This spring Extra Points will feature a series of conversations focused on how faculty and staff around the University of Minnesota are using generative AI to do University work.
Innovation) interviewed Emerging Technologies Faculty Fellows Molly Vasich and Kris Cory, Associate Directors of First Year Writing, Writing Studies, in the College of Liberal Arts. The following has been revised for length and clarity.
Tell us about your roles in First-Year Writing, and how that is informing your work.
Molly Vasich: Kris and I are Associate Directors for First-Year Writing, a program housed in Writing Studies. We support 35 full-time faculty members and 15 graduate instructors who teach sections of First-Year Writing, the only universally required course for undergraduates across the Twin Cities campus. This semester, we have about 2,400 students taking First-Year Writing.
We have large portfolios that include developing model curriculum, professional development and training, and program-wide assessments to measure whether we are meeting our learning and program goals.
Kris Cory: One of the things that really guides our work and leadership and decision-making is the eight guiding frameworks for our program. They are useful in supporting the work we do in classrooms and for the work we do in the program as a whole. These frameworks inform everything we do and help us navigate new challenges, such as moving to asynchronous online teaching during COVID or adapting to generative AI now. The frameworks serve as lenses or guides for all our work.
Interviewers: You mentioned your eight guiding principles. Can you give a couple of examples of how those have guided your approach to generative AI this year?
MV: When Kris and I started as faculty fellows, one of the projects we knew we wanted to work on was developing more guidance for our instructors. We turned to our guiding frameworks to think through these issues. For example, with process-focused frameworks, we asked instructors to consider where and how AI might support steps of the writing process without taking over. We also considered how AI technology might inhibit or support students' growth towards key learning outcomes.
Information literacy is another guiding framework. We thought about the affordances and limitations of using generative AI for finding, evaluating, or synthesizing sources. Understanding large language models and their implications is part of developing critical literacy. These frameworks help us shape policy and teaching practices accordingly.
Set the context for us by telling us about your generative AI project for our fellowship program.
KC: We approached our project by thinking about how we can support instructors and how our instructors can support students in this moment of rapid change with generative AI.
Our project aimed to develop basic guidelines and expectations for how we approach generative AI in our classes, and we included these in our faculty handbook. We also designed some model curriculum activities.
We wanted to embed and model activities that engage with generative AI through a critical literacy framework. These were our central goals for the project and our participation in the fellowship programs.
Tell us how it's going. What have you learned? Have you had any ah-ha moments?
MV: It’s an ongoing experiment! A key takeaway is that instructors need to make expectations clear with students regarding AI policy, and we need to have explicit conversations about AI with students. We expect these two things to happen across all first-year writing sections.
From there, the kinds of activities that instructors are doing with and around AI vary widely. Some instructors explicitly decide to do more analog activities, explaining to students the purpose behind it because of the learning outcomes and goals they want students to achieve. Others are more experimental, having students look at AI platforms themselves, using rhetorical analysis to examine them and determine what kinds of prompts they need to use. There's a wide range, but underlying all these approaches is the intentionality of the instructors' choices.
KC: Instructors are learning with their students and having conversations about how they engage with AI in their classes, creating space to reflect on how it went. We invite our instructors to share what they're doing in the classroom with their colleagues during professional development sessions. There's a range of comfort and confidence levels in working with AI, both among instructors and students. We're inviting instructors to learn with their students. Molly and I are also learning with and from our instructors as they share how they're engaging AI intentionally in the classroom.
On the less fun side, we're also having conversations with instructors as they encounter students using AI in ways that have been prohibited by their class policies – how do we want to approach these situations, and what can we learn from them that will help us design activities and policies more effectively. We're still learning about how students are using AI. We don't want to become policing figures, as that's not a productive relationship to have with students.
Interviewers: Have your instructors come up with any strategies for addressing that, beyond reminding students of what you're doing, why you're doing it, and what the permissible use of AI is?
KC: Part of what we're coming to understand is how often we need to be talking about AI in our classes with students – communicating, being intentional, and explaining why we're doing something and whether or how using genAI is okay or not okay, and why. Having those conversations not once or twice, but again and again, is important so that we're matching AI use with the learning goals of particular activities and assignments, not just the course in a broad way.
In first-year writing, even before generative AI, our approach to learning about citation, working with sources, and avoiding plagiarism has always been developmental. We want to create spaces to talk to students about their writing processes and spaces in the course that provide models, and opportunities to practice and feedback on developing skills. When we talk to students we can learn from them and get more information about how they are using generative AI, so it's an exchange where we're learning about that. We can also talk to students about where, when, and why we are designing things for the use or non-use of AI.
MV: Like Kris mentioned earlier, we have really relied on our program’s guiding frameworks to provide us with direction and how we approach AI and teaching writing. Our class size is 19 or 20 students, allowing for lots of one-on-one feedback. All of our projects are broken into scaffolded steps, with feedback along the way. As instructors, we're following along with the student in their process, so there's never an assignment where we haven't seen all their work on the back end before.
Another guiding framework is metacognition and reflection. Throughout the course, we invite students to think critically about their choices and how they're doing research. This happens throughout the entire course and at multiple points during the project. Engaging with students in discussion and sharing those reflections means it's not just about the final product; it's about their process and experience as writers.
Have there been conversations with students that have been particularly impactful either for you or for them?
MV: One thing that sticks with me was when I noticed that an international student's draft had some evidence that wasn't cited. I asked the student, "Where did this come from?" She said, “I was doing some research on AI to get ideas."
The student saw ChatGPT as a tool and didn't understand the expectations of the draft, how to do citations, or what it meant to patchwrite versus plagiarize. This led to a good conversation between us and ongoing support. I imagine these kinds of conversations are happening regularly in our classes. It was a small but poignant moment because it was one of the first moments that I really started to think about students’ use of generative AI.
Fortunately, I knew that student before this happened. I had already seen her writing and talked to her one-on-one, so I had no reason to believe she was trying to get away with something. Our conversations about AI use came from a place of curiosity, trying to understand her cultural perspective, and working to talk through my own understanding and perspective.
KC: I thought a lot about the work we did during the crisis of COVID and the events surrounding the murder of George Floyd. The learning and work we were doing in our program and thinking about our pedagogy were so intentional during that period. We focused on building community among our instructors and supporting them in building community in their classrooms.
Many of those lessons about good pedagogy feel super important now: developing relationships with students, creating a sense of community and trust, and knowing each other in order to have meaningful conversations. The more impersonal our environments, the less thoughtfulness, accountability, and respect there is. I'm reminded that many things we know support good learning experiences aren't changing, even though a lot of other stuff is. Leaning into those things seems extra important now.
Tell us how you've been disseminating to either the people you work with or people beyond your program.
MV: Through the writing studies department, we went from having a first-year writing handbook to an undergraduate writing studies handbook. The kinds of development we did in first-year writing are now shared across undergraduate classes and the department.
Vasich and Cory also shared their work with Writing Across the Curriculum (WAC), and with their professional organizations via the First Year Experience Conference, the 4 Cs Conference and the MinneTESOL Conference.
Anything else to share?
MV: A poem! I think this poem gets at the urge to write, research, learn, explore, be creative. I’ve been sharing this poem with educator friends as we keep thinking through how to approach and engage AI (or not!).
Resources
Guiding Frameworks For WRIT 1301. University Writing is the only universally required course for undergraduates across the University of Minnesota.