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From: Beth McMurtrie
Subject: Teaching: How to respond when students don’t want to work with AI
This week, I:
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This week, I:
In recent months I’ve heard from professors and faculty developers about a particular AI challenge.
“One question that has been coming up more and more with our instructors is how to handle students who really do not want to engage with AI because of concerns about environmental impact,” writes Mona Thompson, a senior education development specialist in the Teaching and Learning Transformation Center at the University of Maryland at College Park.
“I know many instructors at our university are looking for even more guidance about how to be thoughtful about environmental concerns (which many of them have as well) and also prepare students for a world in which AI is ubiquitous.”
Students who refuse to use artificial intelligence have a variety of objections. Some, as Thompson notes, are worried about the impact data centers are having on the environment. Others question the ethics of using generative AI. Still others have read about the damage AI might do to their own ability to think.
This has been a growing concern at William Peace University, says Elle Corvette, director of faculty development and immersive learning, because the small liberal-arts college has tried hard to be thoughtful about integrating AI into the classroom.
Peace has participated in the American Association of Colleges and Universities’ Institute on AI, Pedagogy, and the Curriculum, for example. Faculty members have attended workshops on AI literacy and AI competency, which are collegewide goals for students as well. All courses now include an AI-use statement in their syllabi. About 95 percent of faculty members, she says, have used AI personally and in some way with their students, even if that was just having conversations about how AI is embedded in many of the tools they use. “We have really, really dived deep into AI,” she says.
This fall, she says, students’ concerns about AI started to emerge.
In one course, for example, an English professor decided to use AI as a critical-analysis tool. He had laid out the argument that employers are looking for AI competency, that AI is a skill set, and that he was preparing students for the jobs of tomorrow. He asked students to handwrite an assignment, put it into AI, and have the tool do a critical analysis of their writing.
One student raised his hand and said he didn’t want to use AI. He had heard about the dangers of cognitive offloading, the idea that using AI could harm one’s thinking and learning. The student mentioned something he had seen on a TikTok video about the problem. Other students then spoke about academic integrity and accidental plagiarism. The college has tried to respond to these kinds of issues in other AI discussions across campus, Corvette notes.
The professor came to talk to Corvette, wondering how best to address students’ concerns while also developing their understanding of AI. Another faculty member came by her office the same day with a similar story. Fortunately, she says, the college uses universal design for learning in course design, which builds in alternative assignments, so the students were well supported at the moment.
But she is wondering how others have handled this challenge. If your goals include AI literacy and AI competency, how does that square with students’ resistance to AI?
The college’s AI task force is now looking at how to address such concerns in a proactive way. “This is going to be a development,” says Corvette. “I don’t think it’s going to ever be a one and done.”
Have you asked students to work with AI as part of a course assignment and found that some students wanted to opt out? If so, what was your response? Has your department or college addressed this issue in its AI guidance? If so, write to me at beth.mcmurtrie@chronicle.com and your example may appear in a future newsletter.
Last week I asked readers to share last-class activities that have been fun or meaningful. Here are two from Sheila Tabanli, an associate teaching professor of mathematics at Rutgers University at New Brunswick. She uses these in her undergraduate math courses and designed them to be grounded in “metacognition, mistake-driven learning, and student well-being.”
“Festival of Errors”: Tabanli got the idea from Make It Stick: The Science of Successful Learning. Throughout the semester, she writes, she tries to build “a judgment-free learning environment where mistakes are openly labeled, discussed, and corrected, including my mistakes.” She even gives students points for speaking up and pointing out her mistakes.
On the last day of class, Tabanli explains, “students choose an error they made on an assessment, redo the problem correctly, and explain the misconception that led to the error. They present their ‘featured mistake’ to classmates in a festive atmosphere where I bring some refreshments for us to enjoy. Students report that this activity strengthens their reflective studying and helps normalize struggle as they see their peers having made and explaining the same mistake!”
Self-Assessment & Participation Reflection: In this activity, Tabanli asks students to “self-grade aspects of their engagement — such as consistent attendance, on-time arrival to class, turning in assignments on time, managing distractions … and general effort. Students award themselves a small number of points in each category, plus one ‘free point’ for completing the reflection.”
“I’ve found that students are thoughtful and generally honest,” she writes, “when evaluating their participation.”
I’ll include more examples of last-class activities in next week’s newsletter. If you have one you’d like to share, please drop me a note at beth.mcmurtrie@chronicle.com
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