Designing a digital education track for medical residents using the Four Component Instructional Design model

Medical educators must teach effectively in strained clinical environments while meeting residents' growing preference for digital resources. However, there is limited guidance on teaching with digital platforms.

In 2021, the authors developed and implemented a two-year Digital Education Track (DET) at Beth Israel Deaconess Medical Center's internal medicine residency program. Using the Four Component Instructional Design (4C/ID) model, they created a curriculum that combines foundational and hands-on digital education skills. The program includes a one-week intensive bootcamp and monthly sessions, where residents learn to create various digital teaching products, including podcasts, infographics, tweetorials, and whiteboard animation videos. The curriculum employs scaffolded learning tasks, supportive information, just-in-time guidance, and part-task practice to build complex teaching skills.

Five cohorts totaling 29 residents have participated in the DET, with 17 graduates to date. Guided by Kirkpatrick's framework, evaluation emphasized Levels 2-4. At Level 2 (learning), graduated residents reported increased self-efficacy in using digital platforms and applying principles of cognitive load theory to their teaching. At Level 3 (behavior change), residents produced a substantial body of digital scholarship, including 22 podcasts (35,000-84,000 downloads each), 16 social media threads (26,500-542,400 impressions), 25 infographics, and 20 whiteboard animations. Faculty reviewed these resources using the revised METRIQ score, independently determining they were of high caliber (mean scores of 2.5-2.9/3 across domains). At Level 4 (results), unsolicited post-publication feedback suggested these resources influenced teaching behaviors and, in some cases, patient care.

The DET offers educators a model for scaffolding instructional design for hands-on skills as medical education adapts to technological change, evolving learner needs, and clinical demands. Future work will include tracking long-term outcomes such as career trajectories and sustained teaching effectiveness and integrating explicit instruction on AI tools within each class.