Abstract
In 2023, early faculty responses to generative AI often framed the classroom as adversarial, emphasizing plagiarism detection, bans, and returns to in-class assessments as mechanisms to control student behavior. This stance echoed longstanding critiques of grades as tools of control rather than support for learning. This reflective case study examines student perceptions of generative AI in a new Honors course on grading in higher education taught in fall 2023 to upper-level undergraduates from varied majors. Students used AI to develop and rehearse interview questions, they read contemporary instructor commentary on AI, and they discussed emerging AI-based feedback tools. Their reflections show that students found AI’s responses about grades generic and normative, they wanted instructors to discuss AI openly rather than simply prohibit it, and they were receptive to AI-generated feedback, mainly because they had received so little feedback in many classes. Together these findings suggest that students saw AI through the same tension present in grading, control versus support for learning, and wanted instructors to prioritize support. A closing reflection describes how these insights shaped three interventions in a long-running general education course.
Publisher
South Dakota State University
Rights
© 2026 The Author
Recommended Citation
Guberman, Daniel, "Control or Support: Early Student Perceptions of Generative AI in a Course on Grading" (2026). The Interdisciplinary Journal for Research on Pedagogy and Learning Design, Vol. 1, Issue 1., Fall 2026. 1.
https://openprairie.sdstate.edu/ijrpld/1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License