Regina Martin, Chair of Denison’s Writing Committee, shares resources and ideas on teaching writing in the age of AI.
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This is my final dispatch for the semester, and I’m pleased to offer this concluding observation: We are not (yet) in an AI apocalypse!
Here’s what I mean by that:
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| A few weeks ago, I experimented with a method for integrating AI into peer review. My goal was to see if AI can be used by students as a tool for evaluating their own writing. When I do peer review, I give students a guide with a series of steps and questions designed to help them dissect their drafts and analyze them via my grading criteria. |
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In my W101, I am using AI-generated writing to teach students two things: (1) the pitfalls of submitting unrefined AI output in their assignments and (2) how to evaluate and revise writing. For example, I developed this group activity to help students learn how to identify unsupported claims.
When prompted to write a college-level essay, AI tends to generate a lot of unsupported claims.
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In my W101, in most class periods, students do a graded in-class writing (ICW) assignment. A few weeks ago, I did an experiment: I required students to use a large language model (LLM) like ChatGPT or Gemini to do the ICW.
I gave them the following instructions: “Use an LLM of your choice to write a response to the ICW prompt.
Students frequently ask AI for feedback on their writing, so we need to teach them how to interpret that feedback. This week I am sharing some materials I developed to do that. In my W101, when students peer review rough drafts, I am now integrating lessons on AI feedback. I teach an 80-minute class, and during the first half, students work in pairs on a traditional peer review exercise.
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| I spent my summer developing a suite of AI literacy assignments that are appropriate for writing courses. Over the next several CfLT newsletters, I will share those. I developed them for my ENGL 342: Utopian and Dystopian Fiction class, which I am currently teaching. The first assignment consists of two parts. I’ll elaborate on the first part this week. |
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| This fall I have redesigned my W101 to experiment with new methods of assessment given that many students will use AI to write their essays. Because the quality of a written artifact is no longer necessarily a sign of student learning or a reflection of their ideas, I have shifted some of my assessment criteria to focus on evidence of student learning. |
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| An important aspect of addressing AI in writing instruction is helping students make better decisions about when and how they use AI to offload cognitive labor. Lori Kumler in ETS created a slide deck with a classroom activity for getting students to think critically about how AI use affects their learning and cognitive abilities. This activity would be appropriate for a class period early in the semester. |
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| As we enter year three of generative AI, where do you fall on the AI spectrum? Do you want to refuse AI? Adopt it minimally? Or Embrace it? This article, “How Can Your Courses be AI Aware,” links out to resources for making writing classes “AI aware” along each category on the spectrum. For example, if you want to resist AI in your writing classes, do so more intentionally. |
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| In my March 25 TTT contribution, I promised some suggestions for rethinking assessment to ensure students are meeting learning goals even if they (mis)use gen-AI to create their high-stakes writing assignments. And in my April 22 TTT contribution, I discussed an example of how I am re-weighting low-risk assessments. As promised, in this edition, I share a new type of assessment I am adding to my writing classes: paper conferences. |
