The quality of higher education and its funding in countries with different levels of socio-economic development

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Higher education institutions train professional and scientific personnel. Therefore, the quality of higher education and its funding are vital for training highly qualified specialists. This study analyzes the annual volume of expenses (investments) per student in groups of countries, divided according to their socio-economic development, and competitiveness of higher education. The division of countries into groups is based on simultaneous compliance with the criteria for the quality of higher education and the level of social and economic development. The Ward’s clustering method was applied. The analysis was conducted based on data from 32 OECD countries and partner countries. The paper found a significant direct correlation between the level of competitiveness of higher education and the amount of its funding per student (R = 0.895). At the same time, a significant direct correlation was revealed between the level of competitiveness of higher education and the human development index (R = 0.787) and the global competitiveness index (R = 0.888). Finally, a significant direct correlation between the amount of expenditures and the level of competitiveness of higher education was found only in the cluster with the highest indicators of socio-economic development (Rs = 0.707). In other clusters, the correlation is weak or weakly inverse.

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    • Figure 1. The range of expenditures per student within the clusters in 2018
    • Figure 2. The relationship between the amount of higher education expenditures and the quality of higher education within clusters
    • Table 1. Correlation between the amount of higher education expenditures, the quality of higher education, and economic and social development
    • Table 2. Clustering of countries by level of socio-economic development in 2018
    • Table 3. The values of the indicators within clusters in 2018
    • Table 4. Countries clustering by the level of socio-economic development in 2014–2018
    • Table 5. Correlation between indicators of the quality of higher education and expenditures per student within clusters
    • Funding acquisition
      Olha Hryhorash, Tetiana Hryhorash
    • Investigation
      Olha Hryhorash, Dmytro Bocharov, Maxim Korneyev, Tatyana Rudyanova, Tetiana Hryhorash
    • Methodology
      Olha Hryhorash, Dmytro Bocharov
    • Project administration
      Olha Hryhorash
    • Software
      Olha Hryhorash, Dmytro Bocharov
    • Supervision
      Olha Hryhorash, Tatyana Rudyanova, Tetiana Hryhorash
    • Writing – original draft
      Olha Hryhorash, Dmytro Bocharov, Maxim Korneyev
    • Conceptualization
      Dmytro Bocharov, Tetiana Hryhorash
    • Data curation
      Dmytro Bocharov, Maxim Korneyev, Tatyana Rudyanova
    • Formal Analysis
      Dmytro Bocharov, Maxim Korneyev, Tatyana Rudyanova
    • Resources
      Dmytro Bocharov, Maxim Korneyev, Tatyana Rudyanova, Tetiana Hryhorash
    • Validation
      Dmytro Bocharov, Maxim Korneyev
    • Writing – review & editing
      Dmytro Bocharov, Maxim Korneyev, Tatyana Rudyanova, Tetiana Hryhorash
    • Visualization
      Tatyana Rudyanova, Tetiana Hryhorash