EFL students’ perceptions about the role of generative artificial intelligence (GAI)-mediated instruction in their emotional engagement and goal orientation: A motivational climate theory (MCT) perspective in focus

Abstract

Research on the contributions of generative artificial intelligence (GAI) technologies to second language (L2) education has soared in the past couple of years. However, there is limited evidence pertaining to the impact of AI-mediated instruction on postgraduate students’ psycho-affective factors and the overall learning climate in English as a foreign language (EFL) context. To address this gap, the present study drew on motivational climate theory (MCT) to explore postgraduate EFL students’ perceptions of the role of GAI technologies in their emotional engagement and goal orientation. To do so, an interview was conducted with 30 postgraduate students using maximum variation sampling. The results of the inductive thematic analysis revealed that AI-mediated instruction had affected both the emotional engagement and goal orientation of the students. In particular, it was found that GAI tools fostered emotional engagement by ‘enlightening teacher-student classroom relationships’, ‘making the overall classroom culture/climate engaging, motivating, and updated’, ‘improving teachers’ action, instruction, and feedback quality’, ‘providing a personalized, interactive, and autonomy supporting education’, and ‘taping into learner-specific idiosyncrasies and individual differences’. Furthermore, GAI tools affected the students’ goal orientation by ‘facilitating the mastery of course content’, ‘setting personalized and achievable goals’, ‘fostering students’ performance comparison in the classroom’, and ‘providing a reflective and adaptive learning environment’. The findings are discussed and implications are provided for EFL teachers, students, teacher educators, and policymakers concerning the interplay of GAI, emotions, goal orientation, and motivational climate.