On the Relationship Between Students' Perceived Support, Students' Self-Efficacy, and Affect-Emotions in AI-Enhanced Learning Environments

In response to the growing integration of artificial intelligence (AI) in educational settings, particularly in language learning, there is a pressing need to understand the psychological and pedagogical factors that influence learners' emotional and academic experiences. EFL learners were selected for this study because language learning involves high levels of emotional engagement, communicative interaction, and cognitive challenge—factors that are especially sensitive to perceived support and self-efficacy in AI-enhanced environments. Building on this foundation, the present study aimed to investigate the complex interactions between teacher support, student self-efficacy, and emotional responses, acknowledging the crucial role these variables play in shaping effective, motivational learning experiences for EFL students. It involved 1115 English as a foreign language (EFL) students from diverse Chinese universities, using convenience sampling for a representative mix of academic levels. Instruments included the teacher support scale (TSS), the college academic self-efficacy scale (CASES), and the emotion scale. Advanced statistical tools like SPSS v27 and AMOS v24 enabled structural equation modelling (SEM) to explore these relationships. Results showed that teacher support and student self-efficacy together explain 57% of emotional variance. Specifically, teacher support alone accounted for 55%, emphasising its role in positive emotional experiences. Student self-efficacy contributed uniquely with 44%, enhancing confidence and motivation in AI-enhanced learning. Overall, the study underscores the significant impact of both teacher support and student self-efficacy on the emotional well-being of EFL students in such learning environments.