AI-Empowered English Oral Instruction: Evolving Principles and Implications for the Development of Pre-Service English Teachers

Abstract

Artificial intelligence is reshaping foreign language education. In English oral instruction, AI offers new pathways to address persistent challenges—student reluctance to speak, limited practice time, and inadequate feedback. This paper first reviews three foundational principles of oral instructional design: design speaking activities that motivate the students to speak, design speaking activities that maximize student talking time and design speaking activities that provide clear instructions. Drawing on AI’s core affordances and existing empirical evidence, the study then proposes three corresponding AI-empowered principles: designing immersive activities that stimulate willingness to speak; designing intelligent activities that enable ample practice with precise feedback; and designing activities that deliver clear instructions with cognitive support. Findings indicate that AI, through immersive scenario construction, instant feedback, and multimodal presentation, effectively reduces oral anxiety, expands practice boundaries, and improves instructional efficiency. For pre-service English teachers—who are both learners and future educators—AI-empowered oral instruction requires them to experience intelligent learning as learners and, as prospective teachers, to develop AI-integrated instructional design competence. The study thus recommends systematic reform of pre-service teacher preparation across competency frameworks, curricula, and training models—incorporating AI-empowered oral teaching competencies into core literacy standards and facilitating the learner-to-designer transition through an “experience–analysis–design” trajectory, thereby advancing the intelligent transformation of foreign language teacher education.