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The Structure of Working Memory in Young Children and Its Relation to Intelligence

Overview
Journal J Mem Lang
Publisher Elsevier
Date 2016 Dec 20
PMID 27990060
Citations 46
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Abstract

This study investigated the structure of working memory in young school-age children by testing the fit of three competing theoretical models using a wide variety of tasks. The best fitting models were then used to assess the relationship between working memory and nonverbal measures of fluid reasoning () and visual processing () intelligence. One hundred sixty-eight English-speaking 7-9 year olds with typical development, from three states, participated. Results showed that Cowan's three-factor embedded processes model fit the data slightly better than Baddeley and Hitch's (1974) three-factor model (specified according to Baddeley, 1986) and decisively better than Baddeley's (2000) four-factor model that included an episodic buffer. The focus of attention factor in Cowan's model was a significant predictor of and . The results suggest that the focus of attention, rather than storage, drives the relationship between working memory, , and in young school-age children. Our results do not rule out the Baddeley and Hitch model, but they place constraints on both it and Cowan's model. A common attentional component is needed for feature binding, running digit span, and visual short-term memory tasks; phonological storage is separate, as is a component of central executive processing involved in task manipulation. The results contribute to a zeitgeist in which working memory models are coming together on common ground (cf. Cowan, Saults, & Blume, 2014; Hu, Allen, Baddeley, & Hitch, 2016).

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References
1.
Engle R, Tuholski S, Laughlin J, Conway A . Working memory, short-term memory, and general fluid intelligence: a latent-variable approach. J Exp Psychol Gen. 1999; 128(3):309-331. DOI: 10.1037//0096-3445.128.3.309. View

2.
Baddeley . The episodic buffer: a new component of working memory?. Trends Cogn Sci. 2000; 4(11):417-423. DOI: 10.1016/s1364-6613(00)01538-2. View

3.
Cowan N . The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav Brain Sci. 2001; 24(1):87-114; discussion 114-85. DOI: 10.1017/s0140525x01003922. View

4.
Oberauer K . Access to information in working memory: exploring the focus of attention. J Exp Psychol Learn Mem Cogn. 2002; 28(3):411-21. View

5.
Kane M, Engle R . Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to Stroop interference. J Exp Psychol Gen. 2003; 132(1):47-70. DOI: 10.1037/0096-3445.132.1.47. View