摘要
在当前学前教育高质量发展的政策背景下,本研究以教育部《幼儿园保育教育质量评估指南》为理论框架,结合人工智能技术对儿童游戏行为的数据采集与分析能力,立足园所实践,系统探讨深度游戏与保教质量提升的内在关联,借助AI行为分析技术实现游戏过程的动态评估与反馈,创新性提出“自主循环”“共生共长”“动态发展”“质量共生”四位一体的游戏质量提升模型,最终形成具有区域推广价值的园本化游戏实践范式,为落实《评估指南》中“以游戏为基本活动”的评估指标提供技术赋能的新型解决方案。
In the current policy context of high-quality development of preschool education,this study takes the Ministry of Education's"Guidelines for Quality Evaluation of Preschool Care Education"as the theoretical framework,combined with the data collection and analysis capabilities of artificial intelligence technology for children's game behavior,based on the practice of kindergartens,systematically explores the inherent relationship between deep games and the improvement of preschool education quality,and uses AI behavior analysis technology to achieve dynamic evaluation and feedback of the game process.It innovatively proposes a four in one game quality improvement model of"autonomous circulation","symbiotic growth","dynamic development",and"quality symbiosis",ultimately forming a localized game practice paradigm with regional promotion value,providing a new technically empowered solution for implementing the evaluation indicators of"games as the basic activity"in the"Evaluation Guidelines".
作者
张春媚
Chunmei Zhang(Cuiping District Government Kindergarten in Yibin City,Yibin,Sichuan 644000)
关键词
深度游戏
保教质量
儿童为本
师幼互动
协同共育
deep gaming
quality of education and protection
child centered
teacher child interaction
collaborative co education
