<![CDATA[This study aims to provide insight and a deeper understanding of how technology acceptance contributes to the development of metacognitive engagement in EFL students by integrating the self-regulatory learning process. This study employed a correlational survey design. The data were collected using a questionnaire based on the Technology Acceptance Model (TAM) and Self-Regulated Learning (SRL), both of which are previously validated. Data analysis was performed using descriptive statistics and Partial Least Squares-Structural Equation Modeling (PLS-SEM). In this model, metacognitive engagement was represented as a second-order construct comprising the SRL dimensions. Model evaluation included testing the measurement model (construct validity and reliability) and the structural model to examine the influence of perceived usefulness and ease of use on metacognitive engagement in AI-assisted writing. The findings revealed that the proposed structural model demonstrated substantial predictive power, with Perceived Usefulness and Perceived Ease of Use jointly explaining 64.7% of the variance in EFL students’ metacognitive engagement in AI-assisted writing (R² = 0.647). Perceived Usefulness (β = 0.498, t = 9.132, p < .001) and Perceived Ease of Use (β = 0.386, t = 6.421, p < .001) had significant positive effects on metacognitive engagement. These results confirmed the H1 and H2 hypotheses proposed in this study, indicating that technology acceptance is significantly associated with self-regulated learning processes underlying metacognitive engagement, thereby providing empirical support for H3. The findings demonstrate that technology acceptance significantly enhances metacognitive engagement in AI-assisted EFL writing. This suggests that AI tools play a meaningful role in fostering reflective, self-regulated writing practices among EFL learners. Keywords: AI-assisted writing, technology acceptance, self-regulated learning, metacognitive engagement, PLS-SEM.]]>
Copyrights © 2026
