Computers and Composition最新文献

Ours is a time of epistemological break that requires a dramatic shift in our theorizing of the socioeconomic relationship of internet-articulated writers to data-mining corporations before we may formulate liberatory pedagogies and practices of internet writing. In the past, Computers and Writing (C&W) theorists joined others in describing a relationship that takes various names: surveillance capitalism, algorithmic capitalism, platform capitalism. Yet, to advance beyond the break, we posit that C&W theorists must recognize data mining as an exploitation belonging instead to a feudal mode of production. Unable to exploit the labors of proletarianized producers, capitalists on the internet transitioned to feudalism by enclosing the digital commons; distributing the commons as universal private property; using the rent form to alienate digicultural producers; subsuming producers’ sociolinguistic behaviors under the feudal mode; appropriating surplus labors of the class of unwaged labor; and placing heterogeneous, differentiated agents on the internet into two economic classes: peasants and lords. In this condition, the peasant class of digicultural producers cannot distance themselves through regulation, volunteerism, cloaking, and shielding. Their subsumed sociolinguistic activities cannot relieve exploitation because the two-sided act of languaging becomes three-sided with the addition of computer programs and AI acting as agents of digital lords.

As a prerequisite for the use of ChatGPT in writing classes, instructors should scaffold students’ (critical) digital literacy of the technology. Part of such scaffolding should include the exploration of relevant frameworks for conceptualizing ChatGPT, including the use of multiple metaphors, like tool and collaborator. By analyzing recent scholarly and news discourse regarding ChatGPT, prompts and outputs from ChatGPT, and the author's own writing process, the essay illustrates the limitations of the tool and collaborator metaphors, while emphasizing the value of multiple metaphors. In particular, the tool metaphor fails to account for ChatGPT's human components – namely its repurposing of thousands of authors’ writing and ideas, from which it draws with no transparency on sources. While the collaborator metaphor appears to address the need to cite ideas that are not one's own, ChatGPT fails to provide the accountability of a human author, even as it includes biased output derived from its training corpus, and while again failing to identify original sources. Medical and surgical metaphors highlight the ways that ChatGPT acts upon both the enormous corpus, or body of human writing, on which it was trained and our social body in our academic communities and beyond.

There have been few studies examining the variation that exists within modes of feedback: for example, comparing how electronic text feedback created using Google Docs differs from electronic text feedback created using Microsoft Word or how audiovisual feedback created using TechSmith Capture differs from audiovisual feedback created using Screencast-O-Matic. However, the programs that instructors use to create feedback have different affordances, meaning that even within a single mode, the feedback students receive on their writing can vary significantly. To better understand the variation that exists within a single mode, this study investigates how affordances of Canvas Speedgrader, Google Docs, and Turnitin GradeMark impacted electronic text feedback.Based on analysis of 131 feedback files created using the 3 programs, in conjunction with 5 student surveys, and 2 instructor interviews, the study provides insights into how instructor written commentary (location, form, type, focus, and mitigation) varied by program and how participants perceived of feedback provided through the 3 programs. The study...s primary finding is that the affordances of the programs used to create electronic text feedbackresulted in significant differences ininstructorcommentary and instructor and student perceptions of feedback.

In the fall of 2020, the nation was grappling with a global pandemic, a racial reckoning, and historic levels of political divide and uncertainty, leading up to a national election in November. During a time when it seemed nothing could manifest itself without being constituted in opposition to a political “other,” memes responding to the counting of ballots in swing states, particularly Nevada, flooded social media. In this article, I use a collection of Nevada election memes to show the power of harnessing humor and community values across national and local audiences. Because memes rely on community norms, their ability to build rhetorical bridges lies in fostering shared commitment and redistributing power dynamics away from institutions and towards the public. Using visual typology and rhetorical topological coding, I will discuss how Nevada election memes showcase strategies of solidarity (linked to common topoi and endoxa), helping audiences cope through a difficult time in our national history and offering an example of how political discourse can be configured around and above political binaries. In our communities, classrooms, and digital spaces, applying this technique reframes political discourse that traditionally capitalizes on division by instead focusing on building discourse grounded in commonality and community.

This quantitative study investigates the capacity of a girls’ summer technology camp, Girls Go Digital, to foster girls’ confidence with and interest in STEM subjects. Following in the lineage of compositionists’ local technofeminist camps to promote girls’ digital literacies (Haas, Tulley, & Blair, 2002; Blair et al., 2011; Almjeld & England, 2015; Macdowell, 2015; Mathis et al., 2016; England & Canella, 2018; Almjeld, 2019), Girls Go Digital is designed to reach girls who may feel discouraged by the environment of the company's mixed gender tech camps. Girls’ confidence is an important target for technofeminist outreach, as it's confidence more than skill that predicts girls’ and women's persistence in STEM. The study's results find that a week of camp at Girls Go Digital led to statistically significant positive impacts on girls’ confidence in their technology skills, as well as their attitudes relating to technology. Camp staff's intentional building of girls’ confidence and interests suggest promising tactics for future technofeminist interventions.

Even though Wikipedia is the 5th largest site on the internet and largely the number one source of information for internet searches, it is often ignored or dismissed by academics who teach writing, research, and information literacy. This article explores the potential value of including instruction in Wikipedia writing in the first-year composition (FYC) classroom. This kind of writing project aligns with existing learning goals for FYC and facilitates instruction in digital literacy, multimodal, and public writing skills. This article provides a case study of teaching Wikipedia writing to FYC students with the support of the Wiki Education program. Through writing for Wikipedia, my students practiced advanced research and writing skills as well as process steps such as drafting and soliciting feedback from external readers. Through working with the Wiki Education program, students learn digital literacy skills such as markdown and working in sandboxes. I also discuss the challenges of teaching Wikipedia writing to first-year students, especially in larger classes or when teaching more than 1–2 sections at a time. I conclude with advice for implementing a Wikipedia writing project in the first-year composition classroom.

Speech to text (STT) technology, also called voice recognition or speech recognition technology, automatically transcribes users’ speech to a computer screen. Research indicates that STT shows promise as an alternative mode of composition, supporting students in making fewer errors, writing more, and writing better. Much of this research takes place in elementary and middle schools, often focusing on students with identified learning disabilities. The current study extends STT research into general education high school classrooms, where students (N = 120) were invited to use it as much or as little as they wanted during one school year. We asked: Who used STT? Did subgroups, such as students labeled with learning disabilities, differ in their choices? When students chose to use STT, what kinds of writing did they do? Did STT compositions differ from non-STT compositions? Finally, what were students’ and teachers’ perceptions of STT? We analyzed field notes, interviews, surveys, and student writing with and without STT, and found mixed results: On average, students wrote more when they used STT than not. A little more than half of students found that STT eased the cognitive load of composition. A little less than half of students found that the tool constrained their composition. Some were put off by technical problems or embarrassment attendant with speaking out loud in class. Students’ choices to use STT correlated with special education designation, but not other designations. Despite students’ mixed reports, teachers were consistently positive about STT and planned to use it in future classes.

This article argues that rhetorical invention in social media environments includes key differences from invention in other spaces and thus demands its own specific consideration that foregrounds its contributing elements. When invention occurs on social media, a variety of forces come together to participate in that act of invention. These forces, which include a varied array of humans, hardware, interfaces, online communities, digital cultures, discourses, moderators, code, algorithms, and infrastructures, all contribute toward processes of rhetorical invention. This article offers a theory of network-emergent rhetorical invention that accounts for the array of actants that converge to make rhetorical invention in social media environments possible. Rather than considering humans as sole agents who autonomously act alone on other forces, network-emergent rhetorical invention considers how humans act with other actants to engage in rhetorical invention on social media.