Foreign Languages Department, Southwest Forestry University, Kunming 650000, China
| Abstract: | In the context of big data and artificial intelligence, large language models (LLMs) have become pivotal tools for university English teachers around the world to reshape pedagogical concepts and optimize instructional pathways. This study investigates the motivational logic and behavioral features of AI-empowered teaching, focusing on Mr. L from a university in southwestern China. A mixed-methods approach was adopted, combining questionnaires, classroom observations, and in-depth interviews, to capture both quantitative and qualitative dimensions of teaching practice. The findings reveal that English teachers in university demonstrate diversified motivations, staged processes, and forward-looking goals in AI-assisted translation instruction. Their key motivations include enhancing students' translation competence, cultivating their AI literacy, and integrating technological applications. At the same time, teacher motivation is influenced by multiple factors, such as individual technological awareness, societal and institutional demands, and the teacher’s professional agency and pedagogical consciousness. The study concludes that AI-driven teaching motivations not only stimulate innovation in classroom methodology but also create new opportunities for reflective practice and professional growth. By presenting an empirical case, the research offers practical insights for foreign language educators seeking to navigate the challenges and opportunities of AI technologies, and provides useful references for promoting effective integration of AI into higher education. |
| Keywords: | AI-Empowered Teaching; Language Teaching Motivation; Educational Subjectivity |
| DOI: | 10.57237/j.ssrf.2025.04.002 |
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