Teaching and Learning with AI Conference

Faculty are spending more time policing AI submissions than designing meaningful assessments. The arms race is unwinnable, and detection tools keep producing false positives that damage real students. Oral assessment offers a different path. When students complete short oral responses on their own time, voice authentication confirms authorship and AI grading runs against the faculty member's rubric, not a vendor's. Aggregate response data even reveals where the teaching itself has a gap. The assessment doesn't just check integrity. It diagnoses the course. This session walks faculty through what changes when assessment becomes a conversation instead of an artifact.