{"title":"Digitalization, Education And Employment Nexus Within The Scope of Life Long Learning: CRITIC Based Gray Relational Analysis Application","authors":"Nazlı Seyhan","doi":"10.52096/usbd.7.30.38","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":30893,"journal":{"name":"International Journal of Social Sciences Educational Studies","volume":"110 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Social Sciences Educational Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52096/usbd.7.30.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.