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Role of Scientific Theory in Simulation Education Research

Pusic, Martin V. MD, PhD; Boutis, Kathy MD, MSc; McGaghie, Willam C. PhD

doi: 10.1097/SIH.0000000000000282
IMSH Research Summit Article
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Summary Statement Scientific theories are consistent explanations about how the world works. They have been shown to be plausible not only from a large amount of independent confirmatory evidence but also because rigorous attempts at falsification have failed. Other desirable features include parsimony, scalability, explanatory, and predictive power. Scientific theories differ from models and laws in the amount of evidence available and/or the degree to which they explain nature. Learning curve theory is a scientific theory with direct applicability to simulation education researchers. In this article, the authors use the example of learning curve theory to illustrate the key features of scientific theories and how they provide a meaningful foundation for simulation-based education research programs.

From the NYU School of Medicine, New York, NY (M.V.P.); Department of Pediatrics (K.B.), Hospital for Sick Children, University of Toronto, Ontario, Canada; and Northwestern University Feinberg School of Medicine (W.C.M.), Chicago, IL.

Reprints: Martin V. Pusic, MD, PhD, Institute for Innovations in Medical Education, 550 First Ave, MSB G109 New York, NY 10016 (e-mail: martin.pusic@nyumc.org).

The authors declare no conflict of interest.

© 2018 Society for Simulation in Healthcare