Vol. 54 No. 3 (2026): Published on September 30, 2026.

DOI https://doi.org/10.18799/26584956/2026/3/2184

Individualization of the educational trajectory of students based on the diagnostics of learning motivation

Relevance. Differences in school preparation and individual learning styles, especially pronounced among first-year students, make the individualization of the educational trajectory a relevant task. Since the stability of such a trajectory is determined primarily by learning motivation, valid psychodiagnostic methods are appropriate for its assessment. Aim. To determine the structure of learning motivation among first-year students of a technical university using the Academic Motivation Scale and to substantiate the use of diagnostic results as a basis for selecting elements of an individualized educational trajectory. Methods. A survey of 64 first-year students of technical programs using the Academic Motivation Scale; processing of results across seven motivation scales; calculation of the share of students with above-average agreement on each scale. Results. Cognitive motivation prevails among most respondents (61.8%), followed by achievement (55.9%), self-development (47.1%) and selfesteem (41.2%) motivation. The predominance of intrinsic motivation is considered as a resource for building an individual educational trajectory based on the link between academic disciplines and the future profession. It is shown that the data on the group motivational profile can serve as a basis for differentiating pedagogical approaches.

For citation: Levin S.M., Isakov A.M. Individualization of the educational trajectory of students based on the diagnostics of learning motivation. Journal of Wellbeing Technologies, 2026, vol. 54, no. 3, pp. 151–159. https://doi.org/10.18799/26584956/2026/3/2184

Keywords:

individualization of learning, educational trajectory, learning motivation, academic motivation scale, motivational profile, technical university students

Authors:

Semen M. Levin

Alexander M. Isakov

References:

СПИСОК ЛИТЕРАТУРЫ

1. Deci E.L., Ryan R.M. The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychological Inquiry, 2000, Vol. 11, Iss. 4, P. 227–268. DOI: https://doi.org/10.1207/S15327965PLI1104_01.

2. Urhahne D., Wijnia L. Theories of motivation in education: an integrative framework. Educational Psychology Review, 2023, Vol. 35, art. 45. DOI: https://doi.org/10.1007/s10648-023-09767-9 EDN: VOZSJE.

3. Howard J.L., Bureau J.S., Guay F., Chong J.X.Y., Ryan R.M. Student motivation and associated outcomes: a metaanalysis from self-determination theory. Perspectives on Psychological Science, 2021, Vol. 16, Iss. 6, P. 1300–1323. DOI: 10.1177/1745691620966789. EDN: DDGGHB.

4. Bureau J.S., Howard J.L., Chong J.X.Y., Guay F. Pathways to student motivation: a meta-analysis of antecedents of autonomous and controlled motivations. Review of Educational Research, 2021, Vol. 92, Iss. 1, P. 46–72. DOI: https://doi.org/10.3102/00346543211042426. EDN: VMPKRD.

5. Botnaru D., Orvis J.N., Langdon J., Niemiec C.P., Landge S.M. Predicting final grades in STEM courses: a path analysis of academic motivation and course-related behavior using self-determination theory. Learning and Motivation, 2021, Vol. 76, art. 101723. DOI: 10.1016/J.LMOT.2021.101723. EDN: YTHZGU.

6. Oláh B., Münnich Á., Kósa K. Identifying academic motivation profiles and their association with mental health in medical school. Medical Education Online, 2023, Vol. 28, Iss. 1, art. 2242597. DOI: https://doi.org/10.1080/10872981.2023.2242597. EDN: PEMXTM.

7. Corpus J.H., Robinson K.A., Wormington S.V. Trajectories of motivation and their academic correlates over the first year of college. Contemporary Educational Psychology, 2020, Vol. 63, art. 101907. DOI: https://doi.org/10.1016/j.cedpsych.2020.101907. EDN: TVKUSM.

8. Kocsis Á., Molnár G. Factors influencing academic performance and dropout rates in higher education. Oxford Review of Education, 2025, Vol. 51, Iss. 3, P. 414–432. DOI: https://doi.org/10.1080/03054985.2024.2316616.

9. Sazonova M., Mikhailova L.V. Transformation of personalized educational trajectories of students of higher educational institutions in the context of the development of digital technologies. AIP Conference Proceedings, 2024, art. 040005. DOI: https://doi.org/10.1063/5.0181962.

10. Theobald M. Self-regulated learning training programs enhance university students’ academic performance, selfregulated learning strategies, and motivation: a meta-analysis. Contemporary Educational Psychology, 2021, Vol. 66, art. 101976. DOI: https://doi.org/10.1016/j.cedpsych.2021.101976. EDN: WUJKRP.

11. Levin S.M. Review on the influence of student engagement and interaction in online learning communities on academic achievement. Journal of Wellbeing Technologies, 2024, Vol. 52, № 2, P. 72–85. DOI: https://doi.org/10.18799/26584956/2024/2/1823. EDN: QAYONQ.

12. Silvers P., O’Connell J., Fewell M. Strategies for creating community in a graduate education online program. Journal of Computing in Teacher Education, 2007, Vol. 23, № 3, P. 81–87.

13. Туманова Д.И. Психолого-педагогические условия формирования сплочённости в студенческом коллективе. Научные исследования молодых учёных: сборник статей Международной научно-практической конференции в 4 ч. Часть 4. Пенза: Наука и Просвещение, 2020. С. 111–115. EDN: APETYN.

14. Сарафанникова А.С., Захарова А.А. Особенности мотивации студентов технических вузов. Современное образование: интеграция образования, науки, бизнеса и власти. Приоритетные ориентиры высшего образования в России: стратегическое партнёрство и технологический суверенитет: материалы международной научно-методической конференции. Томск: Томский государственный университет систем управления и радиоэлектроники, 2024. С. 77–81. EDN: WLZLZC.

15. Гордеева Т.О., Сычёв О.А., Осин Е.Н. Опросник «Шкалы академической мотивации». Психологический журнал, 2014, Т. 35, № 4, С. 96–107. EDN: SJVWLN.

16. Vallerand R.J., Pelletier L.G., Blais M.R., Brière N.M., Senécal C., Vallières E.F. The Academic Motivation Scale: a measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 1992, Vol. 52, № 4, P. 1003–1017. DOI: 10.1177/0013164492052004025. EDN: JSMKYV.

17. Al Ansari A.M., Kumar A.P., AlSaleh A.F.F., Arekat M.R.K., Deifalla A. Validation of academic motivation scale among medical students using factor analysis and structural equation modeling: Middle Eastern perspective. Journal of Education and Health Promotion, 2021, Vol. 10, Iss. 1, art. 176. DOI: https://doi.org/10.4103/jehp.jehp_1553_20. EDN: QUPGUY.

18. Епанчинцева Г.А., Козловская Т.Н. Студенчество как социально-психологическая общность. Вестник Оренбургского государственного университета, 2018, № 2, С. 66–69. EDN: FEIHRJ.

19. Григорьева Е.А., Стоянов А.С. Осознанность и ожидания при выборе вуза и профессии. ГОСРЕГ: Государственное регулирование общественных отношений, 2020, № 2, С. 256–267. EDN: GNMRRC.

20. Большая зарплата или работа по специальности? ВЦИОМ. URL: https://wciom.ru/analyticalreviews/analiticheskii-obzor/bolshaya-zarplata-ili-rabota-po-speczialnosti- (дата обращения 26.10.2025).

REFERENCES

1. Deci E.L., Ryan R.M. The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychological Inquiry, 2000, vol. 11, iss. 4, pp. 227–268. DOI: https://doi.org/10.1207/S15327965PLI1104_01.

2. Urhahne D., Wijnia L. Theories of motivation in education: an integrative framework. Educational Psychology Review, 2023, vol. 35, art. 45. DOI: https://doi.org/10.1007/s10648-023-09767-9. EDN: VOZSJE.

3. Howard J.L., Bureau J.S., Guay F., Chong J.X.Y., Ryan R.M. Student motivation and associated outcomes: a metaanalysis from self-determination theory. Perspectives on Psychological Science, 2021, vol. 16, Iss. 6, pp. 1300–1323. DOI: 10.1177/1745691620966789. EDN: DDGGHB.

4. Bureau J. S., Howard J. L., Chong J. X. Y., Guay F. Pathways to student motivation: a meta-analysis of antecedents of autonomous and controlled motivations. Review of Educational Research, 2021, vol. 92, Iss. 1, pp. 46–72. DOI: https://doi.org/10.3102/00346543211042426. EDN: VMPKRD.

5. Botnaru D., Orvis J.N., Langdon J., Niemiec C.P., Landge S.M. Predicting final grades in STEM courses: a path analysis of academic motivation and course-related behavior using self-determination theory. Learning and Motivation, 2021, vol. 76, art. 101723. DOI: 10.1016/J.LMOT.2021.101723. EDN: YTHZGU.

6. Oláh B., Münnich Á., Kósa K. Identifying academic motivation profiles and their association with mental health in medical school. Medical Education Online, 2023, vol. 28, Iss. 1, art. 2242597. DOI: https://doi.org/10.1080/10872981.2023.2242597. EDN: PEMXTM.

7. Corpus J.H., Robinson K.A., Wormington S.V. Trajectories of motivation and their academic correlates over the first year of college. Contemporary Educational Psychology, 2020, vol. 63, art. 101907. DOI: https://doi.org/10.1016/j.cedpsych.2020.101907. EDN: TVKUSM.

8. Kocsis Á., Molnár G. Factors influencing academic performance and dropout rates in higher education. Oxford Review of Education, 2025, vol. 51, Iss. 3, pp. 414–432. DOI: https://doi.org/10.1080/03054985.2024.2316616.

9. Sazonova M., Mikhailova L. V. Transformation of personalized educational trajectories of students of higher educational institutions in the context of the development of digital technologies. AIP Conference Proceedings, 2024, art. 040005. DOI: https://doi.org/10.1063/5.0181962.

10. Theobald M. Self-regulated learning training programs enhance university students’ academic performance, selfregulated learning strategies, and motivation: a meta-analysis. Contemporary Educational Psychology, 2021, vol. 66, art. 101976. DOI: https://doi.org/10.1016/j.cedpsych.2021.101976. EDN: WUJKRP.

11. Levin S.M. Review on the influence of student engagement and interaction in online learning communities on academic achievement. Journal of Wellbeing Technologies, 2024, vol. 52, no. 2, pp. 72–85. DOI: https://doi.org/10.18799/26584956/2024/2/1823. EDN: QAYONQ.

12. Silvers P., O’Connell J., Fewell M. Strategies for creating community in a graduate education online program. Journal of Computing in Teacher Education, 2007, vol. 23, no. 3, pp. 81–87.

13. Tumanova D.I. Psychological and pedagogical conditions for the formation of cohesion in the student group. Scientific research of young scientists: a collection of articles from the International Scientific and Practical Conference in 4 parts. Part 4. Penza, Science and Education Publ., 2020. pp. 111–115. (In Russ.) EDN: APETYN.

14. Sarafannikova A.S., Zakharova A.A. Features of motivation of engineering university students. Modern Education: Integration of Education, Science, Business, and Government. Priority Guidelines for Higher Education in Russia: Strategic Partnership and Technological Sovereignty. Proc. of the International Scientific and Methodological Conference. Tomsk, Tomsk State University of Control Systems and Radioelectronics Publ., 2024. pp. 77–81. (In Russ.) EDN: WLZLZC.

15. Gordeeva T.O., Sychev O.A., Osin E.N. "Academic motivation scales" questionnaire. Psikhologicheskii zhurnal, 2014, vol. 35, no. 4, pp. 96–107. (In Russ.) EDN: SJVWLN.

16. Vallerand R.J., Pelletier L.G., Blais M.R., Brière N.M., Senécal C., Vallières E.F. The Academic Motivation Scale: a measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 1992, vol. 52, no. 4, pp. 1003–1017. DOI: 10.1177/0013164492052004025. EDN: JSMKYV.

17. Al Ansari A.M., Kumar A.P., AlSaleh A.F.F., Arekat M.R.K., Deifalla A. Validation of academic motivation scale among medical students using factor analysis and structural equation modeling: Middle Eastern perspective. Journal of Education and Health Promotion, 2021, vol. 10, Iss. 1, art. 176. DOI: https://doi.org/10.4103/jehp.jehp_1553_20. EDN: QUPGUY.

18. Epanchintseva G.A., Kozlovskaya T.N. Students as social and psychological community. Vestnik of the Orenburg State University, 2018, no. 2, pp. 66–69. (In Russ.) EDN: FEIHRJ.

19. Grigorieva E.A., Stoyanov A.S. Awareness and expectations when choosing a university and profession. GosReg. Gosudarstvennoe regulirovanie obshchestvennykh otnosheniy, 2020, no. 2, pp. 256–267. (In Russ.) EDN: GNMRRC.

20. A big salary or a job in your specialty? All-Russian Public Opinion Research Center. (In Russ.) Available at: https://wciom.ru/analytical-reviews/analiticheskii-obzor/bolshaya-zarplata-ili-rabota-po-speczialnosti (accessed 26 November 2025).

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