Design And Implementation Of Learning Situation Analysis System Based On MVVM

With the rapid development and widespread application of network information technology,the field of education is gradually evolving towards a trend of networking,intelligence and personalization.The learning situation research platform is a key part of the online learning system,which can deeply analyze and mine data on students’ learning materials,provide effective feedback and suggestions for teachers and students,thereby improving teaching quality and effectiveness.However,traditional learning analysis systems often have problems such as complex interface design,chaotic interaction logic,and inefficient data processing,which affect the user experience and performance of the system.To solve these problems,this paper proposes a learning analysis system architecture based on the MVVM design pattern and front-end separation technology and implements a specific learning analysis system on this basis.This paper mainly studies the implementation method of the front-end separation learning analysis system based on the MVVM design pattern and algorithms for analyzing and predicting student learning situations using data mining technology.This paper is divided into two parts:The first part introduces the architectural design and functional implementation of the learning situation analysis system.The learning situation analysis system adopts the MVVM mode to decouple the interface from data to improve system maintainability and scalability.The front-end of the system uses Vue framework to implement dynamic data binding,componentized development,route management functions;The back-end uses ASP.NET 4.8 framework to implement RESTful-style interface design database management exception handling functions.The system provides multiple role logins(principal student first-second-level administrator)And displays different interfaces and functions according to different roles.The second part introduces algorithm design for analyzing predicting student’s academic performance.This paper uses data mining technology to process feature extraction cluster analysis grade prediction steps on student data on questionnaire survey platforms thus obtaining connections between basic information factors affecting students’ studies connections between factors affecting studies academic performance.This paper verifies feasibility effectiveness front-end separation-based MVVM design pattern-based academic performance analysis systems accuracy practicality analyzing predicting student academic performance using data mining technology through experiments providing new research ideas methods online education field.