title: Learning curves in health professions education.
abstract: Learning curves, which graphically show the relationship between learning effort and achievement, are common in published education research but are not often used in day-to-day educational activities. The purpose of this article is to describe the generation and analysis of learning curves and their applicability to health professions education. The authors argue that the time is right for a closer look at using learning curves-given their desirable properties-to inform both self-directed instruction by individuals and education management by instructors.A typical learning curve is made up of a measure of learning (y-axis), a measure of effort (x-axis), and a mathematical linking function. At the individual level, learning curves make manifest a single person's progress towards competence including his/her rate of learning, the inflection point where learning becomes more effortful, and the remaining distance to mastery attainment. At the group level, overlaid learning curves show the full variation of a group of learners' paths through a given learning domain. Specifically, they make overt the difference between time-based and competency-based approaches to instruction. Additionally, instructors can use learning curve information to more accurately target educational resources to those who most require them.The learning curve approach requires a fine-grained collection of data that will not be possible in all educational settings; however, the increased use of an assessment paradigm that explicitly includes effort and its link to individual achievement could result in increased learner engagement and more effective instructional design.
authors: M.V. Pusic is assistant professor, Emergency Medicine, and director, Division of Education Quality and Analytics, New York University Langone School of Medicine, New York, New York. K. Boutis is associate professor and pediatric emergency physician, Department of Pediatrics, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. R. Hatala is associate professor, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. D.A. Cook is professor, Medicine and Medical Education; director, Online Learning Development and Analysis, Center for Online Learning, Mayo Clinic College of Medicine; and consultant, Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota.
authors: Martin V
authors: MV
authors: Pusic
authors: Kathy
authors: K
authors: Boutis
authors: Rose
authors: R
authors: Hatala
authors: David A
authors: DA
authors: Cook
mesh_terms: D004517:Education, Professional / Q000379:methods*; D004521:Educational Measurement / Q000379:methods*; D006281:Health Occupations / Q000193:education*; D006801:Humans; D059032:Learning Curve; D015233:Models, Statistical