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.

• The informality of video essay narration engendered ideation in drafting and script writing for students. • Students felt more responsible and personally invested in their arguments when they narrated and dramatized them in the video making process. • While students admitted that they tended to “gloss over” written drafts when revising, the video making process prompted students to be more self-motivated in the revising process, enabling them to evaluate and develop their arguments. • Unlike oral presentations, as students viewed their video essays as audience members, they could more clearly discern if their arguments lacked coherence or depth. This self-evaluation resulted in students taking the initiative to revise their final written assignments. Although multimodal assignments have increasingly been incorporated into academic writing curricula, research into their impact on student writing remains limited. This study, conducted at a Singaporean university, required students to transform a written essay draft into a video essay and then revise their draft into a written essay assignment. By comparing students’ initial drafts and their final submissions, and analysing interviews and reflective journals, we identified significant benefits stemming from the transmediation between written and multimodal text. Specifically, we found that 1) transmediation enabled students to self-evaluate their writing as they repeatedly listened to their voiceovers, found concrete visuals to illustrate their ideas, and edited their work to fit the concise video format; 2) students broke with habitual, less useful revision practices as they were freed from the conventional and grammatical concerns of written academic text and narrated their arguments colloquially in their voiceovers; 3) students exhibited an improved awareness of audience and medium; and 4) students were more enthusiastic with the course due to the novelty of the multimodal assignment. These findings suggest that including a video essay assignment during the drafting process can serve as an effective tool in advancing students’ abilities to evaluate their own academic writing.

• 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.

• 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.

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.

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.

Our First-year Writing program began intentional student engagements with generative AI in the fall of 2022. We developed assignments for brainstorming research questions, writing counterarguments, and editing assistance using the AI tools Elicit, Fermat, and Wordtune. Students felt that the tools were helpful for finding ideas to get started with writing, to find sources once they had started writing, and to get help with counterarguments and alternate word choices. But when given the choice to use the assistants or not, most declined. Generative AI at this stage is unreliable, and many students found the tradeoff in reviewing AI suggestions to be too time consuming. And many students expressed a preference for continuing to develop their own voices through writing. Our experience in engaging AI led to the creation of the DEER praxis, which emphasizes defined engagements with AI tools for specific purposes, and generous use of reflection.

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.