数据驱动教育数字化转型的信任机制——教育大数据全生命周期隐私增强模型的构建与典型应用场景分析

Trust Mechanism for the Data-driven Education Digital Transformation——Construction and Typical Application Scenario Analysis of Privacy Enhancement Model for the Full Life Cycle of Educational Big Data

教育大数据正在成为驱动国家教育数字化转型战略行动的核心资源,带来了巨大的教育价值,但教育大数据的采集和分析产生了隐私侵害风险、信任危机等严峻问题,阻碍了数据的共享、开发和利用。如何增强教育大数据在开放共享、共建共用中的隐私保护和信任关系,成为制约数据驱动教育数字化转型的关键难题。对此,文章首先采用文献分析法,剖析了教育大数据隐私保护的研究现状与关键问题。随后,文章从应用场景角度设计了教育大数据全生命周期隐私增强框架,并基于此框架从技术实现角度构建了满足不同实体、不同阶段隐私需求的教育大数据全生命周期隐私增强模型及其应用流程。最后,文章介绍了该模型的典型应用场景,涉及学分与资质认证、教育协同与治理、可信评教、个性化学习服务等多个方面。文章的研究能够厘清教育大数据开放共享时的隐私保护关键问题和技术思路,可为实现教育数据要素化全生命周期的隐私保护、建立健全数据驱动教育数字化转型的信任机制提供参考。

Educational big data is becoming the core resource to drive the strategic action of digital transformation of national education,which brings great educational value.However,the collection and analysis of educational big data has generated privacy invasion risks and trust crisis and other serious problems,hindering the sharing,development and utilization of data.How to enhance the privacy protection and trust relationship of educational big data in open sharing,co-construction and co-employment has become a key problem restricting the data-driven education digital transformation.In regard to this,the paper firstly adopted the literature analysis method to analyze the research status and key issues of privacy protection of educational big data.Then,from the perspective of application scenarios,this paper designed a privacy enhancement framework for the full life cycle of educational big data,and constructed a privacy enhancement model for the full life cycle of educational big data and its application flow from the perspective of technology implementation to meet the privacy requirements of different entities and different stages.Finally,the typical application scenarios of this model were introduced,whose content involved credit and quality certification,education coordination and governance,trust evaluation of teaching,and personalized learning services.This research of the paper can clarify the key issues and technological solutions of privacy protection in open sharing of educational big data,and provide reference for realizing the privacy protection for full life cycle of educational data factionalization and establishing and improving trust mechanism of data-driven education digital transformation.