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Quantitative Analysis and Model Optimisation Research on the Enhancement of the Effect of Students’ Civic and Political Education in Colleges and Universities
The use of existing data analysis tools to analyse students’ data to reflect the achieved teaching effect has been paid attention to by the teaching management department. In this paper, we design a quantitative model for the effect of Civic Education to analyse the clustering of students’ performan...
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Published in: | Applied mathematics and nonlinear sciences 2024-01, Vol.9 (1) |
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Main Author: | |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The use of existing data analysis tools to analyse students’ data to reflect the achieved teaching effect has been paid attention to by the teaching management department. In this paper, we design a quantitative model for the effect of Civic Education to analyse the clustering of students’ performance in Civic Education in different school years and the correlation between different Civic Education courses so as to carry out a quantitative assessment of the improvement of the effect of Civic Education. The clustering effect can be improved by using a GA-CLARANS algorithm for large-scale data computing. The optimized model is used to analyze the performance of civics and politics majors in School B in the freshman and sophomore academic years. The improvement in the students’ performance is mainly related to the courses they are required to take. Among them, the Pearson coefficients between the six compulsory courses are above 0.5, while the Pearson coefficients between the elective courses are mostly between 0.3-0.5, and the Pearson coefficients between some of the elective courses and the compulsory courses are around 0.5. It shows that the main reason for the improvement of the effects of students’ Civic and Political Education is related to the compulsory course curriculum, and some elective courses can play an auxiliary role. |
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ISSN: | 2444-8656 2444-8656 |
DOI: | 10.2478/amns-2024-3602 |