ASR technology in college English speaking instruction: the role of feedback internalization and metacognitive strategies

This study examines how Automatic Speech Recognition (ASR) technology can enhance college English speaking instruction by analyzing its interaction with metacognitive strategies and learner differences. Using questionnaire surveys, factor analysis, and structural equation modeling, we assess how ASR-generated feedback quality, structured reflection tasks, and usage frequency influence feedback internalization, reflective learning, and motivation. The results show that accurate error correction and well-designed reflection tasks significantly improve feedback processing and reflective behavior, while frequent ASR use primarily boosts reflection rather than motivation. Interestingly, ASR accuracy enhances intrinsic motivation but does not directly drive reflection. Language proficiency emerges as a key moderator, with more proficient learners internalizing feedback more effectively and achieving greater speaking gains. The study contributes to second language acquisition theory by integrating metacognitive strategies with ASR-assisted learning. It provides empirical support for intelligent teaching systems and practical guidance for improving oral English instruction, intercultural communication training, and personalized learning. By bridging technology and pedagogy, this research advances active learning methodologies, enhances speaking proficiency, and strengthens the global competitiveness of higher education.