"We don't completely know what works and what doesn't."

Part 2 of an interview with Autumm Caines, Tolu Noah, & Carla Vecchiola

In the last post, we were talking with Autumm Caines, Tolu Noah, and Carla Vecchiola about the No-Prep workshop and their concerns about Generative AI in the teaching and learning space.

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About the Interview series

As part of my work in this space, I seek to highlight the folks I’ve been in conversation with or learning from over the last few years as we navigate teaching and learning in the age of AI.

If you have experiences around AI and education, particularly in the higher education space, that you would like to share, consider being interviewed for this Substack. Whether it is a voice of concern, curiosity, or confusion, we need you all to be part of the conversation!

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Autumm Caines, Tolu Noah, & Carla Vecchiola

Eaton: Just recently, on the POD Network listserv, there was this very rich, deep ongoing discussion about how do we reconcile what it means to be in educational development now with and around AI? Are we towing the institutional lines and promoting these products? What’s our space, and how do we negotiate that?

Caines: I do a lot of faculty consultation work, and I’m hearing about that extra work that they’re doing, about their concerns for cheating–those kinds of things. That’s really where it’s impacting my work a lot.

Then, in my teaching, because I also teach for the University of Minnesota right now. I’m having those conversations with students, and coming back to the fact that we really don’t know what we don’t know. What is the impact on learning? We suspect there are ways of using this technology that support learning and there are ways of using this technology that undermine learning, but we’re still figuring it out. We don’t completely know what works and what doesn’t. I’m having those conversations with students and trying to get them to be self-reflective. I’m trying to get them to think, “Okay, I just used this tool. Did it support my learning or did it undermine my learning?” I think it’s another way that it’s impacting me quite a bit.

Eaton: I don’t want to put the H word (hopeful) out there too strongly because just looking around the world today, that feels challenging. But where are you curious about what generative AI might offer us?

Noah: One area I’m curious about is how GenAI can assist with accessibility. I’m aware of Goblin Tools’ Magic To-Do tool that can assist with breaking down tasks. There are also tools that assist with creating more accessible content, like generating alt text for images. I’m interested in seeing how Gen AI may continue to support accessibility efforts.

Caines: I love that one so much. And I feel I have an inclination. I’ll use the h word. I have a little bit of hope, maybe. That there is a good use for this technology. I suspect that it has to do more with some things that are maybe a little more mechanical, like generating alt text or fixing header levels in HTML or something like that.

I actually built a customized bot for the University of Michigan that is an HTML converter. You go to your Canvas page, and you take the HTML from that page. You give it to this bot, and it checks it for accessibility. Then also stylizes it in U of M colors. It spits out new HTML that you copy and then take that back to your Canvas course.

I feel like those more mechanical kinds of things are just a lot cleaner for me. I don’t have to worry about this thing becoming my friend or any kind of emotional investment in it. I feel a little more comfortable with that.

Vecchiola: The thing that is giving me joy and even maybe a little bit of hope in my own teaching builds off what Autumm was just talking about. I do use her HTML converter. My pages look so much prettier now.

But I think that the thing I’m going to talk about is also mechanical in teaching and getting and reading so many GenAI-created texts, it kind of pushed me over the edge of finally redesigning my class to be specifications-based grading. I’m teaching an urban studies class. My students are doing something every week, whether it’s a mental map, a public observation, or interviewing someone they know, and they have to provide evidence of that in a portfolio.

Each week, they do a declarations quiz to say, I did an analysis connecting my artifact to the reading. I have always taught in a way where the students do the work so that they can get the learning. But I’d been grading everything, and I was afraid of the mechanics of just the points. I just couldn’t figure out how the points all work together and how they would build over the semester. And using AI as a thinking partner just made it clear for me and made me able to sort of take the leap. And I’m loving the declarations quizzes. I’m loving the work that my students are doing. It just helped me get over the formatting, the formula, and the mechanics of specifications grading that had scared me off before.

Eaton: I really like that idea of helping to build that bridge to the thing that you’re wanting to try but find some hesitation. I’m curious to get all of your takes on this. I’ve seen more faculty excited about and leaning into creating simulations, whether that’s debates or interview-type structures. Thoughts?

Caines: I can jump in a little bit. I like customizing the bots to make them behave in specific ways. I think it’s interesting. I like technology; I started off in this field as an instructional technologist and then found my way to instructional design and faculty development. Still, I like technology and making it do what I want it to do. I can go down rabbit holes with technology and spend too long tinkering.

But I was co-teaching a course with Pamela Todoroff, one of our professors here at University of Michigan, Dearborn, and it was a first-year seminar course. We had an interview assignment that was basically centered on asking students what do you want to do? What’s your major? Go find somebody who does that work and interview them.

That’s a fun assignment. Lots of people do it. There’s only one problem. You have to find a professional who will make time in their schedule to talk to you. That can be difficult. We got to the point where they were supposed to do the synthesis. They were also supposed to be doing research at the same time while they’re doing this, and then synthesize the interview and what they found in their research. When we got to that class, half of the students hadn’t been able to schedule their interview yet. We had a problem there, and we saw that that was coming up.

I customized a bot that would pretend to be whatever profession. That’s the first thing it asks you is, what do you want me to be? You can say, I want to be an astronaut or whatever, right? It will pretend to be that type of professional and have that interview with you.

I like it as a stopgap, and we didn’t let them off the hook. It wasn’t like, okay, you’ve had your interview with your bot, you don’t have to go find a human anymore. We still wanted them to go and find that human, but at least it got us over that hump.

Recently, I was in a virtual gathering sharing this, and somebody was very interested in this. She was really interested because she worked with high school students who lived in very rural and remote areas. She would love for them to be able to interview a professional in a field that they’re interested in. That sounded fascinating for her.

Noah: I like what Autumm just mentioned about having students use it for practice interviews and things like that. I think my only hesitation–and I’ve seen this more in K-12 spaces than in higher ed– is when it’s used “to talk” to people who lived in the past–historical figures.

I read a piece by John Warner about the dangers of that kind of fake conversation with people of the past. I also think it’s important to encourage students to leverage other sources of information about the past. Let’s look at primary sources if we really want to know what people thought instead of asking AI to make it up. My main hesitation is when Gen AI is used to mimic real people.

Eaton: Something that’s in my head lately, with a more recent version of ChatGPT, is that it now allows for more than one person to be in a chat. There’s something interesting about that if we think about creating simulations where you have the AI playing as essentially a dungeon master and playing out scenarios. For instance, if you’re in a business course or a law course where everybody coming into that chat has a different role. There’s something that’s a new kind of social learning, or not new new but new with AI that doesn’t have people in their own chat logs, but together working through a problem with the AI guiding what’s going on.

Noah: Yeah, I like that.

Vecchiola: That does sound exciting for collaborative learning. I want my students to interact with each other even in an online asynchronous class. And so that could just be another space for collaborative learning.

Eaton: I want to go back to Tolu for a moment. How might folks use your book to construct some ways to explore and navigate the different challenges and possible opportunities that AI can present for our teaching? Are there other things that boil to the top, where it could be as direct as go to Chapter X for this or Chapter Y grapples with this technique?

Noah: My book is called Designing and Facilitating Workshops with Intentionality, and it offers principles and practices to be mindful of when we’re designing professional learning experiences. The chapters about fostering connection amongst participants, promoting active learning, and encouraging reflection would definitely be great for anyone who’s trying to design more engaging workshops or other forms of professional learning about GenAI or other topics.

My book isn’t specifically about GenAI. I don’t want anyone to think that’s the case. But regardless of what the topic is, there are helpful ideas in there for how you can create an engaging professional learning experience around it.

One side note. A few months after my book came out, two nursing professors who had read it, emailed me, and they told me that they were using it to design a conference presentation for other nurse educators about how to design interactive GenAI workshops. I know that’s kind of meta, but I found it interesting. It’s actually pretty cool. Because although the book isn’t about GenAI, they were able to directly apply the principles to their GenAI conference session in order to help equip other nurse educators to design more engaging programming.

Eaton: That’s part of what you’re offering in that book is “here’s another set of practices that can help you step into these spaces” so that again they’re not like being talked at for whatever ungodly amount of time without really getting these other things that we know are central to learning. Thank you.

The almost-last question: What are you trying or doing next to support faculty regarding generative AI? The answer could be nothing to do with generative AI, because that’s what faculty need right now, and that is an absolutely true, valid statement to be included here.

Vecchiola: Our program that we’re running at U of M Dearbornne is actually called What’s Next? And I have to credit Autumm for that title. She did a lot of the design work. The idea of the program is it’s pulling back to those seven-week programs we were running with our cohorts. We’ve run four different cohorts, and we feel like now is a good time to invite alumni to come back to have deeper conversations about what have they heard from their colleagues. How have they implemented some of the things that they learned in the cohort? What should we be thinking about and talking about next?

We’re inviting back alumni and also others who are just experts or critical folks about GenAI who want to come to have this sort of more engaged conversation.

Noah: I’m trying to find more ways to create space for conversation about GenAI. I’m using Carter Molton’s Analog Inspiration Card Deck. It’s so good! He also just came out with an expansion pack. I used the original deck already for a virtual workshop last semester, and I’ll be doing it again this semester with the expansion pack. I love that the deck encourages educators to think about how their values might shape their approaches to GenAI.

Vecchiola: I also want to say to Tolu that we are still using your format. We’re still running No-Prep sessions. I described our cohort program that we’re doing, but we’re running No-Preps this semester as well. We are even going to run one inspired by Autumm. It’s sort of against AI. It’s on a list of resources of people who are working to avoid AI.

This is such a great framework for conversation, and we want to invite people into conversations. The ones who are not excited about exploring it have been doing things in their classrooms, like slow teaching to avoid GenAI. We want to bring them together and see what kind of robust conversation will come out of it. Thank you for the framework that we just can’t let go of.

Noah: That is so awesome! I love what you said about creating space for people who are more critical to come into the conversation. I feel like that’s needed now more than ever before. It reminds me of Kevin Ganon’s piece for the Chronicle about how those voices need to be part of the conversation.

Eaton: Final question: Is there anything I didn’t ask about, but you want to include, given the conversation that we’ve had? Something that’s kind of lingering that you’re like, I’d be remiss if I didn’t also mention this right now.

Caines: I think we just kind of led right into it. It does feel like we are hungry for more critical conversation around AI right? I just feel like more and more people are just sick of the come and I’ll show you how to prompt engineer kind of situation. It’s becoming more and more obvious that there are really big implications all around for how this technology is going to impact learning and higher education as a field. I think people are really ripe to have those conversations and to push back a little bit more and not just jump on the adopter bandwagon. I’m feeling it anyway.

Noah: I’m excited that those conversations are happening. We need more nuance in all of this for sure.

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Autumm Caines is a liminal space. Part artist/poet, part technologist/administrator, and always aspiring educator, Autumm has worked in higher education for over fifteen years, bouncing between the teaching center, the information technology department, and adjunct teaching positions at a few different institutions. Currently, Autumm works full-time as the Lead Instructional Designer at the University of Michigan – Dearborn.

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Tolulope (Tolu) Noah, Ed.D. is a lifelong educator with a deep passion for teaching, technology, and facilitation. She currently works as an educational developer at California State University, Long Beach, where she designs and facilitates professional learning programs for instructors about teaching and technology. Previously, Tolu was a senior professional learning specialist at Apple, an associate professor in the teacher education program at Azusa Pacific University, and a K-12 teacher. She is also the author of the book, Designing and Facilitating Workshops with Intentionality: A Guide to Crafting Engaging Professional Learning Experiences in Higher Education.

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Carla Vecchiola is Director of the Hub for Teaching and Learning Resources and a History instructor at the University of Michigan–Dearborn. She works to cultivate a shared campus teaching culture grounded in student-centered practice. She brings a deep interest in the cultural politics of cities to both her teaching and her public work as co-curator of Exhibit 3000, the world’s first electronic dance music museum.

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The Update Space

Upcoming Sightings & Shenanigans

• EDUCAUSE Online Program: Teaching with AI. Virtual. Facilitating sessions: ongoing

Recent Recordings, Resources, & Writings:

• Damm, C., & Eaton, L. (2026, March). From prompt to practice: A framework for transparent GenAI use in higher education. EDUCAUSE Review.

• Eaton, L., Nemeroff, A., & Sun, X. (2026). AI-assisted course design and development. In K. S. Ives, M. Cini, & R. Schroeder (Eds.), AI applications in online higher education administration: Strategies for maximizing returns and improving outcomes. Routledge.

• Margin of Thought with Priten: Season 1, Episode 5: How Can We Center Pedagogy During the AI Tech Wave? (February 2026)

• Online Learning in the Second Half with John Nash and Jason Johnston: EP 39 - The Higher Ed AI Solution: Good Pedagogy (January 2026)

• The Peer Review Podcast with Sarah Bunin Benor and Mira Sucharov: Authentic Assessment: Co-Creating AI Policies with Students (December 2025)

• David Bachman interviewed me on his Substack, Entropy Bonus (November 2025)

• The AI Diatribe Podcast with Jason Low (November): Episode 17: Can Universities Keep Pace With AI?

• The Opposite of Cheating Podcast with Dr. Tricia Bertram Gallant (October 2025): Season 2, Episode 31.

• The Learning Stack Podcast with Thomas Thompson (August 2025). “(i)nnovations, AI, Pirates, and Access”.

• Intentional Teaching Podcast with Derek Bruff (August 2025). Episode 73: Study Hall with Lance Eaton, Michelle D. Miller, and David Nelson.

• Dissertation: Elbow Patches To Eye Patches: A Phenomenographic Study Of Scholarly Practices, Research Literature Access, And Academic Piracy

• AI Syllabi Policy Repository: 200+ policies (always looking for more- submit your AI syllabus policy here)

Finally, if you are doing interesting things with AI in the teaching and learning space, particularly for higher education, consider being interviewed for this Substack or even contributing. Complete this form, and I’ll get back to you soon!

We periodically host small-group workshops and leadership sessions for higher ed teams. You can learn more about our current offerings here.

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AI+Edu=Simplified by Lance Eaton is licensed under Attribution-ShareAlike 4.0 International