University of Notre Dame

Conditions et exceptions

No implied coursework permission.

Generative AI offers numerous ways to support your education, such as thinking through ideas, making study guides or practice problems, or providing help with understanding difficult concepts. However, misuse of this technology impedes the University’s mission to develop the gifts and talents that you bring to the ND community. Using it as a substitute for genuine engagement, or to circumvent the necessary intellectual challenges of your coursework, runs counter to the heart of education itself. As you reflect on your own reasons for being here, think carefully about the difference between supplementing your education and replacing it. The purpose of this academic integrity policy is not to be overly punitive, but to ensure that you engage genuinely and deeply with your course material in today's technology-rich learning environment. Of course, AI is changing the world, and you will most likely use it in your chosen field. But the University also wants to ensure that you acquire the knowledge and skills that your assignments are meant to produce, and that you are prepared to apply them after graduation in this new, complex, and ever changing world. With this in mind, remember that representing work that you did not produce as your own, including work generated or materially modified by AI, constitutes academic dishonesty. Use of generative AI in a way that violates an instructor’s articulated policy, or using it to complete coursework in a way not expressly permitted by the faculty member, will be considered a violation of the Honor Code. The University is committed to working continually to help you learn at a depth that prepares you to weather not only this technological pivot, but also the ones that follow. If you have questions about this policy, please contact the Office of Academic Standards at honor@nd.edu.

Collecté: 2026-10-09 · 13–17
SHA-256: 562e2e54b0bac21a8878bfea62340a9cb2b39dda863894db5071e722651a5c1f

Conditions et exceptions

AI-editing exception must be explicit; vendor-detector performance not inferred.

Policy Update: AI Editing Tools (Fall 2024) Policy Update: AI Editing Tools (Fall 2024) AI-powered editing tools like Grammarly and WordTune work by using AI to suggest revisions to your writing, so the suggestions they make are AI-generated text. This means that if your instructor prohibits the use of gen AI on an assignment or in a class, this prohibition includes the use of editing tools, unless explicitly stated otherwise. If your instructor is using an AI detector, even a small number of suggestions from an AI editing tool in your writing can cause it to be flagged as 100% likely to contain AI-generated text. This is not a false positive, as the detector has correctly identified the AI-generated content produced by the editing tool. If they have permitted the use of editing tools, then it may not be an issue, but you should be aware that this result can occur even with minimal AI assistance. Furthermore, using AI-generated suggestions without proper attribution can be considered a form of academic dishonesty. This is because you're incorporating AI-generated content into your writing without citation, just as using content from another source without citation would be considered plagiarism. If you aren’t sure, check the syllabus or ask your instructor for clarification, and consider citing the use of these tools if they are allowed.

Collecté: 2026-10-09 · 11–16
SHA-256: fbc69b63fc010f449de4d084bfa52a893750183971518c01d8192d12cb097a75

Conditions et exceptions

Student/staff tool audiences and restricted data distinguished.

Core AI Tools PUBLIC, INTERNAL, SENSITIVE Google Gemini Available at no cost to all faculty and staff. Integrated with Google Workspace. PUBLIC, INTERNAL, SENSITIVE ChatGPT EDU Available by request and annual fee. Includes tools such as agent builder. PUBLIC, INTERNAL, SENSITIVE Gemini Notebook Available at no cost to all faculty, staff, and students. A research and thinking platform that is grounded in the provided sources to improve results. Know Your Data Before using any AI tool, identify your data classification. 🟢 Public Safe for AI Info intended for broad public release. No adverse effect if shared. 🟡 Internal Safe for AI Business data for internal circulation only. Potential operational impact. 🟠 Sensitive Safe for AI Role-restricted info. Serious privacy or operational risk if leaked. 🔴 Restricted 🚫 PROHIBITED SSNs, Credit Cards, Health Data. Never enter into AI. Critical Reminder: If you are unsure about a data type, DO NOT share it with an AI tool. More about data classifications Other AI Tools Google offers many AI products, many of which are integrated into your Google Workspace account. Compare Google AI offerings Students: All AI use for class work is subject to instructor guidance and the Academic Code of Honor.

Collecté: 2026-10-09 · 25–48
SHA-256: cf39e2d4a803bb862506aeb0e8849757c068f6d9dd7a53e64d14a278b584e4dd

Guidance on the Use of Artificial Intelligence for Assessment Author: University Committee on Academic Technologies (UCAT) AI Subcommittee May 6, 2026 The rapid deployment of artificial intelligence (AI) tools in society at large has invited us to rethink many of our classroom practices, both around what sort of work we expect students to produce and how instructors can or should use AI to aid their efforts to assess student work and assign grades. This document lays out some general guidance from the University Committee on Academic Technologies (UCAT) AI Subcommittee on how instructors should approach assessment practices assisted by AI. Definitions Briefly, we clarify a few terms that are used in varied ways across disciplines. Assessment is the overall process of gathering and evaluating information about student performance, and using this to guide decisions about both teaching and grading. Grading is the specific matter of assigning a letter or number grade to summarize a student’s achievement of learning goals, on a unit of work or the course as a whole. Feedback is the process of providing detailed responses to student work for a variety of purposes, such as correcting errors, encouraging growth, or explaining grades.1 Framing Questions and Guidelines The committee considered two primary questions: Should instructors use AI for grading, and what are the important considerations? Should instructors use AI for feedback, and what are the important considerations? Most importantly: Instructors must remain the final decision-maker on grades. Grading is ultimately a human activity that serves to summarize the student’s progress toward the course learning goals. While AI might be used to assist in generating observations that support grading, such as pointing out technical errors or drafting general comments, instructors retain full responsibility for grades assigned on any work and must be able to explain and justify the observations supporting that grade. AI should not be used for fully automated grading of student work; the final judgement, decision-making power, and the resulting score must reside entirely with the human instructor. Before adopting AI tools to generate feedback or other observations about student work, instructors should carefully consider the following aspects: Instructors should consider what is potentially lost (or gained) by adopting AI-assisted feedback. A close reading of student work is one way that faculty develop a deeper understanding of each student’s strengths and weaknesses, as well as the performance of the class as a whole. By taking the time to digest and respond to student work thoughtfully, faculty have the opportunity to connect more closely with individual students. Consider the tradeoffs in adopting AI tools for assessment: Will an AI-assisted process create more distance between you and your students? Will it provide feedback that is not otherwise available? Will it free up more time for one-on-one engagement with students? A careful consideration of the intended student-faculty relationship should guide decisions about AI adoption. Instructors should disclose to students if, how, and why AI is being used in a course. Indicate whether AI is used for assignment creation, drafting feedback, guiding faculty attention, producing student-visible output, or some other purpose. If AI is not used at all, that should be clearly stated as well. This helps to preserve trust between students and instructors. Similar disclosures should be made in course planning and departmental curriculum discussions in order to help establish norms and expectations across faculty and courses. Consider the example disclosure in Appendix A based on Algahami.2 Instructors should use only tools approved by the University for handling student work. Online AI services vary considerably in how they deal with privacy, security, and the use of input data as training material for later outputs. There are substantial risks that unapproved tools may leak personally identifiable data or cross-contaminate results from different students. Instructors should not feed, or allow access to, student data of any kind into tools not approved for that purpose. (Currently approved tools are noted in reference 3.)

Collecté: 2026-10-09 · 13–34
SHA-256: f61617ce69f734c27b2ce4d25367c8479783c4d558ea7bcbc2a77b8786c89ff7