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General Articles

The role of language proximity in shaping international student mobility flows

ORCID Icon, ORCID Icon & ORCID Icon
Pages 563-574 | Received 18 May 2021, Accepted 20 Apr 2022, Published online: 01 May 2022
 

ABSTRACT

Many papers on international student mobility have analysed different macro factors influencing the decision making of international students. However, only a limited number of studies have considered the role of language distance on international educational choices. This paper aims to fill that gap by identifying the role of language proximity in international degree seeking student flows among 21 countries of the European Economic Area in the years 2005, 2010 and 2015. Our gravity models reveal a statistically significant influence of language proximity on student flows within these 21 countries. We argue that language proximity simplifies academic, cultural and socio-economic integration of international students in the destination country and as a result makes the process of their adaptation to a new environment easier and smoother. Future research should expand on the mechanisms of that influence.

Acknowledgements

Elena Ovchinnikova is grateful to Olga Klachkova, Olga Suchkova, and Evgeny Ivanov for their excellent research assistance and to the Center for Study of Diversity and Social Interactions at the New Economic School for its support.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 To avoid the problem of missing data, for two countries (Austria and Iceland) information from the neighbouring years, 2006 and 2014 is used. Using this method meant that the only missing data were flows to Germany in 2005 and 2010. Taking the Western Europe and North America region as a whole for those years, for each origin country we subtracted the flows to all destination countries. The remaining number of outbound students for each country therefore represented the flows into Germany for 2005 and 2010.

2 Please see Ginsburgh and Weber (Citation2016) for the description of other existing classifications and Adsera and Pytlikova (Citation2015), Isphording and Otten (Citation2014), Baláž, Williams, and Chrančoková (Citation2018) for the application of these classifications in their analyses.

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