When AI Can Answer, Students Must Ask: Three Cycles of Practitioner Action Research Using SIMPL Inquiry™ in College Courses - Keeping Students at the Center of Education

Generative artificial intelligence has sharpened a long-standing question in higher education: how can instructors know whether a finished student product represents meaningful learning? Responses are often framed too narrowly as prohibition or unrestricted use. This article presents SIMPL Inquiry (Student-Driven Inquiry Method of Personal Learning), a pedagogical framework developed through practitioner action research in online Introduction to Philosophy and Ethics courses at three Maryland community colleges. Grounded in St. John's College seminar practice, Universal Design for Learning, and an NEH-funded primary-source seminar course, the method shifts assessment from the final product to the development of student thought. Within instructor-designed boundaries, students process course material, generate their own questions, use AI as a Socratic sparring partner rather than an oracle, verify claims against course and non-AI sources, reflect on how their thinking changed, and extend the inquiry through layered peer dialogue. The article traces three design cycles: a first generation that moved from didactic toward dialogic learning; a second, implemented in fall 2026, that adds explicit epistemological skepticism, analytical and cited peer replies, and a course-long Capstone question; and a planned third that structures small-group dialogue with a three-level reply limit. Student work, including a nursing student's transfer of Cartesian skepticism to AI-supported clinical decisions, and anonymous course-improvement surveys are presented as practitioner evidence, not causal findings. The article also examines tensions in dialogic pedagogy and a rapidly shifting AI policy landscape, and it invites a college or university partner to conduct a longitudinal, grant-funded study across disciplines and across in-person and online courses.