Student academic performance prediction method and system based on Naive Bayes model

Abstract

The invention discloses a student academic performance prediction method and a student academic performance prediction system based on a Naive Bayes model. The method comprises the steps of acquiring learning data of students, and transmitting the acquired data to a database of a first server; implementing data conversion on the learning data of the students stored in the database to acquire a standardized student learning condition data sheet; aiming at the standardized student learning condition data sheet, computing a conditional probability of each property in different classifications and prior probabilities of different classifications by a computation unit in the server; and implementing data conversion on the data of the student to be predicted and inputting the converted data to the trained Naive Bayes model to implement classification prediction on the student data. According to the method and system of the invention, the Naive Bayes model is adopted, and the model is used for accurately predicting the academic performance of the student, with high reliability.

Description

technical field [0001] The invention relates to the fields of educational technology and computer application subjects, in particular to a method and system for predicting students' academic performance based on a naive Bayesian model. Background technique [0002] At present, my country's higher education is developing rapidly, and the number of general institutions of higher learning has reached more than 2,500. In recent years, the continuous decline in the number of students has brought a huge survival crisis to ordinary colleges and universities. How to improve the quality of student training and the employment competitiveness of students has become a problem that many colleges and universities need to solve urgently. As an important core indicator of the quality of student training, students' academic performance has attracted much attention from university administrators. [0003] In my country's colleges and universities, the youth league committee counselor (head ...

AI Technical Summary

Problems solved by technology

The collection of student data is not complete, and it is difficult to conduct a comprehensive analysis and evaluation of students

[0006] 2. For the student achievement data, currently only the student achievement is entered into the teaching management system; the teaching management system stores all the historical data of the student achievement

The evaluation of students' existing abilities is only obtained through the analysis of historical data of students' grades. Without the use of corresponding data processing models, intelligent prediction of students' academic performance cannot be realized.

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