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Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical
Patricia A Carney1, Stefanie S Sebok-Syer2, Martin V Pusic3
1Professor of Family Medicine, Oregon Health & Science University, Portland, OR, USA.
Medical Education Online
|February 23, 2023
Summary
Clinical Competency Committees (CCCs) in graduate medical education (GME) face challenges with incomplete data for trainee progression. Implementing learning analytics (LA) can enhance data quality and decision-making for better educational outcomes.
Area of Science:
- Medical Education
- Data Science
- Educational Technology
Background:
- Clinical Competency Committees (CCCs) in graduate medical education (GME) aim to monitor trainee progression using competency-based principles.
- Current CCC practices face challenges with incomplete, insufficient, or poorly aligned evaluation data, hindering accurate advancement decisions.
- Learning analytics (LA) offers a systematic approach to interpreting diverse trainee data for improved assessment and feedback.
Purpose of the Study:
- To explore the potential of learning analytics (LA) to enhance decision-making processes within Clinical Competency Committees (CCCs).
- To provide recommendations for implementing LA to improve data quality and support educator development in GME.
- To address the gap in guidance for utilizing LA in GME program evaluation.
Main Methods:
- Review of current challenges in CCC data utilization and decision-making.
- Exploration of learning analytics principles and their application to educational data.
- Development of recommendations for integrating LA into GME programs, focusing on data quality and educator development.
Main Results:
- Learning analytics can significantly improve the interpretation and integration of diverse data sources for CCCs.
- Systematic data collection and advanced digital interpretation are key features of LA that benefit educational systems.
- LA facilitates a deeper understanding of educational contexts, ethical decision-making, and clear communication of findings.
Conclusions:
- Implementing learning analytics can address critical data quality and decision-making challenges faced by CCCs.
- Further development and guidance are needed for GME programs to effectively leverage LA for trainee assessment.
- LA holds significant potential to support ethical, accurate, and individualized trainee progression in graduate medical education.
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