The Technology Acceptance Model in EFL Contexts: Examining Motivation as a Mediator Between Teachers' Writing Self-Efficacy and AI Adoption

Despite extensive research on self-efficacy, motivation, and artificial intelligence (AI) in English as a foreign language (EFL) education, their interrelationships remain underexplored. This study targets Iranian EFL teachers' self-efficacy in writing, their writing motivation, and tendency to use AI in academic writing by examining the relationship between these constructs. A quantitative, correlational design was employed. A total of ۲۵۰ EFL teachers were selected via convenience sampling and completed three validated scales: The Academic Writing Self-Efficacy Questionnaire (AWSEQ) to measure writing self-efficacy, the Motivation in Writing Questionnaire (Cahyono & Rahayu, ۲۰۲۰) to measure writing motivation, and the AI Acceptance in Academic Writing scale (Farahian & Rezaee, ۲۰۲۵) to measure AI acceptance. Pearson correlation analyses indicated a strong, positive relationship between self-efficacy and motivation, and weaker but significant relationships between motivation and AI acceptance and self-efficacy and AI acceptance. Furthermore, Structural Equation Modeling (SEM) revealed that teachers' self-efficacy in writing acted as a significant predictor influencing motivation and the tendency to use AI in writing. Furthermore, motivation in writing was identified as a significant partial mediator between self-efficacy and AI acceptance. This suggests that while teachers' confidence directly encourages AI use, a portion of its influence works by first boosting their motivation to write. The results of the study are analyzed in the light of the available literature and suggestions for further studies have been presented.

کلیدواژه ها:

self-efficacy ، Motivation ، Artificial Intelligence (AI) ، academic writing ، EFL teachers