Experts' memory superiority for domain-specific random material generalizes across fields of expertise: A meta-analysis

Sala, G ORCID: 0000-0002-1589-3759 and Gobet, F ORCID: 0000-0002-9317-6886 (2017) Experts' memory superiority for domain-specific random material generalizes across fields of expertise: A meta-analysis. Memory and Cognition, 45 (2). pp. 183-193.

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Abstract

Experts’ remarkable ability to recall meaningful domain-specific material is a classic result in cognitive psychology. Influential explanations for this ability have focused on the acquisition of high-level structures (e.g., schemata) or experts’ capability to process information holistically. However, research on chess players suggests that experts maintain some reliable memory advantage over novices when random stimuli (e.g., shuffled chess positions) are presented. This skill effect cannot be explained by theories emphasizing high-level memory structures or holistic processing of stimuli, because random material does not contain large structures nor wholes. By contrast, theories hypothesizing the presence of small memory structures—such as chunks—predict this outcome, because some chunks still occur by chance in the stimuli, even after randomization. The current meta-analysis assessed the correlation between level of expertise and recall of random material in diverse domains. The overall correlation was moderate but statistically significant (r¯¯=.41,p<.001), and the effect was observed in nearly every study. This outcome suggests that experts partly base their superiority on a vaster amount of small memory structures, in addition to high-level structures or holistic processing. A classic result in cognitive psychology is that experts have an excellent memory for meaningful material taken from their domain of expertise, even when this material is presented only briefly. This result was originally uncovered by De Groot’s (1965) and Chase and Simon’s (1973) study of chess players, and later replicated in many domains, including sports, science, engineering, and games (see Ericsson, Charness, Feltovich, & Hoffman, 2006; Gobet, 2015, for overviews). Experts’ superiority has often been explained by the acquisition of high-level knowledge structures (Chi, Feltovich, & Glaser, 1981; Cooke, Atlas, Lane, & Berger, 1993; Holding & Pfau, 1985; Kalyuga, Ayres, Chandler, & Sweller, 2003; Patel & Groen, 1986), or the ability to process information holistically, unlike nonexperts who have to process it piecemeal or analytically (Curby, Glazek, & Gauthier, 2009; Dreyfus & Dreyfus, 1986; Richler, Wong, & Gauthier, 2011). High-level knowledge structures, such as schemata and verbal concepts, abstract from the detail of the material to memorize. For example, in chess, a complex position could be summarized by the description “an Italian opening, variation Giuoco Pianissimo, with White’s pressure on the white squares.” With holistic processing, it is assumed that the scene or object being perceived is not decomposed into simpler units, but is processed as a unified whole. In a meta-analysis of 13 studies, Gobet and Simon (1996b) showed that, at least with chess, these explanations were not sufficient to explain experts’ superiority. They found that experts maintained some superiority with random positions, in which any high-level structure had been destroyed. With such positions, experts’ advantage cannot be explained by the use of high-level structures (by construction, these do not exist in random positions) nor by holistic processing (there is no whole to process after the location of pieces has been randomized). Gobet and Simon’s (1996b) result was predicted by computer simulations based on the mechanism of chunking (Gobet & Simon, 1996a). As proposed by Chase and Simon (1973), expertise in chess is acquired by learning, through practice and study, a large number of chunks, which are units of both perception and meaning; in chess, chunks consist of constellations of pieces occurring often together in masters’ games. Experts’ superiority with meaningful material (game positions in chess) is explained by their ability to rapidly identify patterns present on the board, and retrieve chunks from their long-term memory (LTM). As shown by the computer simulations, some patterns still occur, by chance, in random positions; as experts are more likely to notice them due to their large store of chunks, they can maintain some superiority. Importantly, this superiority is not an artefact of the specific kind of randomization used, as proposed by Vicente and Wang (1998), because it is maintained with positions obtained with different methods of randomization (Gobet & Waters, 2003; Waters & Gobet, 2008). Gobet and Simon’s (1996b) result is important theoretically, as it can readily be explained by theories based on chunking, such as chunking theory (Chase & Simon, 1973) and template theory (Gobet & Simon, 1996c), but not by theories focusing on high-level representations or holistic processing. However, it is unknown whether this result generalizes to other domains of expertise beyond chess. Therefore, the aim of this study was to establish whether experts maintain some memory superiority with random stimuli in different domains of expertise. Support for this hypothesis would strongly corroborate theories based on chunking.

Item Type:	Article
Uncontrolled Keywords:	Memory, Recall, Expertise, Random, Meta-analysis
Depositing User:	Symplectic Admin
Date Deposited:	13 Feb 2017 09:08
Last Modified:	19 Jan 2023 07:26
DOI:	10.3758/s13421-016-0663-2
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3004290