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Meta-Analytic Structural Equation Models of Executive Functions and Math Intelligence in Preschool Children
Emslander, Valentin; Scherer, Ronny
2021PAEPSY 2021 Tagung der Fachgruppe Pädagogische Psychologie
 

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Keywords :
Executive Functions; Meta-Analytical Structural Equation Modeling; Preschool Children
Abstract :
[en] BACKGROUND: Response inhibition, attention shifting, and working memory updating are the three core executive functions (EFs; Miyake et al., 2000) underlying other cognitive skills that are relevant for learning and everyday life. For example, they have shown to be differentially related to the mathematical component of intelligence (i.e., math intelligence) in school students and adults. While researchers suppose these three EFs to become more differentiated from early childhood to adulthood, neither the link of these constructs nor their structure has been conclusively established in preschool children yet. Primary studies on path models connecting EFs and math intelligence diverge in the exact relation of EFs and math intelligence. It remains unclear whether inhibition, shifting, and updating exhibit distinct but correlated constructs with respect to their relation to math intelligence. OBJECTIVES: With our meta-analysis, we aimed to (a) synthesize the relation between the three EFs and math intelligence in preschool children; and (b) compare plausible models of the effects of EFs on math intelligence. METHODS/RESULTS: Synthesizing data from 47 studies (363 effect sizes, 30,481 participants) from the last two decades via novel multilevel and multivariate meta-analytic models (Pustejovsky & Tipton, 2020), we found the three core EFs to be significantly related to math intelligence: Inhibition ("r" ̅ = .30, 95 % CI [.25, .35]), shifting ("r" ̅ = .32, 95 % CI [.25, .38]), and updating ("r" ̅ = .36, 95 % CI [.31, .40]). Looking at the three core EFs as one construct, the correlation was "r" ̅ = .34, 95 % CI [.31, .37]. Utilizing correlation-based, meta-analytic structural equation modeling (Jak & Cheung, 2020), our results exhibited significant relations of all EFs to math intelligence. These relations did not differ between the three core EFs. DISCUSSION: Our findings corroborate the positive link between EFs and math intelligence in preschool children and are similar to other age groups. From the model testing, we learned that representing EFs by a latent variable, thus capturing the covariance among the three core EFs, explained substantially more variation in math intelligence than representing them as distinct constructs.
Research center :
- Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET)
Disciplines :
Education & instruction
Theoretical & cognitive psychology
Author, co-author :
Emslander, Valentin  ;  University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > LUCET
Scherer, Ronny;  University of Oslo - UiO > Centre for Educational Measurement at the University of Oslo (CEMO), Faculty of Educational Sciences
External co-authors :
yes
Language :
English
Title :
Meta-Analytic Structural Equation Models of Executive Functions and Math Intelligence in Preschool Children
Publication date :
September 2021
Event name :
PAEPSY 2021 Tagung der Fachgruppe Pädagogische Psychologie
Event organizer :
DGPs Fachgruppe Pädagogische Psychologie
Event date :
from 14-09-2021 to 16-09-2021
Audience :
International
References of the abstract :
Jak, S., & Cheung, M. W.-L. (2020). Meta-analytic structural equation modeling with moderating effects on SEM parameters. Psychological Methods, 25(4), 430–455. https://doi.org/10.1037/met0000245 Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis. Cognitive Psychology, 41(1), 49–100. https://doi.org/10.1006/cogp.1999.0734 Pustejovsky, J. E., & Tipton, E. (2020, September 14). Meta-Analysis with Robust Variance Estimation: Expanding the Range of Working Mod-els. https://doi.org/10.31222/osf.io/vyfcj
Focus Area :
Educational Sciences
Available on ORBilu :
since 24 August 2021

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