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Learning Curves in Health Professions Education Simulation Research: A Systematic Review
Neva M Howard1, David A Cook, Rose Hatala
1From the University of North Carolina Chapel Hill School of Medicine (N.M.H.), Chapel Hill, NC; Center for Online Learning (D.A.C.), Mayo Clinic College of Medicine; Division of General Internal Medicine (D.A.C.), Mayo Clinic, Rochester, MN; Department of Medicine (R.H.), University of British Columbia, Vancouver, British Columbia, Canada; and Division of Learning Analytics (M.V.P.), NYU School of Medicine, New York, NY.
Summary Statement:
Learning curves are used in health professions education to graphically represent paths to competence and expertise. However, research using learning curves often omit important information. The authors conducted a systematic review of the reporting quality of learning curves in simulation-based education research to identify specific areas for improvement. Reviewers extracted information on graphical, statistical, and conceptual elements. The authors identified 230 eligible articles. Most learning curve elements were reported infrequently, including use of an optimal linking function, detailed description of feedback or learning intervention, use of advanced visualization techniques such as overlaying and stacking, and depiction of competency thresholds. Reporting did not improve over time for most elements. Reporting of learning curves in health professions education research is incomplete and often underutilizes their desirable properties. Recommendations for improvement of the statistical, graphical, and conceptual reporting of learning curves, as well as applications to simulation research and education, are presented.
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