Volume 35, 2025

EN:

As interest in the singular “they” has burgeoned in scholarly venues and mainstream media over the past decade, writing studies scholars remain surprisingly absent from these conversations. I studied the impact, value, and challenges of teaching this gender-inclusive pronoun in three sections of my institution’s first-year writing course. Prior to instruction on gender-inclusive language, students used the singular “they” liberally and were not aware of how gender-inclusive they were. After learning multiple gender-inclusive writing strategies, students indicated increased awareness of their own use of such language, interest and confidence in using it, and appreciation of its relevance. They preferred the singular “they” to other gender-inclusive writing strategies. But evidence of a disconnect between language use and ideological opposition to gender-inclusive language was also apparent in two (of 71) students’ work. In addition to their work, students’ self-assessments are therefore vital indicators of the value, impact, and challenges of teaching gender-inclusive language: the nexus of perceived use, interest, ability, and relevance drives whether students will transfer their learning to other contexts and reconcile the disconnect, if one exists, between their language use and ideological orientation towards such language. These findings may be relevant to teaching other forms of inclusive, bias-free language.

EN:

Although writing can be a form of knowledge and knowledge-making, it is far from the only way postgraduates create and exchange knowledge. A recent book by Lucia Thesen details several ways in which a writing group at the University of Cape Town anticipates and responds to dominant constructions of knowledge and time within the academy. Ultimately, her discussion illuminates the possible benefits for students when writing interventions are conceived as an alternative to usual forms of assessment and knowledge rather than an instrument used in service of a narrow view of scholarly traditions.

FR:

La norme internationale sur le langage clair (ci-après « la norme ISO ») établit les lignes directrices de la communication écrite. Bien que la norme ISO ne soit disponible qu’en anglais actuellement, les principes qui y sont mentionnés se veulent universels et ils font l’objet d’un consensus. Appuyé par des données empiriques, le travail des experts impliqués a permis la création d’une norme plutôt concise.

Puisque le travail du comité d’experts se base sur des données empiriques, nous nous sommes demandée si le contenu de la norme intégrait les connaissances rédactologiques actuelles. Si tel est le cas, nous verrons si la norme peut servir de fondement à l’enseignement de la rédactologie. Cet article se veut une recension de la norme.

EN:

The International Standard on Plain Language (hereinafter "the ISO standard") sets out guidelines for written communication. Although the ISO standard is currently only available in English, its principles are intended to be universal and are the subject of a consensus. Backed by empirical data, the work of the experts involved has resulted in a rather concise standard.

Since the work of the expert committee is based on empirical data, we wondered whether the content of the standard incorporated current Writing studies knowledge. If so, we'll see whether the standard can serve as a basis for the teaching of Writing studies. This article works as a review of the standard.

EN:

This teaching report describes a workshop delivered at the University of Toronto Mississauga as a part of the Robert Gillespie Academic Skills Centre’s (RGASC) Head Start program. The workshop was premised on two guiding ideas: (1) since the University of Toronto maintains flexible guidelines regarding generative AI (hereafter genAI) policies across courses, undergraduate students benefit from participation in candid discussions of the contextual nature of shifting technological values and (2) first-year university students are in the unique position of also needing to contextualize the shift from high school to university learning contexts, so they are in particular need of opportunities to discuss the diversity of perspectives surrounding the permissibility of genAI use in higher education. The workshop led students through noticing the differences between high school and university learning expectations; applying socially oriented theories of communication; contextualizing “local” genAI syllabus policies; and crafting a personal theory of acceptable genAI use. This report is a collaboration between an undergraduate student (Author 1) and a writing professor (Author 2). To support educators in replicating all or part of this exercise within their own local contexts, workshop materials are appended.

EN:

This article analyzes outputs generated by three popular LLMs (ChatGPT, CoPilot, and Claude), which were prompted to produce a professional research article of literary criticism. Prior analyses of the rhetoric of literary criticism have established a rich profile of this disciplinary discourse community, allowing me to examine whether and how the LLM outputs simulate the characteristic rhetorical actions, purposes, and patterns of argument of research articles in English studies. The study demonstrates that LLMs do generate many of literary criticism’s rhetorical features, effectively signalling the genre. But I argue that, in a more fundamental sense, they fail to undertake its defining social action. For human critics, social action is tightly indexed to the specificities of rhetorical situation, including not only the individual interpreting self but also, and especially, the bounded, integral, public works of prior literary criticism and the literary text itself. LLMs, by contrast, currently generate criticism that recognizes neither that integrity nor those boundaries. I close by recommending that teachers help students recognize the grounding of genre in community, other texts’ integrity, and social action.

EN:

This paper reviews AI discussions to develop a thematic map of scholarship on AI, writing, and writing pedagogies. The project, developed between a university instructor and nine undergraduate students, had two central aims. The first was to synthesize the early research conversations on AI in writing contexts. The second was to identify gaps that will point to important next steps as the scholarly record on AI and writing develops. The paper presents five prominent themes: AI literacy, evaluating AI outputs, rhetoric in Human-AI interactions, AI and bias, and academic integrity. Conversations on AI literacy and academic integrity represent conceptual level discussions around AI and writing. The conversations around evaluation, rhetoric, and bias align more with AI writing practices and how these practices affect teaching and learning. Together, they provide a useful snapshot of scholarship and inform future work in a rapidly developing research conversation.

EN:

Since the launch of ChatGPT in 2022, a range of Generative Artificial Intelligence (GenAI) tools have emerged to support students’ English academic writing, benefiting particularly English as an additional language (EAL) students. Previous studies have primarily focused on undergraduates’ knowledge, perceptions, and practices of GenAI use in writing. Research on postgraduates, especially EAL doctoral students’ engagement with GenAI remains relatively limited; yet, these students are expected to demonstrate a higher level of writing proficiency to effectively disseminate their research within the academic community. To address this gap, this study aims to examine how EAL PhD students engage with GenAI tools behaviourally, cognitively, and affectively in a thesis writing course. Data were collected from students through questionnaire surveys and focus group interviews. Findings reveal that most participants viewed GenAI as a valuable tool for assisting their writing. However, some expressed hesitation about using the technology due to concerns about academic reputation and the originality of their research writing. This study has significant pedagogical implications regarding: i) the support needed by EAL PhD students to effectively use GenAI in their writing; and ii) possible ways to integrate GenAI technology into academic writing courses.

EN:

Generative Artificial Intelligence (GenAI) tools are transforming academic writing support in higher education, but student- and public-facing messaging from Canadian universities, and subsequently their writing centres, has been slow and inconsistent (Cheatle, 2025; Marcel & Kang, 2024; UNESCO, 2024). In the summer of 2024, two writing centre advisors conducted an environmental scan of writing centre websites and publicly available materials related to messages about GenAI literacy support. Documents were collected and assessed for 1) a “statement” or “policy” on GenAI use and assistance in the writing centre and 2) a stance toward using GenAI for writing, which we categorized broadly as able to assist with GenAI writing concerns (i.e., adopt) or disavowing use or assistance in the writing centre (i.e., avoid). Environmental scans facilitate discovery of opportunities and threats during times of change in the interest of making decisions and plans for the future. Our scan provides a snapshot of how writing centres, as well as the institutions they operate within, are positioning themselves within the current GenAI post-secondary landscape. This article contextualizes results within the current post-secondary landscape and offers recommendations and implications for the conceptualization of writing centre work.

EN:

Artificial intelligence (AI) tools increasingly influence writing practices in educational contexts, yet writing studies expertise is too often sidelined in current discussions. This paper presents core insights from rhetorical genre theory and genre-based pedagogy to inform the teaching of research and writing in relation to generative AI tools. Our analysis focuses on three key concepts that are of central concern: intention, process, and trust. These terms bring relevant conceptual dynamics into the foreground—including the role that intention plays in pragmatic analysis, the way that process matters in studies of writing, and the attention that trust receives in philosophy of science. We argue that focusing on these concepts during pedagogical decision-making helps us navigate between extreme hype and grave concern about generative AI tools in the context of research writing. We draw on recent empirical research to demonstrate how longer-standing insights about intention, process, and trust relate to contemporary conditions. Our analysis contributes to ongoing conversations about the role of AI in writing pedagogy by arguing for the continued assertion of deep disciplinary expertise and its attendant pedagogies. As we show, writing studies has the potential to lead—rather than react to—these conversations.

EN:

Generative artificial intelligence is disrupting the pedagogies of educators who teach writing. Amidst the disruption, they are grappling with who this technology is asking them to become. Drawing on Foucault’s metaphor of the prison panopticon as a surveillance mechanism, we explore how teachers are positioned by surveillance of student writing post-generative AI. This paper highlights the experiences of two educators working in distinct policy contexts. Part of a broader study (n=39) exploring how language and literacy teachers in secondary and postsecondary contexts work with, around, or against the use of AI in student writing, the focal perspectives in this paper show the tensions of remaining the teachers they want to be while constrained by their institutional contexts. In understanding how these educators both resist and take-up the role of ‘AI detective’, the findings illustrate how writing pedagogies are shaped by surveillance. The role of the AI detective not only has implications for the ways educators see themselves, but also their ways of seeing learners. This research contributes to theory and practice at the intersection of artificial intelligence, writing practices, and teacher agency, offering critical questions to empower pedagogical responses to generative AI.

FR:

Cet article explore comment les usages collaboratifs des grands modèles de langage (LLM) participent à transformer l’écriture scientifique, en s’appuyant sur une enquête conduite lors du hackathon « Ce que l’IA fait à la pratique de la science » (IXXI et CBPsmn, ENS Lyon, 8–9 juillet 2025). L’analyse s’ancre dans une démarche combinant ethnographie et cadres de la recherche participative (Merilhou-Goudard, 2016) : un ethnographe a co-construit avec les participants les protocoles d’observation et d’analyse, puis ces derniers ont activement contribué à la production et à l’interprétation des données. En mobilisant la perspective de la cognition distribuée (Hutchins, 1995), nous éclairons alors les dynamiques de groupes et les rapports aux LLM où se jouent la négociation de l’écriture scientifique entre les humains et la machine : élaboration collective des prompts, itérations critiques sur les textes générés et validation partagée des résultats. Plutôt qu’une automatisation du processus scriptural des chercheurs, les LLM redéfinissent les dynamiques de collaboration, les rapports disciplinaires et les régimes de scientificité des productions écrites, donnant naissance à une réflexivité médiée et co-produite par la génération automatique de texte.

EN:

This article explores the way large language models (LLMs) are transforming scientific writing practices. The approach adopted combines ethnography and participatory science. The ethnographic work took place during the hackathon “What AI Does to the Practice of Science” (IXXI and CBPsmn, ENS Lyon, July 8–9, 2025), and was led by an ethnographer who co‑constructed data collection and analysis protocols with the participants who actively contributed to the production and the interpretation of the data. Drawing on the perspective of distributed cognition (Hutchins, 1995) as well as frameworks from participatory research (Houillier & Merilhou-Goudard, 2016), we show that every stage of the scientific writing becomes a negotiated space between humans and the machine: the collective crafting of prompts, critical iteration on generated texts, and the participatory validation of resulting final presentation. Far from automating the process, LLMs redefine collaborative dynamics, forms of acculturation, and regimes of scientificity, giving rise to a mediated, co-produced reflexivity.