The odyssey of women in university education: stochastic growth models for studying access and graduation process

Abstract

This research aims to explore the evolution of statistics related to the proportion of women in university student populations (focusing on bachelor’s or equivalent degree programs) over an extensive period, spanning from the founding of the first university until recent times. This is done by utilizing empirical insights derived from comprehensive data series, presented here for the first time and primarily encompassing Greece, UK, Canada and USA. Motivated by the distinctive properties of these series and their sigmoid pattern, we delve into a general family of stochastic growth models for data analysis. A notable contribution of this paper lies in offering a novel interpretation of this family within a competing cause scenario, similar to those used in the theory of event history analysis. We emphasize on key common elements within the two statistical domains of research, thereby highlighting potential future research directions; besides, the interpretability of model parameters stands out as an advantage compared to other approaches such as those based on regression model theory. For assessing the proposed parameter estimation methodology under realistic conditions a simulation study is also conducted. The application and results are aimed at making a significant contribution to research in higher and university education by presenting comprehensive sets of consistent data and statistical tools to capture their fundamental characteristics and trends. Additionally, they can serve as valuable resources for education policy-makers and human resources planners alike.