Design and Implementation of Web Technology Based Student Ability Mining Analysis System

The primary objective of this paper is to conceive and implement a web-based student competence mining and analysis system. Firstly, the adoption of multi-terminal data collection techniques is introduced in order to gather students' learning data. Secondly, the research delves into the theory of rule engines, encompassing rule-based expert systems and the application of declarative programming. Additionally, the application of big data consistent tree distribution storage in the management and analysis of student data is investigated. Regarding the overall system design, the architecture, module structure, and network topology are devised. Subsequently, the system is implemented and undergoes experimental testing, followed by an analysis of the test results. This paper aims to provide an innovative web-based student competence mining and analysis system for the field of education, facilitating educators in better comprehending students' learning situations and capabilities, while offering personalized instruction and guidance. It is anticipated that this system will have a positive impact on educational reform and the enhancement of teaching quality. Furthermore, the system exhibits practicality and potential for widespread use, providing robust support and guidance for educators and students alike.