• Year 7 students can learn to code engaging animated narratives with basic Scratch. • English teachers can learn to sufficient coding to support students coding stories. • Student animated narratives of 2 – 3 min can meet English curricula requirements. • Student multimodality use can be evaluated using a criterion-based framework. • Student coding proficiency can be extended through coding animated narratives. Coding animated stories in the English classroom has been advocated from over a decade ago as an integrated curriculum context for early teaching of computer programming while simultaneously developing students’ multimodal narrative authoring. However, related research has not adequately addressed English curriculum requirements for narrative creation. This article describes the development of a framework for analysing coded animated stories from the perspective of English curriculum expectations. Analysis of 23 stories showed substantial variation in the emphasis given to different multimodal resources among those stories with the most extensive use of such resources. Stories with limited use of these resources excluded those expressing characters’ emotions and positioning the audience to experience the story from a variety of points of view. Stories with extensive multimodal expression were at the upper, but not necessarily highest, coding proficiency levels, while some with high coding proficiency showed limited use of multimodal resources. Implications are drawn for coding as an engaging creative tool in English classrooms.

• Generative AI can help multilingual communicators in professional writing. • Generative AI supports email/report writing and meeting summary. • Practical, ethical and legal concerns remain. • Students’ AI use at workplace informs academic writing teaching and learning. Because multilingual students’ languaging practices are not limited to academic settings, it is important to explore their lived experiences communicating in real-world situations to shed light on how to prepare them in college classrooms in the era of generative AI. Drawing upon writing samples, artifacts and interview data, this case study brings attention to the potential and challenges a multilingual international student face in implementing generative AI-assisted written communication during her 5-month internship in the workplace. The findings indicate that generative AI tools, especially ChatGPT, have the potential to help multilingual communicators meet their written linguistic demands in professional contexts, especially in email writing, report drafting and meeting summary. Generative AI-assisted writing tools could assist multilingual students with idea expression and boost their confidence and agency in communication. Yet, despite its many advantages, practical, ethical and legal concerns remain. This study contributes to the scarce yet budding literature exploring multilingual international students’ AI engagement in professional settings and offers concrete pedagogical implications and directions for future research.

• Indexes are hylomorphic; they turn accidence into substance. • Indexes are authored, not merely produced. • The syntactic, alphabetic, and columnar form of indexes are rhetorically powerful. • Indexes are political because they destabilize hegemonic reading practices. This article, in the area of digital rhetoric, argues that the apparatus of the index is an authored text that bears all of the qualities of creative work. Its primary and distinguishing quality, moreover, is a hylomorphic one that bridges the temporal and material divide by taking the accidence in a text and naming it in substance. This dual nature is especially apparent in indexes that are produced by software, such as MS Word, that require the tagging of a main text to create what is called an “embedded index”; indexes of this sort exist both inside a main text and outside of it, in the tags and in the index list. Because the index both transforms (accidence to idea) and translates (from the main text to index list), the index has rhetorical force, interpreting a text for its readers. It does so as much by its content as by its formal qualities: syntactic, alphabetic, and columnar. Its persuasiveness in tandem with its intervention in the reading process, moreover, has social and political implications since the index can serve as both a means of rebellion and control for those who use and make them.

In this paper, we demonstrate how studying the rhetorics of ChatGPT prompt writing on social media can promote critical AI literacies. Prompt writing is the process of writing instructions for generative AI tools like ChatGPT to elicit desired outputs and there has been an upsurge of conversations about it on social media. To study this rhetorical activity, we build on four overlapping traditions of digital writing research in computers and composition that inform how we frame literacies, how we study social media rhetorics, how we engage iteratively and reflexively with methodologies and technologies, and how we blend computational methods with qualitative methods. Drawing on these four traditions, our paper shows our iterative research process through which we gathered and analyzed a dataset of 32,000 posts (formerly known as tweets) from X (formerly Twitter) about prompt writing posted between November 2022 to May 2023. We present five themes about these emerging AI literacy practices: (1) areas of communication impacted by prompt writing, (2) micro-literacy resources shared for prompt writing, (3) market rhetoric shaping prompt writing, (4) rhetorical characteristics of prompts, and (5) definitions of prompt writing. In discussing these themes and our methodologies, we highlight takeaways for digital writing teachers and researchers who are teaching and analyzing critical AI literacies.

This paper examines ChatGPT's use of evaluative language and engagement strategies while addressing information-seeking queries. It assesses the chatbot's role as a virtual teaching assistant (VTA) across various educational settings. By employing Appraisal theory, the analysis contrasts responses generated by ChatGPT and those added by humans, focusing on the interactants’ attitude, deployment of interpersonal metaphors and evaluations of entities, revealing their views on Australian cultural practice. Two datasets were analysed: the first sample (15,909 words) was retrieved from the subreddit r/AskAnAustralian and the second (10,696 words) was obtained by prompting ChatGPT with the same questions. The findings show that, while human experts mainly opt for subjective explicit formulations to express personal viewpoints, the chatbot's preference goes out to incongruent ‘it is’-constructions to share pre-programmed perspectives, which may reflect ideological bias. Even though ChatGPT displays promising socio-communicative capabilities (SCs), its lack of contextual awareness, required to function cross-culturally as a VTA, may lead to considerable ethical issues. The study's novel contribution lies in the in-depth investigation of how the chatbot's SCs and lexicogrammatical selections may impact its role as a VTA, highlighting the need to develop students’ critical digital literacy skills while using AI learning tools.

In this article, we draw on focus group interviews collected for the Wayfinding Project to explore how university alumni orient themselves as writers while participating in social media after graduation. By looking at alumni's self descriptions of their writing processes across public networks, we are able to trace pathways that recognize the rhetorical and communicative intentions of users, while also acknowledging the roles that serendipity, creativity, and the unexpected play in shaping these literate practices. Specifically, we point to how these alumni describe their experiences as they adapt to addressing audiences across different platforms and confront the “reach” of those platforms for engaging unexpected audiences. Several focus group participants use the term “branding” as a way to describe how they conceive of their writing across multiple social networks. These participants describe their public, networked writing as a form of managing their identities at the same time that they are “branding” themselves to manage the expectations of multiple audiences. In sum, our research shows us how the unexpected audiences generated through social media participation operate in tension with writers’ deliberate shaping of their messages and their self-presentation.

In response to the numerous ethical issues involving big data, this article positions the infrastructural dynamics of big data storage and circulation as a concern for social and environmental justice. After identifying how big data accumulate in place-based ecologies that are made vulnerable to sustain ever-increasing quantities of data, the author explains how most, if not all, digital writing practices are relationally tethered to often distant places. In response, the author argues for developing and sustaining critical infrastructure literacies where big data infrastructures are not perceived as ethereal, cloud-like entities, but as materialities with relations to place, land, water, history, climate, culture, nation, and much else. Attending to infrastructure with a cultural rhetorics orientation attentive to relationality, accountability, and story, the article details four critical practices that place digital citizens within relational matrices where they are asked to account for how data practices affect a constellation of people, places, and environments.

Over the past decade, compositionists have made a number of claims about opportunities presented by Wikipedia for teaching writing. The encyclopedia allows for transparent observation of concepts and skills related to process, research, collaboration, and rhetoric. Beyond observation, Wikipedia allows for public writing with an authentic audience, which often results in increased motivation. Much of this early research has dealt in opportunities and possibilities: speculation about how Wikipedia sponsors particular pedagogies and learning outcomes, and there remains a need for more empirical evidence. This article presents select data from a recent large-scale study conducted by the Wiki Education Foundation that begins to meet this need, and that confirms and extends research from the computers and writing community. Key findings from this research include positive evaluations of Wikipedia-based assignments in general, as well as positive evaluations concerning the capacity of Wikipedia-based assignments to teach critical thinking skills, source evaluation and research, public writing, literature review and synthesis, and peer review. This study also adds significantly to our field's knowledge of how contextual factors related to the course and assignment affect students’ evaluation of a Wikipedia-based assignment. Finally, this article suggests key recommendations for teaching with Wikipedia based on these findings.

This article examines how the Computers in Writing-Intensive Classrooms (CIWIC)/Digital Media and Composition (DMAC) Institute has realized founding director Cynthia L. Selfe's commitment to prioritizing people first, then teaching, then technology. I analyze how institute curricula introduce and model pedagogies for teaching digital composing, foster networking among participants, articulate a critical stance toward technology, and encourage newcomers to enter the field as administrators and scholars (as well as teachers). I also draw on participant documents (social media posts, publications, and CVs) to investigate the uptake of these ideas. Moving forward, I suggest that in light of the institute's growing emphasis on digital composing, 1) knowledge-making should be seen as the larger frame for CIWIC/DMAC work, and 2) research should be added to the institute's existing articulation of the field in terms of people→teaching→technology.