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高等教育学科结构与产业结构转型升级的适应性——基于辽宁省2005—2021年面板数据的分析

The Adaptation of the Structure of Higher Education Disciplines to the Transformation and Upgrading of Industrial Structure——An Analysis based on Panel Data of Liaoning Province from 2005 to 2021
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摘要 促进高等教育与产业结构转型升级协同发展是推动区域经济高质量发展、构建区域新发展格局和实现辽宁经济振兴的客观要求。基于辽宁省2005—2021年的面板数据,运用皮尔逊相关分析法及回归分析法,对辽宁省2005—2021年高等教育学科结构与产业结构现状的适应性进行分析,研究发现,高等教育学科结构存在人文社科类偏基础性学科规模较小,理工类毕业生数量趋于饱和,教育类、经管类、医学类毕业生供不应求等问题。因此,辽宁省高等教育学科结构应加大人文社科类及农学类学科建设的力度,稳定理工类毕业生规模及提升理工类学科人才质量,扩大教育类、经管类、医学类人才培养规模。 The coordinated development of higher education and industrial structure transformation and upgrading is essential to the high-quality development of the regional economy,the new pattern of regional developmentand the economic revitalization of Liaoning province.This paper collects the structural data ofhigher education and industries from 2005 to 2021 via the website of Liaoning Bureau of Statistics,and imports them into SPSS21.0 software.An empirical analysis on the adaptation of discipline structure to the industrial structure is made by using Pearson correlation analysis and regression analysis.It is found that the proportion of fundamental disciplines of humanities and social sciences is too small;the number of graduates in sciences and engineering tends to be saturated;the graduates in education,economics,management,and medicine are in short supply,etc..The paper proposes to strengthen humanities,social science and agricultural sciences,stabilize the number of graduates fromscience and technology,improve talent education in science and technology,and increase the enrollment for education,economics,business administration,and medical science.
作者 朱艳 齐繁 Zhu Yan;Qi Fan(College of Educational Science,Shenyang Normal University,Shenyang Liaoning 110034)
出处 《沈阳师范大学学报(教育科学版)》 2023年第6期36-45,共10页 Journal of Liaoning Educational Administration Institute
基金 国家社会科学基金教育学一般项目(BIA190188)
关键词 辽宁省 高等教育学科结构 产业结构 相关性分析 回归分析 Liaoning province higher education discipline structure industrial structure correlation analysis regression analysis
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