La riuscita del percorso universitario: un'analisi longitudinale sugli studenti dell'Ateneo di Bologna
<em>A longitudinal analysis of academic achievements in the University of Bologna</em> (by Stefania Mignani, Paola Monari, Silvia Bianconcini, Silvia Cagnone). Objectives The aim of this paper is to analyze academic achievement of a cohort of students enrolled in 2001 at one of the most numerous Faculties of the University of Bologna. This represents a first longitudinal study motivated by a new requirement of the University system, that is supporting students in their whole career. Methods and Results We make use of latent growth models 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. Conclusions Latent Growth models are particularly useful in analyzing student performances over time. We identified three different subgroups or cohorts, and we applied linear and non linear latent growth models. The effects of different covariates in the student temporal behavior is also evaluated.
Year of publication: |
2007
|
---|---|
Authors: | Bianconcini, Silvia ; Monari, Paola ; Cagnone, Silvia ; Mignani, Stefania |
Published in: |
RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO. - FrancoAngeli Editore, ISSN 1971-0380. - Vol. 2007/3.2007, 3, 3, p. 25-38
|
Publisher: |
FrancoAngeli Editore |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
A latent curve analysis of unobserved heterogeneity in university achievements
Bianconcini, Silvia, (2007)
-
Latent variable models for ordinal data by using the adaptive quadrature approximation
Cagnone, Silvia, (2013)
-
Latent variable models for ordinal data
Cagnone, Silvia, (2009)
- More ...