A practical, evidence-backed playbook to keep faculty relevant, valued, and uniquely human in an AI-accelerated academy. Organized as four levers you can pull today and scale as you grow.
Integrating AI literacy into your instruction can be daunting, but you don’t have to start from scratch. This presentation will provide instructional design strategies for mapping AI competencies to existing learning outcomes in any discipline. Presenters will guide participants through practical methods for auditing lesson plans and course content, to determine where AI literacy can be meaningfully folded into existing instruction. These strategies are research-informed, field-tested in undergraduate courses, and backed by assessment results. Attendees will leave with an actional plan to make changes in small, low-risk increments.
Standard cloud-based LLMs often present two major hurdles for faculty: "hallucinations" that lead students away from course facts and a "give-away-the-answer" style that bypasses critical thinking. This session showcases a practical solution using Retrieval-Augmented Generation (RAG) to build course-specific AI tutors. Participants will see how instructors can serve as the "boss" of the AI by indexing their own specific materials—lecture recordings, lab manuals, and PDFs—and utilizing a pre-configured Socratic system prompt. We will share data from a Fall 2025 pilot where 91% of students reported the AI helped them identify specific weaknesses in their understanding. Attendees will leave with a blueprint for creating a disciplined AI assistant that stays grounded in their content and their teaching philosophy.
