Iglesias-Sarmiento V, Carriedo N, Rodríguez-Villagra OA, Pérez L. Executive functioning skills and (low) math achievement in primary and secondary school.
J Exp Child Psychol 2023;
235:105715. [PMID:
37307647 DOI:
10.1016/j.jecp.2023.105715]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 05/12/2023] [Accepted: 05/19/2023] [Indexed: 06/14/2023]
Abstract
Schoolchildren with better executive functioning skills achieve better mathematics results. It is less clear how inhibition, cognitive flexibility, and working memory combine to predict mathematics achievement and difficulty throughout primary and secondary school. This study aimed to find the best combination of executive function measures for predicting mathematical achievement in Grades 2, 6, and 10 and to test whether this combination predicts the probability of having mathematical difficulties across school grades even when fluid intelligence and processing speed were included in the models. A total of 426 students-141 2nd graders (72 girls), 143 6th graders (72 girls), and 142 10th graders (79 girls)-were cross-sectionally assessed with 12 executive tasks, one standardized mathematical task, and a standardized test of intelligence. Bayesian regression analyses found various combinations of executive predictors of mathematical achievement for each school grade spanning Grade 2 to measures of cognitive inhibition (negative priming) and cognitive flexibility (verbal fluency); Grade 6 to measures of inhibition: resistance to distractor interference (receptive attention), cognitive flexibility (local-global), and working memory (counting span); and Grade 10 to measures of inhibition: resistance to distractor interference (receptive attention) and prepotent response inhibition (stop signal) and working memory (reading span). Logistic regression showed that the executive models derived from the Bayesian analyses had a similar ability to classify students with mathematical difficulty and their peers with typical achievement to broader cognitive models that included fluid intelligence and processing speed. Measures of processing speed, cognitive flexibility (local-global), and prepotent response inhibition (stop signal) were the main risk factors in Grades 2, 6, and 10, respectively. Cognitive flexibility (verbal fluency) in Grade 2 and fluid intelligence, which was more stable in all three grades, acted as protective factors against mathematical difficulty. These findings inform practical considerations for establishing preventive and intervention proposals.
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