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28 March 2023 A comprehensive competitiveness evaluation model for higher vocational colleges based on factor analysis and K-means method
Weitao Pang, Limin Yi
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Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 125972L (2023) https://doi.org/10.1117/12.2672231
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China
Abstract
In the context of the revision of the new version of the Vocational Education Law, the existing comprehensive competitiveness ranking of higher vocational institutions and the setting standards of undergraduate level vocational institutions were combined. The 56 institutions with good development in the field of vocational education were used as the research objects, and the index extraction and weight calculation of the collected data were carried out by using factor analysis method. Principal component analysis was used for indicator extraction, and the Kaiser normalized maximum variance method was used for weight calculation. The classification of indicators at each level is analyzed and corrected using the kmeans method. The final evaluation system will be set with reference to the actual situation. It is expected that the evaluation results will make effective suggestions for the development of the institutions.
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Weitao Pang and Limin Yi "A comprehensive competitiveness evaluation model for higher vocational colleges based on factor analysis and K-means method", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125972L (28 March 2023); https://doi.org/10.1117/12.2672231
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KEYWORDS
Covariance matrices
Education and training
Factor analysis
Universities
Principal component analysis
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