<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>There is a certain gap between the current situation of matching vocational education graduates and regional industrial development letters in Hubei Province, which needs to be dealt with by the efforts of vocational education institutions, the government, industrial frontiers, and graduates themselves. Aiming at the current problems of Hubei Province that the match between vocational education and industrial development structure is not high enough and the level of cooperation between industry and education needs to be improved, this paper puts forward the optimization strategy of matching between industry and education in vocational education institutions that contains five suggestions. After designing the hierarchical analysis and fuzzy comprehensive evaluation method to construct the evaluation index system, the C1 vocational education institutions that carried out the optimization reform of industry-industry matching according to the strategy of this paper were compared with the remaining two ordinary vocational education institutions. It is found that the overall level of industry-education matching of C1 institutions, 87.489, is the highest among the three institutions and is excellent, and the scores of the first-level indexes are 87.095, 90.216, and 85.371, respectively. The satisfaction levels of faculty, curriculum construction, and enterprise benefit are 0.91, 0.9, and 0.95, thanks to the fact that C1 colleges and universities have introduced off-campus industrial mentors under the guidance of the strategy of optimizing the matching of production and education increased the number of applied skills courses, expanding school-enterprise cooperation and other initiatives have had obvious effects. The employment rate of graduates in their specialty counterparts has steadily increased from 69.4% in 2018 to 88.5% in 2023, and the degree of structural matching between vocational education and industrial development has significantly increased. This paper makes useful thinking and innovative strategies for achieving better matching between vocational education and industrial structure, and promoting industrial development and economic transformation and upgrading in Hubei Province.</p>
</abstract>

There is a certain gap between the current situation of matching vocational education graduates and regional industrial development letters in Hubei Province, which needs to be dealt with by the efforts of vocational education institutions, the government, industrial frontiers, and graduates themselves. Aiming at the current problems of Hubei Province that the match between vocational education and industrial development structure is not high enough and the level of cooperation between industry and education needs to be improved, this paper puts forward the optimization strategy of matching between industry and education in vocational education institutions that contains five suggestions. After designing the hierarchical analysis and fuzzy comprehensive evaluation method to construct the evaluation index system, the C1 vocational education institutions that carried out the optimization reform of industry-industry matching according to the strategy of this paper were compared with the remaining two ordinary vocational education institutions. It is found that the overall level of industry-education matching of C1 institutions, 87.489, is the highest among the three institutions and is excellent, and the scores of the first-level indexes are 87.095, 90.216, and 85.371, respectively. The satisfaction levels of faculty, curriculum construction, and enterprise benefit are 0.91, 0.9, and 0.95, thanks to the fact that C1 colleges and universities have introduced off-campus industrial mentors under the guidance of the strategy of optimizing the matching of production and education increased the number of applied skills courses, expanding school-enterprise cooperation and other initiatives have had obvious effects. The employment rate of graduates in their specialty counterparts has steadily increased from 69.4% in 2018 to 88.5% in 2023, and the degree of structural matching between vocational education and industrial development has significantly increased. This paper makes useful thinking and innovative strategies for achieving better matching between vocational education and industrial structure, and promoting industrial development and economic transformation and upgrading in Hubei Province.

Research on the optimization strategy of matching the structure of vocational education and industrial development in Hubei under the background of big data

Wuhan Technology and Business University, Wuhan

Applied Mathematics and Nonlinear Sciences

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

There is a certain gap between the current situation of matching vocational education graduates and regional industrial development letters in Hubei Province,...

Research on the optimization strategy of matching the structure of vocational education and industrial development in Hubei under the background of big data

Pubblicato online: 05 ago 2024

Pagine: -

Ricevuto: 02 apr 2024

Accettato: 20 giu 2024

DOI: https://doi.org/10.2478/amns-2024-2036

Parole chiave
Vocational education, Fuzzy comprehensive evaluation, Hierarchical analysis, Industry-education matching

© 2024 Xu Cai et al., published by Sciendo

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

Research on the optimization strategy of matching the structure of vocational education and industrial development in Hubei under the background of big data

Pubblicato online: 05 ago 2024

Pagine: -

Ricevuto: 02 apr 2024

Accettato: 20 giu 2024

DOI: https://doi.org/10.2478/amns-2024-2036

Parole chiaveVocational education, Fuzzy comprehensive evaluation, Hierarchical analysis, Industry-education matching

© 2024 Xu Cai et al., published by Sciendo

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

Parole chiave
Vocational education, Fuzzy comprehensive evaluation, Hierarchical analysis, Industry-education matching