Teaching and Learning with AI Conference

As artificial intelligence becomes more accessible across higher education, health sciences faculty face a familiar tension: how to preserve time-tested teaching practices while adopting emerging tools that can strengthen learning, assessment, and faculty workflow. This presentation describes how faculty used BoodleBox—an education-focused platform that consolidates multiple AI applications—to enhance teaching and learning in health sciences contexts. Drawing on faculty-led use cases, the session highlights practical applications aligned with traditional instructional priorities: clear learning outcomes, sound assessment design, consistent rubrics, authentic case-based learning, and supportive feedback practices. Examples include developing case studies and class activities, refining assessments and rubrics, and streamlining course design tasks while maintaining academic integrity and disciplinary standards. Participants will leave with a set of adaptable strategies, implementation considerations, and discussion prompts they can use to evaluate fit, set guardrails, and support responsible adoption of AI in health sciences education—bridging the best of established pedagogy with purposeful innovation.