Structural Equation Modeling in L2 Research: A Systematic Review

Structural equation modeling (SEM), as a flexible and versatile multivariate statistical technique, has been growingly used since its introduction in the 1970s. This article presents a methodological synthesis of the characteristics of the use of SEM in L2 research by examining the reporting practices in light of the current SEM literature to eventually provide some empirically grounded recommendations for future research. A total of 722 instances of SEM found in 145 empirical reports published in 16 leading L2 journals across two periods of 1981-2008 and 2009-2020 were systematically reviewed. Each study was coded for a wide range of analytic and reporting practices. The results indicate that despite the growing popularity of SEM in L2 research, there was a wide variation and inconsistency in its uses and reports within and across the two periods in regard to the underlying assumptions, variables and models, model specification and estimation, and fit statistics. Drawing on the current SEM literature, we will discuss the findings and research implications for future use and reporting of SEM in L2 research.