Teacher and peer support in AI-assisted Chinese EFL learning: A phenomenological study of emotional support and classroom atmosphere.

The impact of artificial intelligence (AI) on educational practices presents new opportunities and challenges for learners and teachers. Although AI tools deliver automated feedback and real-time suggestions for customized learning, the necessity of face-to-face interaction remains. This phenomenological study, focusing on Chinese undergraduate English-as-a-Foreign Language (EFL) learners, examined the interdependence of teacher and peer support in AI-assisted English learning environments. Purposeful sampling identified twenty-two learners who took a semester-long AI-assisted English course at a Chinese comprehensive university. This course offered teacher instruction, AI-assisted activities, collaborative peer work thus, it provided a rich context for examining the interaction of different support systems. Data were collected through semi-structured interviews and narrative frames to gain a reflective portrayal of learners' experiences. Four interconnected themes were uncovered through phenomenological analysis: (1) Teacher Support as Emotional and Interpretive Scaffolding, (2) Peer Support as Collaborative Resilience, (3) Interplay of Teacher and Peer Support in Shaping Classroom Atmosphere, and (4) Emotional Intelligence and Situated Persistence in AI-Assisted Learning. Teacher support was found to bolster learners' confidence, alleviate anxiety, and aid in the interpretation of AI feedback, whereas peer support nurtured mutual problem-solving and empathy. The collaboration of teacher and peer support drove a positive, inclusive atmosphere within the classroom, reinforcing the emotional regulation and perseverance of learners. These findings highlight the necessity of human interaction in AI-assisted language learning and offer significant implications to language teachers, EFL learners, and materials developers.