Author(s)

XiaoXiao Wu, SiMei Pan^*, Chia-Yi Luo, Lin Yun, TsungXian Lin, WenChao Pan

Affiliation(s)

School of Management, Guangzhou Huashang College, Guangzhou 511300, Guangdong, China.

Corresponding Author

SiMei Pan

ABSTRACT

The study of factors affecting secondary school students' performance is an important topic for educators, especially at a time when the state pays special attention to education reform. This paper uses quantile regression to explore in detail how the relevant indicators affecting secondary school students' performance affect students' performance and the degree and direction of influence at each quartile, in order to provide relevant educators as a reference for decision-making on education reform. The results of the study show that weekly study time is significantly underestimated by OLS in the lower quartiles, which means that only about 2 hours of study time per week can improve academic performance; extracurricular activities are also significantly underestimated by OLS in the higher quartiles, which means that increasing the number of extracurricular activities can improve academic performance.

KEYWORDS

Math achievement; Influencing factors; Quantile regression

CITE THIS PAPER

XiaoXiao Wu, SiMei Pan, Chia-Yi Luo, Lin Yun, TsungXian Lin, WenChao Pan. An analysis of factors affecting students' performance in mathematics in a secondary school based on quantile regression. Educational Research and Human Development. 2024, 1(2): 18-23. DOI: https://doi.org/10.61784/erhd3016.

REFERENCES

[1] Luo Qiang, Yu Feifei. Gender Differences in Mathematics Achievement of Junior High School Students and the Mechanism of Influence of Individual Factors Based on the Data of Academic Quality Monitoring of Junior High School Students in the City of S. Journal of Mathematics Education, 2024, 33(2): 27-33.

[2] Yue, Q. Analyzing the Knowledge Mapping of the Current Research Field of Education Informatization in China. Journal of Engineering Studies. 2019, 11(4): 409-417.

[3] Fan Shuyuan Xiong Yonghong. Research on the Function of Teaching Forum in Open Laboratory Teaching. Experimental Technology and Management, 2010, 27(1): 26-28.

[4] Li Wan. Optimization of modeling teaching in the reform of mathematics teaching in colleges and universities under the concept of "1+X" . Learning Weekly, 2024, (31): 21-24.

[5] Deng WX, Zhang X, Chen JW, et al. Hot Spots and Trends of China's Vocational Education Informatization Research. Journal of Ningbo Institute of Vocational Technology, 2024, 28(1): 18-24.

[6] Liu Y. Innovative Application and Practical Exploration of Artificial Intelligence Technology in Higher Education Teaching Evaluation. Information Systems Engineering, 2024, (7): 165-168.

[7] Bie Dunrong. Theoretical Explanation of AI Technology Applied to Teaching and Learning in University Education. Teaching in Chinese Universities, 2024, (3/4): 39-44

[8] Kang Yueyuan, Zhang Junhong, Song Chunli. International Research on Mathematics Education in the Age of Mathematical Intelligence: Frontier Hot Spots and Future Prospects. Journal of Mathematics Education, 2024, 33(5): 67-73.

[9] Li Tieying, Wang Yunfeng. The Dilemma and Optimization Countermeasures of the Integrated Teaching Resource Base Construction of Civic and Political Science Classes in Universities, Secondary and Primary Schools. Zhenjiang Higher Education Journal, 2024, 37(4): 70-74.

[10] Song Qijie. Research on Digital Transformation and Teaching Reform of Secondary Vocational Education in Tourism. Foreign Trade and Economics, 2024, (10): 142-145.