Applying meta-analytic structural equation modeling to second language research: An introduction

Raeisi-Vanani, Amin; Plonsky, Luke; Wang, Wei; Lee, Kejin; Peng, Peng

doi:10.1016/j.rmal.2022.100018

Cited by 7 publications

(6 citation statements)

References 50 publications

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“…Another motivation for replicating meta-analysis lies in its methodological progress that enables the exploration of questions left unresolved in previous meta-analyses (Plonsky, 2012). This aligns with the stringent definition of replication, or a series of modified repetitions of an original study (Porte & McManus, 2019). The 2014 and 2022 studies concluded that their unresolved issue was the establishment of a comprehensive model of L2 reading comprehension.…”

Section: Introductionsupporting

confidence: 52%

“…The potential of this theory to characterize strengths and weaknesses in L2 readers has also been discussed both theoretically (Sparks, 2021) and empirically (Verhoeven & van Leeuwe, 2012). While the traditional meta-analysis, as employed in the 2014 and 2022 studies, is prevalent in the field of L2 research, it only provides aggregated results of bivariate relationships (e.g., L2 reading comprehension and vocabulary, grammar, and metacognitive knowledge) and small-scale interactions among them (Raeisi-Vanani et al, 2022). This limitation impedes the investigation of questions concerning the extent to which interactions among these components predict variance in L2 reading comprehension, aligning with the SVR framework.…”

Section: Introductionmentioning

confidence: 99%

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Robust evidence for the simple view of second language reading: Secondary meta-analysis of Jeon and Yamashita (2022)

Hamada,

Shimizu,

Hoshino

et al. 2024

Stud Second Lang Acquis

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This paper reports a complete secondary analysis of Jeon and Yamashita’s (2022) systematic review to build the second language (L2) model of the simple view of reading (SVR). The same meta-analytic methodologies were maintained, with the exception of applying meta-analytic structural equation modeling (MASEM). This study successfully replicated some of the aggregated correlations but not others, owing to (a) the recoding of the original raw data to recreate a dataset and (b) the motivated change in sample selection from a longitudinal study for MASEM. The MASEM results extended previous findings that L2 comprehension skills contribute more to L2 reading comprehension than L2 decoding skills, and together explain a large amount of variance in L2 reading comprehension. The SVR model with metalinguistic skills showed their contribution to L2 decoding and comprehension skills, but no direct impact on L2 reading comprehension, supporting the parsimonious structure of SVR in L2.

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Section: Introductionsupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Robust evidence for the simple view of second language reading: Secondary meta-analysis of Jeon and Yamashita (2022)

Hamada,

Shimizu,

Hoshino

et al. 2024

Stud Second Lang Acquis

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show abstract

“…In the last two decades or so, research syntheses have gained considerable traction in second language (L2) research (Chong & Plonsky, 2023; Raeisi-Vanani et al, 2022). One form of research synthesis that has become particularly popular in L2 research is the classic meta-analysis.…”

Section: Introductionmentioning

confidence: 99%

Meta-analysis of second language research with complex research designs

Norouzian

Bui

2023

Stud Second Lang Acquis

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Meta-analyses play an instrumental role in informing second language (L2) theory and practice. However, current (i.e., classic) approaches to meta-analysis are limited in their ability to do so because they often fail to capture the complexity inherent in primary studies’ research designs. As we argue in this article, when complex L2 studies are represented by simplistic meta-analyses, the latter cannot reach its potential to contribute to the development of cumulative knowledge. To mitigate this issue, we first discuss the fundamental problems of the classic approaches to meta-analysis of complex L2 research. Second, we introduce an alternative meta-analytic framework that will address those problems. Third, we apply the meta-analytic framework discussed to a complex L2 domain. Fourth, we offer free software to facilitate the conduct of the alternative meta-analytic approach described. Finally, we discuss the implications of this alternative framework for making evidence-based recommendations to the relevant stakeholders.

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“…This approach combines the strengths of meta-analysis, which quantitatively summarises the results of individual studies and structural equation modelling. MASEM is a widely used statistical technique in educational research for synthesising and integrating data from multiple studies because of its ability to synthesise data from multiple studies and estimate a weighted average effect size, which measures the strength of the relationship between two variables (Cheung, 2019;Furlow & Beretvas, 2010;Herhausen et al, 2021;Raeisi-Vanani et al, 2022). It allows researchers to overcome the limitations of individual studies and arrive at a more comprehensive and robust understanding of the relationship between educational variables and outcomes.…”

Section: Introductionmentioning

confidence: 99%

Examining Unified Theory of Acceptance and Use of Technology 2 through Meta-analytic Structural Equation Modelling

2023

JALT

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Like its predecessor, the Unified Theory of Technology and Use of Technology (UTAUT), UTAUT2 has been adopted, adapted and used in extended forms due to its simplicity, parsimony and robustness. This study synthesised 39 empirical studies based on the UTAUT2 model in educational contexts, using the One-stage Meta-Analysis and Structural Equation Modelling (OSMASEM). Although the findings in this study aligned with the initial findings by Ventakesh et al. ( 2012), the model did not perform well compared to those in the initial UTAUT2 study in the explained variance in both behavioural intention and use behaviour. When new relationships were introduced into the UTAUT2 model in this study, constructs like performance expectancy, hedonic motivation, social influence, and price value were new predictors of use behaviour. The meta-analytic structural equation modelling approach used in this study, OSMASEM, allows researchers to use past empirical study data to examine the UTAUT2 framework without replicating similar studies. Using OSMASEM, researchers could easily add past empirical data to train the UTAUT2 model to study the trends in technology acceptance and use in educational contexts.

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Applying meta-analytic structural equation modeling to second language research: An introduction

Cited by 7 publications

References 50 publications

Robust evidence for the simple view of second language reading: Secondary meta-analysis of Jeon and Yamashita (2022)

Robust evidence for the simple view of second language reading: Secondary meta-analysis of Jeon and Yamashita (2022)

Meta-analysis of second language research with complex research designs

Examining Unified Theory of Acceptance and Use of Technology 2 through Meta-analytic Structural Equation Modelling

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