With the continuous advancement of the digital education strategy, generative AI has been gradually integrated into university classrooms, bringing brand-new opportunities for the innovation of college English teaching models. Traditional college English teaching has long been plagued by numerous problems, making it difficult to meet the demands of foreign language talent cultivation in the new era. To address the current teaching dilemmas, this paper takes human-machine collaborative teaching theory and precision teaching theory as theoretical support, systematically sorts out the core characteristics of college English teaching empowered by generative AI, and constructs reform pathways for human-machine collaborative college English teaching under generative AI from five dimensions: reconstruction of teaching subjects, innovation of teaching content, optimization of teaching procedures, upgrading of teaching assessment, and improvement of teachers’ capabilities. The research findings facilitate the implementation of personalized and precise English teaching, and provide theoretical references and practical implications for digital teaching reform of college English in universities.

Yanming Li. Pathways of Human-Machine Collaborative Teaching Reform in College English Classrooms Driven by Generative AI. International Journal of New Developments in Education (2026), Vol. 8, Issue 6: 44-49. https://doi.org/10.25236/IJNDE.2026.080607.

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