# Analysis of Generative AI Policies in Computing Course Syllabi

arXiv: https://arxiv.org/abs/2410.22281 · HTML: https://mlsanity.com/paper/2410.22281/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Oct 2024.

## Built on by (most cited first, 4 of 4)

- [Generative Artificial Intelligence for Academic Research: Evidence from Guidance Issued for Researchers by Higher Education Institutions in the United States](https://mlsanity.com/paper/2503.00664/) (2025)
- [A Comparative Analysis of Institutional and Course Generative AI Policies within Higher Education: Implications for Instruction in Computing Education](https://mlsanity.com/paper/2607.12296/) (2026)
- [Beyond Perspectives: A Trio-Ethnography of Interpretation Evolution in LLM-Supported Programming Education](https://mlsanity.com/paper/2607.22463/) (2026)
- [Generative AI Expands the Intellectual Reach of Course Based Undergraduate Research Experiences (CUREs)](https://mlsanity.com/paper/2608.27638/) (2026)

## Abstract (arXiv)

Since the release of ChatGPT in 2022, Generative AI (GenAI) is increasingly being used in higher education computing classrooms across the United States. While scholars have looked at overall institutional guidance for the use of GenAI and reports have documented the response from schools in the form of broad guidance to instructors, we do not know what policies and practices instructors are actually adopting and how they are being communicated to students through course syllabi. To study instructors' policy guidance, we collected 98 computing course syllabi from 54 R1 institutions in the U.S. and studied the GenAI policies they adopted and the surrounding discourse. Our analysis shows that 1) most instructions related to GenAI use were as part of the academic integrity policy for the course and 2) most syllabi prohibited or restricted GenAI use, often warning students about the broader implications of using GenAI, e.g. lack of veracity, privacy risks, and hindering learning. Beyond this, there was wide variation in how instructors approached GenAI including a focus on how to cite GenAI use, conceptualizing GenAI as an assistant, often in an anthropomorphic manner, and mentioning specific GenAI tools for use. We discuss the implications of our findings and conclude with current best practices for instructors.