Get Me to the Funnery

How AI Is Changing Higher Education: The Course

I’m teaching two sections of a course called How AI Is Changing Higher Education this fall, one for graduate students in Penn’s GSE and one for brand-new undergraduates in Penn’s College of Arts and Sciences. This essay sketches the course and shows how my teaching is entangled with the writing I do here. For reflections on a course I taught last fall, visit AI Log teaches.

Better beginnings

I have a tendency to go on too long when I talk to students about the ideas that inform my teaching. I was winding up to do exactly that on the first day of class with a mini-lecture on how Talks to Teachers on Psychology by William James is the foundation for my structured, active in-class approach to teaching, when Shakespeare rescued me. Not William himself, rather I heard Peter Gould, the director of Get Thee to the Funnery, introduce the work he and his colleagues do to produce a Shakespeare play—this year it was Macbeth—with a group of teenage actors for two weeks each summer.¹

Peter describes the program’s educational framework as working our hearts, minds, bodies, and voices together to encourage individual growth in the service of a collaborative production. This captures the essence of James’s ideas about embodied cognition and human experience that I hope my students and I can use to think and feel our way toward a better understanding of how AI is changing higher education.

That framework will start us off by clearly distinguishing between human cognition as a complex stream of emotional, physical, intellectual, and performative experience and computational neural networks producing outputs from fancy math applied to large datasets of words and images. Heart, mind, body, and voice are an elegant sufficiency to start our work, defining simply that most remarkable natural phenomenon, human intelligence. From there, we will begin to understand these most recent versions of artificial intelligence and what they mean for institutions of higher learning.

On the first day, we will discuss my radical proposal to limit the use of digital technology during class time, while having no limits outside of class time. My hope is that students will accept this sharp division, and that we can use it to create critical distance to think together in class about our educational use of AI out of class. I was inspired to try this by my students last fall, who enthusiastically endorsed the idea of creating digital-free educational class time.

A Brief Tour of “How AI Is Changing Higher Education”

I love reading other teachers’ lesson plans and syllabi, but my course material pales in comparison to beautifully crafted intellectual structures like Henry Farrell’s A Political Economy of AI: a Syllabus, Jane Rosenzweig’s To What Problem is ChatGPT the Solution?, and Eryk Salvaggio’s Critical Topics: AI Images. Reading them is the intellectual equivalent of watching MTV’s Cribs. My class is more Flip or Flop.

By design, my courses are open-ended and risk disaster each time we meet. There is little script and no score. Class meetings are jam sessions. Think backyard hootenanny in Appalachia or a late-night party after the clubs close in New Orleans. Everything depends on people showing up ready to play. Ambitious failure is encouraged, the stakes are low, and when it works, the payoff is a feeling of communal joy in individual and group performance.

“First we read and then we write” is the theoretical structure for the first eight weeks of the course. We will read More Than Words by John Warner and AI Snake Oil by Arvind Narayanan and Sayash Kapoor. I am asking students to buy physical copies so that we can do good, old-fashioned reading of the text together in class, books open to the same page. The in-class activities and writing assignments will be grounded in collective engagement with the words on the page. We will do a lot of group writing, with sentences and paragraphs going up on the whiteboard for discussion.

The first major task is inspired by John Warner’s advice to find your guides. I’ll ask each student to identify a writer, one who has something interesting or useful to say about AI and higher education. They choose an essay by that writer to be read by the class, they write a short essay about what makes their chosen writer interesting and useful, and they deliver a brief, informal talk in class about the value of reading that writer. To help them get started, I give them a list of some of my guides, which includes more than a few subscribers to AI Log.

• Here is A Guide to Finding Your Guide.

The class is built on the experience of writing six short essays. We will experiment with using JeepyTA, an LLM tool, to provide simulated feedback in the drafting process. As I did with my fall course, we will include the tool’s feedback as an additional layer of their peer review and discuss what, if any, educational value it brings. This is an experimental exploration; it does not replace human effort. Writing feedback itself will come in the traditional form of in-class peer review and comments from me.

• Here are the short essay writing assignments as they will appear on the Canvas course site.

• Here is my guide to writing the essays.

The class culminates in a student-led workshop where I sit back and the students get to work educating themselves and their peers (and me!). They will spend the last half of the course working in groups to develop an educational program designed to help students understand how AI is changing higher education, and what we should do about it. If all goes well, the first Monday in December, we’ll take over the wonderful new Research Data and Digital Scholarship Exchange space in Van Pelt Library to run workshops for whoever shows up.

First impressions

Later this week, I will send everyone who registers for the class a welcome letter, a preliminary syllabus, and a link to an introductory video. As I say in the letter, there are some weird things about the course, and it may be better for students who feel anxious about experimental and social approaches to learning to find more traditional options.

Welcome letter & preliminary syllabus

Welcome video (link live on August 20)

Here is the answer to the inevitable question: How does grading work in this class?

AI Log, LLC. ©2025 All rights reserved.

Look for an essay or two in December or January reflecting on how the class went. Subscribe to receive those and other essays directly in your email inbox.

Feel free to share any of the teaching materials I publish here with friends and colleagues.

I talk with people about what AI means for higher education. Find out more about these talks and how we might arrange one.

1. My daughter was one of those teenagers. Her experience reminded me that drama is an excellent model for thinking about structured class activities because to succeed, students must prepare beforehand. Yet, even the most dedicated and excellent preparation does not guarantee perfection, or even success.