Analysis of the Effectiveness of Vocational Guidance Activities of the University Using Machine Learning
Abstract
The purpose of the paper is to characterize the problems as well as some possible directions of development of career guidance activities and work with applicants of a provincial university using the example of Ulyanovsk State University.
Analysis of the effectiveness of existing tools for the interaction of the university with potential students and proposals for their development and modification should be based primarily on the results of studying the target audience, in particular, on the analysis of the needs of today's applicant, on his motives for obtaining higher education, and on the criteria for choosing a university. These characteristics, in addition to general trends dictated by global social and economic changes, have regional specificity. This determines the relevance of the study, despite the considerable attention to these problems.
The authors offer several hypotheses about modern tools for forming the reputation of a provincial university and the reasons for the desire of schoolchildren (especially the most successful ones) to continue their education in another region. Hypothesis testing is carried out based on the analysis of data from a survey of senior schoolchildren of the Ulyanovsk region. The paper describes the structure of the survey conducted in the spring of 2021 and the characteristics of the sample. Statistical methods and machine learning tools are used for the analysis. The paper presents the results of the analysis, their interpretation, and discussion.
In conclusion, the authors identify the main factors affecting the results of admission of students of Ulyanovsk State University in the form of conclusions that provide a basis for the formation of a vector of correction of the content and forms of career guidance, of the university's advertising campaign strategy and the recruiting system for applicants in the region. As expected, in addition to the general characteristics inherent to Russian applicants, features specific to the region under study were identified.
References
2. Avralev N.V., Efimova I.N., Makoveichuk A.V. Innovative approaches to the development of a system for university student recruitment. Integratsiya obrazovaniya = Integration of Education. 2017; 21(2):247-261. (In Russ., abstract in Eng.) doi: https://doi.org/10.15507/1991-9468.087.021.201702.247-261
3. Valeeva R.R., Khusainova G.R. Study of factors influencing the choice of a higher educational institution by applicants. Global'nyi nauchnyi potentsial = Global scientific potential. 2020; (12):136-138. Available at: https://elibrary.ru/item.asp?id=44847021 (accessed 15.11.2021) (In Russ., abstract in Eng.)
4. Glebova G.F. The topical issues of classic university and school cooperation in the regional system of lifelong learning. Nepreryvnoe obrazovanie: XXI vek = Lifelong Education: the XXI century. 2014; (1):119-134. (In Russ., abstract in Eng.) doi: https://doi.org/10.15393/j5.art.2014.2267
5. Knyazkina E.A. Strategies for attracting talented youth to a technical university. Kazanskii pedagogicheskii zhurnal=Kazan Pedagogical Journal. 2021; (1):113-119. (In Russ., abstract in Eng.) doi: https://doi.org/10.51379/KPJ.2021.145.2.014
6. Lorents V.V. The university competitiveness factors. Uspekhi gumanitarnykh nauk = Modern humanities success. 2020; (2):7-12. Available at: https://www.elibrary.ru/item.asp?id=42489028 (accessed 15.11.2021). (In Russ., abstract in Eng.)
7. Maslevich T.P., Safronova N.B., Minaeva N.L. Innovative ways of applicants attraction (based on research of factors of motivation). Vestnik Orenburgskogo gosudarstvennogo universiteta = Vestnik of the Orenburg State University. 2018; (6):52-60. Available at: https://www.elibrary.ru/item.asp?id=36915157 (accessed: 15.11.2021). (In Russ., abstract in Eng.)
8. Ryabokon M.V. Behavior models of entrants when choosing the university. Vestnik Nizhegorodskogo universiteta im. N. I. Lobachevskogo. Seriya: Social'nye nauki = Vestnik of Lobachevsky State University of Nizhni Novgorod. Series: Social Sciences. 2016; (4):177-185. Available at: https://www.elibrary.ru/item.asp?id=28416044 (accessed: 15.11.2021). (In Russ., abstract in Eng.)
9. Tikhonova A.A. Features of the Choice of the Psychology Profession by Students: Motivational Aspect (Using the Example of UlSPU Students). Povolzhskij pedagogicheskij poisk = Volga Region Pedagogical Search. 2019; (1):31-38. (In Russ., abstract in Eng.) doi: https://doi.org/10.33065/2307-1052-2019-1-27-31-38
10. Jukova E.E., Kozyrev M.S., Ilina I.Yu., Melnichuk Yu. A. Analysis of the target audience of the educational services market on the example of Moscow universities. Perspektivy nauki i obrazovania = Perspectives of Science and Education. 2020; (2):430-442. (In Russ., abstract in Eng.) doi: https://doi.org/10.32744/pse.2020.2.34
11. Durdyev S., Ihtiyar A. Structural Equation Model of Factors Influencing Students to Major in Architecture, Engineering, and Construction. Journal of Professional Issues in Engineering Education and Practice. 2019; 145(2):05018019. (In Eng.) doi: https://doi.org/10.1061/(ASCE)EI.1943-5541.0000402
12. Kiselev P., Kiselev B., Matsuta V., Feshchenko A., Bogdanovskaya I., Kosheleva A. Career guidance based on machine learning: social networks in professional identity construction. Procedia Computer Science. 2020; 169:158-163. (In Eng.) doi: https://doi.org/10.1016/j.procs.2020.02.128
13. Debrenne M., Pogorelskaya A.M., Pomorina I.V. Skalaban I.A. A Comparative Analysis of the Factors Determining the Way British, Russian and French University Entrants Choose the University. Tomsk State University Journal. 2019; (446):90-95. (In Russ., abstract in Eng.) doi: https://doi.org/10.17223/15617793/446/12
14. Jukova E.E., Vasyutkina L.V., Chernykh I.N., Vasyutkina A.A. Correlation between the Choice of University and Admission Standards. Journal of Advanced Research in Dynamical and Control Systems. 2020; 12(03):1238-1244. (In Eng.) doi: https://doi.org/10.5373/JARDCS/V12SP3/20201372
15. Gajnanov D.A., Migranova L.I., Minyazev A.I. Cifrovaya model' povedeniya abiturienta v obrazovatel'noj srede [Digital Model of an Applicant's Behavior in the Educational Environment]. Iskusstvennye obshchestva = Artificial Societies. 2020; 15(4). (In Russ., abstract in Eng.) doi: https://doi.org/10.18254/S207751800011658-2
16. Zhezhnych P., Zub K., Berezko O., Shilinh A. A Comparison of Machine Learning Algorithms for Prediction Higher Education Institution’s Entrants Admissions. In: Hu Z., Zhang Q., Petoukhov S., He M. (eds.) Advances in Artificial Systems for Logistics Engineering. ICAILE 2021. Lecture Notes on Data Engineering and Communications Technologies. Vol 82. Springer, Cham; 2021. p. 171-179. (In Eng.) doi: https://doi.org/10.1007/978-3-030-80475-6_17
17. Bhaskaran S.S., Aali M.A. Data Mining Model for Better Admissions in Higher Educational Institutions (HEIs) ‒ A Case Study of Bahrain. In: Hassanien A., Bhatnagar R., Darwish A. (eds.) Advanced Machine Learning Technologies and Applications. AMLTA 2020. Advances in Intelligent Systems and Computing. Vol. 1141. Springer, Singapore; 2021. p. 141-150. (In Eng.) doi: https://doi.org/10.1007/978-981-15-3383-9_13
18. Terentyev K. Educational strategies of university applicants: the development of classifications. Nepreryvnoe obrazovanie: XXI vek = Lifelong Education: The 21st Century. 2015; 3(11). (In Russ., abstract in Eng.) doi: https://doi.org/10.15393/j5.art.2015.2922
19. Skalaban I.A., Osmuk L.A., Kolesova O.V., Cherepanov G.M. Roads old and new: Educational strategies in university choice by Russian students. Vysshee obrazovanie v Rossii = Higher Education in Russia. 2019; 29(2):50-62. (In Russ., abstract in Eng.) doi: https://doi.org/10.31992/0869-3617-2020-29-2-50-62
20. Nuseir M.T., El Refae G.A. Factors influencing the choice of studying at UAE universities: an empirical research on the adoption of educational marketing strategies. Journal of Marketing for Higher Education. 2021. (In Eng.) doi: https://doi.org/10.1080/08841241.2020.1852467
21. Simões C., Soares A.M. Applying to higher education: information sources and choice factors. Studies in Higher Education. 2010; 35(4):371-389. (In Eng.) doi: https://doi.org/10.1080/03075070903096490
22. Delaney J.M., Devereux P.J. Choosing differently? College application behavior and the persistence of educational advantage. Economics of Education Review. 2020; 77:101998. (In Eng.) doi: https://doi.org/10.1016/j.econedurev.2020.101998
23. Jayakumar U.M., Page S.E. Cultural Capital and Opportunities for Exceptionalism: Bias in University Admissions. The Journal of Higher Education. 2021; 92(7):1109-1139. (In Eng.) doi: https://doi.org/10.1080/00221546.2021.1912554
24. Cunninghame I. Influence of policy discourse on student choice in Australian higher education. International Journal of Inclusive Education. 2020. (In Eng.) doi: https://doi.org/10.1080/13603116.2020.1791980
25. Savitskaya E.V., Altunina N.S. Higher Education: Reputational Effects, Distorted Signaling and Propitious Selection. Zhurnal institucional'nyh issledovanij = Journal of Institutional Studies. 2017; 9(1):117-133. (In Russ., abstract in Eng.) doi: https://doi.org/10.17835/2076-6297.2017.9.1.117-133
26. Shushara T.V., Ustinova Yu.D., Alexandrov A.P. Study of the factors of choosing the university by parents of as an important element of strategic marketing in educationю Perspektivy nauki i obrazovania = Perspectives of Science and Education. 2019; (2):453-464. (In Russ., abstract in Eng.) doi: https://doi.org/10.32744/pse.2019.2.34
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication policy of the journal is based on traditional ethical principles of the Russian scientific periodicals and is built in terms of ethical norms of editors and publishers work stated in Code of Conduct and Best Practice Guidelines for Journal Editors and Code of Conduct for Journal Publishers, developed by the Committee on Publication Ethics (COPE). In the course of publishing editorial board of the journal is led by international rules for copyright protection, statutory regulations of the Russian Federation as well as international standards of publishing.
Authors publishing articles in this journal agree to the following: They retain copyright and grant the journal right of first publication of the work, which is automatically licensed under the Creative Commons Attribution License (CC BY license). Users can use, reuse and build upon the material published in this journal provided that such uses are fully attributed.
