Arán Filippetti Vanessa, Richaud María Cristina
a Interdisciplinary Center of Mathematical and Experimental Psychology Research (CIIPME) , National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina.
Child Neuropsychol. 2017 Oct;23(7):864-888. doi: 10.1080/09297049.2016.1199665. Epub 2016 Jul 8.
Though the relationship between executive functions (EFs) and mathematical skills has been well documented, little is known about how both EFs and IQ differentially support diverse math domains in primary students. Inconsistency of results may be due to the statistical techniques employed, specifically, if the analysis is conducted with observed variables, i.e., regression analysis, or at the latent level, i.e., structural equation modeling (SEM). The current study explores the contribution of both EFs and IQ in mathematics through an SEM approach. A total of 118 8- to 12-year-olds were administered measures of EFs, crystallized (Gc) and fluid (Gf) intelligence, and math abilities (i.e., number production, mental calculus and arithmetical problem-solving). Confirmatory factor analysis (CFA) offered support for the three-factor solution of EFs: (1) working memory (WM), (2) shifting, and (3) inhibition. Regarding the relationship among EFs, IQ and math abilities, the results of the SEM analysis showed that (i) WM and age predict number production and mental calculus, and (ii) shifting and sex predict arithmetical problem-solving. In all of the SEM models, EFs partially or totally mediated the relationship between IQ, age and math achievement. These results suggest that EFs differentially supports math abilities in primary-school children and is a more significant predictor of math achievement than IQ level.
尽管执行功能(EFs)与数学技能之间的关系已有充分记录,但对于EFs和智商如何差异地支持小学生的不同数学领域,人们知之甚少。结果的不一致可能归因于所采用的统计技术,具体而言,分析是使用观察变量进行的,即回归分析,还是在潜在层面进行的,即结构方程模型(SEM)。本研究通过SEM方法探索了EFs和智商在数学方面的贡献。对118名8至12岁的儿童进行了EFs、晶体智力(Gc)和流体智力(Gf)以及数学能力(即数字生成、心算和算术问题解决)的测量。验证性因素分析(CFA)为EFs的三因素解决方案提供了支持:(1)工作记忆(WM),(2)转换,以及(3)抑制。关于EFs、智商和数学能力之间的关系,SEM分析结果表明:(i)WM和年龄预测数字生成和心算,以及(ii)转换和性别预测算术问题解决。在所有SEM模型中,EFs部分或完全介导了智商、年龄与数学成绩之间的关系。这些结果表明,EFs差异地支持小学儿童的数学能力,并且比智商水平更能显著预测数学成绩。