Intentional Teaching's 100th Episode

Episode 100 of the Intentional Teaching podcast is coming up, and I would love your help making it a special one.

There are interviews I've aired on the podcast that I find myself referencing all the time in my work with faculty. All my guests are fantastic, of course, but some managed to share some piece of insight that has stuck with me, changing how I think about teaching and learning. And I bet, if you're a listener, you have similar insights from past episodes that keep informing your work as an educator.

Here’s my ask: What’s one idea or example or question or quote from an Intentional Teaching episode that you keep thinking about? Let me know via email—or record a short voice memo on your phone and send that to me. I’m planning to make the 100th episode a kind of clip show, where I share excerpts from past episodes featuring powerful insights—and your comments about why those insights have stuck with you.

Your deadline for this assignment is September 15th, which will be here before you know it!

AI-Aware Online Math Teaching

In the meantime, episode 97 is now available in the Intentional Teaching podcast feed is now available. In it, I talk with Jessica Bernards, an experience online math instructor who teaches at Portland Community College and the University of Oregon. Jessica and I met a few months ago while serving on a panel on fostering student metacognition in math courses. It was clear to both of us that we had a lot in common in how we thought about college math education. Jessica has way more online math teaching experience than I do, however, so I invited her on the podcast to share that teaching experience.

My co-authors and I didn't mention Jessica in The Norton Guide to AI-Aware Teaching, but she's definitely taking an AI-aware approach to her online math courses. She's clear on her learning goals, understands a lot about how AI works (especially when it comes to doing mathematics), and has deep insight into how her students learn and study with and without AI. In the interview, she talks about the moves she makes to make her students' learning visible, to foster a growth mindset in her students (which is critical for math-anxious college students), and how her approach to teaching math online has changed because of AI.

One situational factor that's critical to Jessica's teaching approach: Her online math courses are taught asynchronously. Outside of a few exam sessions she proctors via Zoom, there are no synchronous class sessions in her courses. If you've ever wondered how one can possibly teach math or a similar subject asynchronously online, well, Jessica seems to have that figured out!

A key ingredient in her approach is a lot of attention to individual students and their learning. Every one of her students receives a tailored email from her at least once a week, an email that's informed by all the work the student has recently been doing (or not doing) in the course. She also starts the semester with 10-minute, one-on-one Zoom sessions with each of her students, allowing her to get to know them and jumpstarting productive student-teacher relationships.

You may have heard that generative AI is bad at math. That's not really true these days, which makes all of Jessica's assignments subject to unauthorized AI assistance. As a result, Jessica has shifted 90% of her course grading scheme to those proctored exams. Her assignments are still critical to helping her students learn, so she's taking a number of steps to ensure that students still engage with those assignments, even if they don't count for much in the grading scheme. How does she pull that off? You'll have to listen to the interview to find out!

​You can listen to my conversation with Jessica Bernards here, or search for "Intentional Teaching" in your podcast app.

AI Syllabus Statements as Invitations for Conversations

One of the many AI-related workshops I facilitated this month was a webinar for my publisher, W.W. Norton. We titled it "Opening Lines: AI Syllabus Statements as Invitations for Conversation." There were over 750 people in attendance, so clearly the topic of AI syllabus statements is one of great interest!

I've been collecting examples of AI syllabus statements that thoughtfully engage students in conversations about the role of AI in their learning. I shared a bunch of those examples at the Norton webinar, and I thought I would link out to some of them here in the newsletter, too. All of the following syllabi or syllabus statements do something interesting in this space, and I think they're worth exploring regardless of your stance on AI in your courses.

• ​Ethan King, English, University of Virginia – a red-light approach
• ​Nick Sousanis, Liberal Studies, San Francisco State University – a red-light approach
• ​Daniel Radthorne, Law, University of Virginia – a restricted approach
• ​Teresa Thompson, Accounting, West Valley College – a green-light approach
• ​Steen Blank, Joe Felter, & Eric Volmar, Stanford University – a green-light approach
• ​Marc Watkins, Composition & Rhetoric, University of Mississippi – state your own boundaries
• ​Molly Chehak & Maggie Debelius, Georgetown University – a co-creation approach

The good folks at Norton have made the webinar recording available upon request, so if you'd like to listen to me talk about those syllabus statements, along with other ways of engaging students in productive conversations about AI, you can request a recording here.

The Norton Guide to AI-Aware Teaching

My new book, The Norton Guide to AI-Aware Teaching, co-authored with Annette Vee and Marc Watkins, is now available as an ebook! It's available through major online retailers like Amazon and Barnes & Noble. It's also free for faculty who have adopted a W.W. Norton textbook, so if that's you, ask your Norton rep. If you want to wait for the paperback, it will be available in September 2026, and you can preorder it now.