2020
DOI: 10.1007/s11205-020-02282-2
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Analysing International Student Mobility Flows in Higher Education: A Comparative Study on European Countries

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Cited by 31 publications
(28 citation statements)
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“…The time dimension could be analyzed in more detail by checking for possible differences and similarities across the period, not only comparing each year included but adopting a dynamic approach to the network data (Batagelj et al 2014). A further extension of the present work could be the adoption of a blockmodeling approach, along the lines of (Restaino et al 2020), to highlight the presence of sub-networks and communities in the network of universities. The longitudinal data could be also exploited in a more model-based analysis.…”
Section: Discussionmentioning
confidence: 99%
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“…The time dimension could be analyzed in more detail by checking for possible differences and similarities across the period, not only comparing each year included but adopting a dynamic approach to the network data (Batagelj et al 2014). A further extension of the present work could be the adoption of a blockmodeling approach, along the lines of (Restaino et al 2020), to highlight the presence of sub-networks and communities in the network of universities. The longitudinal data could be also exploited in a more model-based analysis.…”
Section: Discussionmentioning
confidence: 99%
“…The authors provide a general overview of Erasmus mobility trends, revealing 3 different groups of countries: good senders and receivers, good senders only, and good receivers only. The hubs and authorities technique is further extended in Restaino et al ( 2020 ) which in addition adopt a blockmodeling approach on the network of countries involved in the Erasmus mobility both for study and internship abroad. The authors provide also an analysis of homophily behaviors among countries and exploit educational indicators from Eurostat to include investments in higher education.…”
Section: Introduction and Prior Research On The Erasmus Programmentioning
confidence: 99%
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“…Beyond statistical power, larger samples allow for comparisons between, for instance, subgroups of international students. Given its steady increase in the past 20 years [46], international student mobility has gained importance as a driver of international scientific co-operation networks [47]. Universities will therefore seek to counteract the decline in student mobility caused by the COVID-19 pandemic by, for instance, optimising their classroom teaching to meet the needs of international students and incentivise them to cross borders for the purpose of study [47].…”
Section: Plos Onementioning
confidence: 99%
“…Whereas current research has adopted qualitative methods, our approach is quantitative and relies on social network analysis to highlight the structure of students' flows. The network approach is not new to the study of international student mobility (Shields 2013) and Erasmus in particular (Restaino et al 2020;Breznik and Skrbinjek 2020;Breznik 2017;Breznik and Djaković 2016;Derzsi et al 2011;Breznik and Ragozini 2015). Prior research mostly conducted analysis at country level rather than university level, with the exception of De Benedictis and Leoni (2020) who focused on differences by gender and Derzsi et al (2011) who studied the topology of the Erasmus student mobility network in 2003, revealing an exponential degree distribution and a small-word type random network with a giant component.…”
Section: The Erasmus Mobility As a Networkmentioning
confidence: 99%