Students as Partners in Teaching about Generative AI

Last year on the podcast, I talked with Pary Fassihi about the ways she was exploring and integrating the use of generative AI in the writing courses she teaches at Boston University. During that interview, Pary mentioned an AI affiliate program running out of the writing program at Boston University. This program involved matching undergraduate students—the AI Affiliates—with writing instructors, giving the AI Affiliate a role in supporting both the instructor and their students in responsible and effective use of AI in writing.

I was intrigued by this idea. I’ve seen a lot of different kinds of initiatives in the last two years to help faculty wrap their head around AI’s impact on teaching and learning, but this was the first time I heard about a student-as-partner approach. I asked Pary to connect me with an instructor and their AI Affiliate so I could learn more.

Pary introduced me to Christopher McVey, master lecturer in the writing program at Boston University. In the spring of 2024, Chris was matched with an AI Affiliate, Neeza Singh, a data science major minoring in anthropology who is currently a senior. I had a great conversation with Chris and Neeza at the end of the fall semester, and I'm excited to share that conversation on the podcast this week. We talked about Neeza’s role in Chris’ writing course, how her work as an AI Affiliate benefitted both Chris and his students, and the potential for this kind of student-as-partner program, focused on AI, to work in other disciplines.

​You can listen to my conversation with Christopher McVey and Neeza Singh here, or search for "Intentional Teaching" in your podcast app.

AI as an Instructional Assistant

This spring I'm facilitating a reading group on the book Teaching Effectively with ChatGPT by Dan Levy and Angela Pérez Albertos, which is now my number one book recommendation for faculty who want to explore the use of AI in their teaching. One reason I like the book is how practical it is, with lots of concrete examples of AI use by the authors and by other instructors. There are a lot of prompts and chatbot responses in this book aimed at very authentic tasks.

Another reason I like the book is that the authors focus the first half of the book not on student use of AI, but on instructor use of AI. They have ideas on using AI to help write lesson plans, design assignments, build rubrics, and more. That's where I like to start my conversations with faculty about AI, because it means we can get a better handle on the technology's affordances before we tackle the more challenging questions about student use of AI.

To that end, I shared a few takeaways from the reading group on my blog this week in a post titled "Lesson Planning, Iterative AI Prompting, and Rubber Ducks." I talked about different prompting strategies to use when working with AI as an instructional assistant (in lesson planning or assignment design), and I argued that a good back-and-forth with a chatbot can help you think more deeply about your own teaching practices and priorities. Using an AI chatbot to refine your own thinking is perhaps the opposite of outsourcing your work to AI, and I think it offers a more useful frame for how we use AI in our work.

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