Academic Integrity and Generative AI KCC English – AI guide Writing teachers have always had to deal with issues of academic integrity, but the advent of text generation models such as ChatGPT has posed new challenges. Many faculty members are concerned that students’ reliance on AI to complete their work undermines their development as readers, writers, researchers, and critical thinkers. There are also concerns that reliance on generative AI and Large Language Models (LLMs) results in a standardization and homogenization of language that privileges “correctness” and efficiency, over process and deep engagement with text. Moreover, unlike plagiarism and patchwriting, use of AI is harder to identify with the current technology. At the same time, writing teachers recognize that use of AI may be part of students’ educational and professional lives in the future, leading many to wonder if we have a responsibility to teach appropriate and ethical uses of AI in our writing classes. With this debate active and ongoing, this page offers both strategies to encourage students to avoid using AI and ideas for cautiously integrating AI use into writing instruction. The methods below were shared by KCC instructors and are intended to provide inspiration and encourage experimentation as we navigate this new instructional landscape. Information about academic integrity and resources for further reading are also provided. Strategies to discourage AI use in composition classrooms ● Talk to students about the ways that using AI and LLMs to generate writing undermines thinking and communication. ● Discuss how instructors read AI-generated content (often generic, flat, lacking personality) as opposed to reading student-authored work. ● Encourage students to see AI use in the classroom as part of a broader societal trend towards the standardization and homogenization of knowledge and information. ● Work on building classroom community, to emphasize the idea of writing as an opportunity to share ideas instead of only a product to earn a grade ● Assign and evaluate written annotation of hard copies of texts. ● Increase the amount of in-class writing and use this writing as the initial draft for subsequent formal writing. Require that students submit this hand-written work along with formal (typed) writing. ● Use process writing and metacognitive assignments to encourage students to think about writing as a process of discovery and invention. Sample assignments and activities using AI ● Work as a class to develop a small writing task, such as a summary or introduction, and then ask ChatGPT (or another AI tool) to generate the same text in order to compare the two versions. ● After students complete a more substantial, drafted writing project, use the same prompt to generate an AI version. Ask students to identify the strengths and weaknesses of the AI-generated text when compared to their own. ● Have students generate their own research questions and then use ChatGPT to refine these questions according to criteria developed in class ● Ask students to prompt ChatGPT for a list of possible resources and then have the students figure out a way to reduce this list to the 2-3 best sources and articulate their criteria for making these selections. ● After completing a full draft of an essay, students ask ChatGPT for help with “higher order” issues such as the logic of their argumentation or the structure and organization of their essay. To sharpen their metacognitive abilities, students can then write a short reflection about the ChatGPT suggestions they decided to incorporate into their work, the suggestions they chose not to use, and their reasons for making those decisions. Resources General information about institutional policies for handling issues of academic integrity You should include a clear statement of your classroom policies around plagiarism and use of AI that is consistent with Kingsborough and CUNY policy. The current page devoted to Academic Integrity on the KCC website does not specifically address AI use, but it does provide the following as examples of academic dishonesty: “Unauthorized collaboration on a take home assignment,” “Submitting someone else’s work as your own,” and “Presenting another person’s ideas or theories in your own words without acknowledging the source.” This page provides a link to a form to use to report suspected incidents of academic dishonesty. In contrast, CUNY’s Academic Integrity Policy states that use of AI can be considered a form of academic dishonesty and thus a violation of CUNY policy. Finally, the MLA-CCCC has formed a “Joint Task Force on Writing and AI,” which includes guidance around dissonance between institutional and departmental policy, principles for policies in composition classrooms, and principles and standards for our own use of AI in planning, writing, and publishing. Arguments for refusing AI use in writing instruction “Refusing GenAI in Writing Studies: A Quickstart Guide,” written and compiled by Jennifer Sano-Franchini, Megan McIntyre, Maggie Fernandes, articulates the various problems AI poses for writing while also rejecting punitive classroom pedagogy. It includes an extensive bibliography. This brief “Statement on Artificial Intelligence Writing Tools” by the Association for Writing Across the Curriculum” reiterates the important point that “Writing to learn is an intellectual activity that is crucial to the cognitive and social development of learners and writers.” This literature review compiles current research demonstrating the negative effects of over-reliance on AI models on students’ “cognitive abilities, including decision-making, critical thinking, and analytical reasoning.” A short piece in Time by Victoria Livingston discusses problems with AI use in writing (including links to other sources) and describes how her classroom efforts to demonstrate the limitations of LLMs backfired. A blog post by Carmen Kynard discussing the standardization of normative white American English and rhetoric as a direct predecessor to ChatGPT, to which much of the work of exclusionary rubrics has been outsourced. A blog post by Jason Read discussing the processes of reading and writing, emphasizing the unique “technology” of the written text as one that allows thinking and deliberation, as opposed to AI/LLMs, which “proletarianize” these processes. Rationales and strategies for integrating AI into writing instruction This essay in the Journal of Transformative Learning identifies some of the student populations that might benefit from generative AI, including multi-language learners and students with disabilities, while also noting problems such as unequal access and biased outputs. Reports on undergraduate perspectives on AI obtained through a survey. TextGenEd: Teaching with Text Generation Technologies offers a collection of essays about teaching with AI, based on the premise that “Generative AI is the most influential technology in writing in decades.” General resources on plagiarism and academic Integrity In “Plagiarism, Panopticism and the Rhetoric of Academic Integrity,” Sean Zwagerman argues against perceptions that there is a rising tide of plagiarism, contending instead that our phobia and the detection software that feeds it produces violations of academic integrity and thereby produces the educational “other”–the plagiarist defined against the “good” student, who affirms our ideas of individual authorship. “A Foucauldian-Vygotskian Analysis of the Pedagogy of Academic Integrity.” by Stephanie Crook warns against ascribing malicious intent to plagiarism in the context of the complexity of academic discourse around authorship and the distinction of one author’s original voice from another’s. Additional resources “AI Text Generators and Teaching Writing: Starting Points For Inquiry” (curated by Anna Mills): https://wac.colostate.edu/repository/collections/ai-text-generators-and-teaching-writing-starting-points-for-inquiry/ Evgeny Morozov: The AI We Deserve. https://www.bostonreview.net/forum/the-ai-we-deserve/ “Creative and Critical Engagement with AI in Education.” AI Pedagogy Project: https://aipedagogy.org/ “Critical AI Literacy Institute,” Teaching & Learning Center, The Graduate Center, CUNY: https://criticalai.commons.gc.cuny.edu/ “Teach@CUNY AI Toolkit: Critical Strategies and Resources for CUNY Instructors” https://aitoolkit.commons.gc.cuny.edu/