Analysing the determinants of Italian university student mobility pathways

Abstract

In this paper, we study the mobility choices of Italian students in their transition from a bachelor’s to a master’s degree level with an added emphasis on their overall mobility pathways. We consider individual data from the Italian National Student Archive on two cohorts of students who were enrolled in the academic years 2011–2012 and 2014–2015. We followed both cohorts in Italian universities for six academic years. This allowed us to depict five different profiles of students, categorise them as stayers vs. movers, and work at two different levels. Logit models were then adopted to study the probability to be in mobility at a master’s level, given that a student had been a stayer at bachelor’s degree, and to assess the effect of the field of study. Apart from individual characteristics, network centrality measures were encompassed in the model to assess the university attractiveness in influencing mobility choices.

A new measure for the attitude to mobility of Italian students and graduates: a topological data analysis approach

“…This is actually in line with the results reported in Columbu et al. ( 2021a ), in which the authors consider a wider classification of stayer and mover defining five mobility profiles according to the time and the distance at which the students perform the moving. In fact, Columbu et al.…”

“…In fact, Columbu et al. ( 2021a ) state that there are slight differences between the two groups of males and females in the probability of belonging to the five profiles. The students having a high school diploma in a scientific or humanistic area tend to have a higher mobility attitude with respect to the fellows that have a vocational or technical high school diploma.…”

“…In fact, Columbu et al. ( 2021a ) state that there are slight differences between the two groups of males and females in the probability of belonging to the five profiles.…”

Analysing Students’ Mobility at Higher Education Institutions: Case of Ukrainian University During the War

“…Examples of such systems include Mobility Management Systems, Student Management Systems, Student Connectivity Module (Materka et al, 2012) and Erasmus's integrated system for all participating universities -Erasmus+ Without Paper (Fedorchuk et al, 2022). In addition, some education data mining tools that proved to be valuable for other management issues, can also be appropriate to identify patterns and predict students' mobility (e.g., Sankey Diagram (Oran et al, 2019), logistic model and network approach (Columbu et al, 2021)).…”

Students’ university mobility patterns in Europe: an introduction

“…Is it possible to depict some networks between regions of origin and destination that can help us understand mobility patterns? (Columbu et al, 2021). Is there a gender gap in Science, Technology, Engineering, and Mathematics (STEM) courses in terms of degree course completion?…”