2010, the website offers a more stable and accessible record of how AR presents itself and its approach to reading pedagogy.
Rather than documenting the various features that have changed since participants used AR, we instead examined the deeper values, imperatives, and priorities that discursively undergird the development and deployment of such features. For example, we documented Renaissance Learning’s corporate slogan, “See Every Student,” which is underwritten by a logic of personalization and operationalized through the platform’s data practices (e.g., prediction), while the company’s mission — “to accelerate learning for all children and adults of all ability levels and ethnic and social backgrounds worldwide” (Renaissance, n.d.b) — is underwritten, in part, by a logic of speed.
In the case of AR, this logic of speed is operationalized through data practices, along with certificates designed to encourage students to read more books more quickly to accelerate their reading (Robinson, 2020). Through this process, we identified a series of platform logics — competition, speed, and personalization — that structure AR’s platformized mode of reading education.
To understand how these platform logics shaped participants’ reading experiences and identities, we then conducted a thematic analysis (Braun & Clarke, 2006) of PSTs’ literacy autobiographies, generating themes that offered insights into PSTs’ experiences with AR. (See the appendix for an example of the themes that were coded for). Finally, we paired the content analysis of AR with the thematic analysis of the PSTs’ literacy autobiographies together, exploring how the one resonated with the other and then organizing the data around the platform logics of speed, competition, and personalization.
One way scholars have reckoned with the role platforms play in education is by interrogating platform logics, or the mechanisms and principles that guide the behavior of a given digital platform. In a study of Google Classroom, for example, Perrota et al. (2021) described how the logics of datafication and surveillance are encoded in the platform — and also, it is worth noting, in Renaissance’s slogan, “See Every Student” — and thereby shape pedagogical interactions between teachers and students. Such logics are, the authors explained, “slowly but perceptibly shifting [teachers’] efforts from actual teaching to the 24/7 coordination, moderation and facilitation of student engagement” (p. 108). In other words, the platform logics of datafication and surveillance can alter what it means to be a teacher by decentering teacher expertise in favor of what Sefton-Green (2022) termed platform pedagogies, or the assumptions about teaching and learning embedded in digital platforms.
In the case of Google Classroom, its platform pedagogies teach teachers to teach differently, centering the logics of datafication and surveillance and, perhaps, thereby thwarting competing logics like authenticity and trust. With that in mind, in the following section we explain how AR teaches students to read differently, according to the platform logics animating it, and we describe the durable effects these logics can have on readers.
The Logic of Competition
One of the most visible, praised, and critiqued promises of the AR platform is that it will improve students’ reading motivation through the creation of a school and classroom “culture of reading through engagement, choice, and celebration of reading achievement” (Renaissance, n.d.b), a culture in which students become, as one featured principal described, “addicted to the sense of accomplishment” (Renaissance, n.d.c), as reflected in the acquisition of points for successfully completing quizzes. Of course, research does show that individual readers’ motivation is positively influenced when they view themselves as part of a community of readers and when they experience success as readers (Ivey & Johnston, 2015). However, AR embeds a logic of competition into the platform, both historically and currently, firmly rooting motivation in behaviorist concepts of repetition and positive and negative reinforcement.
In their literacy autobiographies, PSTs overwhelmingly identified AR’s logic of competition, specifically its contribution to a specific kind of reading culture, as being one of the platform’s most memorable features. One PST identified AR as a way to “gain friends and keep classroom motivation going” and still remembered how they “reached and surpassed [their] goals almost every quarter.”
Interestingly, although they loved the platform as a child, in retrospect they challenged the way it encouraged them to view education as “an internal and even external competition,” one that placed pressure on them “to be on the same level as everyone else.” For this PST, the pressure to measure up to classmates, a pressure mediated and amplified by the platform, shifted the value of reading toward outperforming others, as opposed to nurturing a more intrinsic love for reading and personal literacy growth.
Another PST, a competitive athlete who prefaced their reflection with the observation that “healthy competition is always fun,” remembered how the pressure to be a competitive reader left them feeling “stuck with [their] reading”:
Even though I was well above my grade reading level, I did not feel talented at reading like the kids that would swing around their purple dog tag with our school mascot carved into it. This created a frustration around reading that I did not deserve to feel.
For this PST, AR’s logic of competition was decidedly unhealthy, inasmuch as it reinforced an antagonistic reading practice, one that led to frustration and a lingering sense of injustice. What such responses, which were echoed throughout the literacy autobiography data, make clear is that AR has not delivered on its promise to shape the reading culture of schools and classrooms. However, some readers remember it as a culture that valued competition over collaboration and engendered negative feelings around reading performance.
Other PSTs noted that, because they were already both reading above their level and doing so for their own enjoyment, the AR platform reinforced their identity as good readers, even while they acknowledged that their purpose shifted from reading for enjoyment to reading to “rack up AR points.” However, just the opposite was true for students who did not already view themselves as skilled, competent readers.
As one PST reflected, “Missing the parties for not reaching reading goals never bothered me; opening a book that was behind the reading level of my peers did bother me though. I would avoid opening a book during class to avoid embarrassment.” In this way, the hypervisibility of students’ and books’ reading levels, which were often emblazoned on classroom walls, coupled with the competitive nature of the AR reading culture caused this less confident reader to read less.
Of course, criticisms of AR’s emphasis on competition are not new. Stevenson and Camarata (2005), for example, expressed concern that the platform’s emphasis on competition would undermine more communal orientations toward classroom literacy engagements, while Schmidt (2008) worried that it may lead teachers to “lose the interest of our students and create literal readers who only want to ‘get points’ and be done with reading” (p. 210). At the very least, PSTs’ literacy autobiographies substantiated such longstanding concerns.
It is worth noting, too, that AR’s website includes language that cautions against using the points system as part of a competitive rewards system. As Renaissance (2014) itself observed, “Sometimes schools approach AR in the same way [as sports] and recognize students who earn the most points,” adding that “we discourage this practice,” because “when schools focus primarily on points, students tend to choose inappropriate books and less skilled readers are handicapped” (p. 12). AR also noted that “when students’ averages drop below 60 percent, their reading growth, as measured on standardized tests, actually slows down … no matter how much time they spend reading, or how many points they earn” (p. 39).
Despite such disclaimers, however, the perhaps irrevocable conclusion of following the logic of competition embedded in the AR platform has meant that school implementations have historically and currently included public displays and rewards for points, similar to the ones that PSTs report in their autobiographies. Indeed, a search for “Accelerated Reader” and “competition” on Teachers Pay Teachers, a platform where teachers can sell their materials to others, generated 14 results, each of which offered some way of organizing competition based on AR points, the most popular of which had 100 reviews.
Given these circumstances, AR’s disclaimers may operate more as an effort at plausible deniability than good faith concern. At the same time, we wonder about the possibility that AR’s platform logic of competition has been amplified, intensified, and legitimized within a broader platform ecology inhabited by social media platforms, personal finance platforms, productivity platforms, and so on. Within such a context, competition over likes, subscribers, followers, and so forth, mirrors the kind of classroom competition over AR points, as does competition over points on ClassDojo (Robinson, 2021) and other digital platforms in education.
The Logic of Speed
As its name suggests, speed is a guiding logic of the AR platform (Robinson, 2020). In literacy education, speed is generally understood as fluency, or the ability to read quickly and accurately. Fluent readers are able to decode words automatically and, thereby, read smoothly and effortlessly. Fluency, therefore, plays a crucial role in supporting comprehension because it allows readers to focus on a text’s meaning.
While AR has been shown to have a small effect on fluency (WWC, 2016), the platform’s more general aim is to motivate students to read more books in less time, as demonstrated by its goal-setting feature, which encourages students to “create personalized goals around comprehension, engaged reading time, and students’ reading levels to keep them on the path to future success” (Accelerated Reader, n.d.). This imperative for speed is also computational, since the platform provides students, parents, and educators with real-time information and insights on student progress, which means an array of servers, protocols, and algorithms steer data across the platform at fiber-optic speeds.
The platform’s emphasis on accruing points, unlocking badges, and earning certificates creates an infrastructure for competition to emerge, such as the “AR Friends” feature, which “encourages students to read books of varying lengths, depending upon their level, to unlock fun character badges” (Renaissance, 2022b). In schools, such incentives often manifest as a sort of year-long race to read as many books as possible, which, of course, is not in and of itself a bad thing. In PSTs’ reflections, however, the imperative to read more books more quickly to earn more points resulted in frustration.
For example, one PST recalled that they “could not read [books] as fast as the kids with higher colors,” referring to peers whose ability to read books faster was signified by a color-coding scheme displayed in the classroom, which led to feelings of failure. Another participant remembered that their friends were “reading circles around” them. “I couldn’t read near as quickly as my peers. … I stopped reading at home entirely despite my mom becoming increasingly worried I would fall behind.” The pressure to keep pace with peers who read more quickly, based on the number of AR quizzes they completed, seemed to undermine participants’ motivation and passion for reading. “My love for reading would take a pause,” one participant wrote, “and I would wait for the spark to be lit once more.”
Just as a vehicle that accelerates too quickly can come to an abrupt and violent halt, so too can young readers, specifically those subject to the platform logic of speed, be driven to read too much too quickly, which can decelerate their literacy development and, as PST’s reflections suggested, leave lasting marks. After all, AR, through its branding and platform logics, encourages a culture of speed, where moving fast is a common sense virtue, a culture reflected in the platform society more broadly.
In a 2012 letter to investors, for example, Facebook CEO Mark Zuckerberg (2012) articulated the company’s “five core values,” one of which was “Move Fast.” “We have a saying,” Zuckerberg wrote, “‘Move fast and break things.’ The idea is that if you never break anything, you’re probably not moving fast enough” (para. 41). On the one hand, this logic of speed can lead to innovation and allow organizations to be nimble in response to rapid change. On the other hand, moving fast can lead to reckless disregard for the unintended consequences of speed, which in the case of Facebook and other social media platforms, has accelerated the spread of misinformation, hate, and cynicism.
The question then is, what are the unintended consequences of AR’s platform logic of speed for young readers? What values of reading as a literacy practice are being accelerated by the platform? And do those values align with literacy educators’ pedagogical values about reading? Despite the push for fluent readers who read at an appropriate rate, highlighting speed and prioritizing high volumes of reading can have unintended consequences, something that Renaissance itself has acknowledged:
Don’t emphasize points over comprehension. Students tend to think of points in concrete terms. In their minds, it’s like money or candy—the more you have, the better. In Accelerated Reader, however, this idea has proven to be too simplistic. Our research shows that when students’ averages drop below 60 percent [on the comprehension quizzes], their reading growth, as measured on standardized tests, actually slows down. This is true no matter how much time they spend reading, or how many points they earn. (Renaissance, 2014, p. 39)
In offering such guidance, Renaissance tacitly admitted that the platform’s very design, which relies heavily on points and rewards, may encourage students to rush to accumulate points over more substantive reading engagement. Indeed, the subtext is that there are students who devote significant time to reading and successfully accumulate points, yet still struggle to read when assessed outside the platform.
This admission raises the possibility that the platform’s reward system actively promotes counterproductive reading habits by unduly valuing the rapid consumption of books. In this way, AR’s design may at times decelerate reading growth by encouraging students to prioritize consumption and speed over understanding. Instead of seriously reckoning with the nature of a platform logic that valorizes speed and incentivizes point-chasing, Renaissance attempted to shift the responsibility onto teachers, telling them, “Don’t emphasize points over comprehension.” Said differently, AR does not harm readers, misguided teachers do. The inescapable reality remains, however, that AR’s design, with its points and badges, communicates to impressionable young readers that the speed at which they race through books is what is most important about reading.
The Logic of Personalization
The wide adoption of AR and other DRPEs across schools in the United States means that they contribute to and benefit from standardization movements in literacy education. However, one of AR’s primary marketing points is that it can tailor itself for individual students. AR promises to provide “personalized goals [that] help students stay focused on the factors that matter the most for reading growth” and individual reading recommendations that “use students’ interests and reading levels to suggest titles” (Renaissance, n.d.b). These recommendations are based in part on text complexity measures, including a Lexile score, which is derived with Lexile Analyzer, “an automated software program that uses an algorithm to evaluate the reading demand — or text complexity — of books, articles and other text” (Metametrics, 2019, p. 2).
Such algorithms purport to approximate what literacy teachers do when they supply readers with texts appropriately matched to readers’ abilities, interests, and reading purposes. As research makes clear, matching a reader with the right text is a complex process weighing multiple factors (Armbruster, 2016). Importantly, AR’s platform logic of personalization can be traced back more than a decade to the period when the PSTs were using the platform — something we discovered by exploring the Internet Archive’s snapshots of the website from 2010. “AR’s advanced technology helps you … personalize reading practice to each student’s current level,” the platform promised (Renaissance, 2010), underscoring that this logic is part of the platform’s own literacy lineage.
As PSTs’ literacy autobiographies suggested, AR’s logic of personalization influences young readers’ approach to text selection. Indeed, several participants mentioned how the text curation feature of AR negatively changed their text selection practices and redefined their sense of what books were readable. Consider this passage from one PST’s literacy autobiography, for example:
The AR reading system created a challenge to pick out books and learn the system of which quizzes I could successfully answer the questions and pass. Oftentimes, for the books I really enjoyed reading, I would not do well on their pesky little quiz questions. Through trial and error . . . my mom and I discovered the “Who Was?” series . . . As much as I loved the “Who Was?” books and the notable people I learned about when reading them, I am disappointed in the way I had to find them and stick to them to progress in the AR program.
Where this PST had previously selected books based on personal enjoyment or interests, the AR platform fundamentally shifted how and why they chose books. Their “trial and error” approach to selecting books for which they could “do well on the AR quizzes” offers an illustration of how a platform can remake readers in its own image. In other words, the platform was not personalizing itself for the reader; rather, readers were reshaping themselves for the platform. Their memory of the platform as “disappointing” shows how platforms can undermine reader agency while claiming to do the opposite. Readers can be led to pick books to suit the platform to become the kind of accelerated reader it imagines.
AR’s platform logic of personalization also structures its approach to assessment, which uses comprehension questions in a quiz format to define what it means to be a skilled reader. Every year, AR creates over 6,000 quizzes for which “questions are dispersed evenly throughout the text to encourage students to read the entire book, not just the beginning or the end” (Renaissance, 2020, para. 10). Worth noting here are the assumptions about reading shaping the platform’s assessments, which position quizzes, not interest in the books themselves, as a primary means of encouraging students to read entire books. While literacy educators do value comprehension as a desirable outcome, one demonstrated through quiz performance on and off digital platforms, AR’s approach to assessment exerts its own pressures on students. As one PST described it,
AR turned reading into a chore. I could not just read the book for fun, I had to read it with full attention to what I was reading just in case that sentence was a prompt for a quiz question. I understand why we had AR reading and the information it gave teachers about students learning and reading, but as a student, I paid the price for that information.
The platform’s logic of personalization, manifested as quiz performance, made it difficult for this PST to distinguish between multiple purposes for reading. On the one hand, the platform purports to encourage students’ love for reading, but on the other hand, it perpetuates a specific platformized mode of reading that can lead students to read for quiz questions (and for points, badges, and certificates), not for enjoyment or edification.
Ultimately, a key danger to the AR platform’s logic of personalization is that the experience of reading will be narrowed, not expanded. Because it defines readerly success through datafied quiz practices, the platform can reconfigure reading around surface-level comprehension and rote recall instead of deep, critical, and communal engagement. Such platform logics of personalization, which are amplified in the recommendation algorithms people encounter each day (e.g., Netflix), can oversimplify the complexity and nuance of the relation between text and reader and, thereby, potentially inhibit educators’ ability to nurture well-rounded readers with expansive tastes.
Implications
AR and the Platformization of (Literacy) Education
By examining the AR platform’s public-facing documentation alongside PSTs’ literacy autobiographies, we have shown how the logics of competition, speed, and personalization shaped their reading practices and identities in durable ways — ways that surfaced as fraught memories when asked, around a decade later, to reflect on their literacy learning experiences. These findings align with work in the field of platform studies in education (Decuypere, 2021; Nichols & Garcia, 2022), where scholars have critically examined the capacity of platforms to reconfigure teaching and learning in their own images. Just as the logics of datafication and surveillance powering Google Classroom can produce platformized pedagogical relations (Perrotta et al., 2021), so too can the animating logics of AR generate a platformized mode of reading education. For some AR readers, learning to read becomes about reading more books more quickly, about winning the reading race against classmates, which as we have shown, can bear upon readers’ lifelong literacy development.
Also, the possibility that AR may lead students to narrow their reading choices in response to the platform’s logics resonates with other research showing that platforms often betray a tendency to constrain the practice of literacy (Nichols & Johnson, 2020; Dixon-Roman et al., 2020). Finally, our findings complement Apps et al.’s (2023) study of teachers’ perception of DRPE’s data practices, which for them offered an impoverished view of reading development, by illustrating how such limited representations of reading can shape students’ literacy identities and practices in lasting ways that extend well beyond their time using the platform.
Preparing Teachers for the Platformized ELA Classroom
While DRPEs like AR are not without opportunities, our critical examination of PSTs’ literacy autobiographies and the AR platform suggests that they are, likewise, not without risks. Such critical perspectives, specifically ones that interrogate the ways DRPEs influence how reading is practiced and taught, are essential for understanding the pressures these technologies exert on literacy education. Indeed, critical orientations toward platforms and their infrastructures can help illuminate issues of power, equity, and ideology that may otherwise go unexamined under the guise of technological neutrality (e.g., Chun, 2021). Absent critical attention to the logics guiding platforms like AR, scholars, educators, and teacher educators risk perpetuating technological solutionism and its consequences in literacy education, specifically the assumption that platforms provide quick fixes for the many structural challenges facing literacy education (e.g., teacher shortages).
Again, what struck us about the PSTs’ reflections was that Heidi made no mention of AR or any other reading platform in the assignment’s directions, yet the platform featured prominently in their memories. While their attention to AR, at a minimum, attests to its popularity in elementary and middle school education, it also underscores the platform’s durable influence on readers. That AR’s influence on PSTs’ reading development was viewed so negatively might give literacy scholars, educators, and teacher educators pause. And not only in response to AR alone, but also to the fact that it is but one platform amidst Renaissance’s suite of platforms, which are themselves a small selection of the countless digital platforms being deployed in today’s classrooms.
We, therefore, invite ELA teacher educators, in particular, to provide PSTs opportunities to engage critically with digital platforms, including but not only DRPEs, throughout ELA teacher preparation programs. Such engagements have the potential to help PSTs develop attunement to platform logics and their capacity to influence their future students’ literacy practices and identities, helping them make thoughtful decisions about whether, when, and how to integrate platforms in their future classrooms. How might ELA teacher educators do this? In particular, how might they help PSTs imagine ways to decenter or reorient such platform logics as competition, speed, and personalization in ways that bend toward more vital reading practices?
For Boldt (2021), vital literacy learning centers movement, improvisation, and affective responses to texts through lively interaction with them and members of the classroom community. Creating vital literacy learning spaces means becoming attuned to how readers’ subjectivities, classroom materialities, literacy events, and so on all contribute to a classroom’s “flow of energy and possibility” (p. 6). Vital literacy classrooms are improvisational, which means they respond to shifts in energy, make connections and meaning across time and contexts, and introduce and interact with difference as individuals and classroom communities. The purpose of vital literacy learning is to engage students in “processes that they experience as powerfully enabling” (p. 12), not limiting or constraining.
The movement, improvisation, and attention to affective responses necessary to sustain vital literacy classrooms are not things that DRPEs do well. After all, governed by calculation, prediction, and standardization, platforms necessarily struggle to accommodate the kinds of embodied movement, spontaneous improvisation, and affective engagement inherent to vital literacy learning. ELA teacher educators can, therefore, play an important role in centering vitality by preparing preservice teachers to respond critically and thoughtfully to the influence of DRPEs on contemporary ELA pedagogy. While we have no easy answers for what often seem like totalizing pressures of platforms, we offer a few potential pathways forward for ELA teacher educators concerned about the issues addressed here.
First, teacher educators might create opportunities for PSTs to examine their own experiences with DRPEs, perhaps as part of a literacy lineage project (Muhammad, 2020) akin to the one that inspired this study. Teacher educators could also invite PSTs to complete a reading survey akin to the one designed by Ripp (2018), which helps teachers excavate their own reading assumptions, biases, values, and so forth. Rich though PSTs’ autobiographies were for this study, more explicit questions about their experiences with DRPEs might allow for even more meaningful reflections on how their own reading experiences were shaped by platform mediations. Teacher educators could also provide opportunities for PSTs to investigate popular DRPEs, themselves, perhaps adapting and conducting an informal content analysis of platforms, akin to the one we have done for this study, to help them uncover and interrogate the underlying values and assumptions structuring platforms.
Additionally, we suggest introducing PSTs to articles that challenge preconceived notions of literacy, with special attention to DRPEs and their logics (e.g., Nichols & Leblanc, 2020; Apps et al., 2023) but also to visions of literacy education that are at odds with those logics. Boldt (2021), for example, highlighted the role improvisation can play in generating vital literacy classrooms, spaces where teachers and students are attuned to each other’s affective states and responses, in turn, responding emergently and reciprocally to one another. To follow such an improvisational logic is in fundamental tension with the predictive, calculating logics of platforms, which algorithmically predetermined and standardized literacy engagements. These kinds of readings can be supplemented with some of the many excellent practitioner texts that show how teachers successfully build reading communities outside of (or in spite of) platforms (e.g., Ebarvia, 2024; Kittle, 2013; Miller & Moss, 2013; Ripp, 2018).
Ultimately, our goal as ELA teacher educators is to support and prepare secondary educators to respond to the influence of platform logics — whether they be those of competition, speed, personalization, or others (e.g., surveillance) — on young readers in ways that bend toward more vital reading practices, as described by Boldt (2021), which are highly contextualized, community sustaining, and improvisational. Given the implausibility of dispensing with digital reading platforms altogether — it is not uncommon, after all, that administrators and school systems require students to spend some amount of time on such platforms — we offer teacher educators a few additional points to consider in conversation with the PSTs with whom they work. First, we echo Nichols and Leblanc’s (2020) questions for teachers to consider about platforms in general (e.g., “Who profits from the use of this platform?”) as well as their suggestions for student inquiry into platforms (e.g., Asking students to reflect on their use of platforms), which offer useful entry points for thinking about platforms in literacy education. Given our specific focus on digital reading platforms like AR, we conclude with a few principles that teacher educators might center in their teacher preparation courses as a critical response to the influence of platform logics on reading education.
Decentering Competition, Decelerating Reading
Examining the logics, promise, and discourse within and around DRPEs is particularly useful for PSTs when it can be laid alongside current research and practitioner texts that examine literacy instruction with the goal of building literate, flexible, and motivated readers rather than selling a product. Multiple studies have noted that teachers’ orientation to reading, books, and literacy practices are highly influential in shaping how students experience reading, both affectively and academically (Mucherah, et al., 2014). Researchers have already noted the ways that competition in literacy classrooms negatively affects students’ reading comprehension and interest in texts (Pesout & Nietfeld, 2021).
Engaging PSTs with research that calls into question the logics of DRPEs, particularly around the value of competition in reading classrooms and the universal value of speed as a reading practice, would be an important first step in equipping PSTs to engage critically with DRPEs. Additionally, multiple practitioner texts can offer portraits to PSTs of reading cultures and communities that decenter competition and instead position reading as a social or cooperative experience using instructional practices like shared reading, guided reading, partner reading, read-alouds, book talks, and book tastings (Ivey & Johnston, 2023; Kittle, 2013; Miller, 2012). Helping PSTs (who may remember their own reading instruction within platformed and virtual spaces) imagine alternative approaches to reading instruction is a vital part of preparing literacy educators who can supplement students’ reading instruction even in platformed schools in ways that position readers as agentive and social.
As Paul Virilio (1977/2006), a philosopher of speed and technology, once wrote, “Reading implies time for reflection, a slowing-down that destroys the mass’s dynamic efficiency” (p. 31). Research has indeed shown that there can be a trade-off between reading speed and comprehension, particularly when it comes to extreme forms of speed reading (Raynor et al., 2016) and that intrinsically motivated readers tend to read more and read more deeply (Troyer et al., 2019). For Virilio, society’s obsession with speed — an obsession reflected in the names of digital platforms like Snapchat, Instagram, TikTok, and yes, AR — can undermine people’s ability to engage in deep contemplation and critical thinking and, thereby, lead to alienation and disconnection. PSTs’ reflections on AR’s encouragement to read more and read more quickly offer a sharp illustration of Virilio’s point, as they expressed feelings of detachment and frustration in response to the imperative to accelerate their reading continually.
In response, teacher educators can make plain the value of slow reading by encouraging future teachers to (a) engage in explicit classroom conversations about the role speed and slowness can play in reading, (b) create time for slow, deliberative reading, (c) de-incentivize the fast reading of books (not fluency as such) as a self-evident virtue, (d) develop formative and summative assessments that encourage deliberative reading, and (e) advocate for the value of slow reading in their professional communications with colleagues and administrators. Indeed, to Daniel Pennac’s (1999) “Readers Bill of Rights,” which articulates 10 ethical imperatives that encourage students to love reading and find joy in it, we would add an 11th right: The right to read slowly.
Conclusion
Although AR promises personalization and responsiveness to students’ abilities and interests, this study has reaffirmed the insufficiency of algorithmic data practices as replacements for the work of experienced, knowledgeable literacy educators. A platform’s perception of a reader — of their interests, their lived experiences, their communities and contexts, their reasons for reading, and their ability — is far more limited than a knowledgeable and skilled teacher’s perception of the same reader. In our study, PSTs’ reflections made clear that AR negatively influenced their reading practices, largely through the ways it narrowed what reading meant and looked like in their classrooms.
Teacher educators should make a deliberate push to equip future literacy teachers with the knowledge and awareness that enable them to resist what increasingly seems like the platform-powered automation of reading pedagogy (Meyer & Whitmore, 2011). From a teacher education standpoint, teacher educators need to build time into coursework that explores how teachers might engage administrators, colleagues, parents, and students in conversations about DRPEs and other platforms to advocate for caution against the wholesale or uncritical adoption of them in schools and districts.
Just as important, teacher educators need to urge PSTs to position DRPE data about student reading as a single point of information, shaped by the ways a give platform structures the practice of reading, about who a reader is and what they can read. In this way, beginning teachers have support as they resist the creeping automation of literacy instruction by centering their own roles in knowing students, families, communities, and multiple texts.
Throughout this inquiry, we were both struck by the way DRPEs have transformed and continue to transform teachers’ and students’ conceptions of reading success, assign a higher value to (and reward) certain reading practices, and exert influence on classroom and school culture around reading. Examining the AR platform alongside the literacy autobiographies of PSTs allowed us to, not only identify and name some of the logics inherent to the AR platform, but also to understand how these logics durably reshaped the reading identities, skills, and purposes of young people who remember it as an integral part of their own reading development and lineage.
Given the ubiquity of DRPEs in literacy education, across elementary and middle schools in particular, it is crucial that literacy educators at all levels understand how digital platforms influence literacy learning, recognize the effects such influence can have on developing readers and writers, and consider how they might respond to that influence within their classrooms in support of vital, improvisational, and community-oriented literacy education.
Author Note
Bradley Robinson, the lead author of this article, served as an editor for this special issue. To maintain the integrity of the peer-review process, the manuscript was handled by outgoing CITE English editor Phil Nichols, who managed all editorial correspondence and decisions according to standard double-blind review procedures.
References
Anderson, R., & Balajthy, E. (2009). Technology in literacy education: Stories about struggling readers and technology. The Reading Teacher, 62(6), 540-542.
Apps, T., Beckman, K., & Howard, S. K. (2023). Valuable data? Using walkthrough methods to understand the impact of digital reading platforms in Australian primary schools. Learning, Media and Technology, 48(2), 294-309.
Armbruster, B. B. (2016). Matching readers and texts: The continuing quest. In D. Lapp, J. Flood, & N. Farnan (Eds.), Content area reading and learning (pp. 47-64). Routledge
Basch, C. H., Meleo-Erwin, Z., Fera, J., Jaime, C., & Basch, C. E. (2021). A global pandemic in the time of viral memes: COVID-19 vaccine misinformation and disinformation on TikTok. Human Vaccines & Immunotherapeutics, 17(8), 2373-2377.
Bengtsson, M. (2016). How to plan and perform a qualitative study using content analysis. NursingPlus Open, 2, 8-14.
Blanco, S. (2022, Aug. 21). Shocker! Test shows physical buttons are less time-consuming in cars than touchscreens. Car and Driver. https://www.caranddriver.com/news/a40949962/car-buttons-easierthan-touchscreens-study/
Boffone, T. (2022). The D’Amelio effect: TikTok, Charli D’Amelio, and the construction of whiteness. In E. Boffone (Ed.), TikTok cultures in the United States (pp. 17-27). Routledge.
Boldt, G. (2021). Theorizing vitality in the literacy classroom. Reading Research Quarterly, 56(2), 207-221.
Bratton, B. H. (2016). The Stack: On software and sovereignty. MIT Press.
Braun V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Chun, W. H. K. (2021). Discriminating data: Correlation, neighborhoods, and the new politics of recognition. MIT Press.
Decuypere, M., Grimaldi, E., & Landri, P. (2021). Introduction: Critical studies of digital education platforms. Critical Studies in Education, 62(1), 1-16.
Dixon-Román, E., Nichols, T. P., & Nyame-Mensah, A. (2020). The racializing forces of/in AI educational technologies. Learning, Media and Technology, 45(3), 236–250.
DreamBox Learning. (2023, Jan. 18). DreamBox Learning appoints Candice Faktor to board of directors. https://www.dreambox.com/press/dreambox-learning-appoints-candice-faktor-to-board-of-directors
Ebarvia, T. (2024). Get free: Antibias literacy instruction for stronger readers, writers, and thinkers. Corwin.
Gross, A. (2017, Oct. 5). New vehicle infotainment systems create increased distractions behind the wheel. AAA. https://newsroom.aaa.com/2017/10/new-vehicle-infotainment-systems-create-increased-distractions-behind-wheel/
Helmond, A. (2015). The platformization of the web: Making web data platform ready. Social Media + Society, 1(2), 1-11.
Hind, S., Kanderske, M., van der Vlist, F. (2022). Making the car “platform ready”: How big tech is driving the platformization of automobility. Social Media + Society, 8(2), 1-13.
Ivey, G., & Johnston, P. H. (2015). Engaged reading as a collaborative transformative practice. Journal of Literacy Research, 47(3), 297-327.
Ivey, G., & Johnston, P. H. (2023). Teens choosing to read: Fostering social, emotional, and intellectual growth through books. Teachers College Press.
Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research (4th ed.). Harcourt.
Kim, J. Y., Fienup, D. M., Oh, A. E., & Wang, Y. (2022). Systematic review and meta-analysis of token economy practices in K-5 educational settings, 2000 to 2019. Behavior Modification, 46(6), 1460-1487.
Kittle, P. (2013). Book love: Developing depth, stamina, and passion in adolescent readers. Heinemann.
Kubin, E., & von Sikorski, C. (2021). The role of (social) media in political polarization: a systematic review. Annals of the International Communication Association, 45(3), 188-206.
Macgilchrist, F. (2021). What is ‘critical’ in critical studies of edtech? Three responses. Learning, Media and Technology, 46(3), 243-249.
Metametrics. (2019). Lexile framework for reading. https://metametricsinc.com/wp-content/uploads/2018/07/Texts-and-Lexile-Measures-1.pdf
Meyer, R. J., & Whitmore, K. F. (2011). Reclaiming reading: Teachers, students, and researchers regaining spaces for thinking and action. Routledge.
Miller, D., & Moss, B. (2013). No more independent reading without support. Heinemann.
Miller, D. (2012). Reading with meaning: Teaching comprehension in the primary grades. (2nd ed.). Routledge.
Mucherah, W., Finch, H., Ball, V. S., & Ambrose-Stahl, D. (2014). Exploring the relationship between classroom climate, reading motivation, and achievement: A look into 7th grade classrooms. International Journal of Learning, Teaching and Educational Research, 8(1), 93-110.
Muhammad, G. (2020). Cultivating genius: An equity framework for culturally and historically responsive literacy. Scholastic.
Nichols, T. P., & Johnston, K. (2020). Rethinking availability in multimodal composing: Frictions in digital design. Journal of Adolescent & Adult Literacy, 64(3), 259–270.
Nichols, T. P., & Garcia, A. (2022). Platform studies in education. Harvard Educational Review, 92(2), 209-230.
Nichols, T. P., & LeBlanc, R. J. (2020). Beyond apps: Digital literacies in a platform society. The Reading Teacher, 74(1), 103-109.
Patton, M. Q. (2002). Qualitative evaluation and research methods (3rd ed.). SAGE Publications, inc.
Pennac, D. (1999). Better than life. Pembroke Publishers Limited.
Perrotta, C., Gulson, K. N., Williamson, B., & Witzenberger, K. (2021). Automation, APIs and the distributed labour of platform pedagogies in Google Classroom. Critical Studies in Education, 62(1), 97-113.
Pesout, O., & Nietfeld, J. (2021). The impact of cooperation and competition on metacognitive monitoring in classroom context. The Journal of Experimental Education, 89(2), 237-258. doi: 10.1080/00220973.2020.1751577
Poell, T., Nieborg, D., & Van Dijck, J. (2019). Platformisation. Internet Policy Review, 8(4), 1–13.
Polit, D. F., & Beck, C. T. (2010).Generalization in quantitative and qualitative research: Myths and strategies, International Journal of Nursing Studies 47(11), 1451-1458.
Rayner, K., Schotter, E. R., Masson, M. E., Potter, M. C., & Treiman, R. (2016). So much to read, so little time: How do we read, and can speed reading help? Psychological Science in the Public Interest, 17(1), 4-34.
Renaissance. (n.d.a). Renaissance: See every student. Retrieved Nov. 7, 2024, from https://intl.renaissance.com/
Renaissance. (n.d.b). Accelerated Reader: Motivating independent reading. Retrieved Nov. 6, 2024, from https://www.renaissance.com/products/accelerated-reader/
Renaissance. (n.d.c). Blazing a new Oregon Trail: First graders read 7,000 books. Retrieved Nov. 6, 2024, from https://www.renaissance.com/success/or-warrenton-hammond-warrenton-grade-school/
Renaissance Learning. (2010, February 9). Overview: Accelerated Reader. Renaissance Learning. Internet Archive. Retrieved Nov. 7, 2024, from https://web.archive.org/web/20100209055657/http://www.renlearn.com/ar/overview
Renaissance. (2014). Getting results with Accelerated Reader. https://uk.renaissance.com/wp-content/uploads/2014/09/Getting-Results-with-Accelerated-Reader.pdf
Renaissance. (2020, Sep. 3). The making of an Accelerated Reader quiz. https://www.renaissance.com/2020/09/03/blog-the-making-of-an-accelerated-reader-quiz/
Renaissance. (2022a). Foster a love for reading. Retrieved Nov. 6, 2024, from https://renaissance.widen.net/s/8bcqzdgjzq
Renaissance. (2022b, March 4). What’s new in Accelerated Reader this spring? Retrieved Nov. 7, 2024, from https://www.renaissance.com/product_update/whats-new-in-accelerated-reader-this-spring/
Ripp, P. (2018). Passionate readers: The art of reaching and engaging every child. Routledge.
Robinson, B. (2020). Speed, technology, and dromocratic literacy. Journal of Literacy and Technology, 21(4), 24-37.
Robinson, B. (2021). The ClassDojo app: Training in the art of dividuation. International Journal of Qualitative Studies in Education, 34(7), 598-612.
Schmidt, R. (2008). Really reading: What does accelerated reader teach adults and children? Language Arts, 85(3), 202-211.
Sefton-Green, J. (2022). Towards platform pedagogies: why thinking about digital platforms as pedagogic devices might be useful. Discourse: Studies in the Cultural Politics of Education, 43(6), 899-911.
Stevenson, J. M., & Camarata, J. (2005). Held hostage by the accelerated reader program. TalkingPoints, 16(2), 16-23.
Stoflet, K. (2019). Introducing the magic of reading—a mother’s story. Renaissance Learning. http://www.renaissance.com
Taylor, D. (2021, March 22). Paris-based edtech Lalilo acquired by US-based Renaissance. https://tech.eu/2021/03/22/paris-based-edtech-lalilo-acquired-by-us-based-renaissance/
Tischner, C. M., Ebner, S. E., Aspiranti, K. B., Klingbeil, D. A., & Fedewa, A. L. (2023). Effectiveness of accelerated reader on children’s reading outcomes: A meta‐analytic review. Dyslexia, 29(1), 22-39.
Troyer, M., Kim, J. S., Hale, E., Wantchekon, K. A., & Armstrong, C. (2019). Relations among intrinsic and extrinsic reading motivation, reading amount, and comprehension: a conceptual replication. Reading and Writing, 32, 1197-1218.
Van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & society, 12(2), 197-208.
Van Dijck, J., Poell, T., & de Waal, M. (2018). The platform society: Public values in a connective world. Oxford University Press.
Virilio, P. (2006). Speed and politics: An essay on dromology. (M. Polizzotti, Trans.). Semiotext(e). Original work published in 1977
Vitello, P. (2014). Terrance Paul, developer of teaching software, dies at 67. The New York Times. https://www.nytimes.com/2014/09/17/technology/terrance-paul-developer-of-teaching-software-dies-at-67.html
What Works Clearinghouse. (2008). Accelerated Reader. https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_accelreader_101408.pdf
What Works Clearinghouse. (2016). Accelerated Reader. https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_acceleratedreader_061416.pdf
Yahoo! Finance. (2023, Oct. 4). World’s largest digital reading platform Epic announced as official reading partner to the Scripps National Spelling Bee. https://finance.yahoo.com/news/world-largest-digital-reading-platform-120000748.html
Zuckerberg, M. (2012). Facebook’s letter from Mark Zuckerberg. The Guardian. https://www.theguardian.com/technology/2012/feb/01/facebook-letter-mark-zuckerberg-text
Appendix
Surfacing Platform Logics: Competition, Speed, and Personalization
v24i4ELA2Appendix 