EXPLORATORY STRUCTURAL EQUATION MODELING IN SECOND LANGUAGE RESEARCH AN APPLIED EXAMPLE USING THE DUALISTIC MODEL OF PASSION

• Published in: Studies in second language acquisition Vol. 44; no. 5; pp. 1477 - 1500
• Main Authors: Alamer, Abdullah, Marsh, Herbert
• Format: Journal Article
• Language: English
• Published: New York Cambridge University Press 01.12.2022
• Subjects: Construct Validity; Correlation; Discriminant Analysis; Error of Measurement; Factor Analysis; Factor Structure; Goodness of Fit; Language Research; Measurement; Predictive Validity; Psychometrics; Regulation; Researchers; Second Language Learning; Statistical analysis; Structural equation modeling; Structural Equation Models; Students; Syntax; Validity
• ISSN: 0272-2631; 1470-1545
• DOI: 10.1017/S0272263121000863

This study offers methodological synergy in the examination of factorial structure in second language (L2) research. It illustrates the effectiveness and flexibility of the recently developed exploratory structural equation modeling (ESEM) method, which integrates the advantages of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) into one complete measurement model. Two sets of data were collected using the L2 Passion Scale, which measures a dualistic model of passion. Study 1 participants were 220 L2 students. A comparison was made between the CFA and the ESEM models. The results demonstrated the superiority of the ESEM method relative to CFA in terms of better goodness-of-fit indices and realistic correlated factors. These results were replicated in another sample of 272 L2 students, providing support for the predictive validity using a structural ESEM model. Guidelines are provided and Mplus syntax files (codes) are included to help analysts apply the methods. We also make the data available publicly. Overall, this research demonstrated the usefulness of ESEM for examining the construct, discriminant, and convergent validity of L2 scales over CFA.