Design And Implementation Of Online Knowledge Evaluation System Of Wisdom Classroom

With the continuous development of technology,big data and artificial intelligence technologies have matured,which have injected new impetus into online education.Online education is gradually transforming into smart education supported by modern information technologies such as data analysis and artificial intelligence.Although traditional online education has broken the boundaries of time and space,so that students can learn anytime,anywhere,there are still some problems.For example,the teaching plan is “one-sided” and lacks pertinence and strategy.The curriculum cannot take into account individual differences between students,such as differences in basics and comprehension abilities,and teachers cannot accurately understand each student's learning progress.Therefore,traditional online education needs to be transformed and upgraded.Students need to have the autonomy to learn,so that students and teachers can obtain timely feedback and evaluation,so that they can develop different learning plans for each student and truly“teaching according to their aptitude”.If an online education platform wants to teach students according to their aptitude,there are two key points.The first point is to check the accuracy,speed,and meticulousness of the evaluation process,so as to quickly and accurately find out the real weakness of the students.The second point is personalized recommendation and matching.Based on the test results,different learning programs are formulated for different students.Based on the above background,this thesis designs and implements the knowledge evaluation subsystem of the AI wisdom adaptation online education platform“Smart Classroom”to detect student learning,quickly and accurately identify student weaknesses,and personalize students for the next step.It is recommended that the learning program provide a data basis.The knowledge evaluation system is divided into two parts: an edge module and a business module.The edge module includes an authentication module.The business module mainly includes four modules: knowledge graph module,test question and test paper module,exam module,and evaluation analysis module.Each module is independent in the form of micro-service.The authentication module is responsible for identifying the user right,so as to filter users with the insu cient right.The knowledge graph module is responsible for the management of knowledge points and learning objectives,which is the basis of the entire system.The test question and test paper module is responsible for the management of test questions and test papers.The exam module is responsible for managing the exam and completing the evaluation,which is the focus of the entire system.The evaluation and analysis module is responsible for analyzing the test results and providing a data basis for intelligently planning the learning path.The solution of the knowledge evaluation system includes three aspects:1.Use microservice architecture and Spring Cloud framework to split the system into multiple sub-services to achieve the design goals of reducing system complexity,improving maintainability and scalability.2.Use a hierarchical structure to divide the system into a presentation layer,a control layer,a service layer,and a data layer to achieve the design goal of reducing the degree of coupling within the program,and improve the scalability and main-tainability of the software system.3.Use the front-end and back-end separation architecture,the front-end uses the popular Vue.js framework,and the back-end provides the front-end with a REST-ful style interface.The two interact through the API gateway to ensure system security,easy to locate problems,and easy to develop and maintain.I am responsible for the design and implementation of the knowledge evaluation subsystem of the online education platform “Smart Classroom”.At present,the system has been put into operation,there are more than ten registered enterprises and schools,and user feedback is good.