A finite mixture model approach on the first year university drop-out probability

University drop-out is one of the most important problems occurring in degree courses. The aim of this study is to analyze the first year drop-out at the University of Pisa. The analysis is focused on identifying the covariates affecting the probability to drop-out and on detecting the possible existence of unobserved subgroups of students having different drop-out rates. A dataset from the administrative data was collected for the cohort of freshmen enrolled to the first cycle degree courses in the academic years 2009 and 2010. The characteristics that affect the subgroups membership should represent an useful information for carrying out academic policy changes that could reduce the drop-out rate