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. During the second half, I work through this slide show.
The slides are designed for students to use outside of class, but when I use them in class I start with the last slide, which links to an AI-generated essay and AI-generated feedback on that essay. Both documents include comments in which I provide feedback on the AI-generated essay and on the AI-generated feedback. I give students a few minutes to peruse those documents, then I lead a discussion eliciting what they learned about AI-generated feedback based on my comments. Finally, I walk them through the slides, pointing to examples in the linked documents to illustrate. Here are the main learning goals:
- Students compare the substantive nature of instructor feedback with the generic, incomplete, and misleading nature of AI feedback.
- Students are able to identify the limitations of most AI-generated feedback.
- Students are able to identify the few ways AI can offer helpful feedback.
- Students learn methods for getting more effective feedback from AI if they choose to use it.