AI@AUC: AI-Resilient Assessment: Motivation, Guardrails, and Critical AI Use

Organizing university The American University in Cairo Event description How can we ensure that students are genuinely learning when they may be tempted to outsource their work to AI, particularly when tasks become challenging? Drawing on the recently released MLA Framework for AI-Resilient Assessment and Grading, this session explores strategies for reducing that temptation and supporting valid assessment. We will first examine strategies that make authentic engagement more appealing, including transparent purpose, student choice, social annotation, and alternative grading. While these approaches are powerful, they may not always be sufficient, so we will also consider guardrails such as digital process observation, proctoring, oral assessment, and the cautious use of AI detection. How can we frame these guardrails as expressions of care rather than suspicion and surveillance? Finally, we will explore ways to guide AI use toward supporting learning and cultivating habits of critical, skeptical engagement. We will look closely at the Peer & AI Review + Reflection (PAIRR) model, which invites students to reflect critically on AI feedback alongside peer feedback. Participants will have time to identify strategies they would like to try in their own teaching and share their hopes and concerns about assessment in the age of AI. Speaker: Anna Mills Participants It is only open to Afretec members