Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 10, Issue 1


Published
on

March 21, 2025


Pages


DOI

Article

Identification of Key Elements and Path Design of Vocational Education Governance Modernization Supported by Deep Learning

Check for updates


Authors

Fan Li Affiliation:
Faculty of Economics and Trade, Guangdong Polytechnic of Industry and Commerce, Guangzhou, Guangdong, 510510, China.


Abstract

Aiming at the problem of identifying key elements for modernizing the governance of vocational education, the article proposes an element identification model based on the improved BiLSTM-CRF, which carries out the improved BERT design based on the Attention mechanism, the improved design based on the local location information, the improved design based on the global attention mechanism, and the improved design based on the LSTMDecoder, respectively. Then we analyze the key elements affecting the modernization of the governance capacity of vocational education, and explore the promotion path of the modernization of the governance capacity of vocational education from five perspectives: governance concept, governance system, governance resources, governance tools and governance mechanism. By using the QCA method to analyze the multiple key factors affecting the modernization of vocational education, it can be found that in the analysis of the condition combination path of sustainability innovation, the modernization of vocational education governance can be classified as organization-driven (H1), internal and external coupling (H2) and resource-enabling (H3), of which the resource-enabling group consistency is 0.8009, the unique coverage rate is 0.069, and the original coverage 0.2436. In this path model, the local economic development conditions and innovation resource input are more adequate.


Keywords

BiLSTM-CRF, Element identification, Path design, Vocational education governance modernization, 68T07


Citation

Li, F. (2025). Identification of key elements and path design of vocational education governance modernization supported by deep learning. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-0567
0 Total citations
0.00 FWCI
0 Recent citations
(2 years)
19 References
Open Access Yes
View full metrics

Published by: Engineering Journals

Engineering Journals Logo