Deciding When and How to Use AI in EFL Speaking Instruction: Evidence from Surveys and Teacher Interviews

Abstract

The integration of Artificial Intelligence (AI) in English as a Foreign Language (EFL) instruction has expanded rapidly, yet little is known about how teachers make pedagogical decisions regarding AI use in speaking classrooms. This study investigates how EFL teachers explain and justify their decisions about when and how to use AI tools in speaking instruction, employing a convergent mixed-methods design. Quantitative data were collected through a survey of 24 teachers, analyzed using descriptive statistics, while qualitative insights were obtained from semi-structured interviews with 12 teachers, analyzed thematically. Findings reveal that teachers adopt a selective, context-sensitive approach, prioritizing AI for pronunciation practice and fluency exercises, where immediate feedback and structured practice are most effective. Teachers exercise professional judgment to balance AI affordances with pedagogical objectives, contextual constraints, and ethical considerations, ensuring that AI supplements rather than replaces human interaction. The study highlights the multidimensional nature of teacher agency in AI-supported speaking instruction and provides practical implications for professional development and curriculum design. Future research could examine AI integration across other language skills, diverse educational contexts, and longitudinal impacts on learners’ speaking proficiency and autonomy.

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