Implementation And Optimization Of National Medical Licensing Examination System

With the collision and integration of Internet technology and education,the teaching work has gradually expanded from the traditional classroom teaching mode to the convenient online teaching mode.The online examination system can overcome the limitations of time,space and region,and further test the degree of knowledge of students effectively.It has become an important way of evaluating the education level.The National Medical Licensing Examination is critical to ensure the quality of medical professionals.To design and implement a online examination system that meets its characteristics can effectively help students to consolidate the structure of medical knowledge,and improve the pass rate of the National Medical Licensing Examination.Based on the characteristics of National Medical Licensing Examination and the needs of the practitioners,this paper designed an online examination system which is based on B/S structure.And the system was optimized by using artificial intelligence algorithms and data mining technology.The main work of this paper are as follows:1.A National Medical Licensing Examination system was implemented.This paper combined relevant theory,technology and needs analysis to establish the overall design goals,and made use of the SSH framework to integrate the various functional modules of the examination system.2.Question types that meet the requirements of National Medical Licensing Examination were designed.According to the requirements of the system,this paper designed seven types of questions,which will help to promote the rationalization and standardization of management of the question bank.3.An intelligent test paper generation strategy based on improved genetic simulated annealing algorithm was designed.By analyzing the theory and requirement of generating test papers,this paper regarded the improved genetic simulated annealing algorithm as an intelligent generating strategy,so as to ensure that the constraints such as score,type,quantity,difficulty and coverage of knowledge points of papers meet the requirements of education,and make the results of generating test papers more objective and scientific.4.Two kinds of examination methods were set up: comprehensive test and self-determination test.The comprehensive examination module is used for students to complete and submit test papers set by teachers within a fixed examination time.After the examination,teachers and students can check the results of automatic scoring by the system.The self-determination test module helps students check for missing and consolidate knowledge.Students can choose courses,chapters and questions taking their own situation into account,and extract the questions which meet the needs.After submitting the papers,the system automatically evaluates the results and displays the correct answers.5.The performance analysis platform was built by data mining technology.Firstly,this paper used multi-level data analysis framework to visualize the relevant indicators of performance data,so as to facilitate teachers to understand the cognitive ability and knowledge level of students.Secondly,based on the improved Apriori algorithm,the relevance between courses is mined and analyzed.It provides decision-making support for teaching management by analyzing a large number of data generated during the examination process,which facilitates the construction of an intelligent examination management model and improves the quality of teaching.