Trends and Determinants of Lifelong Learning: Regional Differences in Europe
Buryk Zoriana1, Orliv Mariana2, Kаren Ismailov3
1Buryk Zoriana, Doctor of Science Public Administration, Senior Lecturer of Regional Management, National Academy for Public Administration Under President of Ukraine.
2Orliv Mariana, Ph.D, Department of Economics, Docent Public Administration and Management, Ivano-Frankivsk National Technical University of Oil and Gas.
3Kаren Ismailov, Сandidate of Juridical Sciences, Head, Department of Odessa State University of Internal Affairs Department of Cyber Security and Information Suppor.
Manuscript received on 30 November 2019 | Revised Manuscript received on 11 December 2019 | Manuscript Published on 19 December 2019 | PP: 93-97 | Volume-8 Issue-4S November 2019 | Retrieval Number: D10291184S19/2019©BEIESP | DOI: 10.35940/ijrte.D1029.1184S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The article analyzes lifelong learning indicators and trends in 33 European countries (EU member countries as well as Norway, Switzerland, Iceland, Macedonia and Serbia) based on Eurostat and World Bank data for 2002-2017. The problems of determining qualitative indicators of lifelong learning as well as monitoring and analysis of learning outcomes are revealed. The necessity for the creation of countries’ own information systems, in which the data are detailed by age and gender, types of education, learning and development methods is substantiated. The correlation analysis of the following quantitative indicators is carried out: early leavers from education and training, tertiary educational attainment, young people neither in employment nor in education and training, employment rates of recent graduates, adult participation in learning, formal and non-formal education and training participation, GDP per capita. Regional differences in life-long learning trends in Europe are identified by the method of tree clustering. The quality of the differentiation is iteratively optimized by the K-Means method. Three clusters of countries are distinguished which essentially differ in the following parameters: tertiary educational attainment, employment rates of recent graduates, adult participation in learning. Determinants of the lifelong learning development are analyzed in the context of achieving the sustainable development goals. The propositions on priorities in elaboration of the further lifelong learning policy for each clusters are substantiated, taking into account the need to adhere to the principles of social justice and economic efficiency.
Keywords: Lifelong Learning, Adult Education, Sustainable Development, Training, Formal Education, Non-Formal Education, Clasters.
Scope of the Article: Social Sciences