A latent curve analysis of unobserved heterogeneity in university achievements

The aim of this paper is to analyze academic achievement of a cohort of students enrolled in 2001 at the Faculty of Economics of the University of Bologna by using a latent growth model for longitudinal data. The basic idea of this approach is that individuals differ in their growth over time according to a continuous underlying or latent trajectory. Random coefficients in the model permit each individual to have a different trajectory. Latent growth models can be incorporated in the Structural Equation Models (SEMs) framework by viewing the random coefficients as latent variables. Hence model identification and estimation are performed according to the conventions of the SEM analysis. The effects of different covariates in the student temporal behavior is also evaluated.