Pathways and Practices for Reforming English Language Teaching in Higher Vocational Colleges through Artificial Intelligence

Abstract

Rapid advances in artificial intelligence (AI) are fundamentally transforming global education and teaching practices. Generative AI, large language models, and intelligent interactive tools are creating unprecedented possibilities for English language teaching in higher vocational colleges. As a public foundational course in vocational education, English teaching is expected not only to develop students’ basic language skills but also to robustly support their career development, workplace communication, and intercultural interaction. However, conventional teaching practices still face significant limitations in aligning course content with specific occupational contexts, providing individualized learning support, promoting active classroom interaction, and accurately evaluating learning outcomes. This paper systematically examines the underlying rationale and practical challenges of applying AI to English language teaching in higher vocational colleges. Drawing on the core objectives of modern vocational education, it proposes a comprehensive reform framework covering learning objectives, teaching resources, instructional implementation, learning assessment, and teacher professional development. Furthermore, it explores an innovative teaching model oriented toward occupational competence, supported by human–AI collaboration and informed by real-time learning-process data. The proposed approach aims to facilitate a critical shift from traditional knowledge transmission to applied language use, from uniform instruction to highly personalized learning, and from purely outcome-based assessment to a comprehensive evaluation combining both process and results. Ultimately, this study offers practical, actionable insights for the digital transformation of English language teaching and the continuous improvement of talent cultivation in higher vocational education.