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Complex perceptual-cognitive expertise in a simulated task environment

Complex perceptual-cognitive expertise in a simulated task environment

Ward, Paul, Ericsson, K. Anders and Williams, A. Mark (2012) Complex perceptual-cognitive expertise in a simulated task environment. Journal of Cognitive Engineering and Decision Making, 7 (3). pp. 231-254. ISSN 1555-3434 (doi:https://doi.org/10.1177/1555343412461254)

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Abstract

In popular models of expertise and decision making in complex environments, such as the recognition primed decision (RPD) model and take-the-first (TTF) heuristic, expert and skilled decision makers are described as generating few response options and typically choose the best option first. To explain these behaviors, proponents of TTF have suggested that a negative relationship exists between the number of options generated and decision quality. In the current article, we use a prediction and situational option generation paradigm to assess perceptual-cognitive skill in the complex domain of soccer to determine whether these claims explain how decision makers make predictions about others in the environment. In three experiments we provide evidence to show that superior prediction performance was supported by a situation model-type mechanism as proposed by long-term working memory (LTWM) theory rather than simpler heuristics, such as TTF or RPD. The similarity between LTWM mechanisms and relevant macrocognitive processes is discussed. The data have important implications for how future experts should be trained and, in particular, for developing skilled comprehension, apprehension, and prediction skill.

Item Type: Article
Uncontrolled Keywords: anticipation, decision making, long-term working memory, option generation, prediction, recognition-primed decision model, take-the-first heuristic
Subjects: Q Science > QM Human anatomy
Q Science > QP Physiology
Pre-2014 Departments: School of Science
Last Modified: 14 Oct 2016 09:23
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/9521

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