UPDATED AUGUST 2025

There is no question that the ever-growing landscape of generative AI tools (e.g., ChatGPT, CoPilot, DALL-E) continue to impact higher education. Since we started gathering and sharing resources on the subject, more and more products and platforms that we use everyday have some level of AI tool integration (e.g., Microsoft, Blackboard, Zoom, Workday). The recommendations we shared on this page last fall remain relevant. What has been updated are some of the resources and learning opportunities. Look for this page to continue to be updated throughout the year. 

1. Understand how AI works. Take the time to learn more about the basics as well as the range implications. 
2. Talk to your students. Rather than wondering about each other's expectations and experiences, invite a conversation. In advance of such a conversation, consider the extent to which you already have clarity. How do you expect students to use or not use generative AI? What are your policies and guidance? How can you help students navigate choices in your class and beyond? 
3. Critical thinking is more important than ever: When should one use AI? When should one not use AI? How should AI output be evaluated? What are the right questions to ask about rapidly evolving new technologies? What assumptions are being made? Who benefits and who is harmed? 
4. Take an "education first" approach. Helping students learn means providing clear guidance instead of relying on policies and policing. Lean into trust as we are all learners in this space. Such guidance can appear in your syllabus but should accompany assignment instructions, as well. It may very well be that a single syllabus-based policy isn't nuanced enough to address the use (or non-use) of AI as it relates to particular assignment. 
5. DO NOT rely on products billed as AI detectors. Such software is unreliable at best and problematic on multiple levels. 
6. There is no one right answer to addressing AI in your teaching, scholarship and work, but reflecting on your own values will inform your next steps in learning.
7. Do you plan to require student engagement with third party tools (many of which have terms of use associated with creating accounts) and if so, do students notified in advance and are you prepared to offer assignment completion alternatives?  

Syllabus Policies & Assignment Guidelines

In addition to clarity of expectations in a syllabus, we highly recommend including "point of use" guidance around AI as part of a specific assignment's guidelines. Several excellent collections of sample verbiage:

Generative AI and the College Classroom, Center for Engaged Pedagogy, Barnard College [A beautiful site with instructor decision-making infographics and concise recommendations and syllabus statement examples]

Use prohibited, Use only with prior permission, Use only with acknowledgment, Use is freely permitted with no acknowledgment, University of Delaware

Syllabus Policies for AI Generative Tools, Lance Eaton

Padlet collection of university policies, Western University of Health Sciences

AI Literacy in the Age of Generative AI, Guidance for Syllabus Language, University Libraries, Texas Tech University University 

5 Steps to Update Assignments to Foster Critical Thinking and Authentic Learning in an AI Age, Faculty Focus blog post, 2025

Citation guidelines: APA and MLA

Teaching with Generative AI, San Francisco State University 

Yee, Kevin; Whittington, Kirby; Doggette, Erin; and Uttich, Laurie, "ChatGPT Assignments to Use in Your Classroom Today" (2023). OER work with a stellar overview of ChatGPT followed by examples of assignments arranged in topical categories.

Yee, Kevin; Uttich, Laurie; Main, Eric; and Giltner, Liz, "AI Hacks for Educators" (2024) OER compilation of instructor-focused applications.

Assessing Student Learning

The ways in which we assess student learning in both in-person and online environments are likely to change. From writing assignments to multiple choice exams, the implications of generative AI are significant. In addition to the resources above, we offer two additional approaches: 

Reflective annotations - on either writing assignments or exams, ask students to go deeper and respond to prompts such as: Why did you make this choice? How did you approach finding a solution? Was it challenging/useful/satisfying and why? For additional examples, see Built-in Self-Assessment: A Case for Annotation, Faculty Focus blog and Rethinking Reflective Writing Assessments in the Face of Generative AI, University of New South Wales Sydney. Better yet, consider using a social annotation approach. Hypothesis is a tool supported by GVSU (see the Hypothesis overview and related IT Knowledge Base article).  

Authentic assessments - sometimes referred to as "meaningful" assessments, the general idea is moving away from recall tasks to application and real-world contexts. Two online tutorials we recommend are Designing Authentic Assessments, Queens University and Authentic Assessments, University of Illinois Chicago. See also the IT Knowledge Base article on the topic. 

Equity Considerations

AI comes with costs. What may appear free (for now) requires extensive resources and generates concerns about equitable access. Some questions to consider: 

1. What are the sources of data? Who has given permission for their work to be included? 
2. Does everyone have equal access to tools? Generative AI tools with enhanced features over free versions come with ongoing costs. 
3. What resources are being used to stand up generative AI? You may be surprised to learn about the environmental impacts. 
4. If you suspect that a student has used of ChatGPT, for example, to complete an assignment, what can you do? We strongly advise against detection tools which have been shown to be ineffective. Assuming that you have provided students with clear guidance on use of AI tools, the best first step is to have a conversation with the student. 
5. Two things that we know for certain is that standalone generative AI tools are evolving rapidly and that AI is increasingly becoming embedded into existing technologies (Office365, Zoom) in ways that are obvious or not. How will you keep up and help students make ethical choices? 

For three quick takes on the issues raised above:

• FAQ, ChatGPT in the Classroom, Andrew Maynard, Arizona State University 
• Saenko, K. (2023). A computer scientist breaks down generative AI’s hefty carbon footprint. Scientific American. 
• Abrams, Z. (2024, April 1). Addressing equity and ethics in artificial intelligence. Monitor on Psychology, 55(3). 

Related GVSU Policies and Resources

Acceptable Use Policy for Public AI Solutions, Information Technology

Academic Misconduct Policies and Procedures, Office of Student Conduct and Conflict Resolution

Social Media and Third Party Tools in Teaching, eLearning Technologies

Writing with Artificial Intelligence and ChatGPT, Supplemental Writing Skills 

Writing with Artificial Intelligence and ChatGPT, Department of Writing 

Policy on Working With AI-Assisted Writing Tools, Writing Center 

OURS Generative AI Policy, Office of Undergraduate Research and Scholarship

Artificial Intelligence use in a Research Project, Thesis, or Dissertation, Graduate Education Policies and Procedures Manual

AI Guidelines for Communicators, University Communications 

Protocols and Details Regarding Unit Personnel Meetings (addresses AI tools in the context of personnel actions), Office of the Provost 

Additional Resources

1. Bowen, J. A., & Watson, C. E. (2024). Teaching with AI: A Practical Guide to a New Era of Human Learning. Johns Hopkins University Press. [The Pew FTLC is sponsoring several Learning Communities around this book and hosted viewings of a webinar series with the authors that was well received.]
2. Framework for Responsible AI Integration in PreK-20 Education, Center for Innovation, Design, and Digital Learning, 2025 
3. AI Playbook for Teaching and Learning Leaders: A Community Guide, University of Guelph, 2025
4. Artificial Intelligence and the Academic Professions, AAUP, 2025
5. Why AI is making us worse thinkers (and how to avoid it), Untools post addressing the phenomenon of cognitive offloading, 2025
6. AI Pedagogy Playbook, MetaLAB at Harvard, 2025
7. A few thinkers on AI we follow:
   1. John Warner, The Biblioracle Recommends
   2. Bryan Alexander, Bryan's Substack
   3. Renée Cummings, University of Virginia 
   4. Lance Eaton, AI + Education = Simplified
   5. Timnit Gebru, Distributed AI Research Institute 
   6. Ethan Mollick, One Useful Thing

Do you have a resource that you have found particularly helpful? We welcome your suggestions for additions to this page.