Design And Implementation Of Online Education Big Data Visualization And Analysis System

In recent years,with the rapid development of online education platforms in China,visual analysis and mining of learning behaviour data generated in the process of online education has become a key topic in order to improve the level of scientific decisionmaking in online education and promote the reform of online education teaching.The learning behaviour data generated by online education platforms has a strong real-time nature,usually in the form of data streams,which are constantly updated with time.Existing big data visualisation and analysis systems are mainly based on offline data and cannot handle the streaming data generated by online education platforms in real time.In this paper,we design and implement an online education big data visualisation and analysis system,which is dedicated to solving the problem of collecting,processing and visualising and analysing real-time streaming data and offline batch data generated by online education platforms.In addition,this paper designs an XGBoost-based dropout prediction algorithm based on the real-time streaming data of user behaviour from Academy Online,which enables real-time training and prediction of user dropout behaviour through an incremental training strategy on real-time streaming data,making full use of the timeliness of real-time streaming data to enhance the accuracy of prediction.In this paper,the system is designed and developed in strict accordance with software engineering thinking.In this paper,the functional requirements of the online education big data visualisation and analysis system are analysed,and the outline design is based on a comparison of current popular technologies to determine the technology selection of the system.The outline design of the system mainly includes architecture design,functional module division and database design.The next step is the detailed design and implementation of the system.The XGBoost-based dropout prediction algorithm is designed,and the concrete implementation of each functional module of the system is presented using class diagrams,timing diagrams and corresponding code.Finally,the system is tested both functionally and non-functionally to check the implementation and operation of the system.The system has now been fully developed and tested,and has been deployed on the server,providing a complete online education big data collection,analysis,storage and visualisation service.