Kate Navickas & Laura Davies
Cornell University, SUNY Cortland
This is a two-part assignment sequence that asks students to explore their own beliefs about how generative AI affects writing and writers. The first assignment asks students to write a 1-page creative non-fiction “Writing Philosophy”; then, we collate all students’ writing philosophies and analyze them as a class dataset in the Writing Philosophies Case Study assignment. The assignment sequence challenges students to put their own experiences with AI in conversation with both scholarship on writing and their peers’ experiences.
Learning Goals
Original Assignment Context
This is a two-part assignment used in a first-year writing class organized as a semester-long inquiry about how AI affects writing and writers. These assignments were taught as the third and fourth assignment in the semester because we wanted students to have time to read and discuss articles about writing and AI in class and explore their beliefs about writing and AI. During the semester, students also experimented with different generative AI platforms in class and reflected on those experiences.
Laura and Kate have both taught this assignment in their own institutional contexts. At SUNY Cortland, Laura taught this course in a first-year writing course capped at 22 students and an honors first-year writing section capped at 15 students. Meanwhile, at Cornell, Kate taught this in an alternative route first-year writing course, capped at 12, for students who self-identify as wanting more writing support (i.e., basic writing). In both contexts, students found this to be a challenging and exciting assignment.
Materials Needed: Each semester we have taught this assignment, we have added and revamped the readings that students engage with during the first half of the semester (prior and during the writing philosophy assignment). Some of the writing- and learning- focused readings that students had been engaging with include:
Alvero, A.J. et al. “Large language models, social demography, and hegemony: comparing authorship in human and synthetic text.” Journal of Big Data, vol. 11, no. 138, 2024, pp. 1-28.
Anson, Chris. “AI-Based Text Generation and the Social Construction of ‘Fraudulent Authorship’: A Revisitation.” Composition Studies, vol. 50, no. 1, 2022, pp. 37–46.
Bertoff, Ann E. “Recognition, Representation, and Revision.” Basic Writing, vol. 3, fall/winter 1981, pp. 19-32.
Brooke, Collin, and Allison Carr. “Failure Can Be an Important Part of Writing Development.” Naming What We Know: Threshold Concepts in Writing Studies. Eds. Linda Adler-Kassner and Elizabeth Wardle, University Press of Colorado, 2015, pp. 62-64.
Chayka, Kyle. “A.I. Is Homogenizing Our Thoughts.” The New Yorker, 25 June 2025.
Downs, Doug. “Revision Is Central to Developing Writing.” Naming What We Know: Threshold Concepts in Writing Studies. Eds. Linda Adler-Kassner and Elizabeth Wardle, University Press of Colorado, 2015, pp. 66-67.
Jamieson, Sandra. “The AI “Crisis” and a Return to Pedagogy” Composition Studies, vol. 50, no. 3, 2022, pp. 153–157.
Lindberg, Nathan. "We Should Promote GenAI Writing Tools for Linguistic Equity." Writing Center Journal, vol. 43, no. 1, 2025, pp. 159-66.
Morrison, Aimée. “Meta-Writing: AI and Writing,” Composition Studies, vol. 51, no. 1, 2023, pp. 155–161.
Sano-Franchini, Jennifer et al. “Refusing GenAI in Writing Studies: A Quickstart Guide.” 2024.
Vee, Annette. “Large Language Models Write Answers.” Composition Studies, vol. 51, no. 1, 2023, pp. 176–181.
Walsh, James D. “Who Wouldn't Cheat? In only two years, ChatGPT has unraveled the entire academic project.” New York Magazine, vol. 58, no. 10, 5 May 2025.
Warner, John. “Addressing the Transactional Model of School: We need to attack thoughtless ChatGPT use from the demand side.” The Biblioracle Recommends Substack, 11 May 2025.
Weixin Liang et al, “GPT Detectors Are Biased Against Non-Native English Writers.” Patterns, vol. 4, no. 7, 14 July 2023.
Interview with Rebecca Winthrop. “We Have to Really Rethink the Purpose of Education,” The Ezra Klein Show, a New York Times podcast, 13 May 2025.
Optional, but recommended: We printed physical 1-sided copies of each of the student’s final writing philosophies and gave each student a full set of the class philosophies. So, for a class of 17 students, each student received a set of 17 final writing philosophies, one from each of their peers. We spent an entire week reading and analyzing these philosophies together. Having a physical set is very helpful for annotation and creating smaller data sets around themes.
Time Frame: 3-4 weeks. Students write the writing philosophy quickly, in just one week. This includes a first draft and a revision. The second assignment needs two weeks but could benefit from three.
Overview
For the first part of the assignment, the Writing Philosophy, we ask students to brainstorm specific experiences they had using AI to write; then, they quickly draft a one-page Writing Philosophy, complete an in-class peer review, and revise them. The Writing Philosophy was a new and challenging genre for them. Essentially, we encourage them to reflect on their core values and beliefs and how they might develop one about writing that emerges from one specific experience. The peer review process is essential for this assignment, as students learn from reading how their peers approached the assignment. Since students will be writing about their peers’ philosophies in part two, we also spend time talking through developing an engaging title that captures their philosophy.
The second part of the assignment, the Writing Philosophies Case Study, involves at least two weeks. The first week, the class reads through the class’s set of revised Writing Philosophies. During the first class, we do a basic analysis, with each student having one physically printed set of philosophies in front of them. In this basic analysis, students read through the set and create thematic categories that emerge from it. For example, we often first try to categorize all philosophies according to their stance towards AI: pro-AI, anti-AI, or a middle ground. Other categories that emerge are ethical issues with using AI, arguments regarding why and how AI is a beneficial tool, the kinds of experiences in which students have over-relied on AI to their own detriment, and the emotional experiences and social pressures around using AI. This approach to analysis comes from a grounded theory approach to research–one that allows categories and patterns to emerge from the data itself instead of imposing a top-down theory on the data. After a class or two of creating categories and listing philosophies that go with them (which may include some debate!), students are asked to select a single category to focus on that includes at least five of their peers’ philosophies (which may or may not include their own).
We have found that students struggle a bit with locating similarities and differences within their selected theme. However, deeper synthesis requires not only locating a broader theme in the dataset (e.g., reflective use of AI) but then grouping the 5+ philosophies within that theme (e.g., three philosophies were reflective about their AI use and three were not).
For the second week of the Case Study assignment, we ask students to zoom into their set of five and use Writing Analytically’s “The Method” to do a deeper textual analysis, locating repetitions, strands, binaries, and anomalies. Through this work (further analysis and grouping the five philosophies), students are encouraged to develop a claim about their category. They also learn to introduce the larger project of the class, the category they have selected and why, and the individual philosophies.
For this assignment, we do not ask students to use AI tools to analyze the class writing philosophies. The goal of the assignment is to closely read and critically analyze the set of writing philosophies, and we want students to do this invention and critical thinking work without AI assistance. Students work in small groups and as a class to read the philosophies and identify themes and patterns they find significant. We have had conversations with students about the possibility of using AI for this part of the assignment. These conversations have been productive, as through them students consider issues of consent and privacy (i.e., do they have permission to put their classmate’s philosophy in an AI platform?). A few students did use AI tools to supplement their own analysis of the class philosophies, yet they found that the AI analysis focused on surface-level language and features of the writing philosophies. The student-driven analysis, on the other hand, drew on prior class conversations and the course readings alongside the analysis of the philosophies themselves. These student-driven analyses were more robust, complex, and interesting.
Part 1: Writing Philosophy
In this unit we will continue to reflect on what it means to be a writer who uses AI to help with writing. We will be reading some articles from Writing Studies scholars on revision, failure, and the ways that AI is often approached by teachers.
Your work will be to develop your own personal one-page writing philosophy. (This is a strict page length: you can write your philosophy single-spaced, but it does need to fit on a single page!) A philosophy is a document that offers your belief about writing and AI and uses some outside perspectives and examples to support and help explain that belief.
The focus of your philosophy might involve answering one of these questions:
To explain your perspective, you will need to:
Your writing philosophy should primarily be telling the story of one experience you’ve had using AI for the purpose of writing. You will want to put readers in the moment–explain the full context and setting, what happened, what you did, what happened after, and then, you’ll need to reflect on how you feel about this experience now and what that tells us about your belief about AI.
Some tips for writing about experiences:
Philosophies as a genre tend to be very personal. So you are welcome to use “I,” to use specific personal examples and feelings, and be passionate about your perspective!
Part 2: Writing Philosophies Case Study
This assignment asks you to use your classmates’ writing philosophies (part 1) as a database to analyze our collective beliefs about writing and generative AI.
What this means is that we will read and study everyone’s writing philosophies as a set: looking for patterns, noticing similarities and differences, and developing set-specific questions to deepen our analysis. In this work, we will learn how to analyze a large dataset, how to represent both the whole set and individual responses as evidence in our writing, how to notice trends, anomalies, and other patterns in texts, and how to use this analysis to make an argument about what this set tells us about student perspectives on writing and generative AI.
You will compose a 4-6-page analysis of your classmates’ writing philosophies. This analysis must include:
We would be remiss in not honoring that the Writing Philosophies Case Study assignment has evolved from an assignment designed by Tracy Carrick, Kate’s colleague at Cornell University. Carrick teaches a version of this assignment in which students develop an edited collection where they analyze their peers’ one-page snapshot stories of food experiences, interview peers for bios, and write a collection introduction that synthesizes trends in the selected stories. Tracy and Kate have also taught the assignment focused on students’ experiences with language.
Kate and Laura have a forthcoming (fall 2025) Composition Studies course design article that offers a broader explanation of the entire FYC course that focuses on “AI and Writing.”