Menus, not traffic lights: A different way to think about AI and assessments
Liu offers two things to faculty figuring out how to talk to their students about AI in the classroom: First, he models the shift from regulation to guidance, arguing that instructors should help students develop judgment rather than prescribe in advance when and how to use AI. Second, he invites us to think past unilinear adoption taxonomies (less vs. more AI) toward ones that acknowledge the case-by-case specificity of tool use.
As educators who know our students and our teaching and assessment contexts, we are uniquely positioned to know what menu items to recommend. For any one assessment (and student, for that matter), there will be ways to use AI and tools that are more suitable or less suitable. Sometimes it will be more productive and responsible for students to use particular AI tools to engage with literature and edit their text. Other times it will be more suitable for students to other AI tools to provoke reflection, draft a structure, and then provide feedback on text. Want to order five desserts? Maybe not for this assessment, but it’s a great idea for the next one.