Year: 2024
Type: article
Abstract: In recent years, with the continuous expansion of college enrollment, the number of students is increasing year by year, so the scale of classroom teaching is also getting larger and larger, so that it is difficult for teachers to track and understand the learning situation of each student, which affects the quality of teaching to a certain extent. At the same time, every year, a certain number of students in colleges and universities fail the exam, repeat the grade, or even drop out. If these problems cannot be solved in time, they will seriously affect the psychological health and future development of students, and also affect the employment rate of graduates, and thus affect the development of schools. How to predict the situation of students, so that students in the study of trouble, hesitation, timely interference, so that students successfully complete the university study life. Through the analysis of the failed students, it is found that about 80% of the failed students are advanced mathematics. Therefore, this paper will use the machine learning technology based on BP neural network to analyze the scores of senior students in the final exam of advanced mathematics. According to the different scores, the scores will be divided into four categories: excellent, good, medium and failed. Through the establishment of the grade prediction model, the paper predicts the grade of the college students in the final exam of higher mathematics, and then gives the students learning guidance.
DOI: 10.54097/emdz9943
Authors: Daohai Zhang, Shang Zhang
Institution: Xinjiang University of Political Science and Law
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
Funder: Xinjiang University
OpenAlex ID: W4404475384