Design of study early-warning system based on machine learning

Hui Mao; Zheng Fang; Zhen Liu; Zhiqing Han

doi:10.1117/12.2682433

20 June 2023 Design of study early-warning system based on machine learning

Hui Mao, Zheng Fang, Zhen Liu, Zhiqing Han

Proceedings Volume 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023); 1271527 (2023) https://doi.org/10.1117/12.2682433
Event: Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 2023, Dalian, China

Abstract

How to predict the students’ learning trend, according to the current situation of students' learning, is meaningful for the management of students' learning process. This paper presents a study early-warning system based on machine learning, using the method of machine learning with the data related to the scores of students’ professional courses, retaking percentage, graduation rate and bachelor's degree data of three classes of School of Information Engineering of Wuhan Business University, which establish a prediction model of student learning trend evaluation (whether there is a risk of not obtaining the degree). It provides reference for college students' study management and can improve the quality and efficiency of teaching management.

Citation Download Citation

Hui Mao, Zheng Fang, Zhen Liu, and Zhiqing Han "Design of study early-warning system based on machine learning", Proc. SPIE 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 1271527 (20 June 2023); https://doi.org/10.1117/12.2682433

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