Enhancing children’s numerical skills through a play-based intervention at kindergarten and at home: a quasi-experimental study

Chambrier, Anne-Françoise de; Baye, Ariane; Tinnes-Vigne, Mélanie; Tazouti, Youssef; Vlassis, Joëlle; Poncelet, Débora; Giauque, Nadine; Fagnant, Annick; Luxembourger, Christophe; Auquière, Amélie; Kerger, Sylvie; Dierendonck, Christophe

doi:10.1016/j.ecresq.2020.09.003

Cited by 24 publications

(20 citation statements)

References 102 publications

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“…A limitation of the research base on early math interventions conducted in informal learning environments is the lack of representation of children with disabilities. When studies reported disability information, it was to inform readers that children with disabilities were excluded from the intervention (e.g., de Chambrier et al, 2019; Starkey & Klein, 2000). This was surprising, since research consistently reports on the early achievement gaps that exist for children with or at-risk-of disabilities (Burchinal et al, 2011; Chu et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

A Meta-Analysis and Quality Review of Mathematics Interventions Conducted in Informal Learning Environments with Caregivers and Children

Nelson¹,

Carter

Boedeker

et al. 2023

Review of Educational Research

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The purposes of this study included conducting a meta-analysis and reviewing the study reporting quality of math interventions implemented in informal learning environments (e.g., the home) by children’s caregivers. This meta-analysis included 25 preschool to third-grade math interventions with 83 effect sizes that yielded a statistically significant summary effect (g = 0.26, 95% CI [0.07, 0.45) on children’s math achievement. Significant moderators of the treatment effect included the intensity of caregiver training and type of outcome measure. There were larger average effects for interventions with caregiver training that included follow-up support and for outcomes that were comprehensive early numeracy measures. Studies met 58.0% of reporting quality indicators, and analyses revealed that quality of reporting has improved in recent years. The results of this study offer several recommendations for researchers and practitioners, particularly given the growing evidence base of math interventions conducted in informal learning environments.

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Section: Discussionmentioning

confidence: 99%

A Meta-Analysis and Quality Review of Mathematics Interventions Conducted in Informal Learning Environments with Caregivers and Children

Nelson¹,

Carter

Boedeker

et al. 2023

Review of Educational Research

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“…Economic and educational policies and programs that help support early STEM experiences by addressing adverse childhood experiences as well as limited access to high-quality child care and preschool may also be benefical (McClure et al, 2017; Peters, 2021). Additional possiblities for addressing racial and ethnic disparities in advanced science and mathematics achievement include increasing children’s early exposure to science and mathematics content through universal pre-K (Amadon et al, 2022) and preschool interventions (Dumas et al, 2019), practices using validated school-based instructional methods (e.g., peer-assisted tutoring, small-group instruction, play-based games) (de Chambrier et al, 2021; Dietrichson et al, 2021), and increased access to challenging curricula and summer programs (Little et al, 2018; Olszewski-Kubilius & Corwith, 2018).…”

Section: Discussionmentioning

confidence: 99%

*Racial and Ethnic Disparities in Advanced Science and Mathematics Achievement During Elementary School

Morgan

Farkas

et al. 2022

Gifted Child Quarterly

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We analyzed a population-based cohort ( N = 10,922) to investigate the onset and stability of racial and ethnic disparities in advanced (i.e., above the 90th percentile) science and mathematics achievement during elementary school as well as the antecedent, opportunity, and propensity factors that explained these disparities. About 13% to 16% of White students versus 3% to 4% of Black or Hispanic students displayed advanced science or mathematics achievement during kindergarten. The antecedent factor of family socioeconomic status and the propensity factors of student science, mathematics, and reading achievement by kindergarten consistently explained whether students displayed advanced science or mathematics achievement during first, second, third, fourth, or fifth grade. These and additional factors substantially or fully explained initially observed disparities between Black or Hispanic and White students in advanced science or mathematics achievement during elementary school. Economic and educational policies designed to increase racial and ethnic representation in STEM course taking, degree completion, and workforce participation may need to begin by elementary school.

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“…The present article is based on pretest data collected during a quasi-experimental study conducted in four education systems in continental Europe (Belgium, France, Luxembourg and Switzerland), and aimed at measuring the efficacy of a 12 week numerical games intervention with pupils aged from 4 to 6 years (for details and results, see de Chambrier et al, 2021 ). There were 23 participating schools (46 classrooms) with pupils from mixed socio-economic backgrounds.…”

Section: Methodsmentioning

confidence: 99%

Investigating the Dimensionality of Early Numeracy Using the Bifactor Exploratory Structural Equation Modeling Framework

et al. 2021

Self Cite

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The few studies that have analyzed the factorial structure of early number skills have mainly used confirmatory factor analysis (CFA) and have yielded inconsistent results, since early numeracy is considered to be unidimensional, multidimensional or even underpinned by a general factor. Recently, the bifactor exploratory structural equation modeling (bifactor-ESEM)—which has been proposed as a way to overcome the shortcomings of both the CFA and the exploratory structural equation modeling (ESEM)—proved to be valuable to account for the multidimensionality and the hierarchical nature of several psychological constructs. The present study is the first to investigate the dimensionality of early number skills measurement through the application of the bifactor-ESEM framework. Using data from 644 prekindergarten and kindergarten children (4 to 6 years old), several competing models were contrasted: the one-factor CFA model; the independent cluster model (ICM-CFA); the exploratory structural equation modeling (ESEM); and their bifactor counterpart (bifactor-CFA and bifactor-ESEM, respectively). Results indicated acceptable fit indexes for the one-factor CFA and the ICM-CFA models and excellent fit for the others. Among these, the bifactor-ESEM with one general factor and three specific factors (Counting, Relations, Arithmetic) not only showed the best model fit, but also the best coherent factor loadings structure and full measurement invariance across gender. The bifactor-ESEM appears relevant to help disentangle and account for general and specific factors of early numerical ability. While early numerical ability appears to be mainly underpinned by a general factor whose exact nature still has to be determined, this study highlights that specific latent dimensions with substantive value also exist. Identifying these specific facets is important in order to increase quality of early numerical ability measurement, predictive validity, and for practical implications.

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Enhancing children’s numerical skills through a play-based intervention at kindergarten and at home: a quasi-experimental study

Cited by 24 publications

References 102 publications

A Meta-Analysis and Quality Review of Mathematics Interventions Conducted in Informal Learning Environments with Caregivers and Children

A Meta-Analysis and Quality Review of Mathematics Interventions Conducted in Informal Learning Environments with Caregivers and Children

*Racial and Ethnic Disparities in Advanced Science and Mathematics Achievement During Elementary School

Investigating the Dimensionality of Early Numeracy Using the Bifactor Exploratory Structural Equation Modeling Framework

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