心理学
认知心理学
应用心理学
认知科学
任务(项目管理)
德雷福斯技能获得模型
作者
K. Anders Ericsson,Ralf Krampe,Clemens Tesch-Römer
出处
期刊:Psychological Review
[American Psychological Association]
日期:1993-07-01
卷期号:100 (3): 363-406
被引量:6986
标识
DOI:10.1037/0033-295x.100.3.363
摘要
because observed behavior is the result of interactions between environmental factors and genes during the extended period of development. Therefore, to better understand expert and exceptional performance, we must require that the account specify the different environmental factors that could selectively promote and facilitate the achievement of such performance. In addition, recent research on expert performance and expertise (Chi, Glaser, & Farr, 1988; Ericsson & Smith, 1991a) has shown that important characteristics of experts' superior performance are acquired through experience and that the effect of practice on performance is larger than earlier believed possible. For this reason, an account of exceptional performance must specify the environmental circumstances, such as the duration and structure of activities, and necessary minimal biological attributes that lead to the acquisition of such characteristics and a corresponding level of performance. An account that explains how a majority of individuals can attain a given level of expert performance might seem inherently unable to explain the exceptional performance of only a small number of individuals. However, if such an empirical account could be empirically supported, then the extreme characteristics of experts could be viewed as having been acquired through learning and adaptation, and studies of expert performance could provide unique insights into the possibilities and limits of change in cognitive capacities and bodily functions. In this article we propose a theoretical framework that explains expert performance in terms of acquired characteristics resulting from extended deliberate practice and that limits the role of innate (inherited) characteristics to general levels of activity and emotionality. We provide empirical support from two new studies and from already published evidence on expert performance in many different domains.
科研通智能强力驱动
Strongly Powered by AbleSci AI