Innovative Models and Practical Pathways for AI-Enabled English Teaching in Vocational Education
Abstract
In the context of educational digital transformation and the high-quality development of vocational education, AI technology, with
its advantages of personalized adaptation, contextualized simulation, and intelligent feedback loop, provides a new pathway to the problems
in vocational education English teaching, such as curriculum-occupation disjunction and profession, outdated and rigid teaching methods, and
superficial assessment. Grounding in the vocational and practical nature of English teaching in vocational education, this study explores AI
enabled reform methodologies for vocational English teaching. It synthesizes actionable strategies to enhance the synergistic integration of
information technology and instructional practice, thereby establishing a theoretical foundation for elevating teaching quality and cultivating
globally competent technical talents, while providing implementable insights.
its advantages of personalized adaptation, contextualized simulation, and intelligent feedback loop, provides a new pathway to the problems
in vocational education English teaching, such as curriculum-occupation disjunction and profession, outdated and rigid teaching methods, and
superficial assessment. Grounding in the vocational and practical nature of English teaching in vocational education, this study explores AI
enabled reform methodologies for vocational English teaching. It synthesizes actionable strategies to enhance the synergistic integration of
information technology and instructional practice, thereby establishing a theoretical foundation for elevating teaching quality and cultivating
globally competent technical talents, while providing implementable insights.
Keywords
AI;Vocational Education; English Teaching; Innovative Model; Practical Pathway
Full Text:
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[2] Tingdong Ye, Jingliang Lai, Yan Ai. (2026) Visual Analysis of AI-Enabled Classroom Teaching in Vocational Education: From the Per
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[3] Zhiqun Zhao,Yuefan Yu. (2026) Generative AI-Enabled Teaching in Vocational Education: Theory and Case Studies [J]. Chinese Voca
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DOI: http://dx.doi.org/10.70711/aitr.v3i10.9203
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