基于TPACK框架的高职英语教师人机协同教学能力困境与提升路径探索

An Exploration of the Dilemmas and Improvement Paths of Higher Vocational English Teachers’ Human-AI Collaborative Teaching Competence Based on the TPACK Framework

摘要: 人机协同教学已成为职业教育数字化转型的重要议题，高职英语教师教学能力结构也面临新的调整。本研究以TPACK框架为理论视角，采用文献分析法与半结构化深度访谈法，以四川文化传媒职业学院5位英语教师为探索对象。研究发现，教师主要面临工具选择与教学适配困难、人机职责边界模糊、培训与英语教学场景衔接不足、评价机制不完善四方面问题，这些问题相互影响，共同制约人机协同教学能力发展。基于此，本研究初步构建AI工具甄别与教学化适配、人机协同教学设计、学情诊断与精准反馈、教学反思与持续迭代四项能力，并提出院校场景化研修工作坊这一有待检验的提升路径，为高职英语教师专业发展提供参考。

Abstract: Human-AI collaborative teaching has become an important issue in the digital transformation of vocational education, and the competence structure of higher vocational English teachers is also facing new adjustments. Taking the TPACK framework as the theoretical perspective, this study adopts literature analysis and semi-structured in-depth interviews, with five English teachers from Sichuan Vocational College of Culture and Communication as the subjects of exploration. The study finds that teachers mainly face four types of problems: difficulty in tool selection and instructional adaptation, ambiguous division of human-AI responsibilities, insufficient connection between training and English teaching scenarios, and an imperfect evaluation mechanism; these problems influence one another, jointly constraining the development of human-AI collaborative teaching competence. Based on this, the study preliminarily constructs four competencies—AI tool identification and pedagogical adaptation, human-AI collaborative instructional design, learning diagnosis and precise feedback, and teaching reflection and continuous iteration—and proposes institution-based scenario-oriented training workshops as an improvement path yet to be verified, providing a reference for the professional development of higher vocational English teachers.