Last week, I was (virtually) invited to speak to a group of universities in Poland known as the Merito Group. The setup wasn’t entirely ideal as I had no sense of the audience and no opportunities for questions or conversation, but I did want to share it here with folks because if you’re just catching up with my work since I started the substack, then you might not have learned about the work over the last year that has deeply informed my working and thinking around generative AI. As always, you can check out the resources on the Annotated Slide Deck.
Student EngAIgement: Working with Students with New Technologies
I’m Lance Eaton and I’m here to talk to you about the work that I’ve been doing, coupled with a framework on how you might also consider exploring and engaging with generative AI as well as looking to incorporate your students into this work.
Today’s talk is an extension of work I’ve been doing for 15 years in education and technology. I’ve had the privilege and desire to explore this space in many ways, learning about both its possibility and of course, its problems and challenges.
In the past decade, I’ve worked on different projects such as exploring hybrid flexible course design in the mid-2010s, well before the pandemic. I’ve examined how digital technologies can change how we think about and perform service learning. I’ve considered the power and importance of student agency and how open educational practices such as open pedagogy can improve student learning and meaning-making. I’ve also grown concerned about how surveillance and data practices can be another form of power-hoarding over student learning and agency including how we think about parity in the LMS.
Often, I’m trying to figure out where is the balance of technology as a means of improving opportunity and agency for students while recognizing that the tools themselves are not neutral and come with trade-offs that can be problematic.
All of which is to say that when generative AI was propelled onto the scene last November, I had lots of different feels and thoughts about it and those continue to evolve through today.
First, let's acknowledge that so much has been going on or at least so much feels like it has been going on with generative AI that it can feel like you missed the train and you're stranded somewhere.
That's why I love this quote from Laura Dumin, a colleague who has also been doing a lot of work in generative AI and education in the last year. And she's one among many that I could point to and would point to encourage you to follow.
Others include amazing folks such as Bryan Alexander, Maha Bali, Amanda Bickerstaff, Autumm Caines, Sarah Elaine Eaton, Anna Mills and many others. And don't worry--that list is in the annotated slide deck.
The core of this message is that there's lots out there and if you're feeling behind or lost, there's lots of us doing public work and making sure y'all can catch the latest train. There’s different trains too and take the train that’s right for you.
Before getting into the agenda, at the bottom and going into the chat right now is a link to what I call the Annotated Slidedeck. This document contains much of what I’m saying today as well as resources and prompts for you to try. It’s covered with a Creative Commons license which means you’re welcome to share with others and repurpose.
So what is the conversation going to be today?
How College Unbound engaged students and generative AI
I’ll walk you through how we looked to students in order to figure out generative AI and how powerfully transformative that has been.
Where’s the current value in generative AI in education
I’ll share some simple things you can try out and use to get moving with generative AI if you haven’t tried it yet or are looking for useful approaches to using it
What you might try next
I’ll give you some next steps to try out and go forward, particularly as a group of educators.
I can provide the slide deck for you to use and explore more but if you want to truly learn more and do more–it’s going to be your colleagues that you’re going to do it with. We’ll take a look at what y’all are doing and gain strength from the amazing talent in this room.
Sound like a plan? I hope so because I don’t have a back up slide deck to work through. Ok, I do, but it’s so much less fun!
When ChatGPT dropped in December 2022, it landed mostly with a thud. Many folks were wrapping up what they perceived (real or otherwise) as their first “normal” semester since the pandemic started in Spring 2020. It can be understood why folks weren’t paying attention to some new tech being touted by tech bros and anyone with an opinion on Twitter.
But some of us in higher ed, did hear about it and did start to realize the implications of ChatGPT. Folks like Maha Bali, Autumm Caines, Anna Mills, Bryan Alexander, and others were beginning to have public conversations before the end of December. Hereto, I started to play with it and share some of my thoughts publicly as I’m apt to do–whether on social media or on my blog.
Autumm Caines–a colleague and friend of mine came to me with an interesting question about its possible appearance and use by someone in her class at College Unbound. We talked about what did this mean and how did we want to think through it. I’m indebted for her insight and deliberation as we moved from concern to curiosity; from angst to excitement–and honestly, some respect for the potential students for so quickly leveraging a tool in a new way.
This was important. College Unbound centers students’ voices and works to address the educational trauma that a reasonable share of our students experience at the hands of traditional education. Any framework where we even began to accuse students, directly or indirectly, felt like a dangerous place for us to go. A false positive would be antithetical to what we stand for. So we approached it with curiosity. Autumm posted a note to her students saying she thought students might have been playing with this tool and she would love to learn more if they did. She didn’t hear back but that led us to the next step.
I put together an anonymous short survey and sent it out to all students. It asked if they knew about it, if they were using it, and if so, in what ways did they use it. We got back some results that showed students were using it to improve understanding, navigate being multi-language learners, and brainstorm. These were useful insights and so that led me to realize that we needed to know more and think more deeply about it–and not do so in the absence of students but with students.
So I then had an idea.
I realized that a course on AI & Education where the students and I learn about Generative AI while also playing with it and thinking about it in an educational context would make for a great learning experience. And, we could craft the guidelines for institutional policy. It struck me and made absolute sense. My Provost was quickly on board and we realized in general that this could be an ongoing structure not just for Generative AI but other aspects of the college when we encountered new things–be it technology or other structural elements of the institution.
My partner, because she’s also brilliant added to the idea and recommended I run the course twice. We have two 8-week sessions in a given semester. So Spring Session 1, I ran the course to develop the policy with the students. Session 2, we test-piloted those guidelines with specific assignments that the students had in other classes. The goal was to try them out and see if they made sense or consider loopholes or other issues.
Before the class could start, our faculty still needed guidance. So I put together and shared out this Generative AI Strategy that both issued a temporary policy and provided the larger context for how we get to something more stable.
At the same time, because, well, I’ve been doing this kind of work for a while and I’m deeply invested on open educational practices, I began to crowdsource Generative AI policies in Syllabi and sharing that out so folks had examples to work with. Currently, we have over 40 examples and you can also add your own if you fill out the form at the top of this crowdsourced document.
The 2 classes were amazing and I can’t stress this enough. Having students join a class where their work will mean something–where they will further employ their agency–it’s so beautiful. It led to a lot of discoveries, conversations, and ways of understanding the tool that I just wouldn’t have had were I just talking with other faculty and folks in higher ed. Students had lots of initial and complicated feelings and thoughts, and throughout the course, they just continued to become more developed and thoughtful. They challenged one another and my own thinking as we played around with ChatGPT, read about it from different perspectives, and considered what does this tool mean for work, learning, and evaluation.
This was evident early on and led me to see if students would be open to being on a panel at the NERCOMP conference in March. Students and NERCOMP were both interested, so they spoke to a room of some 30 leaders in higher education about their insights. And needless to say, they crushed it. And at that point, I knew, that while I certainly have a place in the discussion in places like these, their voices need to be heard and they need to be core to the conversation. Since then, they have been invited onto podcasts, panels, featured in the Chronicle of Higher Ed, and well, are here to continue to share their wisdom.
So session 1 of the AI & Education course came up with the guidelines; Session 2 test-drove them and edited them. You can take a review at them at this link.
The faculty reviewed them in a very similar fashion–a collaborative document where faculty were using the comment feature to share thoughts, questions, and challenges. This is a great dialogue among faculty as they interact, share concerns and make new realizations.
Once done, the students had a final look at it and then we’ve put it forward as a proposal for CU to consider as institutional policy. Additionally, some students continue to meet with me as we look to different projects and opportunities such as speaking engagements, podcasts, and even writing projects. They been invited to participate in Academic convocations and as part of leadership panels at national conferences.
The thing that I can’t stress enough about all this is how powerful and important it has been for me to be in this space with them. They have many different lenses to be thinking about generative AI–ones that are substantially different than my own identities and positionality. We as educators can often think that we know best and understand all of this in ways that are more important or relevant than students. We may think that is the case, but we’re going to miss a lot if we make that assumption when it comes to this set of tools and how they will show up in our lives.
The rest of the talk explored some things that I’ve already shared here such as some tips and tricks for starting to use it and general recommendations for getting started. All of which can be found in the Annotated Slidedeck.
AI+Edu=Simplified by Lance Eaton is licensed under Attribution-ShareAlike 4.0 International
Thank you for all of this.