智能教育与教学
Journal of Intelligent Education and Teaching
- Publisher:Eastern Sunshine Publishing House Limited
- ISSN Print:3080-8405(P)
- ISSN Online:3080-8413(O)
- Subject Category:Educational Sciences
- Publication Frequency:Monthly
- Submissions:3
- Views:224
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智能教育的技术演进、课堂重构与实践进路
The Technological Evolution, Classroom Reconstruction, and Practical Pathways of Smart Education
Published: 2026-10-14
Author: 李晓栋 ,刘义浩 ,程龙岩 ,杨涵涵 ,赵爽 ,王梅云 :河南省人民医院影像科 河南郑州; LI Xiaodong ,LIU Yihao ,CHENG Longyan ,YANG Hanhan ,ZHAO Shuang ,WANG Mei-yun :Department of Radiology, Henan Provincial People's Hospital, Zhengzhou;
Chinese Abstract: 生成式人工智能、教育大模型与多智能体技术的交叉融合，正推动教育从“信息化”向“智能化”加速转型。智能教育并非在既有课堂之上简单叠加技术工具，其深层指向在于教学目标、教学结构、师生关系与评价方式等教育核心要素的系统性重构。本文在厘清智能教育的内涵特征与技术底座的基础上，沿“教、学、评、管”四个维度分析技术对教学过程的重构路径，归纳智能教学系统、教学智能体、多智能体协同与教师智能研修四类已具雏形的实践样态，并重点讨论应用浅层化、伦理风险、教师主体性焦虑、效果评估方法学短板与数字鸿沟再生产五重现实困境。本文认为，推进智能教育应以育人价值为根本锚点，分层分类推进师生数字素养建设，同步完善标准与伦理的制度供给，并由政府、企业、学校与研究机构协同构建良性生态；其最终指向是规模化因材施教的实现与教育高质量发展的达成。
Abstract: The convergence of generative artificial intelligence, large-scale educational models, and multi-agent technologies is accelerating the transformation of education from "informatization" to "intelligence". Smart education does not merely involve adding technological tools onto existing classrooms; rather, it fundamentally entails a systematic reconstruction of core educational elements such as teaching objectives, instructional structures, teacher-student relationships, and assessment methods. Based on clarifying the connotative characteristics and technological foundations of smart education, this paper analyzes the pathways through which technology reshapes the teaching process along four dimensions—teaching, learning, evaluation, and management. It identifies four emerging practical models: intelligent teaching systems, teaching agents, multi-agent collaboration, and intelligent professional development for teachers. Furthermore, it discusses five pressing real-world challenges: superficial application, ethical risks, anxiety over teacher agency, methodological gaps in effectiveness evaluation, and the reproduction of the digital divide. The paper argues that advancing smart education should be grounded in educational values, with tiered and categorized efforts to enhance digital literacy among teachers and students, accompanied by the simultaneous development of standards and ethical frameworks. A collaborative ecosystem involving governments, enterprises, schools, and research institutions is essential. Ultimately, the goal is to achieve large-scale personalized instruction and high-quality educational development.
Chinese Keywords: 智能教育；人机协同教学；教育大模型；教师数字素养；教育评价
Keywords: smart education; human-machine collaborative teaching; educational large models; teacher digital literacy; educational evaluation