Teaching and Learning with AI Conference

Most professors are still somewhere in the realm of ambivalence about AI, unsure exactly how to react.  For the last year, the University of Dayton has responded with a “bottom-up” approach of creating spaces for vulnerable conversation and learning, rather than simply instituting a top-down AI policy.  The dialogues and writings generated by this approach have enabled faculty to share fears, hopes, observations, and tested strategies, building an atmosphere of trust and solidarity.  This presentation will discuss why dwelling in ambivalence is a necessary and even productive stage, and how to grow faculty trust in an age of apprehension. #facultydialogue, #institutionalchange, #AIattitudes

AI gives students the power to generate a polished case summary in seconds, but closer examination often reveals a lack of critical thinking and strategic judgment, which AI can support but never replace. This session shares a classroom-tested, mastery-based case critique system designed to build workforce-ready thinking in an AI-enabled world. Students learn to use strategy tools as the “lens” for analysis (not buzzwords) through a phased structure (Learning → Development → Mastery) and a simple 3-paragraph critique model. The rubric foregrounds evidence, reasoning, tradeoffs, and actionable recommendations.