Travel time to university as determinant on students performances

This research aims to investigate the impact of home-university travel time on university students' performance. The study uses a two-step process where, first, home-university travel times are estimated using a data-driven methodology and then evaluated for their impact on students' performance using statistical methods. The accessibility to university is measured using GPS data of anonymous individuals in the Comune di Milano collected by Cuebiq Inc. The estimated commuting time to university is used to create isochronous maps with Kernel Regression Estimation. The second phase uses personal and academic information of first-year engineering students from Politecnico di Milano to investigate the effect of travel time on performance. In this step Generalized Linear Mixed Effect methods are applied. The study is innovative as it is one of the first to focus on the topic and, in particular, it uses a new model for the estimation of commuting time.