Developing AI Literacy

This week on the podcast, I talk with Alex Ambrose, professor of the practice and director of the Lab for AI in Teaching and Learning at the Kaneb Center for Teaching Excellence at Notre Dame. I heard Alex on the Kaneb Center's podcast, Designed for Learning hosted by Jim Lang, a few months ago, and I was very interested in what Alex had to say about the evolving state of generative AI in education at Notre Dame. I was thrilled when Alex agreed to come on Intentional Teaching so I could ask him more questions!

We covered a lot of ground in the interview, including Notre Dame's decision this spring to make Google Gemini available to all faculty, students, and staff and a project by the Notre Dame physics faculty to train an AI chatbot to give useful feedback to students on their handwritten physics problem solving. You can listen to the entire interview with Alex Ambrose here, or search for "Intentional Teaching" in your podcast app. Here are a few of my takeaways from the conversation:

Faculty AI Literacy

Alex helped lead a semester-long "Teaching Well with AI" academy for Notre Dame faculty. He and his team conducted pre- and post-assessment of the faculty involved, looking at their confidence in various aspects of AI literacy. They saw the biggest gains after this professional development series in participants' self-reported skills in prompting AI chatbots well. This doesn't surprise me, because it is often the case that a few small, non-intuitive changes in how I prompt AI can make a big difference in the utility of its output.

Alex noted that the faculty reported much smaller gains in understanding AI's limitations. He said that wasn't because the program didn't address AI limitations, rather it was because the faculty involved moved from being "unconsciously incompetent" to "consciously incompetent." In other words, they didn't know what they didn't know before the academy, but they left it having a much better sense of what they didn't know. I can relate! I often feel that I can't keep up with changing AI technologies, and that's with me spending a lot of effort doing so.

​You can read more about the Notre Dame faculty survey here.

Student AI Literacy

On the student side, Alex shared some results from a big survey of first-year undergraduates in writing and Romance language courses at Notre Dame in January 2025. Where did these students report learning about generative AI? Friends, family, and social media were the primary sources for half of the students. Only 7 percent of the students named the university as their primary source of intel on genAI! These students weren't learning about AI from their school, but they wanted to.

When asked about the areas where they would like more guidance from the university, the top responses were "developing effective strategies for genAI use in career readiness" and "in learning." These results are consistent with many other students surveys I've seen. Students want help using AI effectively (to get things done but not undermine their own learning) and, in most cases, ethically. This is why I think it's important for all instructors to learn about AI and consider ways to adapt their teaching to its presence in our students' lives.

​You can read more about the Notre Dame student survey here.

We Need to Do Better This Time

Alex made a call for higher ed to respond to these needs. "Yes, we have to have these big AI ethical conversations and talk about access," he said in the interview, "but we also need to start moving into AI literacy. Yes, AI policy on cheating is important, but let's also talk about AI pedagogy as well. Yes, AI can be harmful, a crutch and a weapon for learning, but it also can be a lever and a tool." He and I agreed that higher ed didn't do a great job, on the whole, teaching digital information literacy a decade ago when social media was transforming public discourse. Alex noted that the impact of that was evident in the last few U.S. presidential elections.

Alex and I also agreed that higher ed needs to do a better job this time around helping our students grapple with the ways AI is changing our information environment. I think what was missing last time around was a systematic shift in the undergraduate curriculum to address digital information literacy. I don't think higher ed will meet the current AI moment without that kind of curricular change. As I've said before, I don't think every instructor needs to embrace AI in their teaching, but we do need to have a plan at the program or major level to address AI literacy.

For the full conversation with Alex Ambrose, you can listen on the Intentional Teaching podcast website or search for "Intentional Teaching" in your podcast app.

An AI Assignment Playbook

Back in May I led a webinar for AI x Education, a student-run organization exploring the present and future of generative AI in teaching and learning. My session was called "The AI Assignment Playbook: Strategies for Teaching with and about Generative AI," and I just saw that it's been posted to YouTube.

In the talk, I shared a few important lenses through which I consider generative AI, as well as some ideas for using AI as a kind of instructional assistant. Most of the session was dedicated to examples of assignments that thoughtfully integrate AI to support student learning, expanding on my "Red Lights, Green Lights, and AI-Integrated Assignments" blog post from March.

If you'd like some ideas for integrating AI into assignments that support and don't undermine student learning, you can watch the webinar recording here.

Thanks for reading!

If you found this newsletter useful, please forward it to a colleague who might like it! That's one of the best ways you can support the work I'm doing here at Intentional Teaching.

Or consider subscribing to the Intentional Teaching podcast. For just $3 US per month, you can help defray production costs for the podcast and newsletter and you get access to subscriber-only podcast bonus episodes.