LDM-EDBME: Leveraging Data Mining for Enhancing Development of Basic Mathematics Education at Middle School in Chinese Rural Region

DOI

10.2991/978-94-6463-192-0_127How to use a DOI?

Keywords

Education Data Mining; Mathematics; Big Data; Classification

Abstract

We explores the use of data mining to predict math scores and improve education quality in rural Chinese primary schools. Traditional academic performance evaluation has limitations, and data mining can provide more accurate insights into students’ learning situations. By analyzing classification prediction theory, this research sheds light on the factors affecting math performance and provides effective solutions for teachers to help students achieve better academic performance.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Mingcai Liu
AU  - Weixia Lu
AU  - Yingbiao Hu
PY  - 2023
DA  - 2023/07/04
TI  - LDM-EDBME: Leveraging Data Mining for Enhancing Development of Basic Mathematics Education at Middle School in Chinese Rural Region
BT  - Proceedings of the 2023 2nd International Conference on Educational Innovation and Multimedia Technology (EIMT 2023)
PB  - Atlantis Press
SP  - 970
EP  - 976
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-192-0_127
DO  - 10.2991/978-94-6463-192-0_127
ID  - Liu2023
ER  -