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Investigating the Unique Predictors of Word-Problem Solving Using Meta-Analytic Structural Equation Modeling

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Abstract

The purpose of the present study is to clarify the contributions of cognitive skills (nonverbal reasoning, language comprehension, working memory, attention, processing speed) and academic skills (mathematics facts retrieval, mathematics computation, mathematics vocabulary, reading comprehension) in performing mathematics word problems among elementary school students. With the two-stage meta-analytic structural equation modeling approach, I synthesized 112 correlation matrices from 98 empirical studies (N = 111,346) and fitted the hypothesized partial mediation model. Overall, path analysis indicated that language comprehension, working memory, attention, mathematics vocabulary, and mathematics computation were unique predictors of word-problem solving. Subgroup analysis demonstrated different unique predictors for younger and older students to perform word problems (K-2nd grades versus 3rd–5th grades). Implications, limitations, and future directions are discussed.

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Acknowledgements

The author would like to thank Sarah Powell at University of Texas at Austin and Jiangang Zeng at Louisiana State University for helpful discussions.

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Lin, X. Investigating the Unique Predictors of Word-Problem Solving Using Meta-Analytic Structural Equation Modeling. Educ Psychol Rev 33, 1097–1124 (2021). https://doi.org/10.1007/s10648-020-09554-w

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