Migration and students' performance: detecting geographical differences following a curves clustering approach

Boscaino, Giovanni; Sottile, Gianluca; Adelfio, Giada

doi:10.1080/02664763.2020.1845624

Cited by 2 publications

(2 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, student mobility from the South to the Center and North of the country has increased, 30% of students living in the South decided to enrol in universities in the Center-North in 2017 Attanasio and Priulla (2020). Boscaino et al in (2020) argue that this kind of mobility can be affected by better job-market opportunities in the Center-North, so it looks as if university quality is less important. Furthermore, Santelli et al in (2019) showed how southern regions are affected by increasing rates of outward bound students-especially in Sicily-arguing that mobility to the North is driven by job-market opportunities at destination.…”

Section: Introductionmentioning

confidence: 99%

A network analysis of student mobility patterns from high school to master’s

et al. 2021

View full text Add to dashboard Cite

Human migration involves the movement of people from one place to another. An example of undirected migration is Italian student mobility where students move from the South to the Center-North. This kind of mobility has become of general interest, and this work explores student mobility from Sicily towards universities outside the island. The data used in this paper regards six cohorts of students, from 2008/09 to 2013/14. In particular, our goal is to study the 3-step migration path: the area of origin (Sicilian provinces), the regional university for the bachelor's degree, and the regional university for the master's. Our analysis is conducted by building a multipartite network with four sets of nodes: students; Sicilian provinces; bachelor region of studies; and the master region of studies. By projecting the students' set onto the others, we obtain a tripartite network where the number of students represents the link weight. Results show that the big Sicilian cities-Palermo, Catania, and Messina-have different preferential paths compared to small Sicilian cities. Furthermore, the results reveal preferential paths of 3-step mobility that only, in part, reflect a south-north orientation in the transition from the region of study for the bachelor degree to that for the master's.

show abstract

Section: Introductionmentioning

confidence: 99%

A network analysis of student mobility patterns from high school to master’s

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In particular, our analysis adds further knowledge to the existing literature regarding the relationship between mobility and student performance in the Italian setting, such as Enea (2018), who explored the mobility of southerners from their first level to second level university degrees by considering both the time-to-graduation and the final marks for their bachelor's degrees. Moreover, Attanasio et al (2018) studied Italian university science students' careers during the last decade, and an analysis was carried out by Boscaino et al (2018), which only referred to Sicilian students.…”

mentioning

confidence: 99%

Movers and stayers in STEM enrollment in Italy: who performs better?

D’Agostino

Ghellini

Lombardi

2021

Genus

View full text Add to dashboard Cite

Recently, the mobility behavior of Italian university students has garnered increasing interest from both social scientists and politicians. The very particular geographical characteristics of the country, together with the recognized persistence of a significant economic gap between the southern and northern regions, drive a large number of students to move from the first macro-region to the latter. As this phenomenon has several economic and social implications for policy-makers—at both central and local levels—it has led to various theories and prejudices. The present article will study the differences between the performance of STEM students who have decided to move from the south to the north and those who have decided to stay close to their hometowns. We devised multilevel modelling techniques to analyze this issue using administrative microdata from the Italian Ministry for Universities and Research (MUR), including eight cohorts of students from AY 2008–2009 to AY 2015–16, who enrolled in STEM fields after earning their high school diploma. One of the main findings is that individuals who moved from the south show lower levels of performance than their stayer counterparts who are enrolled in northern or central universities.

show abstract

Migration and students' performance: detecting geographical differences following a curves clustering approach

Cited by 2 publications

References 33 publications

A network analysis of student mobility patterns from high school to master’s

A network analysis of student mobility patterns from high school to master’s

Movers and stayers in STEM enrollment in Italy: who performs better?

Contact Info

Product

Resources

About