“拼图”+“测评”双核驱动：AI时代教师培训的融合创新模式探索

Jigsaw and Assessment Crossover: A Dual-Driven Innovation Model for Teacher Training in the AI Era

摘要: 随着人工智能(AI)技术在教育领域的渗透，提升英语教师AI融合教学能力成为重要议题，而传统培训模式面临参与度低、学用脱节等挑战。本文介绍并分析了一次针对新东方成熟英语教师的AI辅助教学培训创新实践。该培训以“跨界融合”为核心设计理念，通过两大核心实践——将拼图教学法创新应用于师训视频学习以打破信息线性壁垒，以及将标准化考试(如托福)的测评逻辑融入过程性评估以实现“以评促学”——并强调教育理论与AI技术的深度结合(即“用教学法驯服AI”)。实践获得了参训教师的高度认可，显著提升了参与度、知识保持率与高阶思维能力。本文旨在详细解析此次培训的Crossover设计亮点(如拼图教学法视频化、以评促学题目设计、非线性信息流、理论技术融合)、理论依据及实践成效，为AI时代的教师专业发展提供一种高参与、高认知、高实践的“双核驱动”融合培训新模式的参考。

Abstract: With the growing integration of AI in education, enhancing English teachers’ ability to apply AI in teaching has become critical. Traditional training models, however, often suffer from low engagement and poor transfer of learning to practice. This paper presents an innovative AI-assisted teacher training program designed for experienced English teachers in New Oriental. Centered on the concept of “Crossover”, the model features two core components: 1) The innovative use of the jigsaw method in video-based learning to break down linear information flow; 2) The integration of standardized assessment logic (e.g., TOEFL) into the formative evaluation to promote learning through assessment (“assessment-driven learning”). The design emphasizes the deep fusion of pedagogy and AI technology—“taming AI with pedagogy.” Results showed high participant satisfaction and significant improvements in engagement, knowledge retention, and higher-order thinking. This study unpacks the key design elements (e.g., video-integrated jigsaw learning, non-linear information structure, theory-technology synergy), theoretical foundations, and practical outcomes, offering insights into a dual-driven fusion model for teacher professional development in the AI era.