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This topic has appeared in the English Wikipedia rankings 1 time. It first appeared on 2026-04-22 and was most recently seen on 2026-04-22.
Adaptive expertise is a broad construct that encompasses a range of cognitive, motivational, and personality-related components, as well as habits of mind and dispositions. Generally, problem-solvers demonstrate adaptive expertise when they are able to efficiently solve previously encountered tasks and generate new procedures for new tasks. This definition can be contrasted with more traditional ideas of expertise popularized by Chi and others, which do not typically consider adaptation to completely novel situations. Its empirical validity has been examined in a number of training and learning contexts. The term was first coined by Giyoo Hatano and Kayoko Inagaki, to tease out the variability within groups of experts. Hatano and Inagaki, described two types of expertise: routine expertise, or classic expertise, and adaptive expertise. They defined routine expertise as involving mastering procedures in such a way as to become highly efficient and accurate, whereas developing adaptive expertise requires an individual to develop conceptual understanding that allows the "expert" to invent new solutions to problems and even new procedures for solving problems. To illustrate, imagine two sushi chefs: one who makes every piece perfectly but routinely makes the same few types over and over, and one produces new menus frequently. To some, this is an unfair comparison, as ones' environment supports behavior. For example, the routine of the classic expert sushi chef may be tied to his restaurant environment, and this chef may be able to break out of the routines easily given a different situation. However, the adaptive expert chef clearly demonstrates flexible knowledge and performance of sushi-making. Learning Scientists are interested in adaptive expertise, in part because they would like to understand the types of learning trajectories that may allow practitioners break free from routines when necessary.
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