<p>The dropout phenomenon in higher education refers to students leaving their programs before completing their degrees. Despite recent improvements in graduation rates, Italy remains among the lowest in OECD countries, with a graduation rate of 45%, well below the OECD average of 69%. High dropout rates, particularly during the first two years of study, are influenced by both institutional factors, such as the decentralization of teaching and the expansion of degree programs, and student-specific factors, including academic performance and geographic distance from universities. Although reforms like the Bologna Process’s 3+2 model have aimed to improve retention, challenges persist. This paper employs multinomial logistic regression analysis, combined with finite mixture models, to explore the complex factors driving student dropout, offering insights for early intervention strategies and institutional reforms aimed at mitigating this issue.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Predicting dropout from higher education with multinomial finite mixture models: empirical evidence from Italy

  • Marco Forti,
  • Massimo Bilancia,
  • Barbara Cafarelli,
  • Emiliano del Gobbo,
  • Andrea Nigri

摘要

The dropout phenomenon in higher education refers to students leaving their programs before completing their degrees. Despite recent improvements in graduation rates, Italy remains among the lowest in OECD countries, with a graduation rate of 45%, well below the OECD average of 69%. High dropout rates, particularly during the first two years of study, are influenced by both institutional factors, such as the decentralization of teaching and the expansion of degree programs, and student-specific factors, including academic performance and geographic distance from universities. Although reforms like the Bologna Process’s 3+2 model have aimed to improve retention, challenges persist. This paper employs multinomial logistic regression analysis, combined with finite mixture models, to explore the complex factors driving student dropout, offering insights for early intervention strategies and institutional reforms aimed at mitigating this issue.