Presentation Roles of Task Complexity and Language Proficiency in AI Chatbot-Mediated English Speaking Task more

Previous research on technology-mediated task-based language teaching has primarily examined how technological tools and task design influence English speaking performance. However, limited attention has been given to how varying levels of task complexity interact with learners’ language proficiency. Accordingly, this study investigates the effects of task complexity and language proficiency on English speaking performance, speaking anxiety, and willingness to communicate among Taiwanese undergraduate students in AI chatbot-mediated speaking tasks. A total of 160 undergraduates participated. Eighty students with low English proficiency were randomly assigned to either a low-proficiency simple-task group or a low-proficiency complex-task group (40 students each). Another 80 students with high English proficiency were randomly assigned to a high-proficiency simple-task group or a high-proficiency complex-task group (40 students each). Data were collected through pre- and post-speaking tests, pre- and post-surveys, and semi-structured interviews. The expected results will demonstrate that different levels of AI chatbot-mediated speaking task complexity differentially affect learners’ speaking performance across proficiency levels, while also reducing speaking anxiety and enhancing willingness to communicate. Interview results will further indicate generally positive learner perceptions toward integrating AI chatbots into speaking tasks. Overall, this study offers pedagogical insights for the design of AI-mediated task-based speaking instruction.