What about AI?
"Toward Critical AI Literacy in the Writing Classroom" (Loring Pfeiffer)
Throughout this academic year, I have been incorporating class sessions about generative AI into the writing courses I teach. My students and I create a class policy around the use of generative AI, we test its effectiveness at creating more argumentative thesis statements, we use it to help generate research questions, etc.
These class sessions have surfaced many student misconceptions about AI. In a writing assignment about AI, a student submitted an AI-generated summary that included hallucinated citations from after the article was published. Because the student didn’t grasp how the technology had produced the content they had included in their submission, they didn’t understand that AI could hallucinate. Another student declared in one of our workshops about summary and AI that they thought AI-generated summaries were “less biased” than human-generated ones. It was only when, following up on that comment, I showed the class some of the clearly biased transcripts that generative AI has created, that that student became aware of the predispositions that have been hard coded into this technology.
In this panel discussion, I would present briefly on some of the activities about generative AI that I have incorporated into my teaching. I would then invite conversation about how teaching with generative AI - threatening as this new technology may seem - can productively surface students’ misconceptions about it and, in so doing, allow teachers to begin honing students’ critical AI literacy.
"AI Feedback Combined with Peer Review: A Human-Centered Approach to AI Tools" (Lisa Sperber, Marit MacArthur, Carl Whithaus)
Recent research demonstrates that AI feedback is comparable to human feedback when criteria are used (Steiss et. al., 2024), suggesting AI can be a valuable feedback tool. Writing teachers will need to make decisions about if, how, when and why to use AI for feedback. While AI feedback can offer support, it must be used in a human-centered process. Writing Project teachers understand the importance of authentic human involvement in student writing. If we remove humans from feedback, we go against the body of research demonstrating students’ relationships with teachers and peers impacts their engagement, motivation, and sense of belonging, which in turn correlate with student success and retention (Kirby & Thomas 2021). Moreover, as Anson (2023) points out, humans provide crucial practice for understanding the social and rhetorical dimensions of writing, a key threshold concept associated with learning transfer (Downs & Robertson, 2015). In addition to teacher feedback, peers review remains a best practice in writing pedagogy (Anson 2023). Many studies show that students learn from providing criteria-based feedback (Lundstrom & Baker, 2015; Min, 2006), suggesting that AI feedback should be paired with peer review. Since many students question the competence of their peer reviewers (Alnasser, 2018), however, AI can provide reassurance. In our presentation, we will very briefly share preliminary results of a study that combines AI feedback with peer review in college composition and writing across the curriculum courses (5-7 minutes). We will then focus on sharing the AI feedback and peer review activity we have developed, walking participants through a feedback worksheet and explaining the rationale behind it. This approach supports students’ reflection on AI use, so they are better able to use AI tools in ways that align with their own goals as writers and encourage critical AI literacy.