Rhetorical Engagements
These assignments ask students to consider how computational machines have already and will become enmeshed in communicative acts and how we work with them to produce symbolic meaning.
- Creating AI Audience Avatars to Enhance Audience Awareness in Multimodal Composition
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Morgan Harms-Abasolo
University of Nebraska OmahaIn this lesson, first-year writing students learn to engineer ChatGPT prompts to create an artificial intelligence (AI) Audience Avatar that functions as a mock focus group for their upcoming multimodal argument. As students interview their simulated audience members, they identify biased or stereotypical language to foster critical awareness of how AI simulates audience identity. The activity supports rhetorical knowledge transfer by helping students adapt their arguments to new audiences, genres, and purposes. This lesson can be adapted for any class level focused on rhetoric, multimodal composition, and communication.
- Cultural Inquiry Report: Affordances and Constraints to Generative AI for an Interview Activity
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Shakil Rabbi
Virginia Tech UniversityThis assignment asks undergraduate students to use Generative AI tools for an interview activity. Generative AI tools are used prior to the interview to generate questions and help students practice interviews, and post-interview to generate transcriptions of the interviews and clean the transcriptions. Students are also encouraged to make use of Generative AI in critical ways to analyze the interview transcript, with a focus on information. Generative AI cannot adequately identify without extensive contextualization (e.g. cultural frames and conversational pauses).
- Gender and Genre: Generative AI and the Feminist Manifesto
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Caroline J. Smith
The George Washington UniversityIn my first-year writing seminar, “Communicating Feminism,” I end the semester with an assignment that asks students to use an LLM (large language model) to generate a feminist manifesto. They annotate this manifesto, referencing course materials, and they also write a reflection on the manifesto, analyzing how well (or poorly) they feel their manifesto aligns with the conventions of the genre that we have previously established as a class. This assignment requires that students engage with both the content and the structure of the manifesto while also encouraging students to consider how gender politics might affect AI generated materials.
- Probing Biases with Generative AI
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Talla Enaya and Christopher Eaton
University of Toronto MississaugaThis assignment asks students to consider two aspects of AI bias: 1) potential biases that are present in AI generated outputs; and 2) how the biases that learners bring to the chatbot manifest in the outputs they receive. Students must answer a guiding question about course content using a chatbot to answer the question from the perspective of different characters/perspectives (e.g., a concerned parent; the Dean). Learners must then use the outputs to answer a series of questions related to AI biases so that they can become better equipped to account for and navigate these biases in their writing.
- Reflective Multimodal Feedback Practices Across Writing Contexts
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Kirsti Cole, Biven Alexander, Wil Carr, Brody McCurdy, and Bethany Van Scooter
North Carolina State UniversityThis collaboratively developed assignment engages students in designing and practicing ethical, multimodal feedback within digital and GenAI-assisted writing contexts. Over three scaffolded weeks, students co-create feedback criteria and rubrics, experiment with giving and receiving feedback across formats (written, audio, screencast), and critically evaluate AI-generated feedback. Designed to promote transparency, reflection, and agency in writing assessment, this assignment encourages students to think deeply about labor, authorship, and equity, which are key concerns in an era of generative AI and digital composing.