Measuring Competency Based Medical Education: Using Artificial Intelligence to Analyze Curriculum
by Linda Penrod
Keyword(s)
Linda Penrod AI
A hands on demonstration and lecture on innovative Artificial Intelligence driven solutions for migrating medical education programs to a Competency Based Medical Education (CBME) model. Real world examples of the power of machine learning to harvest assessment data across multiple subsystems including education curriculum assessments such as BlackBoard and ExamSoft and active simulation based practice (including A/V). Automate data mapping against core competency measurements such as Entrustable Professional Activities (EPAs), Body Systems, or Skills. Leverage existing data to create a machine learning driven proactive monitoring system for learner performance, creating learner remediation plans and reviewing individualized learner “fingerprints” of competency mastery across all educational phases.
Credit
Credit Hours:0.5