We’ve launched a semi-regular feature to keep you informed about how artificial intelligence (AI)—especially generative AI (GenAI)—is shaping teaching and learning at Carleton and beyond. As we move beyond our four-pronged approach to developing an AI strategy for your course, this month we’re turning our attention to a new question on many educators’ minds: Where should student AI literacy live?
In a recent post on Educating AI, Nick Potkalitsky argues that AI literacy isn’t just a technical skill—it’s a critical thinking competency. He offers a compelling and nuanced analysis of the current state of AI literacy in schools, whereby institutions are looking to two distinct models of AI literacy. The isolation model puts AI literacy education in designated spaces whereas the distribution model empowers each educator to integrate AI literacy into their field. Potkalitsky’s proposed solution is a hybrid model that combines coordination with contextualization.
Why is AI literacy important? AI content—or AI Slop, as it’s begun to be called—is pervasive. Students are learning from AI tools directly, whether schools teach it or not. AI literacy isn’t about teaching students how to use AI, per se, but rather helping them develop critical thinking habits that transcend contexts. Within the realm of academia, this must be paired with learning literacy; that is, students need to know how their exposure to, and use of, AI impacts their learning within each field and course.
Avoiding AI is not neutral. Educators who ignore AI are still shaping students’ understanding—often in problematic ways. To quote Potkalitsky directly:
“The teachers who insist they won’t ‘do AI’ in their classrooms aren’t preserving their autonomy—they’re surrendering it. When students bring AI-generated historical analysis to history class, the teacher who refuses to engage with its evaluation isn’t avoiding AI literacy; they’re teaching it implicitly. They’re teaching students that AI-generated content doesn’t warrant critical examination, that sources don’t need verification, that the distinction between human and artificial reasoning doesn’t matter. These aren’t pedagogically neutral choices.”
This sentiment resonates across higher education: as AI tools become more integrated into daily workflows, the challenge is no longer whether students use them, but how thoughtfully they do so.
Have something to share or a question about AI in your course? We want to hear from you! Reach out to us with your ideas, challenges or success stories.