终身学习范围内的数字化、教育和就业关系:基于批评家的灰色关联分析应用

Nazlı Seyhan
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引用次数: 0

摘要

欧洲联盟制定了许多关于终身学习的政策、决定、战略和项目,并制定了一些目标,特别是在教育、就业和竞争力方面。今天的技术发展及其对教育和就业的影响不容忽视。在本研究中,在欧盟终身学习目标的范围内,对欧盟国家的技术发展、教育和就业指标及其表现进行了评估,并讨论了名列前茅和落后的国家。本研究的目的是利用数字化世界中终身学习范围内重要的一些技术、教育和就业数据,利用基于critical的灰色关联分析方法评估欧盟国家的绩效。特别是,受数字技能教育的高等教育水平的个人的教育变量,这些人是我们这个时代所带来的,他们接近于参与商业生活,应届毕业生的就业,受过高等教育的失业率,政府用于教育的支出占GDP的份额,信息通信技术部门占GDP的份额,这表明了技术对就业的影响,以及信息通信技术专家在总就业中的份额。等变量都包含在研究范围内。在研究中包含的变量的帮助下,根据CRITIC方法的结果,可以看到最重要的前五个标准是接受高等教育的学生(12.11%),早期离开教育和培训(9.32%),ICT行业在GDP中的份额(8.38%),受过高等教育的失业率(8.08%),总失业率(-7.08%)。然而,在使用CRITIC方法获得的权重的灰色关联分析结果中,瑞典、芬兰、西班牙、丹麦、马耳他、德国通过提供技术、教育和就业的平衡而在绩效排名中名列前茅,发现波兰、拉脱维亚、克罗地亚和斯洛文尼亚等国家也处于最后一名。关键词:Lıfelong Learnıng,数字化,就业,GIA方法产品编号:A20,C19, C44, D83, I3, O33。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digitalization, Education And Employment Nexus Within The Scope of Life Long Learning: CRITIC Based Gray Relational Analysis Application
The European Union has developed many policies, decisions, strategies and projects on lifelong learning and has set some targets, especially in education, employment and competitiveness. Today's technological developments and the effects of these developments on education and employment cannot be ignored. In this study, within the scope of the objectives of lifelong learning in the EU, the technological developments in the EU countries, education and employment indicators and their performances are evaluated and the countries that come to the fore and fall behind are discussed. The aim of this study is to evaluate the performance of EU countries with the CRITIC-based Gray relational analysis method with some technology, education and employment data that are important within the scope of lifelong learning in the digitalized world. In particular, the education variables of individuals at higher education level who are educated with digital skills brought by our age and close to taking part in business life, employment of new graduates, unemployment with advanced education, the share of government expenditures spent on education in GDP, the share of the ICT Sector in GDP, which shows the effects of technology on employment, and the share of ICT experts in total employment. etc. variables are included in the scope of the study. With the help of the variables included in the study, according to the findings of the CRITIC method, it was seen that the most important first five criteria were students enrolled in Higher Education (12,11%), leave education and training early (9.32%), the share of the ICT Sector in GDP (8.38%), highly educated unemployment (8.08%), Total unemployment rate (-7.08%). However, in the Gray Relational Analysis findings using the weights obtained by the CRITIC method, Sweden, Finland, Spain, Denmark, Malta, Germany took the lead in the performance ranking by providing the balance of technology, education and employment, it has been found that countries such as Poland, Latvia, Croatia, and Slovenia are also in the last place. Key Words: Lıfelong Learnıng, Digitalization, Employment, GIA Method. Jel Cods: A20,C19, C44, D83, I3, O33.
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