Learning to Read in Chinese: A Meta-analytic Structural Equation Modeling Analysis of Cognitive-Linguistic Skills in Chinese Word Reading

Resumen

This paper reports the first meta-analytic structural equation modeling of lower-level cognitive-linguistic predictors (rapid automatized naming/RAN, orthographic awareness/OA, phonological awareness/PA, morphological awareness/MA, and vocabulary) on word reading among native Chinese-speaking children, based on pooled correlational matrices (k = 288; N = 47,121). Moderator analyses explored how the (relative) effects of these skills varied across readers of different Chinese scripts (simplified vs. traditional), methods of literacy instruction (without or with a phonetic coding system), and grade levels. We found that (1) all skills significantly and independently affected word reading with the meaning-based pathways (MA and vocabulary) playing the most salient role; (2) children reading traditional script relied more heavily on MA than those reading simplified script; (3) receiving phonological instruction strengthened the role of PA but reduced reliance on MA in word reading; and (4) developmentally, children gradually shifted from greater reliance on a more phonology-based strategy (i.e., a more salient role of PA) to a meaning-based strategy (i.e., more salient roles of MA and vocabulary) in word reading, while the effects of OA and RAN remained stable. These findings demonstrated the interplaying effects of cognitive-linguistic skills in Chinese word reading. They reaffirmed universal and language/script-specific processes in reading acquisition, while also underscoring the differential orchestration and optimization of component processes in reading acquisition across contexts and developmental stages.

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Cómo citar (APA 7)

Li, X., Zhang, D., Liu, S., & Liu, Y. (2025). Learning to Read in Chinese: A Meta-analytic Structural Equation Modeling Analysis of Cognitive-Linguistic Skills in Chinese Word Reading. https://doi.org/10.31234/osf.io/7qwre_v2