The influence of Artificial Intelligence in modification of Competency Based Medical Education: A Systematic Review
DOI:
https://doi.org/10.64149/J.Carcinog.24.3s.209-212Keywords:
Artificial Intelligence, Competency-Based Medical Education, Machine Learning, Medical Curriculum, Simulation, Assessment.Abstract
Background: Competency-Based Medical Education (CBME) has been widely adopted across the globe to shift medical training from time-based to outcome-driven learning. With the rapid advancement of Artificial Intelligence (AI), there is growing interest in its integration into CBME to personalize learning, optimize assessment, and enhance medical training outcomes. This systematic review aims to explore the influence of AI on the modification of CBME in undergraduate and postgraduate medical education, highlighting opportunities, challenges, and implications for future educational practice.
Methods: A systematic search was conducted in PubMed, Scopus, Web of Science, and ERIC databases for studies published between January 2010 and June 2025. Keywords included "Artificial Intelligence," "machine learning," "competency-based medical education," and "medical curriculum." Eligible studies were original research articles, reviews, or reports discussing AI interventions in CBME. PRISMA guidelines were followed, and data were synthesized narratively due to heterogeneity.
Results: Of 1,248 studies identified, 67 met inclusion criteria. AI applications in CBME were categorized into four domains: personalized adaptive learning platforms, competency assessment and feedback systems, simulation and virtual patient encounters, and administrative and curricular decision support. AI improved learner engagement, diagnostic reasoning, and individualized competency tracking. However, challenges included lack of faculty preparedness, ethical concerns on data privacy, algorithmic bias, and infrastructural limitations.
Conclusion: AI has demonstrated significant potential in modifying CBME by enabling learner-centered education, improving assessment objectivity, and supporting outcome-based curricular reforms. However, its sustainable integration requires faculty training, ethical frameworks, and alignment with accreditation standards. Future research must focus on long-term outcomes of AI-assisted CBME, especially in low- and middle-income countries.
