LibGuides: Artificial Intelligence Guide for Faculty & Students: University and Classroom AI Policies

The disparity between students and lecturers highlights the need for a nuanced approach to policy development and its clarification. The students' engagement with the technology reflects an openness to integrate it responsibly, contrasting with lecturers fears of plagiarism. These opposing perspectives underscore issues of trust and the absence of a uniform policy to guide concepts of fair use. The implications are profound, requiring balanced policies that maintain authorial integrity whilst utilizing technological advancements for educational enrichment. (Duah & McGivern, 2023, p. 185).

Conclusions from the following study on the ethical and practical use of generative artificial intelligence in a university in the UK:
Duah, J. E., & McGivern, P. (2024). How generative artificial intelligence has blurred notions of authorial identity and academic norms in higher education, necessitating clear university usage policies. International Journal of Information & Learning Technology, 41(2), 180–193. https://doi-org.lib-proxy.jsu.edu/10.1108/IJILT-11-2023-0213

Jacksonville State University Scholars' Code

Higher Education Policies on AI: Examples

Duke University's 'Artificial Intelligence Policies: Guidelines & Considerations'

2024 EDUCAUSE Action Plan: AI Policies & Guidelines

Harvard University's "Initial Guidelines for the Use of Generative AI Tools at Harvard"

Columbia University's "Generative AI Policy'

Liberty University's "Artificial Intelligence & Academic Integrity Faculty Guidance"

Stanford University's "Generative AI Policy Guidance'

Journal Articles on AI Policies & Guidelines in Higher Education

Wu, C., Zhang, H., & Carroll, J. M. (2024). AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities. Future Internet, 16(10), 354. https://doi-org.lib-proxy.jsu.edu/10.3390/fi16100354

Overono, A. L., & Ditta, A. S. (2024). The Use of AI Disclosure Statements in Teaching: Developing Skills for Psychologists of the Future. Teaching of Psychology, 1. https://doi-org.lib-proxy.jsu.edu/10.1177/00986283241275664

Artificial Intelligence Checklist for Faculty

This checklist for University of Arizona faculty was created "to provide faculty with tools to review assignments for suspected cases of Artificial Intelligence (AI) use prior to sending the information to the Academic Integrity team for an informal review..." This one page checklist is an example of what faculty should consider when suspecting a student has used AI in an unacceptable manner.

University of Arizona's Artificial Intelligence Checklist for Faculty

aI policy

Nobody wins in an Academic Integrity Arms Race: How Artificial Intelligence is Changing the Way Colleges Think About Teaching

Lance Eaton's "Syllabi Policies for AI Generative Tools' Database

Lance Eaton, a student working on his doctoral degree in higher education at the University of Massachusetts, designed this database of syllabi policies for AI generative tools. The purpose of this database is to help "other instructors see the range of policies available by other educators to help in the development of their own for navigating AI-Generative Tools (such as ChatGpt, MidJourney, Dall-E, etc)." Faculty are invited to "download or share this resource or parts of it with their colleagues, institutions, and communities of practice."

Syllabi Policies for AI Generative Tools

The University of Arizona's Artificial Intelligence in Teaching and Learning

The University of Arizona has put together this excellent resource guide for faculty which includes "Guidance for Syllabus Language' and examples of strategies to 'adjust assignments' in this new era of genAI.

Artificial intelligence in Teaching & Learning