Students and AI Literacy with Annette Vee

Annette Vee is an associate professor of English at the University of Pittsburgh and co-author (with Marc Watkins and your podcast host) of the forthcoming book The Norton Guide to AI-Aware Teaching. Annette and I met through this writing project, and I invited her on the podcast to get to know her better. 

Annette and I cover a lot of ground in our conversation: how computational literacy is changing in light of AI, whether there is such a thing as “AI literacy,” what she has learned from talking to hundreds of students about AI, and why AI needs to be on the college curriculum. 

Episode Resources

Annette Vee’s faculty website

Annette Vee on LinkedIn

Annette Vee’s Computation & Writing newsletter

AI & How We Teach, a Norton newsletter for AI-aware teachers

The Norton Guide to AI-Aware Teaching, forthcoming by Annette Vee, Marc Watkins, and Derek Bruff

“How Are Students Using AI? A Research Toolkit for Faculty” webinar recording

“What Past Education Technology Failures Can Teach Us about the Future of AI in Schools” by Justin Reich

Transcript

Derek Bruff: 0:05

Welcome to Intentional Teaching, a podcast aimed at educators to help them develop foundational teaching skills and explore new ideas in teaching. I'm your host, Derek Bruff. I hope this podcast helps you be more intentional in how you teach and in how you develop as a teacher over time.

Derek Bruff: 0:21

Happy New Year! In this first episode of 2026, I wanted to share a conversation I had recently with Annette Vee, Associate Professor of English at the University of Pittsburgh. Annette and I are co-authors, along with Marc Watkins, on the Norton Guide to AI Aware Teaching, scheduled to release later this year. Annette and I met through this writing project, and I invited her on the podcast to get to know her better. I had already talked with Marc on the podcast back in June of 2024, and I wanted to feature Annette's work solo in an episode before having the three of us on to talk about the book closer to its release date.

Derek Bruff: 0:59

Annette was directing the composition program at the University of Pittsburgh in the fall of 2022 when ChatGPT was launched. However, she had already been thinking a lot about artificial intelligence before then. Annette has an interesting background, having worked in the computer game industry and in a neuroscience lab. Her research is at the intersection of computation and writing, and her first book was titled Coding Literacy: How Computer Programming is Changing Writing. All that meant that she was already experimenting with generative AI before most of us learned about it through ChatGPT.

Derek Bruff: 1:32

Annette and I cover a lot of ground in our conversation: how computational literacy is changing in light of AI and its ability to generate code, whether there is such a thing as AI literacy, what she has learned from talking to hundreds of students about AI, and why AI needs to be on the college curriculum.

Derek Bruff: 1:51

Before we get to the interview, here's my New Year's pitch for you, dear listener. If you find this podcast useful, would you consider becoming a subscriber? For just $3 US per month, you'll help defray production and hosting costs and get access to the occasional short bonus episode. See the show notes for a link to subscribe. You might also have a button in your podcast app for doing that. And if subscribing isn't for you, no worries, but it would be great if you could follow the podcast in whatever podcast app you use. That helps the show appear higher in search results, which helps more people find the podcast.

Derek Bruff: 2:24

Now my conversation with Annette Vee. Hi Annette, welcome to the podcast. I'm very glad to have you here and to talk with you about your uh your your your corner of the AI world right now. Thanks for being here.

Annette Vee: 2:38

Thanks, Derek. I'm excited to be here.

Derek Bruff: 2:41

And uh we've been talking a lot lately uh as we work on this book project together.

Annette Vee: 2:46

But um Yes, we have. Which has been great.

Derek Bruff: 2:50

Yeah, yeah. I'm excited and how it's coming along, but I'm also excited to get to know you a little bit better. So let me start off with my usual opening question. Can you tell us about a time when you realized you wanted to be an educator?

Annette Vee: 3:03

You know, I thought about this question, and um I realized I just kind of fell into it. There wasn't like a revelatory moment. I admire so many of your guests for like their real revelatory moments, and it's beautiful. But I think so. My my parents were both teachers. My mom was a special ed teacher, and my dad uh taught in community college. And so I spent time in schools. Um, and so I said, I'm not going to be a teacher. And then I don't know, I guess at the end of college it was like, well, here I am. And you know, then I did, I went through teacher training to do high school. Um, and that was actually a little rocky. And then I went to grad school, and then I don't know. And then I think I liked teaching in college. I I do like working with students. I mean, now I really like teaching. I think this is the right job, but I think that it wasn't like a um here's my moment uh space for me at any point.

Derek Bruff: 4:00

So what um what then motivated the decision to go to grad school?

Annette Vee: 4:06

Um, I had a crappy job and I was, I mean, it was all right. I was I was working uh in the computer game industry, which actually is like part of my backstory, um which is you know not in itself bad, but I was the secretary. And um, you know, and like I was kind of like, this is I'm not gonna be here forever. And then I worked in a neuroscience lab at the University of Wisconsin, Madison, and that was, you know, that was cool. I did editing and uh sleep depriving pigeons as you do. And um then I just I started taking classes because I missed school and I was in Madison and you know, the University of Wisconsin Madison is there. And I went in for English because that's what my undergrad degree was for, and then and then I wandered into composition and rhetoric um after uh getting my master's in literature. And then I felt like I then I felt like I was, you know, kind of in the right space. But um so that's why I went to graduate school. It feels like I should have much more of like a faded, this is where I, you know, should have been, but it just like that's how it, that's actually how it works.

Derek Bruff: 5:18

Just a bit of wandering for a while.

Annette Vee: 5:20

If there was some wandering, there was some wandering, which, you know, if anybody out there is still wandering. I mean, I'm still wandering.

Derek Bruff: 5:29

So uh your first book, Coding Literacy, is about computer programming through this lens of literacy studies. And so uh I think you made the argument that I heard a lot in the last 10 years, which is we need to be teaching students some type of computational literacy. And that means different things to different people. Um but given the role of computation and coding and computer software in our lives, that we need to be more um literate, right? We need to we need to understand how these things work. And so um I'm curious to get your take on that argument now about computational literacy. Uh given the the notion of vibe coding, that these AI tools can write code pretty well in many instances. Um and in fact, the I as I understand it, the job market for computer science graduates is is tanking right now because these entry-level positions that needed a lot of coding skills are being replaced by AI. And so, how do you think about computational literacy here at the tail end of 2025, given where we are with AI?

Annette Vee: 6:40

It's a good question. And I will say I've thought a lot about it. I guess I'm I'm of multiple minds of it. So I don't think I was wrong in saying that I think we should be paying attention to the ways that um computer programming is really infrastructural, uh, and that the ability to manipulate computers is like a literacy. I mean, one of the things, you know, when you get a PhD um thinking about literacy, like I take literacy really seriously as a term and concept. So um, so I kind of that book was like a lot of it was like working through like what is literacy, right? And is this actually a literacy? You know, is it not, you know, some sort of literacy is used like as a throwaway term for a lot of like any sort of skill, right? And and so that book was actually me working through is this or is this not a literacy? And I I did come up with I I think it, I think it is, um, for all the reasons I said in the book, you know, about it being infrastructural and um a form of expression and you know that has power and things like that. And um I think those things are still true.

Annette Vee: 7:47

Um and I think that um how it plays out in terms of does AI democratize um coding literacy uh in a way that um has been promised really since the 1960s, with you know, the advent of um easier programming languages, of you know, Fortran um to some degree, COBOL to a greater degree, um BASIC for sure. I've done a lot of work on the history of BASIC. Um, and that was an express uh um objective of BASIC was to democratize programming. Um, when when um John Kemeny and Thomas Kurtz uh worked on that at Dartmouth in the 1960s. And so um, and there has been, I mean, even since the 1960s, there was a there was a conference um called Computers in the World of the Future, um, and there's a book that has the proceeds of it, and um, and there's this like fascinating dialogue between you know these luminaries of um uh computation at the time saying, you know, in 10 years there will be no need for programmers because the languages and the technology will be so good that we will just be able to talk to them like English. And so that has been promised um since the 1960s, and we've consistently kind of made progress in that, you know, area that like computer programming languages do sound a little bit more like English. There's, you know, error handling, there's like all sorts of things that are much easier than used to be, right? But it has gotten more complex. You know, we move further up the stack of abstraction, and um, so it just looks different.

Annette Vee: 9:28

Um, and now I think, you know, we we really are closer to being able to use natural, um, and let me mark this, English, not necessarily natural language for programming. Um I mean, I haven't tried vibe coding in other languages. I'd be curious, you know, how well that works. But um, but I think I think that it doesn't do away with the kind of fundamental need for understanding how steps work, how a computer works, how um it matters to us in communication. Um and so, you know, I think if you know some of those things, you're certainly better equipped to um understand what questions can you ask that um some sort of app or program can answer. Um so I I do think that that's still fundamentally important. Um but I think that the paths um for how you get there and who can get there might be shifting radically.

Derek Bruff: 10:27

Right. Where eight years ago we might have thought about, say, some of these very visual programming languages where you can get second and third graders putting blocks together and making algorithms, right? Yeah. So that's a really easy entryway to a kind of computational thinking. Um now we have this other entryway that works very differently than that.

Annette Vee: 10:50

Absolutely. And you know, I mean, Seymour Pappert was working on um Logo beginning in the 1960s too, and that was, you know, teaching, yep, I grew up with Logo and BASIC. And you know, I mean, there's like a whole and you know, if you grew up in the 1980s, that was also part of like, you know, like global kind of politics, right? As we were being trained to beat the Russians.

Derek Bruff: 11:12

Right, yeah.

Annette Vee: 11:13

There's like there's some sinister stuff back there.

Derek Bruff: 11:15

Um, I was not thinking about that when I was moving my little turtle around the screen in Logo.

Annette Vee: 11:20

No, of course not, but you were you were getting ready to beat the Russians when you were doing that. That was the objective.

Derek Bruff: 11:26

Yeah, yeah.

Annette Vee: 11:27

That's where the funding came from.

Derek Bruff: 11:30

Right. Yeah. And by the time I actually went to college and majored in computer science, we we we in the 90s we had other issues.

Annette Vee: 11:38

That's right. Exactly.

Derek Bruff: 11:39

Yeah. So um, okay, so maybe the kind of methods or the applications or the kind of contexts for computational literacy have changed a lot since generative AI. Um, but the kind of need, particularly kind of as you say, I don't know what exactly what you mean by infrastructure, but the way that it helps build our world. Um, I think it's important to understand that. Yeah.

Annette Vee: 12:00

Yeah.

Derek Bruff: 12:00

Yeah. Okay. Well, um what about the term AI literacy? How do you think of that term? And who who should be teaching AI literacy?

Annette Vee: 12:12

Well, I mean, I'm a pragmatist. So I guess I use the term because that's what other people are using. But every time I use it, it hurts my soul a little bit. Uh because I'm a literacy person, you know? And like I just spent a whole freaking book like breaking down the concept of literacy and, you know, what is and isn't a literacy. And I think that AI literacy like isn't really illiteracy, like from that perspective. Um it's just it, it's like um, you know, so so some of the critique um that has been said by you know people far smarter than me about um computational literacy or computer literacy, um, like say in the 1980s and 90s was like, you know, literacy was boiled down to such a um kind of a small thing. It was like, can you insert a disk? Can you, you know, control alt delete? Like, right? Like I, you know, some of these things are not timeless. Um, they're, you know, little specific things that have to do with like, you know, Windows 3.1. Like this is not important knowledge anymore.

Annette Vee: 13:21

So um anyway, I I I don't think that AI literacy, um, I hope you can hear the scare quotes there, um, is like that exactly. But um I do think that I do think that the way that it's generally framed is a lot more about like how do you do prompt engineering? How do you um you know understand how they work? You know, like great, like that's good. Um, but prompt engineering has, you know, changed in the few years that it has even been a thing. Like it's you know, I mean, now I feel like you kind of need scare quotes around that, right? Um because the AI systems are shifting so much to be able to um kind of process what we give them um more efficiently and you know, understand, I use that word in scare quotes again.

Annette Vee: 14:08

But um I I think it's important for us to have some sort of knowledge about AI systems. So if literacy is the way to get it, you know, that's great, that's fine. Um I think that it's important to know how they work, how um they're being used in different disciplines, how it's possible to use them in different disciplines, um, how to, you know, manipulate them, how to be in control of them so that they're not, you know, kind of manipulating us. I, you know, I feel a little defensive about that. Um uh but also, you know, how do you help people take advantage of it?

Annette Vee: 14:40

And and always when I'm thinking about education too, I think about it from an equity standpoint. Um, and you know, I mean, I was interested in computers. Um, I went through BASIC and Logo, I had a Commodore 64, I was like into that stuff until middle school when I realized like only boys did that. And so I stopped doing that. And, you know, I mean, I can look back at that now and say, like, I don't know, could life have been different? Um but that was the 1980s um and early 90s, and so and so this is where I am, and I don't regret that, but it's it's like I I think about it now, and I think about you know how um women are generally later adopters for technologies and um you know these things, despite all of the rhetoric about democratizing technologies, blah, blah, blah. Like it never actually happens that way. So um, so I feel invested in that. Um, so you asked, you know, who should be teaching it, whatever this is. Um, I don't have a good definition of it. I mean, I think it's gonna it's just gonna shift because it's like, how do you manipulate these systems, right?

Derek Bruff: 15:44

Um I've been using the term AI know-how.

Annette Vee: 15:47

Oh, I like that. I like the much.

Derek Bruff: 15:50

Some people have very precise definitions of literacy, and I don't know what they are, so I don't want to step into that world. But I feel like know-how is is yeah, the it's how do you manipulate these systems in useful ways? How do you evaluate the results critically, right? There's a bit of that in there.

Annette Vee: 16:05

Yeah, I like that. I maybe I'll start using your term, Derek, um, because it it is, it feels more contingent, you know, and more um pragmatic.

Derek Bruff: 16:13

Um, right. And it may be different. It's that's know-how changes over time. Yeah.

Annette Vee: 16:20

That's right. And I think that's all that's all we can do at this point with AI because it it is changing so fast. Um but uh but I do think, yeah, we should we should be working on it in education and teaching folks. Um and who should be doing that? I mean, I think I think it can't be quite as top-down as um a lot of other things, because you know, literally, there's not a lot of expertise out there. Um, so you know, we can do some training. I mean, I, you know, I'm always happy to offer whatever I know, but it's it's fairly limited because um that's just how it is. Um, and so I I think that um this is uh this is actually um when I think about the positive aspects of AI, it's a space for collaborative learning. Um, it's a space for us to learn together with students, it's a space for us to learn from each other and kind of trade expertise in a way that um we often um we often can't, you know, when you're like deeply embedded in a field and you have a PhD and you've spent 15 years thinking about something, you know, it's just like I learned things from my undergrads, but like it's just different, you know, once you've like read and and spent a lot of time in a field. But AI really, you know, it does kind of democratize the um educational space, the learning space. Let me correct that, the learning space. Um, because I think we can learn together. So um so that's what I think um the teaching and learning of AI kind of has to be, is much more um in-person, rhizomatic, um, you know, collaborative, that kind of thing.

Derek Bruff: 17:55

So um uh an idea I floated here on the podcast before, and there was a piece recently by Justin Reich from MIT, who I think made this case quite eloquently in the Conversation. Um I'll link to that in the show notes. But um uh Justin basically argued that uh when the internet arrived and we tried to teach students how to critically evaluate information they encountered on the internet, we spent about 10 years doing it really badly. Um and and he adds, and I observed that, right? Being, you know, teaching in the days of Wikipedia. Um but you know, he says we we didn't have the research basis. We we actually didn't know how to teach inform critical information literacy well um until we had enough of a kind of research basis to to know what we were doing. Um and but I've been thinking about this for a while. I feel like higher ed did not do a great job of helping students with that type of information literacy. Like, are we gonna do any better this time around? Do we need to approach this differently?

Annette Vee: 18:59

Do we does it need to have more top-down or if it's gonna be different this time around, I think we need to have more humility about what we don't know. And that means being um ignorant and showing our ignorance in front of students um and saying, you know, we are in this together. This is actually a truly difficult space. Um, and I think, you know, I've I've read some of your work on this too, which I really appreciate. That's like, you know, how do you find genuine problems um and work them out together? Like that's it's different from you know, asking um questions that you already know the answer to. Um and it's actually a a real space of learning. Um, but most of our systems are not set up well to handle that.

Derek Bruff: 19:49

Yes. Yes. I think there's also um a disciplinary uh context here that's important in that the ways that AI is playing out in different Different domains of knowledge can look very different. It made sense to go to our librarians to learn about critical information literacy 15 years ago because there was a set of tools that were broadly applicable. I don't know that that AI Like at UVA, we have our faculty AI fellows, AI guides, and we were intentional about trying to recruit them from across the departments on campus because the kind of the movement within these fields around AI is so different. Um I think that's part of it, is that there's not a kind of single solution. Not that there was really uh 15 years ago, but there's definitely not a single solution now.

Annette Vee: 20:37

I think that's true. Yeah, and AI is so much more shape-shifting. And it um I mean, it's it's more controversial too, for sure, for you know, a hundred different reasons. Um, but I, you know, I think like so there's disciplinary expertise involved here, but there's also um outside of um universities expertise. And that I think, you know, it's actually crucial for us to be talking to people in professions as it's being integrated. You know, Tim Laquintano and I have been doing this interview study where we're talking to um uh really early adopters of AI in professions, and um, and there's been some other work that's come out um since then too. People are absolutely adopting it and they're creating all sorts of efficiencies in their worlds. Um, some of it goes under the radar because they don't want their bosses to know, you know, and that's actually really interesting work, right? And is that good or bad? I mean, I don't know. I'm not like providing some judgment here, but it's certainly um real applications of AI. Um, so uh, you know, and for efficiency gains, for thinking, for, you know, all sorts of complicated um applications. So um I think that we need to take it much more seriously than the kind of, you know, is this helping um kind of question that shows up um uh more obviously.

Derek Bruff: 22:08

Yeah. Well, let me use that to pivot to the other big topic I wanted to ask you about, um, which is um not not looking to industry or professions to see what is happening with AI, but looking towards our students. Um part of our part of our construct of AI aware teaching in the book involves knowing and better understanding how your students think about AI, how they use AI, um, what are their perspectives, what are their experiences. Um can you tell us about some of the work you've done at Pitt to learn more about your students and how they come to AI?

Annette Vee: 22:43

Mm-hmm. Yeah, I mean, I first of all, I just want to underscore like we absolutely do need to be thinking about students and talking to students. Um so um, yeah, so I started surveying students in December of 2022 because I was um directing the composition program and I thought, oh, this is vague. Um and so, you know, I just reached out to instructors um who I knew and they handed out a survey and um and then I started doing it regularly at the end of every term um for the last few years. And um that's been um really helpful data. Um, I mean, I will say I did it without IRB initially because there wasn't enough time because it was for program improvement. I mean, you know, that's like one of the clear exceptions, right? And so I retroactively asked them um if I could use that data. Um so that was good.

Annette Vee: 23:35

But um so yeah, I mean, so we've seen changes over time um from students' knowledge about um AI uh from how they refer to it to their feelings about it. Um they have kind of much more complex feelings about it than they did um in spring of 2023, um, which was kind of, I would say, like peak kind of interest. Um so yeah, I think that's actually really important. Um and um and then this spring, um, this this past spring in 2025, um I ran a focus group study um where I recruited um I think 11 other faculty at the University of Pittsburgh Main campus in Oakland, um, and then our regional campuses. Um and we all talked to students. We ended up talking to 95 students in focus groups, um, and we learned so much from it. Um, and it was, you know, um, I mean, my department chair participated, one of our student advisors, the director of the writing center at one of our regionals, and you know, I mean, that we had like a lot of um teachers involved in this, and we learned a lot. Um, and um, and so, you know, we have a little report on that, and um, we've got a manuscript under review now.

Annette Vee: 24:54

But but the most important thing was that, you know, we learned from students about their mixed feelings, about their uses of it, um, about you know, their experiences of faculty using it potentially. Um, and you know, some of the things we found out that I I think maybe I'd known, but you know, really underscored like their feelings of guilt when using it, um, their um kind of resentment at some of their peers using it, you know, that they feel forced into using it sometimes, um, sometimes their excitement about it um and their innovation with it, um, all the different ways that they were using it, and you know, um their self-justification for it, you know, that they could judge their peers on it, but they could um, you know, I mean, that it was okay that they did it because their assignment was due the next day, you know. There was a little bit of that. Um, and kind of you could tell sometimes as they were talking, you know, that they realized maybe this wasn't a great justification. And, you know, we had students too who are like ideologically opposed to AI and would say that at the beginning of the interview. And then by the end, you know, you realize like they used it to pass their math class, you know? And so like the cognitive dissonance that's happening there, um, I think is really difficult for students.

Annette Vee: 26:13

Um, and they were really eager for those conversations. Like that was the other thing we really learned is that students were really glad to be talking with us and to working, be working through these ideas. Um, they talked about it with each other, but they didn't have a chance to talk with faculty in any sort of structured way, you know. Um, and so what basically what I've been doing since then um is uh trying to encourage, you know, every other university, um, college, high school, whatever, to talk to their own students about AI. Um, and so, you know, with Norton, I put on a um a big webinar and you know, shared a whole bunch of resources. And, you know, I'll make those things more public um at some point when I get around to it to writing up, which will probably be in January. But um I think um, yeah, I mean, I just think, you know, also the research often comes from our ones, right? And so I think that we actually really need to know a lot about how um returning students, adult students, veteran students, students at HBCUs, um students in rural institutions, um, how are they taking up AI and what does it mean for them? Um, because I think that we need to be responsive to that in um in our teaching.

Derek Bruff: 27:26

So I'm hearing one that if I'm standing in front of a class full of students and I'm wondering what they're thinking about AI, it's gonna be a lot of different things, right? It's hard to say there are big trends, right? It's complicated. Um, and different students will come at it from very different points of view and maybe even have some internally inconsistent views about AI. Um, but also that they're eager to have good conversations about it and to work through some of these issues um with faculty. Um yeah. Are you um I know you you've been on sabbatical this fall, so you're not teaching, but are there are there ways that your your research on student perspectives on AI has started to inform your teaching practice?

Annette Vee: 28:08

Yeah, I mean, I I I've been thinking about it, you know, as as you said, I haven't been teaching since um since I ran that study, but um, but I am thinking a lot more about uh from a curricular level, like how we can build in um, you know, spaces to talk to students and have them work through um, you know, questions of dealing with AI and discernment about AI, um, you know, when to use it, when not to, when how they should use it, how they shouldn't. Like that's you know, that's really complicated. And I do think there's a lot of policies that say to students, you know, don't use it when you shortcut learning and only use it, you know, when it's like aiding your learning and thinking. And I think that's an impossible question for students to answer. That's a really hard question. And I use AI a lot, and I can't answer that question sometimes, you know? Like if I'm using it to think through a complicated idea, is is that good for me? I don't know. I mean, it's it's almost certainly more efficient.

Derek Bruff: 29:06

So um and and you may have, I mean, you and I have more experience with that type of discernment.

Annette Vee: 29:13

Oh, yeah.

Derek Bruff: 29:14

Right? When do I go to a colleague? When do I go to the books and research something? Right. How how do I how do I kind of prompt my own thinking more deeply?

Annette Vee: 29:22

That's right. I mean, we have a whole career's worth of discernment. Yeah.

Derek Bruff: 29:25

And our students don't have that.

Annette Vee: 29:26

No, they don't. And you know, it's not their fault. It's just like that's asking a lot of them. Um so I think that we really do need to be working through it together. Um, anyway, so I I think um, you know, from a curricular standpoint, I'm thinking about, you know, I'm doing faculty training internally. I'm I've been um now uh consulting with our CIO and thinking about how we roll out the technologies and work with uh faculty for that. And um, so I I'm thinking about how we at scale help students work through these questions within disciplines. Um, you know, so not just like a standalone here's, you know, some videos on AI literacy, which, you know, I mean is probably good to some extent, um, but isn't going to be how you really have students wrestle with these questions deeply. So um anyway, so that's part of how I'm thinking about it teaching, you know, in the public work that I do, um, you know, writing about it.

Annette Vee: 30:23

And uh, you know, the other thing is I'm I'm always like I'm especially in this moment where I think we really need to be working together, like I'm always happy to give everything away. Um so you know, I share everything and um do open educational resources as much as possible. Um, you know, if people find it useful, um, I feel like I, you know, I want to share.

Annette Vee: 30:43

Um, but in my own teaching, um, I guess um I you know you know I tend to teach more techie classes just because that's you know that's been my expertise. Um and so at PIT, I helped to design um about five years ago a major that we have called the Digital Narrative and Interactive Design Major. It's collaborative between the English department and the School of Computing and Information. Um, and that's kind of um where my teaching has been even before that major, but now it fits you know quite squarely in that major. Um, and so, you know, I'm just co-taught a course um with a colleague, Matt Burton, from School of Computing and Information, called Writing Machines. And it was all about like AI and how writing is automated, and we took kind of a long history, and it's it's related to the um to the book that I'm writing. And um, and that kind of stuff I think is, you know, I mean, like we had them explore cool things with AI and reflect on it and do hands-on stuff.

Annette Vee: 31:42

And so that I think is, you know, one way that I am trying to open up those spaces for students to wrestle with AI. Um, but I think there's also really good spaces for them to um reject AI and reject technology kind of more um explicitly. Um and that's partly, you know, all the things that we know now about um young people in social media and you know, our inability to kind of disconnect. I mean, that's me too, but I didn't grow up with it, and I think it's just much harder for them. So, you know, I mean, I mean, now I'm also talking to colleagues about like how do we make spaces on campus that are like cozy spaces that you like check your phone at the door and you just read a book, you know? Like I think that we need that too. Um, and so I guess that kind of exemplifies the kind of AI awareness, right? Is like, I think that both AI resistance and AI engagement are necessary, um, but they need to be really intentional given the landscape that we're in. Um, so that's that's how my thinking about AI and and talking to students is is shaping my teaching.

Derek Bruff: 32:48

Yeah. Do you have any advice? I know you're you're in the process of sharing some of the materials from your focus groups and your surveys, um, but do you have advice for faculty or administrators or staff members at other institutions who would like to talk to their students more about this?

Annette Vee: 33:01

Mm-hmm. Yeah. Um well, first of all, I mean, I'm happy to share the resources directly if people reach out, um, if they listen to this podcast and it's not out yet. Um, but I think that um I think ideally you find some spaces that aren't just within the class that you're teaching in that kind of weighted, graded space. Um so, you know, is there a way to, you know, get your department to fund pizza and have students come and talk about it? Is there a way to, you know, I actually one of my favorite things is when I come in as an outside speaker, and um this has happened a couple of times, um, when I and starting at Syracuse with um Patrick Berry, I think helped come up with this idea, but um where you know, I I work with students and faculty together about like thinking about how AI works. And I mean it's a great space of co-learning when people are into it. And you know, the couple times I've done it, it's been great.

Derek Bruff: 33:59

Um so um that's you're there as kind of a third party, right? These students and faculty may or may not have existing working relationships, I imagine, when you're coming in this way. But but you're there as a kind of mediator and a convener and a facilitator so that they can have good conversations about it.

Annette Vee: 34:17

That's right. Yeah. And you know, I do open surveys there and you know, project the answers. It's anonymous. And so faculty see what the students in the room that are their students say about AI, and and students can hear from faculty in that way too. I think that's actually really important, you know. Um, it's almost like a like a kind of space of therapy or something. You know, it's like here's two parties that want to fix things and they're sometimes not connecting. Um, and um you might need somebody to come in from the outside to kind of help that connection. But I think that can happen internally too. It just, you know, it takes some effort. Um and um and I think it can happen in classes too, but I think it has to happen from a space of um from a non-judgmental space, you know, often perhaps an anonymous space to the degree that it can be within a class. Um, but I I think that we really do need to make spaces for um for students to talk and for students to, you know, possibly even student facilitated conversations. Like I'm, you know, starting to work now with like the undergrads who are in leadership roles, um, you know, to facilitate some of those conversations um so that they can kind of learn from each other.

Derek Bruff: 35:31

Yeah. Okay, so lots of good ideas there. Um uh yeah, I I'm intrigued by different institutions have have kind of empowered students in different ways to try to help with the space. Um and I don't know that I've seen one of that model where you would have essentially student facilitators of student faculty dialogues. Um, but I'm sure it's happening somewhere out there. Um well, Annette, this has been delightful. Thank you for taking us on a little tour of your world and uh sharing some uh advice and ways of thinking about this AI as it interacts with our teaching lives. So um yeah, thanks. Thanks for being here.

Annette Vee: 36:09

Thank you so much, Derek. It's really great to talk with you. Thanks for the invitation. Of course.

Derek Bruff: 36:17

That was Annette Vee, Associate Professor of English at the University of Pittsburgh, and co-author of the forthcoming book, The Norton Guide to AI Aware Teaching. Thanks to Annette for coming on the show, and thanks to Norton for connecting me with Annette. It's been a joy to work on this book with her and with Marc Watkins. I can't wait to get it in readers' hands later this year.

Derek Bruff: 36:36

For more information about Annette and her work, see the show notes for lots of links. There's her computation and writing newsletter, and the Norton newsletter, AI and How We Teach, where Annette is a regular contributor. And if you're particularly interested in Annette's work listening to students about AI, I've got a link to the Norton webinar she recorded recently about her research toolkit for faculty.

Derek Bruff: 37:00

Intentional Teaching is sponsored by UPSEA, the Online and Professional Education Association. In the show notes, you'll find a link to the UPSEA website where you can find out about their research, networking opportunities, and professional development offerings.

Derek Bruff: 37:15

This episode of Intentional Teaching was produced and edited by me, Derek Bruff. See the show notes for links to my website and socials, and to the Intentional Teaching newsletter, which goes out most weeks on Thursday or Friday. If you found this or any episode of Intentional Teaching useful, would you consider sharing it with a colleague? As always, thanks for listening.