Knowledge partitioning: Context-dependent use of expertise

Although exceptional performance is a defining attribute of expertise, expe rts sometimes exhibit striking errors and performance limitations. This art icle reports two experiments in which experts predicted the spread of bush fires, a domain characterized by complex but well-understood physical dynam ics. Although accuracy was typically high, large errors were observed when two primary predictor variables were in opposition. In a second study, the experts' behavior-in contrast to that of novices-was additionally shown to depend on problem context. In one context, experts again committed errors, whereas in another, equally domain-relevant context, the correct prediction s were made. Critically, when comparing performance across contexts, comple tely opposing predictions were made under identical physical conditions. We therefore suggest that expertise may comprise separate, and sometimes even mutually exclusive, components of knowledge.