Digital Multimodal Composing Competence and Writing Enjoyment: Modeling Self-Efficacy and Cognitive Engagement among EFL Students

As digital tools reshape academic writing, digital multimodal composing (DMC) is increasingly relevant in EFL contexts, yet links between digital multimodal composing competence, cognitive, and affective factors remain underdeveloped. This study investigated the direct and indirect relationships among digital multimodal composing competence (DMCC), academic writing self-efficacy (AWSE), cognitive engagement (CE), and writing enjoyment (WE) in higher education. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), data from 215 students across 18 universities were analyzed. Results revealed that DMCC strongly predicted AWSE and also significantly predicted CE and WE. AWSE significantly influenced CE and WE, while CE did not significantly predict WE. These findings highlight the mediating role of self-efficacy in linking digital competence to both cognitive engagement and writing enjoyment, suggesting that competence alone is insufficient without confidence. Pedagogically, scaffolded multimodal tasks with reflective guidance can strengthen competence and confidence, leading to greater cognitive engagement and enjoyment in writing. Future research should examine additional mediators and adopt longitudinal or cross-cultural designs to validate and extend these findings.