Airpak-based art and design talent training innovation model framework
In this paper, the 15 original variables of the Airpak-based influence factor scale for art and design talent training were first determined, and the five-level scoring method was applied to score the 15 influence factors. Then, we used factor analysis to factorize the data, standardize the sample d...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.00590 |
| _version_ | 1797340780815187968 |
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| author | Qiao Hui Jang Dongyeul |
| author_facet | Qiao Hui Jang Dongyeul |
| author_sort | Qiao Hui |
| collection | DOAJ |
| description | In this paper, the 15 original variables of the Airpak-based influence factor scale for art and design talent training were first determined, and the five-level scoring method was applied to score the 15 influence factors. Then, we used factor analysis to factorize the data, standardize the sample data, construct a coordinate system with common factors, and use the projection of each variable in the coordinate system instead of the original variables to construct the correlation coefficient matrix R. Then, we solved the correlation coefficient matrix between each variable, selected the number of common factors, and calculated the eigenvectors of the factor loading matrix A to construct the influence factor analysis model. Finally, the model is used to analyze the weight of each influencing factor of Airpak-based art and design talent cultivation and to build an innovative path for talent cultivation. In terms of students’ own factors, the influence weight of learning enthusiasm on talent cultivation is 0.48, and the influence weights of learning achievement and design talent are 0.43 and 0.545, respectively; in terms of teaching level factors, the influence weights of teachers’ teaching ability, professional level and design experience on talent cultivation are 0.44, 0.5 and 0.37 respectively. The research of this paper has an important reference and reference value for the cultivation of art and design talents. |
| first_indexed | 2024-03-08T10:08:14Z |
| format | Article |
| id | doaj.art-ef83b32530404716b6c86551d6cbf4d8 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:08:14Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-ef83b32530404716b6c86551d6cbf4d82024-01-29T08:52:34ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.00590Airpak-based art and design talent training innovation model frameworkQiao Hui0Jang Dongyeul11College of Art, Zhejiang Shuren University, Hangzhou, Zhejiang, 310000, China.2International Graduate School of Convergence Design, Hanseo University, Seosan, Chungcheongnamdo, 31962, South Korea.In this paper, the 15 original variables of the Airpak-based influence factor scale for art and design talent training were first determined, and the five-level scoring method was applied to score the 15 influence factors. Then, we used factor analysis to factorize the data, standardize the sample data, construct a coordinate system with common factors, and use the projection of each variable in the coordinate system instead of the original variables to construct the correlation coefficient matrix R. Then, we solved the correlation coefficient matrix between each variable, selected the number of common factors, and calculated the eigenvectors of the factor loading matrix A to construct the influence factor analysis model. Finally, the model is used to analyze the weight of each influencing factor of Airpak-based art and design talent cultivation and to build an innovative path for talent cultivation. In terms of students’ own factors, the influence weight of learning enthusiasm on talent cultivation is 0.48, and the influence weights of learning achievement and design talent are 0.43 and 0.545, respectively; in terms of teaching level factors, the influence weights of teachers’ teaching ability, professional level and design experience on talent cultivation are 0.44, 0.5 and 0.37 respectively. The research of this paper has an important reference and reference value for the cultivation of art and design talents.https://doi.org/10.2478/amns.2023.2.00590factor analysisloading matrixairpakcoefficient matrixart design65d17 |
| spellingShingle | Qiao Hui Jang Dongyeul Airpak-based art and design talent training innovation model framework Applied Mathematics and Nonlinear Sciences factor analysis loading matrix airpak coefficient matrix art design 65d17 |
| title | Airpak-based art and design talent training innovation model framework |
| title_full | Airpak-based art and design talent training innovation model framework |
| title_fullStr | Airpak-based art and design talent training innovation model framework |
| title_full_unstemmed | Airpak-based art and design talent training innovation model framework |
| title_short | Airpak-based art and design talent training innovation model framework |
| title_sort | airpak based art and design talent training innovation model framework |
| topic | factor analysis loading matrix airpak coefficient matrix art design 65d17 |
| url | https://doi.org/10.2478/amns.2023.2.00590 |
| work_keys_str_mv | AT qiaohui airpakbasedartanddesigntalenttraininginnovationmodelframework AT jangdongyeul airpakbasedartanddesigntalenttraininginnovationmodelframework |