Before You Dive in: An AI-Enhanced Scaffolding Strategy for Clinician Learners in Graduate Education
Eulho Jung, Anita Samuel, Jerusalem MerkebuClinicians often struggle to engage with abstract learning theories due to limited cognitive readiness and time constraints. To address this challenge in a graduate-level learning theories course, we implemented “Before You Dive In” (BYDI), an AI-supported instructional strategy offering optional pre-reading supports. BYDI included reflective study guides, AI-generated podcasts, and concise reading summaries, all delivered asynchronously to accommodate adult learners’ schedules. The intervention aimed to scaffold learners’ understanding and foster engagement with dense theoretical content. Learner feedback indicated that BYDI helped activate prior knowledge, reduce cognitive overload, and improve reading focus. Analysis through the lenses of schema development and self-regulated learning suggests that BYDI facilitated the formation of conceptual frameworks and promoted autonomous, strategic study behaviors. This innovation demonstrates how technology-enhanced scaffolding can improve theory engagement in adult education, particularly in time-pressured professional contexts.