The panel’s focus is informed by and situated within a growing body of scholarship on AI, writing, and pedagogy. Foundational work such as Sperber et al.’s “Open Practices for Wicked Problems,” Baron’s Who Wrote This? and Duffy and Helens-Hart’s “Student Perceptions and Use of GenAI for Writing, stress the need to situate AI conversations in relation to actual classroom experiences. Meanwhile, broader interdisciplinary works, such as Miller’s The Artist in the Machine, Crawford’s Atlas of AI, Przegalińska’s Converging Minds, Gavin’s Generative AI and the Future of the Humanities, and Dorbin’s AI and Writing, provide critical lenses on creativity, power, ethics, authorship, and literacy that inform this panel’s attention to writing pedagogy.
In light of this scholarly context, the panel brings together four presenters addressing key pedagogical questions about AI and writing. Each will speak for twelve minutes at most. The session opens with Saroj GC outlining central issues and introducing the panelists.
Then, Purna Chandra Bhusal addresses pervasive AI’s growing influence across higher education writing instruction and classrooms and proposes ‘voicing’ as an alternative pedagogical tool to ‘voiding.’ In his formulation, voicing means AI as a tool but a source to foster and voice students’ agency and learning experiences through writing (in English) and voiding refers to the tendency to escape, avoid, or reject AI tools due to anxiety about their use. His proposition is based on pedagogical experiences that encourage students to revise, refine, and communicate their ideas more effectively thus bring their voices in their writing.
Next, Susan Ray, continues to acknowledge the pervasiveness of the tools and doubts students are unlikely to stop using AI, may instead hide its use, potentially harming their learning. She will report on her experience of redesign of the freshman composition curriculum by integrating the AI Transparency Journal, a structured practice that asks students to document various activities including the prompt/output, surprising elements and failures, biases notice, students’ thinking diverged from the machine’s suggestions. Her work was informed from a student survey that had implications regarding positive/negative impressions of students’ interaction with AI tools, plagiarism incidents, retention, and insights from post‑course reflections addressing issues of ethical boundaries, voice, and the tools’ confident yet unsupported outputs.
The last two presenters, while staying close to the nexus between AI and writing, will move beyond immediate writing experiences. Jennifer C. Lee situates her presentation at a lower-division, GE level and demonstrates how GenAI can be used for simple brainstorming activities and feedback while holding a firm line against students using GenAI to write materials for them. She will also contextualize the limitations of GenAI for prompted writing, including discussions of its negative impacts on critical thinking. The speaker as a WPA also will pair her argument with policy-oriented materials, handouts, and lessons that openly discuss the flaws of GenAI, the relationship between writing and thinking, and the emergent realities of a technology more nuanced than public conversations suggest. She argues that faculties should maintain a well-rounded awareness of GenAI developments and bring those discussions into the classroom to reinforce ethics-forward practice.
David Ornelas will examine, while these technologies promise efficiency and collaboration, they also raise urgent questions about whose language, identities, and perspectives represented within machine‑generated discourse, particularly for scholars concerned with equity, representation, and agency. He examines how generative AI tools produce, obscure, or reshape queer identities and discourse in machine‑generated writing. Reporting from ongoing mixed‑methods research, Ornelas will examine how LLMs respond to prompts related to queer identities and experiences and how these responses reflect or suppress queer perspectives. By considering writers’ interactions with AI outputs, he emphasizes ethical, critical engagement and seeks to expand conversations beyond efficiency or authorship toward deeper considerations of identity, discourse, and representation in AI‑mediated composition.
Finally, the presider will open floor for Q&A session