This Profile revisits Janet Emig’s influential article, explaining its original context and arguing for its continuing relevance in the current AI moment. The author encourages recovering the term “originating” and refocusing attention on how the timing, speed, and pacing of composing affect learning.
This article reports on a collaboration between a scholar of writing studies and a scholar of education to denaturalize the idea of writing at the graduate level being learned passively through disciplinary courses. Being able to communicate expertise clearly is a key competency of graduate education. Yet graduate writers often receive insufficient support. The authors redesigned a master’s-level course in the field of education, adding explicit writing instruction, peer review and revision activities, and a course text on writing, and shifting the core assignment from an end-of-term paper to a multistage, peer-oriented project. The authors then studied the impact of the writing instruction on one student through the lens of literacy scholar and teacher educator Gholdy Muhammad’s instructional equity framework. This narrative case study relays how one student processed and implemented the writing activities both in the course and, later, as a teacher. Her narrative suggests benefit in cross-departmental partnerships for integrating writing instruction into graduate courses across disciplines for holistic graduate learning.
This article reports on responses to a survey that invited students and instructors involved in writing-intensive courses to reflect on their views regarding the concern that generative artificial intelligence (GenAI) could be used in ways that undermine learning. Coding of both populations’ responses to an open-ended question suggests that students and instructors share a common reference world that could result in deliberative conversations regarding GenAI, writing, and learning. These results help define the nature of that reference world and offer emerging topoi from which productive discussion about the place of GenAI in postsecondary writing instruction could proceed.
This letter was written for the CCCC membership in September 2025; it has been lightly edited for publication here.
The integration of generative artificial intelligence (AI) into academic writing has raised questions about the syntactic complexity of AI-generated texts compared to human-authored essays. While studies have explored syntactic complexity in human writing, limited research has compared AI-generated argumentative and narrative texts, particularly in isolating cognitive overload and proficiency factors. This study addressed this gap by examining genre-specific syntactic patterns in AI-generated essays. Using the L2 Syntactic Complexity Analyzer, the study analyzed four hundred AI-generated essays (two hundred argumentative and two hundred narrative) and employed paired T-tests and Pearson correlation coefficients to identify differences and relationships among syntactic measures. Results showed that argumentative essays demonstrated higher syntactic complexity than narrative essays, especially in production unit length, coordination, and phrasal sophistication, while subordination measures remained similar. Correlation analysis revealed that argumentative essays compartmentalized ideas through coordinated and nominally complex structures, while narrative essays integrated descriptive richness through longer sentences and embedded clauses. The findings suggest that genre-specific rhetorical demands shape syntactic complexity in AI-generated writing. Implications for teaching and learning writing and future studies are discussed.
This Research Brief discusses transformers-the core engine for most artificial intelligence applications. The brief situates transformer technology within the field of rhetoric and composition by surveying recent studies; highlights the innovative aspects of transformers; and, finally, thinks through (Majdik and Graham) the operations of transformers and generative AI through Miller's theory of topoi, illustrating one way in which rhetoric and composition scholars and teachers can critically engage with generative AI in instruction and research.
From an unsettled, ambivalent middle between discourses of generative AI integration and refusal, we offer a critical-ethical stance for AI-engaged writing assignments. We apply a critical thinking framework to these assignments, assert critical AI literacy as a kind of critical thinking, and discuss how critical thinking and critical AI literacy can facilitate ethical discernment about generative AI use. This unsettled, critical-ethical stance positions scholars in our field to support context-sensitive pedagogical responses to generative AI across first-year writing, Writing Across the Curriculum, writing centers, and beyond.
In response to disruptions introduced to the job market by AI r & eacute;sum & eacute; screeners, this article introduces a novel theoretical framework for the life cycle of artificial intelligence systems to help unblackbox r & eacute;sum & eacute; screening AI systems. It then applies the AI life cycle framework to a digital case study of RChilli's job-r & eacute;sum & eacute; matching algorithm. The article introduces an eleven-step computational job-r & eacute;sum & eacute; matching assignment that writing instructors can use in their classrooms to explore the pedagogical implications offered by the AI life cycle framework. The assignment helps students simulate important phases in AI production and development while highlighting biases and ethical concerns in AI screening of r & eacute;sum & eacute;s. By exploring job-r & eacute;sum & eacute; analytics, this study helps to teach critical AI and data literacy, make job-r & eacute;sum & eacute; matching algorithms more explainable, and transform howprofessional writing can be taught in the age of automated hiring.
This article seeks to present a model of critical factors that influence writing transfer by exploring and extending conversations happening in the field. The article identifies five critical and interconnected factors that support writing transfer: connection, perception, reflection, disposition, and fortification. These factors emerge from an integration of writing transfer scholarship and data from a longitudinal study of student writers. In that study, six participants were followed for seven years (from first-year composition past graduation and into the workforce) and asked to explain their experiences and perceptions of writing. I offer these five factors to spark a broader conversation about how multiple overlapping influences contribute to writing transfer and to encourage further research into how these factors interact and reinforce one another.
In a relatively short time, market and political forces have intensified the reach of artificial intelligence (AI). AI has become, in a word, climatic-not only a discrete technological system but also a creeping assemblage of ideological, material, and political forces. This article tracks these forces by developing rhetorical climates of AI as a conceptual framework. In doing so, I aim to (1) link the harms of climate change with the rapid buildout of AI infrastructure and (2) shift the frame of the conversation by emphasizing the extractive, exploitative, enclosed, and knotted supremacist conditions that have been prerequisites for building AI systems at scale. While these pervading rhetorical climates may seem unchangeable, I track how microclimates of resistance have developed, in the past and in the present. In particular, I emphasize the importance of bodily intelligence in navigating asymmetrical conditions of power felt in the AI industry. The article concludes by discussing how rhetoric and writing studies can weather the unfolding rhetorical climates of AI by diagnosing conditions, seizing moments, and plotting futures to imagine a less extractive and less harmful world.
This article focuses on the seldom-discussed literacies of the Hip Hop audio engineer through the experiences of Lyrix, a Black woman audio engineer from the Midwest. Grounded in the literature of literacy scholars invested in the sonic dimensions of Hip Hop culture, two research questions guide this article: How does one develop their expertise as an audio engineer, and what insights can be gathered about literacy learning by focusing on marginalized Hip Hop figures, such as women audio engineers? This article ultimately argues that Lyrix's experience underscores a nonlinear approach to sonic literacy education, highlighting a transitory approach that ruptures and flows through barriers of access. The article concludes with suggested starting points for future research on Hip Hop literacy studies in particular and literacy studies more broadly.
In gaming, cheat codes change how players engage a system by inviting exploration and reducing the fear of failure. Drawing on writing center pedagogy, this article proposes a similar framework for navigating generative AI in writing instruction and positions play as a method for developing critical AI literacy. Writing centers have long served as spaces where students engage collaboratively with new technologies and construct meaning through dialogue. This article extends that tradition by positioning writing center pedagogy as a framework for helping students examine AI's ethical implications through treating it as a rhetorical situation to be unpacked, which demands principled, human-centered engagement rooted in values such as collaborative exploration. By weaving together writing center praxis and game-informed pedagogy, this article contributes to ongoing conversations in writing studies about how to integrate AI in ways that support critical thinking and ethical reflection. It demonstrates how playful, classroom-tested activities can animate discussions of bias and representation while helping students build rhetorical discernment through experience. Ultimately, the article argues that ethical literacy must be practiced through relational, iterative work. As writing classrooms become one of the few remaining spaces where students encounter generative AI with support and critical context, writing instructors have a vital opportunity to help students learn to write with, against, and around powerful technologies.
