基于命题任务驱动的AI融合型教学——以《二次函数与最值问题》复习课为例

AI-Integrated Teaching Based on Proposition Task-Driven Theory—Taking the Review Lesson on “Quadratic Functions and Maximum/Minimum Problems” as an Example

摘要: 基于命题任务驱动的AI融合型复习课模式，能够有效实现学生角色的重置与高阶思维的培养。研究以二次函数最值问题复习课为例，通过创设命制一道中考题的核心任务，制定出四种命题策略，主要包括：由定到动、由理解到设计、由直译到转化、由应用到优化，引导学生完成从知识再现到知识创造的深度建构。

Abstract: The AI-integrated review class model driven by proposition tasks can effectively achieve the reset of student roles and the cultivation of higher-order thinking. Taking the review class on the maximum and minimum problems of quadratic functions as an example, the study creates a core task of designing a middle school entrance exam question, and develops four proposition strategies, mainly including: from fixed to dynamic, from understanding to design, from literal translation to transformation, and from application to optimization, guiding students to complete the deep construction from knowledge reproduction to knowledge creation.