Teaching with GenAI

Syllabus statements like these from the UMN Senate Committee on Educational Policy are a launch point for providing specifics about what is and isn’t allowed in your courses. Whether you decide to allow or prohibit GenAI, be explicit about your expectations for the course and for individual assignments.

Syllabus Statements

Daniel Stanford’s Substack offers a blogpost that distills key characteristics of good GenAI syllabus policies. The piece also provides a curated list of good syllabus statement examples from a range of disciplines showing policies that range from restricted to permissive use of AI by students. 

The Best AI Syllabus Policies I’ve Seen So Far

Leon Furze’s AI Assessment Scale: Version 2 blogpost provides instructors with clear language that is flexible enough to work across disciplines and assessment types on how and why AI can or cannot be used for a given task. The scale provides explicit guidance to learners for each of the five levels:  1) No AI, 2) idea generation and structuring, 3) editing; 4) task completion with human evaluation, and 5) Full AI. Find the 2024 publication on which the blogpost is based linked below. 

The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment 

The Center for Educational Innovation’s Generative AI in Teaching: Context and Strategies provides a nuanced overview to guide decisions about whether and how to use AI in one’s teaching. 

Generative AI in Teaching: Context and Strategies

The Center for Educational Innovation’s Generative AI Teaching Resources is a curated and regularly updated list of resources focused on creating assignments and guiding students. It contains readings, podcasts, mini-courses, and collections of sample syllabus statements and assignments from a range of disciplines.

Generative AI Teaching Resources

Leon Furze’s Teaching AI Ethics offers an in-depth guide on integrating AI ethics into education, covering nine key areas to deepen teaching and student engagement with AI's societal impacts.

Teaching AI Ethics

Join the UMN systemwide AI Community of Practice, a Google group open to anyone curious about the intersection between AI and ethics, academics, business, labor, technology, learning, and everything in-between. All disciplines and interests are welcome.  As a member of the group, you will be added to the listserv and receive invitations to gather monthly via Zoom to discuss emerging topics, innovations, and teaching strategies. 

UMN AI Community of Practice

In three Zoom sessions over fall semester, faculty, staff, and graduate students across UMN are invited to collaboratively explore “Teaching with AI:  A Practical Guide to a New Era of Human Learning” by José Antonio Bowen and C Edward Watson. Participants can expect to learn about the origins of AI, generative AI’s impacts on education, and new strategies and ideas that impact cognition and learning. E-books are available at each campus library. You need not read the book to benefit from the discussions.

"Teaching with AI" Book Club

Login with your UMN ID to Training Hub to find upcoming and recorded sessions related to teaching with GenAI. Simply enter Generative AI in the keyword search for all units. 

Training Hub

Zoom AI Companion is an opt-in, University-vetted suite of AI tools that enable meeting hosts (i.e., instructors) to generate class session summaries and “smart” recordings. The tool can also be set to enable students to ask AI Companion questions about what has been said earlier in the class session. Instructors who wish to explore whether Zoom AI Companion might be useful in their courses will find guidance about its affordances and limitations in this resource.

Zoom AI Companion - Guidance for Instructors 

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Microsoft Copilot

Microsoft Copilot: Guidance for Instructors