• Students reported better understanding of writing with screencast assignments. • Students reported technology gains from screencast and screen recording assignments. • Students reported screencast and screen recording assignments were not complicated. • Blending spontaneous speech with the writing process helped students. • Students may feel self conscious when recording their screens and voices. Inexperienced writers often resist meaningful revision, which underscores the need for pedagogical approaches that foster deeper engagement. This study explores the use of student-led screen recordings and screencasts as pedagogical tools to promote students’ ownership and confidence in their writing processes. Our study surveyed 76 student writers in First-Year Writing classrooms to investigate this approach. The findings suggest that these assignments are easy to use, focus writers’ attention on the writing process, and leverage learning opportunities afforded by the transmodal blends of writing, video, and speech. Specifically, students reported more benefits from screencast assignments that allowed them to blend spontaneous speech into the writing process. Additionally, students reported that their technology skills improved after completing either the screencast or screen recording assignment. One downside was that students tended to feel self-conscious when recording their screens and voices. Overall, these student-led assignments are worth exploring in composition classrooms as they can lead to a deeper, more hands-on understanding of the writing process.

• 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.

• Postgraduates engaged behaviorally, affectively, and cognitively with GenAI feedback. • Postgraduates dealt with ChatGPT primarily as a tool for refining their proposals, not for generating content. • Postgraduates demonstrated agency by actively questioning, annotating, and negotiating feedback. • Postgraduates engaged in diverse affective responses, ranging from appreciation to frustration. As Generative artificial intelligence (GenAI) tools such as ChatGPT are becoming increasingly integrated into English as a Foreign Language (EFL) academic writing context, learners’ engagement with AI-generated feedback remains insufficiently examined. This case study investigated how four Chinese EFL postgraduates joining a course in a Malaysian university engaged with ChatGPT feedback while revising their academic research proposals. The study triangulated screen recordings, pre- and post-revision drafts, and stimulated recall interviews. Participants displayed a range of behavioural strategies, including accepting, questioning, rejecting suggestions, annotating visually, and seeking external validation. Affective responses ranged from appreciation and curiosity to doubt and frustration, particularly when feedback appeared conflicting or imprecise. Cognitively, learners applied various strategies such as evaluating, comparing, negotiating feedback, and regulating its use. Yet, they showed differing levels of engagement, shaped by individual perceptions and writing intentions. Importantly, participants regarded ChatGPT as a tool for linguistic refinement rather than content generation. Overall, the findings revealed that learners did not passively receive feedback but interacted with it in agentive and critical ways. The study highlights the interplay among these three dimensions of engagement and the importance of individual differences when evaluating the pedagogical potential of GenAI-generated feedback in academic writing.

User experience (UX) as both a vocation and a skillset is currently in the center of a wicked knot: emerging technologies such as generative artificial intelligence (GenAI) and large language models (LLMs) are (for the moment) widely accessible in unprecedented ways and are already heavily integrated into modern workplace practices and educational spaces. Further, workplace demands have led to a change in perception of the function and value of UX, and the field is facing new obstacles to hiring and research funding. Our article argues that a resituation of UX is needed: we-as instructors and administrators-need to focus on UX as an act of slow, embodied, and multimodal UX composition. To do this work, we offer the strategy of détournement as central to UX curriculum and preparing students for design work in a variety of rhetorical situations, expressed through our example assignments for instructors to implement within the college classroom.

Content personalization or tailoring content as per the needs of users has been a focus of technical communicators’ work since a very long time. Recently, algorithms have helped trace users’ characteristics such as devices they use, platforms they work on, local language spoken, etc. to personalize content through strategies like responsive content, automatic translation and so on. AI tools have extended algorithmic capabilities for personalization, but at the same time increased the randomness of personalized content. That is, algorithms produce different results for the same user at different times or different results for different users at the same time with the same prompt thus shifting the agency of both rhetors (or content creators) and the audience (or content users). While conventional technical communication pedagogy has focused on writing for users, and more recently on writing for algorithms which serve the users, today it is crucial to understand how technologies like AI impact knowledge consumption processes from a user experience perspective? And how can we teach content personalization and adaptive techniques in the increasingly digital spaces of audience interactions? These questions motivated our research. To follow the roles of algorithms and technical communicators closely, we analyzed three different case studies where algorithms are responsible for a high level of personalization beyond the decisions made by technical communicators. Our findings suggest that we must teach students to investigate concepts such as user personas in UX for understanding audiences, several methods of decision-making for content assets, and rhetorical ecology for a holistic view of content production to dissemination.

Effective source use is a critical skill for first-year writing students because it prepares them for academic, professional, and civic engagement; however, existing research demonstrates that selecting appropriate sources and engaging them insightfully remains a significant challenge. While students struggle with the combined pressures to read, evaluate, and synthesize scholarly sources, we argue that online media including news articles, opinion pieces, and social media posts are a potent but underutilized resource for building students’ competence and confidence with source use. In this article, we present the methods that we have collaboratively developed as an instruction librarian and a first-year writing instructor to propose a new approach to teaching undergraduate research using online media. We detail strategies for teaching advanced search skills using Google and social media platforms like Reddit and X (formerly Twitter), as well as a “reception study” writing assignment that requires students to develop source evaluation and synthesis skills for engaging these online sources. The success of our module highlights that enabling students to build their research skills in the context of these more familiar source formats can lead them to an enriched understanding of the research process—including formulating an authentic research inquiry and engaging meaningfully with real audiences—while also building their skills in accessing, evaluating, and synthesizing diverse sources. Furthermore, by developing research skills in the context of social media platforms and online popular media sources, students gain a practical sense of the relevance of academic research skills to their daily research habits.

How can posthumanism help us reframe AI-mediated literacy practices? And what implications does such reframing have for cultivating AI literacy in language and literacy education? This article explores these two imperative questions through a case study analyzing two multilingual undergraduate students’ meaning-making and meaning-negotiation intra-actions with AI technologies in a writing classroom. The case study reveals a productive tension between these students’ experiments with posthumanist literacy and their entrenched humanistic assumptions. Ultimately, through the case study, the authors hope to demonstrate that reframing and re-engaging with AI literacy through a posthumanist lens may offer students and educators a relational approach to developing and cultivating AI literacy.

• Hispanic women engage more in check-in assignments than men. • Hispanic enrollment (37.71 %) exceeds community college average. • Main themes: course perceptions, personal challenges, faculty-student relations. • Check-in assignments enhance engagement and faculty-student bonds for Hispanic women. • Advanced course students report more personal challenges, greater faculty reliance. While online community college students’ engagement with coursework, class retention, and motivation to participate are critical for academic success, these needs often go unmet for diverse and underrepresented populations, especially in the absence of culturally responsive and inclusive teaching practices. This study contributes to the limited research on culturally responsive pedagogy in online community college settings by exploring the implementation and impact of high-context communication practices in that setting, with a focus on improving engagement and academic outcomes for diverse student populations. Drawing on frameworks of culturally responsive teaching and high-context communication, the research examines the effectiveness of “check-in assignments” as a low-stakes, personalized intervention designed to foster stronger faculty-student relationships, enhance student belonging, and bridge cultural communication gaps in online learning environments. Using a mixed-methods approach, the study analyzes quantitative data on assignment engagement and qualitative themes from student responses. Findings indicate that high-context communication practices promote deeper engagement, especially among Hispanic and non-Hispanic females, while highlighting disparities in engagement among male students. Key themes—course perceptions, personal challenges, and faculty-student relationships—underscore the role of culturally informed interventions in addressing the needs of underrepresented groups and enhancing engagement and academic success. Future research could expand on these findings by exploring longitudinal outcomes and adaptive strategies for diverse learning environments.

This article explores teaching writing with generative AI as critical play where students and teachers engage in an ethically dialectical and aleatory game with generative AI. I qualitatively surveyed 24 writing teachers about how they teach writing with generative AI as well as its advantages and disadvantages. I discovered that teachers used generative AI to teach about the ethics of generative AI's design and rhetorical use to avoid plagiarism. Teachers also critically played with generative AI to teach the writing process of invention, drafting, revision, and editing. Specifically, the critical, dialectical interplay of human and machine invents in aleatory and emergent ways, creating moments of epiphany for students and teachers within the writing process for invention, drafting, revision, and editing while the real time pace of generative AI democratizes education, making writing and teaching more accessible for them.

The question of how generative Artificial Intelligence (Gen AI) will reshape communication is causing questions and concerns across the field of education, particular literacy and writing classrooms. Although important questions have surfaced surrounding the varied effects on writing instruction and ethical implications of AI in the classroom, there are calls for deeper investigations about how these tools might shape multimodal composing processes. This study builds upon this developing field by exploring how 21 university students in literacy education courses multimodally composed with generative AI and their perspectives on the use of AI in the classroom. Data sources included screen capture and video observations, design interviews, pre- and post- surveys, and multimodal products. Through qualitative and multimodal analysis, four main themes emerged for understanding preservice teachers’ multimodal composing processes: (1) composing was an iterative process of prompting guided by the AI tools, (2) composers exhibited two distinct processes when designing their projects, (3) AI shaped creative possibilities, and (4) play, humor, and surprise served a key function while composing. Preservice teachers’ perspectives also revealed insights into how AI shaped engagement with content, the importance of scaffolding AI in the classroom, and how ethics were intertwined with technical function and teaching beliefs.

• This study explores GenAI's role in multimodal composition, including Adobe Firefly and DALL·E. • GenAI reshapes the composition stages of invention, designing, and revising. • Despite its limitations, GenAI offers alternative solutions to wicked problems. • Post-GenAI use, students critically revise and iterate their compositions. • The study contributes to future research and teaching of AI-assisted composition. This study explores the integration of generative artificial intelligence (GenAI) design technologies, including Adobe Firefly and DALL·E, into the teaching and learning of multimodal composition. Through focus group discussions and case studies, this paper demonstrates the potential of GenAI in reshaping the various stages of the composition process, including invention, designing, and revising. The findings reveal that GenAI technologies have the potential to enhance students’ multimodal composition practices and offer alternative solutions to the wicked problems encountered during the design process. Specifically, GenAI facilitates invention by offering design inspirations and enriches designing by expanding, removing, and editing the student-produced design contents. The students in this study also shared their critical stance on the revision process by modifying and iterating their designs after their uses of GenAI. Through showcasing both the opportunities and challenges of GenAI technologies, this paper contributes to the ongoing scholarly conversations on multimodal composition and pedagogy. Moreover, the paper offers implications for the future research and teaching of GenAI-assisted multimodal composition projects, with the aim of encouraging thoughtful integration of GenAI technologies to foster critical AI literacy among college composition students.

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.

The predictive relationship between handwriting automaticity and children's writing performance is well documented. However, less is known about the relationship between keyboarding automaticity and children's keyboard-based writing performance. In this exploratory study, we examined the unique contributions of automaticity in both writing modalities in predicting Grade 2 students (N = 49) paper-based and keyboard-based writing performance (i.e., compositional quality and fluency) after controlling for students’ literacy skills (i.e., spelling, word reading, and reading comprehension), attitudes toward writing, gender, and nesting due to classroom. Multilevel modelling results showed that automaticity predicted students’ paper-based compositional quality and keyboard-based compositional quality and fluency. Findings further suggested that the relationship between automaticity and writing performance was stronger in keyboard-based text composing than in paper-based text composing. These results reinforce the role of automaticity of transcription skills in predicating the writing performance of beginning writers across modalities and stress the significance of explicit pedagogy and frequent instances of practice to promote the mastery of transcription skills across modalities in the early years of schooling.

This article describes five first-year writing instructors’ experiences with personalizing shared curriculum across three different course delivery formats (face-to-face, hybrid, online). The data is drawn from teaching journals that the co-authors, a non-tenure track, part-time Lecturer and a tenured Writing Program Administrator, and three Graduate Student Teaching Associates completed throughout Fall 2022. The findings illustrate both benefits and drawbacks related to shared curriculum: discussing and troubleshooting curriculum in a community of practice is highly valuable, but separating course delivery from course design is challenging. In our study, those challenges manifested as disconnects between course content and disciplinary identity, as well as personal feelings of failure. On the other hand, the need to personalize shared curriculum across multiple delivery formats proved productive, especially when instructors used asynchronous online materials as a starting point to develop hybrid and face-to-face lesson plans. Ultimately, we advocate for more conversations about how writing programs can support contingent faculty as they personalize shared curriculum through both course delivery and design, and we offer an example of a successful community of practice that revises shared curriculum in response to community members’ experiences with teaching in multiple modalities.

We share our experiences working with large-language model generative AI for a full semester in a professional writing course, integrating it into all projects. We discuss how we adapted our teaching, learning, and writing to using (or purposefully not using) AI. Issues we discuss include balancing integration of AI to avoid potential overreliance, the importance of centering authorial agency and decision-making, negotiating grading and evaluation, the benefits and drawbacks of AI throughout the writing process, and the relationships we build or could build with AI. We close with recommendations for faculty and students.

As a component of the Community of Inquiry Framework, social presence is typically defined as students “feeling real” enough to interact with and learn from peers online. This article complicates social presence for an online writing instruction (OWI) context, differentiating between social presence, social comfort, attitudes about online learning, and social learning. The study was initially designed to examine graduate students’ perceptions of social presence as an element of online teaching and learning in two sections of an Online Composition Pedagogy course offered in Spring 2020 and Summer 2020. The COVID-19 pandemic intensified the project, since students were now learning about hybrid and online pedagogy against the backdrop of their own experiences as emergency remote students and teachers. Analysis of 21 students’ reflections written during the courses indicates that distinguishing between social presence per se and social comfort, attitudes, and learning helps to account for the individual and social contexts of course participants. Ultimately, this article argues that simply inviting students to “feel real” or positioning yourself as a “real” instructor is not sufficient for establishing the types of social interactions that composition studies values.

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.