So much has changed since we originally wrote about ChatGPT and artificial intelligence: new chatbots, new AI programs, more powerful outputs. It’s all dizzying to keep up with, leaving us exhausted at the thought of preparing our courses. Some are excited about what AI offers as far as writing and overall work support. How do we appropriately address how AI relates to the work of teaching and learning without being completely overwhelmed? I suggest openly and humbly.
From the firehose of articles, blog, webinars, and crowdsourced resources, I offer a simple “syllabus” with the intention of offering starting points trying to avoid cognitive overload. In it I share the pieces I remember and go back to as I navigate this topic. Here I share a few key points to hold onto:
Say something about AI in the syllabus and with students directly.
While there are vastly different opinions and approaches to using AI, this point is consistent: students need guidance, transparency, standards, and rationale. This doesn’t require having it all figured out, but at least some preliminary thought and sharing with students your current thinking and policies. Browse Classroom Policies for AI Generative Tools to see which ones you gravitate towards, adapt for your needs, and include in the syllabus and assessments.
Focus on the 1-2 key assessments or activities, and evaluate for AI influence.
The AI conversation prompts us to consider what is most important for students in the coursework and how to maintain its relevancy. Consider these grounding questions to evaluate and update assignments mindful of AI (Bruff, 2023):
- Why does this assignment make sense for this course?
- What are specific learning objectives for this assignment?
- How might students use AI tools while working on this assignment?
- How might AI undercut the goals of this assignment? How could you mitigate this?
- How might AI enhance the assignment? Where would students need help figuring that out?
- Focus on the process. How could you make the assignment more meaningful for students or support them more in the work?
Explain what students get out of the process of coursework.
Key point at the heart of academic integrity and related discussions: what is the motivation to do the work itself? What does it build in the student? What does a student miss out on when not fully engaged?
Define standards and expectations for student skills.
This is also about checking in on our expectations of student outcomes. Higher ed teaching specialist Maha Bali uses a cake as a metaphor for AI, asking these questions:
- When/where would it be acceptable for students to take shortcuts such as buying from a bakery, baking from a box, or buying a Twinkie instead of baking from scratch?
- How would you encourage home made?
These key points and references are shared in my Syllabus: ChatGPT and Artificial Intelligence, a resources built to grow with the learners who interact with it, just as we should do in our own corners of education.
Save and adapt a Google Doc version of this teaching tip.
About the Author
Written by Christina Moore, Center for Excellence in Teaching and Learning at Oakland University. Image from Open AI’s ChatGPT. Others may share and adapt under Creative Commons License CC BY-NC.
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