TY - JOUR
T1 - Learning Curves in Health Professions Education
AU - Pusic, Martin V.
AU - Boutis, Kathy
AU - Hatala, Rose
AU - Cook, David A.
N1 - Publisher Copyright:
Copyright © by the Association of American Medical Colleges. Unauthorized reproduction of this article is prohibited.
PY - 2015/8/31
Y1 - 2015/8/31
N2 - 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.
AB - 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.
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U2 - 10.1097/ACM.0000000000000681
DO - 10.1097/ACM.0000000000000681
M3 - Article
C2 - 25806621
AN - SCOPUS:84938277813
SN - 1040-2446
VL - 90
SP - 1034
EP - 1042
JO - Academic Medicine
JF - Academic Medicine
IS - 8
ER -