The extended UTAUT model’s impact on English learning behavioral intentions in AI-IDLE contexts: the roles of grit, flow, and basic psychological needs

This study examined the factors that affect learners’ behavioral intentions to engage with AI-mediated informal digital learning of English (AI-IDLE). Using the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model, it examined the mediating roles of grit and flow, and the moderating roles of basic psychological needs (perceived autonomy, perceived competence, and perceived relatedness) between independent variables (performance expectancy, effort expectancy, social influence, facilitating conditions, and self-efficacy) and the dependent variable (behavioral intentions). Data from 559 EFL learners in mainland China were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings revealed that social influence, facilitating conditions, self-efficacy, and flow significantly affected behavioral intentions. Flow served as an important mediator between UTAUT constructs and behavioral intentions, while grit did not have a mediating role. Additionally, basic psychological needs moderated several relationships, highlighting the importance of personalized learning experiences in AI-IDLE. These findings suggest targeted interventions based on their psychological needs to enhance learner engagement.