Generative AI tools are increasingly capable of producing student-like responses to course assignments. But what does that mean for your teaching and assessment practices? In this interactive session, you’ll test one or more of your own course assessments in different AI tools to see what students might be able to generate. Together, we’ll reflect on what we find, discuss the limitations and strengths of AI-generated work, and explore practical next steps—whether you’re mid-semester and unable to change an assignment, or looking ahead to redesign for future terms. You’ll leave with strategies you can apply immediately to clarify expectations with students, small process-oriented adjustments you can add to existing assignments, and considerations for longer-term assessment design.

Learning Outcomes

By the end of this session, participants will be able to:

• Identify how generative AI tools respond to their own course assessments.
• Recognize the strengths and limitations of AI-generated responses compared to student work, including where AI outputs align with or fall short of expectations.
• Plan immediate, low-effort strategies to clarify expectations with students and incorporate process-oriented adjustments into existing assignments.
• Consider ideas for longer-term adjustments to assessment design to strengthen learning outcomes and account for student access to AI tools.