Over the past 3 years, Teaching Faculty Nathan Jung, Ph.D., has been an early adopter of generative artificial intelligence (AI) in his courses in the Program for Engineering Communication. On March 5, he’ll lead an Exploring AI in Teaching session on using AI to support student success. Jung spoke to CTLM about why he started incorporating AI into his courses and how this work has blossomed.
Tell us a little about your teaching context – who are your students and what are they learning?
I teach writing, speaking, and applied ethics in the Program for Engineering Communication. Our students are drawn from all over the College of Engineering; we often have, for example, nuclear, biomedical, and civil engineering students working side-by-side on original projects. They are mostly upper-level students preparing for senior design courses and the workplace.
Our main Engineering Communication course is a crucial asset for these students. It ensures they have the communications and ethical literacy skills required to successfully navigate the engineering profession. I think we have a great arrangement! I get to learn from my students about the incredible work they do in their subfields, and in return, I offer high-level training in communications and applied ethics.
How did you learn about AI and how did you decide to make the plunge?
While I have seen machine learning projects in areas like autonomous vehicles for many years, the advent of advanced generative writing with ChatGPT 3.5 in November 2022 was surprising to say the least! But I had no hesitation taking the plunge in Spring 2022. Partly out of necessity, because my students were already active users and it was obvious to me that in a few years we would have a freshman class of AI natives. But I saw an enormous opportunity to help students use the technology responsibly and help shape the discourse. I was probably primed for this view by my PhD research, which concerned the relationship between writing and technology, going back to the Gutenberg printing press. While I didn’t know it at the time, my humanities background in book history proved crucial to navigating AI!
What has it been like these past couple years as you’ve learned about and incorporated generative AI in your teaching? Does this feel like a big change or not so much?
Personally, I have found these last few years to be an extremely exciting time in the history of writing and writing instruction. While some things remain the same – a persuasive, compelling, and carefully-crafted piece of writing has the same power and features that it did two or three years ago – the process we use to create documents is undergoing rapid evolutions that I can only compare to the advent of online research, cloud-based writing, spell-checkers, and other major shifts in our approaches to composition. At times it feels like a very big change indeed! But most of the time I see generative AI as offering new ways to achieve old goals.
Register for Nathan Jung’s Exploring AI in Teaching session
Do you collaborate on uses of AI in teaching with others in your department or outside UW?
Yes, I collaborate widely and eagerly. AI is a genuinely disruptive, multi-purpose technology that spans all aspects of the university classroom from the syllabus to lesson plans to grading. Since no single person or discipline can get a full handle on its wide-ranging impacts, I completely rely on collaboration with the stellar teaching faculty in my program and the work done by the CTLM. I have also interfaced with the Greater Madison Writing Project, and I am currently serving as the co-editor for a special issue of the peer-reviewed Journal of the Midwest Modern Language Association on the topic of “Intelligence,” which will include diverse articles on new applications of AI in the humanities and a roundtable on AI pedagogy. Finally, I am very fortunate to be able to lean on my engineering students for their expertise in the technical dimensions of AI, as well as our amazing STEM librarians for information literacy and data ethics angles.
Your March 5 talk is about using AI to support student success, which may seem counterintuitive to some. How did you come to appreciate these applications of AI?
I asked my students why and how they were using it, and I listened to their answers with an open mind. I teach students from all over the world, with different relationships to the English language, and several of them expressed to me how helpful the technology was for tasks like correcting grammar and calibrating tone in unfamiliar contexts. Others told me that they liked using it for project management purposes – to create schedules to keep them on-task. Others appreciated dialoguing with AI during brainstorming, or using it to create study aids from their notes. No one conceived of AI as a single-purpose tool for pumping out complete essays. Instead, they described completely legitimate uses for a general-purpose tool.
What is your advice to others on how to wade in the AI pool (whether or not they decide to use it)?
First, try and bracket the discourses around productivity-savior and techno-apocalypses. Instead, keep an open mind and start using AI yourself to better understand its affordances and limitations. Have some fun with it. Once you get a better handle on the things AI does well – for example, condensing and summarizing information of all kinds – you will start to intuitively think of AI as a resource when you encounter certain kinds of tasks. At this point, you can start to explore the different platforms in the wider AI ecosystem.
In terms of teaching, ground yourself in your learning objectives. What are your main goals for the course? Are they forever tied to a particular assignment? Think about breaking down your assignments into discrete tasks, and assessing where AI might assist students in the process. Start small – introduce the technology in a low-stakes in-class activity or assignment and track the results. Embrace unexpected outcomes – this is where genuine learning happens for both you and your students – and finally, be upfront with students about the experimental nature of what you are trying to do. They will appreciate the sense that they are collaborating with you and they will understand that this is largely uncharted territory – the exact terrain we want to cover in university courses.