当前智慧教育领域中,各类智慧教育平台与高校教学管理系统间存在数据壁垒,海量学情数据呈现多源、异构、动态等特征,传统处理手段难以满足数据高效共享与个性化应用的需求,为此,提出一种基于知识图谱的多源异构学情数据共享融合与智能服务技术。首先,制定统一的数据标准协议,建立跨平台数据流通机制;其次,依托知识图谱、深度学习及知识推理技术,实现学情数据的统一建模与池化、语义消歧及高效存储,构建虚拟化学情大数据资源池;最后,通过数据按需重构与智能检索,为师生及高校管理者提供个性化数据服务。最终实现＂数据一资源—能力＂的转化,助力高等教育质量的提升。

In the current field of smart education,there are data barriers between various smart education platforms and university teaching management systems.Massive learning situation data present characteristics such as multi-source, heterogeneous,and dynamic,and traditional processing methods are difficult to meet the requirements of efficient data sharing and personalized application.Therefore,this paper proposes a technology for sharing,integration and intelligent service of multi-source heterogeneous learning situation data based on knowledge graph.Firstly,a unified data standard protocol is formulated and a cross-platform data circulation mechanism is established.Secondly,relying on knowledge graph,deep learning and knowledge reasoning technology,unified modeling and pooling,semantic disambiguation and efficient storage of learning situation data are achieved,and a virtual learning situation big data resource pool is constructed.Finally,through on-demand data reconstruction and intelligent retrieval,personalized data services are provided for teachers,students and university managers.Ultimately,the transformation from＂data-resources- capabilities＂is achieved,contributing to the improvement of higher education quality.