Student data traceability analysis method

Abstract

The invention discloses a student data traceability analysis method, which is used for solving the problem that a stable and accurate student data traceability analysis method does not exist at present. The method comprises the steps of obtaining a mark value of to-be-traced target student data; judging whether the mark value of the target student data can be traced back in a preset student data mark value set or not according to a preset tracing analysis algorithm; and if the mark value of the target student data can be traced back in a preset student data mark value set, outputting the traced information of the existing student data. According to the method, the tracing value between the to-be-traced target student data and the preset student data is calculated, so that the purpose of quickly and accurately obtaining the tracing result from the preset student data is achieved.

Description

technical field [0001] The invention relates to the technical field of data analysis, in particular to a retrospective analysis method for student data. Background technique [0002] In school educational administration management, the management of tens of thousands of student data will be involved. Most of the current management methods are based on document management, such as using excel and other software to store and uniformly manage student data. However, when the amount of data is large, use document Management will have various problems such as software programs are easy to get stuck, inconvenient to find, and poor confidentiality. With more and more student data, the requirements for teaching efficiency, training effect, quality assessment, etc. are also increasing rapidly, making the management of student data more and more complicated and time-consuming. At present, there is still no effective student data management method that takes into account the confidenti...

AI Technical Summary

Problems solved by technology

[0002] In school educational administration management, the management of tens of thousands of student data will be involved. Most of the current management methods are based on document management, such as using excel and other software to store and manage student data in a unified manner. Management will have various problems such as software programs are easy to get stuck, inconvenient to find, and poor confidentiality

With more and more student data, the requirements for teaching efficiency, training effect, quality assessment, etc. are also increasing rapidly, making the management of student data more and more complicated and time-consuming

At present, there is still no effective student data management method that takes into account the confidentiality of students' personal information and the fast and stable data search and traceability.

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