Key points:
- Students harness AI’s power as they learn to use it as an assistant and not a replacement
- Students using AI: It’s not that scary and shouldn’t be banned
- Baked-in bias or sweet equity: AI’s role in motivation and deep learning
- For more news on AI use, visit eCN’s AI in Education hub
My first-year college students have a very narrow perspective of AI. “In high school,” wrote one student on an anonymous survey I give at the start of the semester, “I stayed far away from the tool because it was emphasized to me as a way of cheating rather than a study tool.” This seems to be the norm: AI as the mortal enemy of all classroom teachers.
I, on the other hand, want my students to use AI every day in class and for every assignment. It is, I explain to them, the perfect study tool if used correctly. It can help with everything from brainstorming to outlining to feedback. It is, in fact, the ideal scaffolding for all those students who are stuck, unable to clearly articulate their thoughts, start their papers, or strengthen their arguments.
For the last two years I have guided my college students on how to use AI. I emphasize that it is a 24/7 personalized tutor and mentor that can help them think better about the complex issues we are studying.
I of course acknowledge that students are overwhelmingly using AI to cheat, and trying to catch them, much less teach them how to use it correctly, is unbelievably difficult. But the reality is that we are far beyond pretending this issue doesn’t exist or that we can keep it at arm’s length.
So to all the teachers out there: Resistance is futile. Or as Julius Caesar supposedly said, if you can’t defeat your enemy, have him as your friend.
I therefore want to lay out a typology that has helped me think about AI as exactly such a friend.
A typology for using AI
It is critical to realize there is an entire spectrum of possibilities for how to use AI, or what philosophers call the boundaries of our intellectual autonomy. On one extreme is its complete rejection; I think of this as absolute “cognitive autonomy.” On the other extreme is its complete acceptance; basically, you enter the essay prompt into ChatGPT and ask it to write the paper for you. I think of this as absolute “cognitive outsourcing.”
While these polar opposites are easy to understand, it is everything in the middle that is of most importance to figure out. I suggest, therefore, we think of this as different levels of cognitive offloading. Minor AI-assisted support can be thought of as simply scaffolding students’ learning; major AI-assisted support is a more aspirational cognitive apprenticeship, helping students see how an “expert” might do it. Both are key to supporting students’ academic success.
[Table 1]
AI-assisted support as scaffolding
Students are novice learners, and, as such, need guidance. This means extensive scaffolding, which might be “chunking, sequencing, detailing, reviewing, or any other means to structure the task and its components so as to fit it into the learner’s zone of proximal development.”
I cannot tell you how often students used to come to my office unsure of how to start their papers. Before ChatGPT, I would spend 15-20 minutes brainstorming topics, prodding and pushing until we had narrowed it down.
Today, I teach my students a set of in-class AI prompts, based on a standard model of supporting writing, on how to brainstorm, focus, and develop their ideas. “I didn’t really know where to start,” wrote one student at the end of last semester, “and ChatGPT helped me think about questions, and I was able to start planning what I wanted to do based on the different options.” Another student wrote, “I started off with pretty much no idea and was able to use ChatGPT to find a topic that I’m interested in and I’m working with it to narrow it down.” When I now meet with students, our conversations are so much more productive, as we now have a focus.
AI-assisted support as an apprenticeship
As students dig deeper into the topics we study–of poverty, race, gender, and ethics–they realize just how complex they really are. These are “wicked problems,” I explain, because there are so many variables, so much ambiguity, and so many ways to define the issues. It’s no wonder they’re hard to think through, much less write about.
I therefore teach my students another set of AI prompts to help them see what good thinking about such issues looks like. This is formally known as a cognitive apprenticeship: “one needs to deliberately bring the thinking to the surface, to make it visible, whether it’s in reading, writing, problem solving.” AI is so good at doing this by walking students step-by-step through its output.
This is critical for students who don’t yet know how to fully think about, contextualize, or organize their thoughts. Seeing AI offer suggestions for a thesis statement or a paper outline in real-time, with explanations, is incredibly helpful. “The outlines,” one student commented, “helped me from getting too stuck on small details and reminded me to think about the big picture.” “It asked me questions,” another student said, “that made me think a lot about my topic and consider different things I wouldn’t have thought of on my own.”
[Table 2]
Looking ahead
So much about the future of AI in education is unknown. But what I do know for certain is that we must all learn how to embrace our enemies. As one of my students put it, “I didn’t realize that ChatGPT is actually there for me to use as a teaching assistant. I feel confident that the work I complete with ChatGPT will not get me into trouble, because I know how to use it as an assistant rather than a replacement.” Julius Caesar would be proud.
Dan Sarofian-Butin, PhD, is a Full Professor in, and Founding Dean of, the School of Education & Social Policy at Merrimack College.