I’m not a fan of using AI for day-to-day activities, or for art. It’s not that I think that nobody should use AI, or that AI isn’t useful in some circumstances. I just… don’t use it for the research and writing that I do (most of the peer-reviewed work I reference lives behind paywalls). And using it for literary writing or visual art is appropriating, at best, or even outright stealing. No, thank you.
(Also, I wish that browsers, word processors, Adobe products, and even WordPress would just knock it the f— off. Stop foisting it on me; I don’t want it and won’t use it… go away.)
I am interested in how instructors are teaching with (or trying to avoid) AI, because from what I’m seeing in the world, students using AI to generate some or all of their work has become a significant issue for teachers. It’s difficult to know how to address it, because AI is a thing that’s here. How do we interact with it, and teach others to interact with it, in ways that are responsible, ethical, fair, and useful?
In other words, it’s not just about using AI — it’s also about pedagogy. I don’t have answers, but I’ve seen what seem like some good ideas, including having students generate a piece of writing using AI and then asking them to fact-check it and revise it as necessary. I’m also seeing some instructors going back to requiring at least some handwritten work for drafting.
Another approach I’ve seen is one that one of my professors used this semester: requiring a lot of writing over the course of several weeks, much of it reflective writing based on personal experience (with citations based on course reading), along with written responses to classmates. AI wasn’t forbidden, per se (we could have used it if it was appropriately cited), but when you have to produce that much original writing, in that style, your distinctive “voice” becomes recognizable. That kind of writing isn’t appropriate for a lot of academic work, and we did have a couple of longer, less narrative, writing exercises, but it worked well for this class. (It was a lot of writing, though. I don’t envy our professor having to wade through all of it.)
The other class I took this semester was a coding class that focused on PHP and Javascript. It was a good class, challenging and structured well. Do I know how to use either PHP or Javascript as an expert? Lol, no. But I know more than I did at the beginning of the semester, so I guess that’s a win — good foundation and all that. What was particularly interesting to me, though, was the way the instructor asked us to use AI.
For the most part, we were required to demonstrate that we could use the concepts he introduced to us in the way they were introduced, without the use of AI. Most of our assignments consisted of small, simple (if you know what you’re doing, which I… did not) coding exercises that followed the logic of his demonstrations, but focused on a slightly different problem. (In my evaluation of the class, I said that this approach is an “infuriatingly effective” way for me to learn, because the problems he asked us to solve were just different enough from his demonstrations that I really had to think through how to use the concepts he was asking us to use.)
He asked us to use AI on three separate occasions over the 15 weeks, in three different ways:
- Early in the semester, we were asked to prompt an AI (of our choosing) to solve a simple coding problem, make sure the code executed the way we intended, and comment on whether we understood what the AI did and why. (The AI produced code that was far more complex than I could read, much less write, at that point in the semester. It worked, but I wasn’t sure how.)
- Several weeks later, we were asked to manually code the scaffolding for an assignment, and once the code worked the way it was assigned, prompt an AI to add additional functionality that we had not yet covered in the class. (I had to instruct the AI not to change the structure of my code, to make sure that I could still navigate it after the new code was added — I’m a beginner! We had to turn in/upload to a class server both instances of code.)
- For our final assignment, we were to use an AI to code a simple web app (with HTML, CSS, Javascript and PHP) that met his specifications — vibe coding! I used GitHub Copilot/GPT-5 mini in Visual Studio Code, so I was using AI within the context of an IDE (I found working within a specific environment very helpful). It required a fair amount of intervention to get where I wanted to go. (Granted, someone with better prompting skills would probably be much more efficient.) But by the end of the semester I could at least read the code and understand most of the logic — or ask the AI to explain what it was doing — so I could make the adjustments I needed or wanted to meet the expectations for the assignment.
As a person who does not use LLMs on the regular, I thought these exercises, in this progression, were an interesting and effective way to introduce AI. The exercises asked us to solve specific problems, and encouraged us to develop an understanding not just of the end product, but of the working parts. Exercises 2 and 3 also introduced us to different ways of using AI: to generate code that complemented manually written code, and to generate most of the code and adjust it as we tested it. Using AI to generate code to let a machine do the work of machines seems like a good use case to me. And because code needs to be checked and adjusted to make sure it’s doing what it’s supposed to do — no matter who (or what) generates it — that workflow seems like a defensible use of an AI.
Carmen Yount 