Beijing Advanced Innovation Center for Future Education

陈思睿,余胜泉.教育数字化转型的数据赋能基础与实践[J].电化教育研究,2024,45(06):66-73.DOI:10.13811/j.cnki.eer.2024.06.008. Chen Sirui, Yu Shengquan. The Data Empowerment Foundation and Practice of Educational Digital Transformation [J]. E-Education Research, 2024, 45(06): 66 - 73. DOI: 10.13811/j.cnki.eer.2024.06.008.


题名:教育数字化转型的数据赋能基础与实践

Title: The Data Empowerment Foundation and Practice of Educational Digital Transformation

作者:陈思睿; 余胜泉

Authors: Chen Sirui; Yu Shengquan

关键词:数字化转型;教育信息生态;数据赋能;教育治理;教育服务

Keywords: Digital transformation; Educational information ecology; Data empowerment; Educational governance; Educational services

摘要:教育数字化转型是教育发展和变革的必然趋势,而利用数据赋能教育质量提升是当下数字化转型的重点与难点。研究首先从信息生态和数据流转的视角,分析现有数据难以有效赋能教育实践的问题成因,并据此提出数据赋能教育高质量发展的基础原理——以促进教育治理中人的业务协作与效率提升为原则,建立数据高效流转的服务体系。其次,以公共教育服务平台“智慧学伴”的架构设计与应用形态为例,阐释如何构建面向多角色业务协同的数据服务,探索有效利用数据赋能区域教育质量提升的实践路径。研究提出,通过教育数据的中台化、分析模型的可解释化和应用服务的定制化,能够有效促进基于数据流转的教育业务协同,实现教育治理的全要素生产效率提升。

Abstract: The digital transformation of education is an inevitable trend in the development and reform of education, and leveraging data to empower the improvement of educational quality is the key and difficult point of the current digital transformation. Firstly, from the perspectives of information ecology and data flow, this research analyzes the causes of the problem that existing data is difficult to effectively empower educational practice, and accordingly puts forward the basic principle for data to empower the high-quality development of education - to establish a service system for efficient data flow based on the principle of promoting the business collaboration and efficiency improvement of people in educational governance. Secondly, taking the architecture design and application form of the public education service platform "Intelligent Learning Companion" as an example, it explains how to build data services oriented to multi-role business collaboration and explores the practical path for effectively using data to empower the improvement of regional educational quality. The research proposes that through the centralization of educational data, the interpretability of analysis models, and the customization of application services, it can effectively promote the educational business collaboration based on data flow and achieve the improvement of the total factor productivity in educational governance.