مشخصات پژوهش

Significance of the Research The present study, drawing on the tenets of Social Cognitive Theory (Bandura, 1977, 2010) and Control-Value Theory (Pekrun, 2006), offers a broader lens for understanding the complex network of cognitive and affective variables such as AI literacy, AI self-efficacy, and AI-induced emotions that shape EFL learners’ engagement in Informal Digital Learning of English (IDLE). Given the limited empirical attention to how AI literacy is translated into IDLE engagement through the joint mediating roles of AI self-efficacy and AI-induced emotions among Iranian EFL learners, this area warrants systematic investigation. Addressing this gap, the present study contributes to the growing body of literature on AI-mediated language learning by positioning AI literacy as a foundational cognitive competence that does not directly translate into engagement but operates through layered psychological mechanisms. Specifically, by incorporating AI self-efficacy and AI-induced emotions as mediators, the study advances a more process-oriented understanding of how learners’ cognitive resources are filtered through motivational beliefs and affective experiences before being enacted in autonomous digital learning practices. This integrated model moves beyond linear explanations of technology use and instead conceptualizes IDLE engagement as the outcome of interacting cognitive-affective systems within AI-embedded learning ecologies. Theoretically, the study extends existing models of AI-mediated language learning by integrating Social Cognitive Theory and Control-Value Theory into a unified explanatory framework. In doing so, it highlights the complementary roles of self-efficacy as a motivational mechanism and emotions as value-based affective responses in shaping learner behavior. This integration contributes to a more fine-grained understanding of learner agency in digital environments and responds to the increasing need in CALL research for models that account