Willingness to Communicate and its High-Evidence Factors: A Meta-Analytic Structural Equation Modeling Approach

This study aimed to synthesize the structural relationships among willingness to communicate (WTC) and its high-evidence factors in second language (L2) learning contexts by adopting meta-analytic structural equation modeling (MASEM). The MASEM approach is designed to construct a structural equation model (SEM) to explain correlations between variables by pooling correlation coefficients reported in previous literature. This study integrated 44 independent samples (N = 12,094) and built a MASEM model to investigate the structural relations of WTC, its three high-evidence factors (learners’ perceived L2 competence, L2 motivation, and L2 anxiety), and frequency of learners’ L2 use. The results of meta-analysis successfully supported our proposed model of L2 WTC. Furthermore, among the three high-evidence factors, it was found that learners’ perceived L2 competence influenced L2 WTC the most. In addition, the results of the moderator analyses indicated that learners’ L2 proficiency and WTC contexts (inside vs. outside classrooms) significantly influenced the relationships between L2 WTC and its high-evidence factors. The implications of these results are discussed in further depth and detail.