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使用元结构方程模型构建认知-阅读成就关系的共识模型

Toward a Consensus Model of Cognitive-Reading Achievement Relations Using Meta-Structural Equation Modeling.

作者信息

Hajovsky Daniel B, Niileksela Christopher R, Flanagan Dawn P, Alfonso Vincent C, Schneider William Joel, Robbins Jacob

机构信息

Department of Educational Psychology, Texas A&M University, College Station, TX 77845, USA.

Department of Educational Psychology, University of Kansas, Lawrence, KS 66045, USA.

出版信息

J Intell. 2025 Aug 16;13(8):104. doi: 10.3390/jintelligence13080104.

DOI:10.3390/jintelligence13080104
PMID:40863201
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12387132/
Abstract

Cognitive tests measure psychological constructs that predict the development of academic skills. Research on cognitive-reading achievement relations has primarily been completed with single-test batteries and samples, resulting in inconsistencies across studies. The current study developed a consensus model of cognitive-reading achievement relations using meta-structural equation modeling (meta-SEM) through a cross-sectional analysis of subtest correlations from English-language norm-referenced tests. The full dataset used for this study included 49,959 correlations across 599 distinct correlation matrices. These included correlations among 1112 subtests extracted from 137 different cognitive and achievement test batteries. The meta-SEM approach allowed for increased sampling of cognitive and academic reading skills measured by various test batteries to better inform the validity of construct relations. The findings were generally consistent with previous research, suggesting that cognitive abilities are important predictors of reading skills and generalize across different test batteries and samples. The findings are also consistent with integrated cognitive-reading models and have implications for assessment and intervention frameworks.

摘要

认知测试测量的心理结构能够预测学术技能的发展。关于认知与阅读成绩关系的研究主要是使用单一测试组合和样本完成的,导致各研究结果不一致。本研究通过对英语常模参照测试的子测试相关性进行横断面分析,采用元结构方程建模(meta-SEM)建立了认知与阅读成绩关系的共识模型。本研究使用的完整数据集包括599个不同相关矩阵中的49959个相关性。这些相关性包括从137种不同的认知和成绩测试组合中提取的1112个子测试之间的相关性。元结构方程建模方法允许增加对各种测试组合所测量的认知和学术阅读技能的抽样,以便更好地了解结构关系的有效性。研究结果总体上与先前的研究一致,表明认知能力是阅读技能的重要预测因素,并且在不同的测试组合和样本中具有普遍性。研究结果也与综合认知-阅读模型一致,并对评估和干预框架具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/9b6a7d341ebb/jintelligence-13-00104-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/766184c6035d/jintelligence-13-00104-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/35f0c5784c0b/jintelligence-13-00104-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/9b6a7d341ebb/jintelligence-13-00104-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/766184c6035d/jintelligence-13-00104-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/35f0c5784c0b/jintelligence-13-00104-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8de0/12387132/9b6a7d341ebb/jintelligence-13-00104-g003.jpg

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