What most Matters in Strengthening Educational Competitiveness?: An Application of FS/QCA Method

AbstractThis study was conducted in order to investigate the relationships between different factors affecting educational competitiveness, which is crucial to enhancing national competitiveness in every country, and to put forward policy implications whereby each country may raise the level of its educational competitiveness. PISA score was selected as an indicator representing the educational competitiveness of 22 OECD countries, and this included some independent variables, such as per capita GDP, total public expenditure on education as a percentage of GDP, and total per capita public expenditure on education (US dollars), affecting educational competitiveness. We employed the fuzzy set analysis method (FS/QCA) to analyze the complex causal relationships among the factors affecting educational competitiveness. The research results show that there are three significant combinations of variables affecting educational competitiveness (PISA score). Model 1 is a configuration of four variables (high total expenditure on education as a percentage of GDP, high total per capita expenditure on education, high ratio of private-source expenditure on education to GDP, and high GDP), and includes Netherlands, Finland, Australia, and Ireland. Model 2 is a configuration of five variables (low total expenditure on education, low total per capita expenditure on education, low ration of students to teaching staff, low private-source expenditure on education, and low GDP, and includes Poland. Model 3 is a configuration of five variables (low total expenditure on education, low total per capita expenditure on education, high private-source expenditure on education, high ratio of students to teaching staff, and high GDP), and includes Japan. Finally, the study suggests that each country should endeavour to enhance its own educational competitiveness, considering how the factors associated with this relate to each other