Comprehensive Quality Evaluation for Secondary School Students Based on Big Data

DOI

10.2991/978-94-6463-172-2_206How to use a DOI?

Keywords

comprehensive quality evaluation model; big data; rank and grade; student’s comprehensive abilities

Abstract

The present study proposes a kind of comprehensive quality evaluation model based on big data with an attempt to rank and grade secondary school students’ comprehensive quality ability in Shandong, in order to optimize the traditional comprehensive quality evaluation model. The model is a fusion of TOPSIS method, RSR method, and entropy weight method. The Pandas package in the Python programming language is used for data extraction and data processing, the Matplotlib package is used to draw line graphs, and the Numpy package is used for model implementation and computation. The results of the ranking reveal that 2 students have imbalanced comprehensive quality development and that 5 students with balanced comprehensive quality development achieve higher rankings. The grading results reveal that 12% of the students receive an “excellent” rating, 68% receive a “good” rating, and 20% receive a “poor” rating. The results prove that the model optimizes the traditional comprehensive quality evaluation method and focuses more on the comprehensive development of students in the process of ranking and grading them. The proposed model is significant for the development of comprehensive quality evaluation model.

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.

Download article (PDF)

TY  - CONF
AU  - Yulong Chen
AU  - Yanyan Li
AU  - Wenzheng Li
AU  - Xinyou Li
AU  - Weiqi Zhou
AU  - Xiaoye Wang
AU  - Yiyi Long
AU  - Yi Wu
PY  - 2023
DA  - 2023/06/30
TI  - Comprehensive Quality Evaluation for Secondary School Students Based on Big Data
BT  - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
PB  - Atlantis Press
SP  - 1861
EP  - 1868
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-172-2_206
DO  - 10.2991/978-94-6463-172-2_206
ID  - Chen2023
ER  -