Novosibirsk State Pedagogical University Bulletin, 2018, vol. 8, no. 6, pp. 183–199
© Luchko O., Patlasov O. Y., Mukhametdinova S., 2018
UDC: 
378.1+519.1+331.5

Developing efficient mechanism for management of educational migration flows based on economic and mathematical modelling

Luchko O. 1 (Omsk, Russian Federation), Patlasov O. Y. 2 (Omsk, Russian Federation), Mukhametdinova S. 1 (Omsk, Russian Federation)
1 Omsk humanitarian Academy
2 Omsk Regional Institution
Full text (Open Access) — Downloaded 3843
Abstract: 

Introduction. The authors investigate the problem of migration flows management in the field of education, based on mathematical and economic modelling. The purpose of the article is to identify the techniques of efficient educational migration management as a part of migration balance.
Materials and Methods. The authors utilized such research methods as questionnaires, expert evaluation, economic and mathematical modeling and tools of cognitive modeling in accordance with R. Axelrod’s methodology which is applied for the analysis of open systems containing hardly formalizable links between their components, taking into account the external influence.
Results. The analysis of current trends in migration processes has been conducted in the context of globalization and educational migration as their integral part. The features of educational migration flows in the Omsk region and their impact on the migration balance have been revealed. The authors identify controlling factors having most significant influence on the migration balance as a resultant factor depending on the intensity of educational migration and the degree of their mutual influence, taking into account the impact of the external environment. A cognitive model of migration balance has been introduced. It became the basis for a series of simulation experiments with specialized software which allowed to predict the effect of changes in the influence of various controlling factors on the migration balance. Recommendations for an efficient mechanism of managing migration educational flows in the Omsk region have been proposed.
Conclusions. In conclusion, the authors summarize the main techniques of efficient educational migration management as a part of migration balance. The study reveals the main control factors influencing the level of migration balance in the Omsk region. Among them are: better quality of higher education in Russia, geographic location, national discrimination and language barriers in the Republic of Kazakhstan, etc. A system of measures to manage educational migration flows as the most important components of the migration balance, taking into account the specifics of the Omsk Region, has been developed.

Keywords: 

Educational migration; Migration balance; Economic and mathematical methods; Questionnaire method; Control factors; Resulting factor; Cognitive modeling

93.973 Labour Market Integration | Emigrants and Immigrants | Earnings Gap

https://www.scopus.com/record/display.uri?src=s&origin=cto&ctoId=CTODS_1...

Developing efficient mechanism for management of educational migration flows based on economic and mathematical modelling

For citation:
Luchko O., Patlasov O. Y., Mukhametdinova S. Developing efficient mechanism for management of educational migration flows based on economic and mathematical modelling. Novosibirsk State Pedagogical University Bulletin, 2018, vol. 8, no. 6, pp. 183–199. DOI: http://dx.doi.org/10.15293/2226-3365.1806.11
References: 
  1. Söhn J. Back to school in a new country? The educational participation of adult immigrants in a life-course perspective. Journal of International Migration and Integration, 2016, vol. 17, issue 1, pp. 193–214. DOI: https://doi.org/10.1007/s12134-014-0401-1  
  2. Akumova N. V., Ivanov G. S. Current status of labour migration in the context of the overall migration in Russia. Law and Education, 2013, no. 10, pp. 114–122. (In Russian) URL: https://elibrary.ru/item.asp?id=20298428
  3. King R., Mata-Codesal D., Vullnetari J. Migration, development, gender and the ‘black box’ of remittances: Comparative findings from Albania and Ecuador. Comparative Migration Studies, 2013, vol. 1, issue 1, pp. 69–96. DOI: https://doi.org/10.5117/CMS2013.1.KING
  4. Patlasov O. Yu. Marketing-labor market management. Monograph. Tomsk, National Research Tomsk State University Publ., 2000, 640 p. (In Russian) URL: https://elibrary.ru/item.asp?id=24494212
  5. Kogan I. Potenziale nutzen!. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 2012, vol. 64, issue 1, pp. 67–89. DOI: https://doi.org/10.1007/s11577-012-0157-6
  6. Böhme M. H. Migration and educational aspirations – Another channel of brain gain?. IZA Journal of Migration, 2015, vol. 4, p. 12. DOI: https://doi.org/10.1186/s40176-015-0036-9
  7. Guveli A., Ganzeboom H. B. G., Platt L., Nauck B., Baykara-Krumme H., Eroğlu Ş., Bayrakdar S., Sözeri E. K., Spierings N. Educational attainment. Intergenerational Consequences of Migration. London, Palgrave Macmillan Publ., 2016, pp. 71–89. DOI: https://doi.org/10.1057/9781137501424_5
  8. Fursa E. V., Rogova T. M. International educational migration: Basic trends and features of modern development. Journal of Economic Regulation, 2012, no. 3, pp. 42–51. (In Russian) URL: https://elibrary.ru/item.asp?id=17992924
  9. Tran L. T., Pham L. International students in transnational mobility: Intercultural connectedness with domestic and international peers, institutions and the wider community. Compare: A Journal of Comparative and International Education, 2016, vol. 46, issue 4, pp. 560–581. DOI: https://doi.org/10.1080/03057925.2015.1057479  
  10. Fenoll A. A., Kuehn Z. Compulsory schooling laws and migration across European countries. Demography, 2017, vol. 54, issue 6, pp. 2181–2200. DOI: https://doi.org/10.1007/s13524-017-0615-x
  11. Van de Werfhorst H. G., Heath A. Selectivity of migration and the educational disadvantages of second-generation immigrants in ten host societies. European Journal of Population, 2018, pp. 1–32. DOI: https://doi.org/10.1007/s10680-018-9484-2
  12. Zakharchenko M. I. Regional aspects of educational migration. Kazan Science, 2016, no. 7, pp. 16–18. (In Russian) URL: https://elibrary.ru/item.asp?id=26460137  
  13. Dementieva S. V., Giniyatova E. V. Educational migration to Tomsk Polytechnic University: Mechanisms and practices of effective adaptation. Bulletin of the Tomsk Polytechnic University, 2012, no. 321, pp. 187–190. (In Russian) URL: https://elibrary.ru/item.asp?id=18796105  
  14. Luchko O., Mukhametdinova S., Patlasov O. Y. Using the tool-kit of cognitive modeling within the analysis of a vector educational migration. Novosibirsk State Pedagogical University Bulletin, 2017, no. 6, pp. 232–248. (In Russian) DOI: http://dx.doi.org/10.15293/2226-3365.1706.14   
  15. Luchko O. N., Muhametdinova S. Н. Influence of educational migration on education system the border regions of Russia (on example of Omsk Region). Science of the Person: Humanitarian Researches, 2017, no. 3, pp. 98–104. (In Russian) URL: https://elibrary.ru/item.asp?id=30483776
  16. Arkhipov A. Yu., Rogova T. M., Savchenkova I. N., Fursa Ye. V. Activity of higher education institutes for attraction, training and adaptation of foreign students (on example of the Southern Federal University). Terra Economicus, 2013, vol. 11, no. 1-2, pp. 124–128. (In Russian) URL: https://elibrary.ru/item.asp?id=19113902
  17. Kargina E. V. Development of international student support system as an instrument for attracting international students to Russian higher education institutions. Vector of Science of Togliatti State University. Series: Pedagogy, Psychology, 2014, no. 2, pp. 102–105. (In Russian) URL: https://elibrary.ru/item.asp?id=21955222
  18. Luchko O. N., Muhametdinova S. Н. Modeling the dynamics of the higher education system development within the Russian region bordering on the republic of Kazakhstan in the conditions of vector educational migration (On the Example of the Omsk Region). Science of the Person: Humanitarian Researches, 2017, no. 4, pp. 72–79. (In Russian) DOI: https://doi.org/10.17238/issn1998-5320.2017.30.72   URL: https://elibrary.ru/item.asp?id=32574836  
  19. Luchko O. N., Marenko V. A. Construction of a model of educational process with the use of cognitive technologies. Electronic Periodical Edition Information Environment of Education and Science, 2013, no. 17, pp. 38–41. (In Russian) URL: https://elibrary.ru/item.asp?id=20961308
  20. Luchko O. N., Marenko V. A. Cognitive Modeling as a Tool to Support Decision-Making. Omsk, Novosibirsk, Omsk State Service Institute Publ., Siberian Branch of the Russian Academy of Sciences Publ., 2014, 119 p. (In Russian) URL: https://elibrary.ru/item.asp?id=24063435  
Date of the publication 31.12.2018