Understanding the phenomenon of intra- and international student mobility has become increasingly relevant to the organization of tertiary education systems. Using microdata information provided by the Italian National Student Archive on the cohorts of students enrolled at university in the academic years 2011–12 and 2014–15, we consider a network analysis approach to investigate the incoming and outgoing student flows between territories and universities. More specifically, the paper aims to shed light on the dynamics of Italian student mobility networks at both the bachelor's and master's degree levels by considering attractiveness indicators combined with network centrality measures, clustering techniques for network data and explanatory models. We analyze the partition of the global network structure by means of blockmodeling analysis and we explain the determinants of the differences among universities in attracting students adopting a quantile regression analysis.

Geography of Italian student mobility: A network analysis approach

Columbu S.;Porcu M.;Sulis I.
;
2021-01-01

Abstract

Understanding the phenomenon of intra- and international student mobility has become increasingly relevant to the organization of tertiary education systems. Using microdata information provided by the Italian National Student Archive on the cohorts of students enrolled at university in the academic years 2011–12 and 2014–15, we consider a network analysis approach to investigate the incoming and outgoing student flows between territories and universities. More specifically, the paper aims to shed light on the dynamics of Italian student mobility networks at both the bachelor's and master's degree levels by considering attractiveness indicators combined with network centrality measures, clustering techniques for network data and explanatory models. We analyze the partition of the global network structure by means of blockmodeling analysis and we explain the determinants of the differences among universities in attracting students adopting a quantile regression analysis.
2021
Attractiveness; Blockmodeling; Network centrality; Quantile regression; Student mobility
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/300689
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