Abstract

Secondary vocational education faces constant challenges such as the absence of higher quality, industrial structure upgrading, and a mismatch between the supply of skills and the needs of a specific industry. Therefore, investigating the relationship between the structures of secondary vocational school (SVS) programmes and industries can help us understand their positive interactions and reduce skill mismatch, which is of great significance to the strategies of secondary vocational education and sustainable economic development. Studies on the interactive relationship between SVS programmes and industries and the use of quantitative methods are still lacking. To address this research gap, this paper uses the perspective of coupling and coordination to build a conceptual framework and a computation model to measure the relationship between the two. The method of grey relational analysis is utilized to explore the influencing factors between indicators of SVS programmes and the coupling coordination degree(CCD). Using data from Tianjin, China, the findings are as follows: The interaction between the structure of the SVS programme and industries shows that with the increase in the contribution of the SVS programme structure to the coupling system, the CCD between the two also increases. Compared with the primary and tertiary industries, the secondary industrial structure is more closely related to the SVS programme’s structure, the interaction between the two has a high degree of influence, and the correlation is relatively high between the indicators of secondary industry programmes in SVSs and the CCD. It is necessary to adjust the number of programmes, increase the number of students in the secondary-industry-related programmes and reduce the number of students in the programmes of the primary and tertiary industries to adapt to the needs of a dynamic industrial structure gradually. SVSs should improve programmes in primary and tertiary industries to enhance students’ skills, prepare them for a competitive labour market and strengthen students’ transition from school to work. This study found that the coupling coordination relationship between the two is affected by the following crucial factors: interaction between the two, the contribution of the programme’s structure, regional featured or key industries, and changes in admission policies by the local education authority.

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