Research On College Education Data Open Service

With the continuous development of new technologies such as big data and cloud computing,big data has become a research hotspot in the world.It has been used in many fields,and has become a development booster and a progressive ladder for the development of various industries.In the field of education,with the rapid improvement of the level of educational information,the idea of education big data has gone deep into people's minds.More and more teaching staff and researchers are increasingly aware of the need for data,and expect to obtain educational data for data mining and learning analysis.However,teaching staff and researchers conduct data-driven teaching research,mostly at the theoretical and methodological level.The main reason is that there is no good data to support the research process and there is no convenient access to data.Driven research progress is very slow.In response to this problem,this paper focuses on the education data open service model,architecture,and key technologies.Based on this,it has established a college education data open service system to provide open services and solve the inconvenience of data acquisition for college teaching staff and researchers.First,it elaborates the category of college education data from three dimensions of the subject of the generated data,the explicitness and recessiveness of the data evaluation,and the stability of the data content.Combining the category and business characteristics of college education data,the paper proposes a data open service model that is consistent with the characteristics of college,and designs the architecture of the data open service system.Second,the key technologies in the open service process of college education data are researched,including:understanding of user needs,data processing and data analysis service technology,unified user identification of data objects and data desensitization technology.According to the understanding of user needs,the need mapping rule model is used to understand the user's need for public data,the use of semantic analysis technology to understand the user's personalized data needs or the need for multiple data source integrated data.For data processing,the metadata feature extraction is used to structure the unstructured data in the data source.For data analysis,we use social network analysis,K-means clustering algorithms and mathematical statistics for mining and analysis of education data.For data service,a data service registration model is proposed and all data service interfaces are managed in a unified manner.For the unified user identification of data objects,the student number and the teacher number are used to carry out unified user identification on the records of the multi-source heterogeneous data sets.For data desensitization,asymmetric encryption algorithm is used to encrypt sensitive user information.Finally,we design and implement a college education data open service prototype system to provide educators and researchers with convenient access to data.