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The implementation of new curriculum reform and the “double reduction” educational policies in China have called for reducing classroom burdens while enhancing teaching quality and efficiency. The innovative application of Generative AI (GenAI) in classroom teaching marks a significant milestone in advancing educational digitalization. This study examined the impact of GenAI on elementary school English review lessons, addressing critical issues such as the absence of precise data-driven instruction, ineffective student collaboration, and inadequate personalized feedback. Guided by Large Unit Teaching (LUT) instructional design focused on developing core English competencies and the innovative “Teacher-Student-Machine” triadic structure empowered by GenAI, this study used literature research, theoretical deduction, action research, and evaluation research methods. The study followed a structured process of status investigation, theoretical analysis, model construction, and effect analysis. Initially, it clarified the teaching process of elementary school large unit English review lessons, establishing the “Review-Check-Practice-Advance (RCPA)” teaching sequence. A preliminary human-machine collaborative RCPA model was constructed and refined through two rounds of action research. Results evaluated by artificial intelligence analysis systems indicated that the RCPA teaching model effectively stimulated students’ interest in learning English, enhanced core English competencies and transformed classroom activities.

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Empowering Elementary School English Review Lessons with Generative AI: Constructing the RCPA Human-Machine Collaborative Teaching Model

  • 会议论文

  • 发表日期：

    2026年

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  • Jiawei Li,
  • Youru Xie,
  • Yi Lu,
  • Wei Chen,
  • Ziru Ouyang,
  • Lihong Zeng

摘要

The implementation of new curriculum reform and the “double reduction” educational policies in China have called for reducing classroom burdens while enhancing teaching quality and efficiency. The innovative application of Generative AI (GenAI) in classroom teaching marks a significant milestone in advancing educational digitalization. This study examined the impact of GenAI on elementary school English review lessons, addressing critical issues such as the absence of precise data-driven instruction, ineffective student collaboration, and inadequate personalized feedback. Guided by Large Unit Teaching (LUT) instructional design focused on developing core English competencies and the innovative “Teacher-Student-Machine” triadic structure empowered by GenAI, this study used literature research, theoretical deduction, action research, and evaluation research methods. The study followed a structured process of status investigation, theoretical analysis, model construction, and effect analysis. Initially, it clarified the teaching process of elementary school large unit English review lessons, establishing the “Review-Check-Practice-Advance (RCPA)” teaching sequence. A preliminary human-machine collaborative RCPA model was constructed and refined through two rounds of action research. Results evaluated by artificial intelligence analysis systems indicated that the RCPA teaching model effectively stimulated students’ interest in learning English, enhanced core English competencies and transformed classroom activities.