درخت حوزه‌های تخصصی

Informal digital learning of English (IDLE) is now a routine part of many learners’ everyday media use, yet it remains unclear how these out-of-class digital practices translate into competence for real-world intercultural communication. Building on work that conceptualizes IDLE as both receptive and productive engagement, this study tested a mediation model in which EFL grit and classroom boredom help explain the link between IDLE and intercultural communicative competence (ICC). A cross-sectional online survey was administered to 219 intermediate Iranian EFL learners (aged 15–20) studying in private language schools in Urmia. After screening, 218 valid cases were retained for analysis. Measures included receptive and productive IDLE, ICC (25 items), EFL grit (18 items), and boredom in practical English classes (27 items). The hypothesized model was examined using partial least squares structural equation modelling with bootstrapped confidence intervals. Results indicated that both receptive and productive IDLE were positively associated with ICC. In addition, higher grit and lower classroom boredom partially mediated these relationships. The findings suggest that learners’ sustained effort (grit) and their classroom emotional experience (boredom) are key psychological routes through which everyday digital English engagement may contribute to intercultural development. Implications are discussed for connecting IDLE experiences to classroom reflection, reducing boredom, and supporting perseverance in EFL learning.

The growing integration of artificial intelligence (AI) into English language education has created new opportunities to enhance reading instruction. This study investigated the effect of AI-driven reading instruction on EFL learners’ reading autonomy and explored learners’ perceptions of AI-driven reading environments. A sequential explanatory mixed-methods design including a quasi-experimental pretest–posttest nonequivalent control-group design followed by the qualitative phase using extreme (polar) case sampling and semi-structured interviews, was employed during a five-week intervention. Fifty-four intermediate EFL learners from a Language school in Kerman, Iran were selected through Oxford Placement Test and were randomly assigned to an experimental group (n = 27), which received AI-driven reading instruction through ReadTheory, and a control group (n = 27), which received traditional reading instruction. Quantitative data were collected using pre- and post-tests of reading autonomy questionnaire, while qualitative data were obtained through semi-structured interviews. The quantitative data were analyzed using Analysis of Covariance (ANCOVA) after checking the required assumptions, and the interview data were analyzed through inductive thematic analysis. The findings revealed that AI-driven instruction significantly enhanced learners’ overall reading autonomy as well as its cognitive, metacognitive, affective-motivational, and action-oriented dimensions. However, no statistically significant improvement was found in the social dimension of reading autonomy. Furthermore, qualitative findings indicated that learners perceived ReadTheory as a tutor-like support system, providing personalized and adaptive learning for them. The study concludes that AI-driven platforms can serve as a valuable pedagogical tool for enhancing learners’ reading autonomy when integrated with appropriate instructional support.