Development of Lifelong Learning in the Countries of the European Union: K-Means Cluster Analysis Evaluation - Ivana Vrdoljak (Interdisciplinary Description of Complex Systems)
The article analyses lifelong learning development across EU countries, focusing on disparities in doctoral education. A cluster analysis methodology is used to identify homogeneous groups of countries based on various indicators, such as the number of doctoral graduates divided by age and gender and GDP per capita. The analysis categorises countries into clusters based on similarities, applying the K-means clustering technique. This method groups countries to highlight differences in lifelong learning, particularly emphasising economic development. Cluster analysis reveals significant differences between economically advanced European countries and less developed regions, particularly in Eastern Europe. The results underline that Western European countries show a higher number of doctoral graduates, both in total and within the 25-34 age group, compared to Eastern European nations, where these figures are considerably lower. The study concludes that fostering lifelong learning is crucial for socio-economic development, and countries must implement strategies to enhance participation in higher education.