In episode 34, I consider another way of looking at my success with AI in the classroom: through assessment. To my mind, AI has imposed a great deal of guesswork into assessment of student writing: "Did my student write this, or was it written by AI?" Since AI is here to stay as part of just about anyone's writing ecosystem, it's important to focus on what really matters: "Is writing being written in a way that still helps it meet audience expectations?" I offer a brief overview of how I try to tackle that question, using the rhetorical concept of evidence as an example. Are my students using evidence in a way that seems to fit with a given genre? Using the term "evidence" with my students as a key term for knowledge about writing and having classroom activities about how evidence might vary depending on a given genre has set me up to make assessment a little bit easier, whether AI played a role in the writing or not.

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In this episode, I share a short lesson plan I used to begin a conversation with students about AI on the first day of classes. I showed them an AI-generated ad that stirred some controversy, we had a brief discussion regarding students' judgments about the ethics of AI use, and then I also introduced some of my own. I hope you find this short(er) episode helpful!

In this long overdue episode, I'm excited to share my own recent classroom success. After coaching and encouragement on my part, notetaking on my students' part, and then asking students to pull their laptops out periodically for several drafting sessions for their rhetorical analysis papers, the result was very little AI use. On this episode, I'll talk through how I feel I know and how I went about it.


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After my first week of teaching this semester, it's time for a report. I promised to share my AI policy, which will be first up in this episode. I'll also share my classroom "coaching" report. Earlier this summer, I discussed the possibility of adapting the way in which my favorite workout trainers try to motivate me to stay focused for the duration of my workouts. Did I do a good job during the first week in keeping my students focused on writing practice? I'll also share briefly how I used Cornell notes and how I feel I made a mistake in my presentation that may have disrupted students' working memory. I'd also like to discuss briefly what I plan to do this coming week--it's still early in the semester, so I need a way to get students to buy into the applicability of writing courses to other things they are doing: not just in an abstract way, but as concretely and immediately as possible. Join me on this journey!

Perkins, D. N., & Salomon, G. (2012). Knowledge to go: A motivational and dispositional view of transfer. Educational Psychologist, 47(3), 248–258. https://doi.org/10.1080/00461520.2012.693354

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Electronic technologies have been embedded in classrooms for decades, but the emergence of genAI has prompted some professors to resort back to handwritten assessments, such as bluebooks and notes. The concern, of course, is cognitive offloading--that an overreliance on genAI for learning tasks short-circuits the learning process by taking away opportunities for cognitive processing.  In this episode, I present a few studies from the decade before genAI that show how electronic technologies can be detrimental to learning, which prompted me to ask students for daily handwritten notes for participation. However, my method still needed improvement: I also relate how, last year, I stumbled upon the Cornell note taking method, which has important learning strategies built in. Toward the end, I provide a sample to show what it looks like in my classes with students' practice with conceptual knowledge and metacognition. The Cornell note taking system makes it easy for students to review their notes and use them later, and it's also easy for teachers to assess them.

Show notes

Brookings Institution synopsis of 3 handwriting vs. screen studies
Dynarski, S. M. (2017, August 10). For better learning in college lectures, lay down the laptop and pick up a pen. https://www.brookings.edu/articles/for-better-learning-in-college-lectures-lay-down-the-laptop-and-pick-up-a-pen/

Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task

Nataliya Kosmyna, Eugene Hauptmann, Ye Tong Yuan, Jessica Situ, Xian-Hao Liao, Ashly Vivian Beresnitzky, Iris Braunstein, Pattie Maes

Get the paper "Your Brain on ChatGPT" in PDF format:
https://arxiv.org/abs/2506.08872

Research team's web page for the study at MIT:
https://www.media.mit.edu/projects/your-brain-on-chatgpt/overview/

Official Web site for "Your Brain on ChatGPT":
https://www.brainonllm.com/

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As a follow up to episode 28, I made a plan to introduce reflection about genAI on my first day of classes. I start by reviewing a post I encountered on social media that got me thinking in more detail about asking students to reflect on genAI. From there, I present the new lesson plan and then offer several more ideas for learning about genAI as the semester progresses. And, let's face it: I'll be learning along with my students. As the accomplished novice that I am, I not only need to enhance my own knowledge about genAI, but I also need to know what students are thinking about it. This lesson will help me, as a writing instructor, begin that journey this semester in a more intentional way this semester than before.


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As my start date for fall semester draws nearer, I've started thinking in more detail about the kinds of knowledge students need to help them with writing. The distinction Doug Downs and Elizabeth Wardle made in 2007 concerning the need to *learn about* writing--as opposed to *learning to write*--has resonated with me for a long time. And now, I'd argue that the same idea applies to AI--it's not that writers need to learn how to write with AI, but rather that they need to learn *about* AI. With that in mind, I talk through a set of rhetorical skills, or knowledge about writing, that I typically bring to my writing classes and then reflect on what knowledge I can add about AI in the upcoming semester.

Show notes:
Downs, D. & Wardle, E. (2007). Teaching about writing, righting misconceptions: (Re)envisioning “First-year Composition” as “Introduction to Writing Studies.” College Composition and Communication, 58(4), 552-584.



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In this continuation of reflection on my teaching, I present (briefly) the basic routine I use for developing lesson plans: review, launch, deliver, apply, and close (RLDAC). From there, I share two full lesson plans that I described in episode 26: one that I have traditionally used to introduce learners to the rhetorical concept of presence from Chaim Perelman, and the other an adjusted version that focuses on the concept of presence but adds an element of writing with genAI. Both of my lesson plans follow RLDAC, which is a great communication tool for conveying course content in the classroom. RLDAC has really been a game changer for me, and I'd like to share that story in the near future on the podcast. I'd also like to record an episode soon where I develop a lesson plan about AI in real time.

Teaching Writing in College is available: 

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As a follow-up to episode 25, I outline changes to one of my existing lesson plans to keep student learning focused on the rhetorical strategy of presence. This episode includes a brief rehearsal about how context is central to writing, a brief anecdote of successful teaching with the rhetorical concept of presence, and a before/after explanation of how I plan to adapt an existing lesson plan to support student learning in the context of AI. And as I was putting the slides together, I fortuitously developed a framework for supporting student learning in the context of AI: Learn the Tools, Use the Tools, Practice the Tools, and Reflect on the Tools (LUPR). I might elaborate on or revise this framework as I continue to think about student learning in the context of AI.

Teaching Writing in College is available: 

YouTube (video): https://www.youtube.com/playlist?list=PLUWbbrcygqkZvxqdPCqhuzu0yyx5trJUw

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Parsing the differences between writing from genAI and writing from people can be frustrating or intimidating. But it can also be fruitful for thinking about how humans and machines handle (or don't handle) context. In this episode, I use the rhetorical concept of "presence" from Chaim Perelman to compare a piece of my own writing to a piece from ChatGPT. This comparison helps highlight different ways in which I, as a human, would approach descriptive writing versus how ChatGPT does. The differences I find highlight the problem of context for writing by humans and machines alike. This episode will be a springboard for a follow-up about adjustments I’d like to make to the way I teach the rhetorical skill of "presence" in my classes.
Apple Podcasts: https://podcasts.apple.com/us/podcast/teaching-writing-in-college/id1667922309
YouTube: https://www.youtube.com/playlist?list=PLUWbbrcygqkZvxqdPCqhuzu0yyx5trJUw
Spotify: https://open.spotify.com/show/4TxG7hTN6qaJHN9euDBIZU?si=ur3jQve0TdyeSLKVyLsNgw
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