<p>Generative artificial intelligence (GenAI) chatbots, such as ChatGPT and ERNIE Bot, are documented to influence student learning experience and student engagement. However, factors affecting student engagement in GenAI chatbots learning context are less understood. Self-determination theory (SDT) suggests student basic needs satisfaction–autonomy, competence, and relatedness– are associated with student behavioral, cognitive, emotional and agentic engagement. Teacher support– autonomy, structure, and involvement– derived by the three SDT needs. Hence, this study aims to clarify how factors (i.e., teacher support, student needs satisfaction) affect student engagement in this GenAI context in second language (L2) education. It examines the mediating effect of needs satisfaction on the relationship between teacher support and student engagement with a chatbot Data was collected from 364 university students through a questionnaire. The participants learned English as second language with ERNIE Bot under teacher support for four sessions. Our results revealed that needs satisfaction could partially mediate the relationship between teacher support and student behavioral, cognitive, and agentic engagement. They also suggest that needs satisfaction fully mediates the relationship between teacher support and emotional engagement. These suggests that GenAI chatbots better emotionally engage students in language learning than teachers do. One possible explanation for this is that students found learning with chatbots to be enjoyable and stress-free in L2 education. The results suggest teachers should take AI chatbot’s affordance and student feeling into account for emotional engagement when using GenAI chatbots. We suggest future studies should include additional factors such as personality and peer support.</p>