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<p>To cultivate more application-oriented talents needed in the market, this paper puts forward a series of innovative development strategies for the integration of industry and education for the government, schools, and enterprises. The indicators used to determine whether the integration of industry and education is good or bad are relatively complicated because it is a long-term and complex teaching mode. In this paper, we use hierarchical analysis to construct a reasonable and clear evaluation index framework and use the convolutional neural network algorithm to calculate the weight value of each index, to comprehensively reflect the impact of the mechanism of industry-teaching integration on students, schools, and enterprises. According to the results of the evaluation system, the weights of the indicator “school running form” and the indicator “employment rate of graduates” reach 0.71 and 0.43 respectively, which fully indicates that the mechanism of integration of industry and education promotes the transformation of several courses in the school, and also helps students to solve the problem of employment. Employment Problems. In addition, the global weight value of the indicator “training cost of new employees” is only 0.01, which greatly reduces the recruitment and training cost of enterprises through the integration of industry and education. Therefore, the convolutional neural network adopted in this paper can effectively calculate the weight value and judge that the innovative development strategy of industry-teaching integration is of great help to all three parties.</p>
</abstract>

To cultivate more application-oriented talents needed in the market, this paper puts forward a series of innovative development strategies for the integration of industry and education for the government, schools, and enterprises. The indicators used to determine whether the integration of industry and education is good or bad are relatively complicated because it is a long-term and complex teaching mode. In this paper, we use hierarchical analysis to construct a reasonable and clear evaluation index framework and use the convolutional neural network algorithm to calculate the weight value of each index, to comprehensively reflect the impact of the mechanism of industry-teaching integration on students, schools, and enterprises. According to the results of the evaluation system, the weights of the indicator “school running form” and the indicator “employment rate of graduates” reach 0.71 and 0.43 respectively, which fully indicates that the mechanism of integration of industry and education promotes the transformation of several courses in the school, and also helps students to solve the problem of employment. Employment Problems. In addition, the global weight value of the indicator “training cost of new employees” is only 0.01, which greatly reduces the recruitment and training cost of enterprises through the integration of industry and education. Therefore, the convolutional neural network adopted in this paper can effectively calculate the weight value and judge that the innovative development strategy of industry-teaching integration is of great help to all three parties.

Innovative Development Strategies for the Integration of Industry and Education in Colleges and Universities in the Internet Era

Development Planning Office of Xuzhou Medical University

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

To cultivate more application-oriented talents needed in the market, this paper puts forward a series of innovative development strategies for the integration...

Innovative Development Strategies for the Integration of Industry and Education in Colleges and Universities in the Internet Era

Data publikacji: 31 sty 2024

Zakres stron: -

Otrzymano: 22 gru 2023

Przyjęty: 28 gru 2023

DOI: https://doi.org/10.2478/amns-2024-0267

Słowa kluczowe
Hierarchical analysis, Convolutional neural network, Evaluation index, Weight, Innovation of industry-teaching integration

© 2024 Lei Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Innovative Development Strategies for the Integration of Industry and Education in Colleges and Universities in the Internet Era

Data publikacji: 31 sty 2024

Zakres stron: -

Otrzymano: 22 gru 2023

Przyjęty: 28 gru 2023

DOI: https://doi.org/10.2478/amns-2024-0267

Słowa kluczoweHierarchical analysis, Convolutional neural network, Evaluation index, Weight, Innovation of industry-teaching integration

© 2024 Lei Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Hierarchical analysis, Convolutional neural network, Evaluation index, Weight, Innovation of industry-teaching integration