Preview

Vysshee Obrazovanie v Rossii = Higher Education in Russia

Advanced search

Choice of Field of Study: A Network of Motives and Students’ Motivational Profiles

https://doi.org/10.31992/0869-3617-2026-35-3-10-32

Abstract

The choice of an educational and professional trajectory is an important stage in the life course and is associated with subsequent professional development and psychological well-being. The present study aims to analyze the motivational foundations of students’ choice of field of study, with a focus on differences between STEM and non-STEM fields as well as gender differences. An integrative approach is employed, combining methods of network psychometrics and person-oriented analysis. Using a sample of students enrolled in different programs (bachelor’s and specialist degrees) from 31 universities (N = 7,196; 64% female; 38% enrolled in STEM fields), the structure of interrelations among motives for choosing a field of study was reconstructed using an Ising model, and latent motivational profiles were identified via latent class analysis. The results show that motivation for choosing a field of study constitutes a connected system in which distinct clusters (e.g., social motives, pragmatic motives) and bridging nodes (e.g., intrinsic personal interest) can be identified. Latent class analysis revealed five motivational profiles, the distribution of which differs between STEM and non-STEM fields as well as between male and female students. The findings underscore the importance of a comprehensive approach to the study of motivation in the choice of field of study.

About the Authors

S. B. Malykh

Russian Federation

Sergey B. Malykh – Dr.Sci. (Psychology), Academician of the Russian Academy of Education, professor, academician-secretary of the Division of the psychology and developmental physiology

Researcher ID: I-3697-2013



A. O. Tabueva
Russian Academy of Education
Russian Federation

Anna O. Tabueva – leading analyst

Researcher ID: AAO-2545-2020

8 Pogodinskaya str., Moscow, 119121

 



Y. V. Kuzmina
Psychological Institute of RAE
Russian Federation

Yulia V. Kuzmina – Ph.D. (Psychology), researcher

Researcher ID: I-3187-2015

9 Mokhovaya str., bldg. 4, Moscow, 125009

 



P. V. Kolyasnikov

Russian Federation

Pavel V. Kolyasnikov – leading analyst

Researcher ID: O-1885-2018

 



A. S. Malykh
Russian Academy of Education
Russian Federation

Artem S. Malykh – leading analyst

Researcher ID: AAO-3640-2020

8 Pogodinskaya str., Moscow, 119121



References

1. Yam, F. C., Korkmaz, O. (2024). Linking Career Decision Regret to Psychological Well-Being: Serial Mediation of Vocational Outcome Expectations and Proactive Career Behaviors. Current Psychology. Vol. 43, no. 41, pp. 32274-32287, doi: 10.1007/s12144-024-06656-4.

2. Sharok, V.V. (2018). Emotional and Motivational Factors of Satisfaction with University Education. Sibirskii psikhologicheskii zhurnal = Siberian Journal of Psychology. No. 69, pp. 33-45, doi: 10.17223/17267080/69/2 (In Russ., abstract in Eng.).

3. Kolesnikova, E.M., Kudenko, I.A. (2020). Interest in STEM Professions at School: Problems of Career Guidance]. Sotsiologicheskie issledovaniya = Sociological Studies. No. 4, pp. 124-133, doi: 10.31857/S013216250009117-1 (In Russ., abstract in Eng.).

4. Maloshonok, N.G., Shcheglova, I.A., Vilkova, K.A., Abramova, M.O. (2022). How to Attract Girls to Stem and Help Them Succeed: A Review of Practices for Overcoming Gender Stereotypes. Vysshee obrazovanie v Rossii = Higher Education in Russia. Vol. 31, no. 11, pp. 63-89, doi: 10.31992/0869-3617-2022-31-11-63-89 (In Russ., abstract in Eng.).

5. Lipshits-Braziler. Y., Arieli. S., Daniel. E. (2025). Personal Values and Career-Related Preferences among Young Adults. Journal of Personality. Vol. 93, no. 2, pp. 378-393, doi: 10.1111/jopy.12935.

6. Skatova, A., Ferguson, E. (2014). Why Do Different People Choose Different University Degrees? Motivation and the Choice of Degree. Frontiers in Psychology. Vol. 5, article no. 1244, doi: 10.3389/fpsyg.2014.01244.

7. Kuz’mina, Yu.V. (2013). [The Choice of Major: Direct and Indirect Effects of Family Factors]. Vysshee obrazovanie v Rossii = Higher Education in Russia. No. 10, pp. 133–140. Available at: https://elibrary.ru/download/elibrary_20745156_67794625.pdf (accessed 03.02.2026). (In Russ., abstract in Eng.).

8. Van Tuijl, C., van der Molen, J.H.W. (2016). Study Choice and Career Development in STEM Fields: An Overview and Integration of the Research. International Journal of Technology and Design Education. Vol. 26, no. 2, pp. 159-183, doi: 10.1007/s10798-015-9308-1.

9. Lebedeva, N.V., Vilkova, K.A. (2022). Why Do Girls Not Choose STEM? Gender Differences in Motivational Orientations. Monitoring obshchestvennogo mneniya: ekonomicheskie i sotsial’nye peremeny = Monitoring of Public Opinion: Economic and Social Changes. No. 3, doi: 10.14515/monitoring.2022.3.1923 (In Russ., abstract in Eng.).

10. Savinskaya, O.B., Lebedeva, N.V., Vilkova, K.A. (2022). Gender Stereotypes and Women’s Strategies in Higher STEM Education: A Review of the Interdisciplinary Field. The Journal of Social Policy Studies. Vol. 20, no. 3, pp. 505-520, doi: 10.17323/727-0634-2022-20-3-505-520 (In Russ., abstract in Eng.).

11. Al’mukhambetova, A., Kuzhabekova, A., Kim, T. (2025). Factors That Facilitate and Hinder Women’s Retention in Mathematically Intensive STEM fields: Experience of Female Undergraduates from Kazakhstan. Voprosy obrazovaniya = Educational Studies Moscow. No. 1, pp. 25-53, doi: 10.17323/vo-2025-18297 (In Russ., abstract in Eng.).

12. Shin, J.E.L., Levy, S.R., London, B. (2016). Effects of Role Model Exposure on STEM and Non- STEM Student Engagement. Journal of Applied Social Psychology. Vol. 46, no. 7, pp. 410-427, doi: 10.1111/jasp.12371.

13. Wegemer, C.M., Eccles, J.S. (2019). Gendered STEM Career Choices: Altruistic Values, Beliefs, and Identity. Journal of Vocational Behavior. Vol. 110, pp. 28-42, doi: 10.1016/j. jvb.2018.11.013.

14. Diekman, A.B., Brown, E.R., Johnston, A.M., Clark, E.K. (2010). Seeking Congruity between Goals and Roles: A New Look at Why Women Opt Out of Science, Technology, Engineering, and Mathematics Careers. Psychological Science. Vol. 21, no. 8, pp. 1051-1057, doi: 10.1177/0956797610379682.

15. Lv, B., Wang, J., Zheng, Y., Peng, X., Ping, X. (2022). Gender Differences in High School Students’ STEM Career Expectations: An Analysis Based on Multi-Group Structural Equation Model. Journal of Research in Science Teaching. Vol. 59, no. 10, pp. 1739-1764, doi: 10.1002/tea.21772.

16. Maloshonok, N.G., Shcheglova, I.A., Vilkova, K.A., Abramova, M.O. (2022). Gender Stereotypes and the Choice of Engineering Field of Study. Voprosy obrazovaniya = Educational Studies Moscow. No. 3, pp. 149-186, doi: 10.17323/1814-9545-2022-3-149-186 (In Russ., abstract in Eng.).

17. Ismatullina, V.I., Maslennikova, E.P. (2021). Sex Differences in Motivation and Self-Assessment of Academic Abilities among High School Students Preferring STEM Fields as a Future Career. Differentsial’naya psikhologiya i psikhofiziologiya segodnya: sposobnosti, obrazovanie, professionalizm [Differential Psychology and Psychophysiology Today: Abilities, Education, Professionalism]. No. 1, pp. 433-437, doi: 10.24412/cl-36667-2021-1-433-437 (In Russ.).

18. Frenzel, A.C., Pekrun, R., Goetz, T. (2007). Girls and Mathematics – A “Hopeless” Issue? A Control-Value Approach to Gender Differences in Emotions Towards Mathematics. European Journal of Psychology of Education. Vol. 22, no. 4, article no. 497, doi: 10.1007/BF03173468.

19. Bogdanova, O.E., Miklashevskii, A.A., Bogdanova, E.L., Soldatenkova, O.B. (2019). Academic Achievement of School Students in Mathematics and Foreign Language: Individual Characteristics and Gender Stereotypes. Sibirskii psikhologicheskii zhurnal = Siberian Journal of Psychology. No. 73, pp. 176-196, doi: 10.17223/17267080/73/11 (In Russ., abstract in Eng.).

20. Jiang, S., Simpkins, S.D., Eccles, J.S. (2020). Individuals’ Math and Science Motivation and Their Subsequent STEM Choices and Achievement in High School and College: A Longitudinal Study of Gender and College Generation Status Differences. Developmental Psychology. Vol. 56, no. 11, pp. 2137-2151, doi: 10.1037/dev0001110.

21. Morosanova, V.I., Potanina, A.M. (2024). Individual-Typological Trajectories of School Engagement in Adolescents: A Longitudinal Study. Psikhologicheskaya nauka i obrazovanie = Psychological Science and Education. Vol. 26, no. 6, pp. 178-191, doi: 10.17759/pse.2024290612 (In Russ., abstract in Eng.).

22. Wang, C.K.J., Liu, W.C., Nie, Y., Chye, Y.L.S., Lim, B.S.C. et al. (2017). Latent Profile Analysis of Students’ Motivation and Outcomes in Mathematics: An Organismic Integration Theory Perspective. Heliyon. Vol. 3, no. 5, article no. e00308, doi: 10.1016/j.heliyon.2017.e00308.

23. Gordeeva, T.O., Sychev, O.A. (2017). Motivational Profiles as Predictors of Self-Regulation and Academic Achievement of Students. Vestnik Moskovskogo universiteta. Seriya 14. Psikhologiya = Lomonosov Psychology Journal. No. 1, pp. 67-87, doi: 10.11621/vsp.2017.01.69 (In Russ., abstract in Eng.).

24. Jiang, L., Zhou, N., Gu, M. M., Li, X. (2025). Exploring Student Motivation and Engagement in EMI: A Latent Profile Analysis. Language and Education. Vol. 39, no. 1, pp. 72-90, doi: 10.1080/09500782.2024.2311146.

25. Jähne, M.F., Naumann, A., Moeller, J., Baars, J., Dietrich, J. (2025). Which Insights Can Research on Achievement Motivation Gain from Network Analysis? Comparing Different Network Methods Empirically. Motivation Science. Advance online publication, doi: 10.1037/mot0000397.

26. Epskamp, S., Borsboom, D., Fried, E.I. (2018). Estimating Psychological Networks and Their Accuracy: A Tutorial Paper. Behavior Research Methods. Vol. 50, no. 1, pp. 195-212, doi: 10.3758/s13428-017-0862-1.

27. Van Borkulo, C.D., Borsboom, D., Epskamp, S., Blanken, T.F., Boschloo, L., Schoevers, R.A., Waldorp, L.J. (2014). A New Method for Constructing Networks from Binary Data. Scientific Reports. Vol. 4, no. 1, article no. 5918, doi: 10.1038/srep05918.

28. Opsahl, T., Agneessens, F., Skvoretz, J. (2010). Node Centrality in Weighted Networks: Generalizing Degree and Shortest Paths. Social Networks. Vol. 32, no. 3, pp. 245-251, doi: 10.1016/j.socnet.2010.03.006.

29. Robinaugh, D.J., Millner, A.J., McNally, R.J. (2016). Identifying Highly Influential Nodes in the Complicated Grief Network. Journal of Abnormal Psychology. Vol. 125, no. 6, article no. 747, doi: 10.1037/abn0000181.

30. Nylund, K.L., Asparouhov, T., Muthén, B.O. (2007). Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study. Structural Equation Modeling: A Multidisciplinary Journal. Vol. 14, no. 4, pp. 535-569, doi: 10.1080/10705510701575396.

31. Ryan, R.M., Deci, E.L. (2020). Intrinsic and Extrinsic Motivation from a Self-Determination Theory Perspective: Definitions, Theory, Practices, and Future Directions. Contemporary Educational Psychology. Vol. 61, article no. 101860, doi:. 10.1016/j.cedpsych.2020.101860.

32. Simon, R.A., Aulls, M.W., Dedic, H., Hubbard, K., Hall, N. (2015). Exploring Student Persistence in STEM Programs: A Motivational Model. Canadian Journal of Education / Revue canadienne de l’éducation. Vol. 38, no. 1, pp. 1-27. Available at: https://cje-rce.ca/index.php/cje-rce/article/view/1729/1739 (accessed 10.10.2025).

33. Luttenberger, S., Paechter, M., Ertl, B. (2019). Self-Concept and Support Experienced in School as Key Variables for the Motivation of Women Enrolled in STEM Subjects with a Low and Moderate Proportion of Females. Frontiers in Psychology. Vol. 10, article no. 1242, doi: 10.3389/ fpsyg.2019.01242.

34. Lent, R.W., Brown, S.D., Hackett, G. (1994). Toward a Unifying Social Cognitive Theory of Career and Academic Interest, Choice, and Performance. Journal of Vocational Behavior. Vol. 45, no. 1, pp. 79-122, doi: 10.1006/jvbe.1994.1027.

35. Bandura, A. (2001). Social Cognitive Theory: An Agentic Perspective. Annual Review of Psychology. Vol. 52, no. 1, pp. 1-26, doi: 10.1146/annurev.psych.52.1.1.

36. Ismatullina, V., Adamovich, T., Zakharov, I., Vasin, G., Voronin ,I. (2022). The Place of Gender Stereotypes in the Network of Cognitive Abilities, Self-Perceived Ability and Intrinsic Value of School in School Children Depending on Sex and Preferences in STEM. Behavioral Sciences. Vol. 12, no. 3, article no. 75, doi: 10.3390/bs12030075.

37. Savinskaya, O.B., Mkhitaryan, T.A. (2018). Technical Disciplines (STEM) as a Female Career Choice: Achievement, Self-Assessment and the Hidden Curriculum. Zhenshchina v rossiiskom obshchestve = Woman in Russian Society. No. 3 (88), pp. 34-48, doi: 10.21064/WinRS.2018.3.4 (In Russ., abstract in Eng.).

38. Ramaci, T., Pellerone, M., Ledda, C., Presti, G., Squatrito, V., Rapisarda, V. (2017). Gender Stereotypes in Occupational Choice: A Cross-Sectional Study on a Group of Italian Adolescents. Psychology Research and Behavior Management. Vol. 10, pp. 109-117, doi: 10.2147/PRBM. S134132.


Review

Views: 463

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0869-3617 (Print)
ISSN 2072-0459 (Online)