【作 者】：
谢幼如， 陈 薇， 邱 艺
【关 键 词 】：
人工智能； 教学重构； 课堂场景； 场景化教学； 智能体
【栏 目】：
理论探讨
【中文摘要】：
随着国家教育数字化战略行动2.0的启动，依托课堂这一育人主阵地，利用人工智能重构课堂教学，解决教育个性化、高质量、大规模三大难题，是纵深推进教育教学改革的重要突破口。研究以智慧教育理论、场景化教学理论、教学设计理论为指导，开展人工智能赋能高校课堂教学重构研究，系统回应高校课堂教学“为何重构”“凭何重构”“如何重构”三大核心问题。首先，立足高校课堂数字化转型、高质量发展、规模化因材施教的三维动因，论述了课堂教学重构的必要性。其次，指向大规模个性化创新型人才培养的范式转型，构建了人工智能赋能高校课堂教学重构的“育人导向—场景调适—结构升维”理论逻辑，阐释了课堂教学重构的理论依据。最后，有机融合目标、内容、活动和评价的教学设计理论体系与“师—生—机”三元交互新范式，形成了面向“师—生—机”三元课堂的人机协同教学设计方法；并构建了“国家智慧教育公共服务平台+智能体”赋能的人机交互理解、人机融智探究、人机共创生成三种典型高校课堂场景，提出了人工智能赋能高校课堂教学重构的场景化实施路径，系统论述了课堂教学重构的教学设计与实施路径。研究旨在为构建新型课堂教学组织形态、打造未来课堂、实现人工智能驱动的大规模因材施教提供理论支持与实践借鉴。
【英文摘要】：
With the launch of the National Education Digitalization Strategy Action Plan 2.0, relying on the classroom as the main arena for nurturing talents and using artificial intelligence to reconstruct classroom teaching to solve the three major problems of personalized, high-quality and large-scale education is an important breakthrough for further advancing educational and teaching reforms. Guided by the theories of smart education, scenario-based teaching, and instructional design, this study conducts research on the reconstruction of classroom teaching empowered by AI in universities, systematically addressing three core questions of "why to reconstruct", "on what basis to reconstruct", and "how to reconstruct". Firstly, based on the three-dimensional driving forces of digital transformation, high-quality development, and large-scale personalized instruction in higher education classrooms, this study argues for the necessity of classroom reconstruction. Secondly, pointing to a paradigm shift of cultivating large-scale personalized innovative talent, this study constructs the theoretical logic of "education-oriented approach,scenario adaptation, structural elevation" for AI-empowered reconstruction of university classroom teaching, and explains the theoretical basis for the reconstruction of classroom teaching. Finally, by organically integrating the theoretical framework of instructional design that includs objectives, content, activities and assessment with the new triadic interaction paradigm of "teacher-student-machine", this study develops a human-machine collaborative classroom instructional design methodology for triadic classrooms. Additionally, this study constructs three typical university classroom scenarios empowered by the "National Smart Education Public Service Platform +Agents": human-machine interaction understanding scenario, human-machine collaborative inquiry scenario, and human-machine co-creation and generation scenario. It further proposes a scenario-based implementation pathway for the AI-empowered reconstruction of university classroom teaching, and systematically elaborates on the instructional design and implementation approach for the reconstruction of classroom teaching. This study aims to provide theoretical support and practical reference for constructing a new form of classroom teaching organization, creating future classrooms, and realizing AI-driven large-scale personalized education.