Multidimensional educational experience as the basis for student satisfaction
https://doi.org/10.46554/1993-0453-2026-5-259-119-131
Abstract
In the context of increasing competition in higher education, universities are increasingly turning to the analysis for student experience as a key indicator of educational quality. However, conventional scale-based methods for measuring satisfaction fail to capture the underlying causes of student evaluations and overlook the multidimensional nature of educational experience. This study proposes a two-stage approach to analyzing the feedback from 4910 students of a federal university, combining frequency analysis of open-ended responses with expert rubrication. This design makes it possible to systematize over 15 000 textual comments and to identify latent interconnections among various aspects of the educational process, internships, research activities, infrastructure, information environment, and socio-psychological climate. The findings show that students’ perceptions of the educational environment are shaped as multidimensional experience. The students evaluate the university as an integrated system, and a decline in the quality of one component leads to reduced satisfaction with others. The key drivers of satisfaction include respectful treatment, support, transparent communication, user-friendly digital services, and an overall service-oriented logic of interaction. The results have practical value for improving quality management systems in higher education, developing digital services, and designing an effective framework for «student – university» interaction.
About the Authors
K. A. Danilova
Ural Federal University named after the first President of Russia B.N. Yeltsin
Russian Federation
Russian Federation
Kseniya A. Danilova – Candidate of Economic Sciences, Associate Professor of the Department of Management
Yekaterinburg
D. G. Sandler
Ural Federal University named after the first President of Russia B.N. Yeltsin
Russian Federation
Russian Federation
Daniil G. Sandler – Doctor of Economics, Associate Professor, Head of the Department of Management
Yekaterinburg
A. D. Zorina
Ural Federal University named after the first President of Russia B.N. Yeltsin
Russian Federation
Russian Federation
Anna D. Zorina – deputy head of the Strategic Development and Marketing Office
Yekaterinburg
M. S. Sosnin
Ural Federal University named after the first President of Russia B.N. Yeltsin
Russian Federation
Russian Federation
Maxim S. Sosnin – undergraduate student, lead engineer of the Quality Management Department
Yekaterinburg
References
1. Marginson S. Competition and markets in higher education: a "glonacal" analysis // Policy Futures in Education. 2004. No. 2 (2). doi:10.2304/PFIE.2004.2.2.2.
2. Information and analytical materials on the results of monitoring the activities of educational institutions of higher education. URL: https://monitoring.miccedu.ru/?m=vpo&year=2024 (date of access: 06.10.2025).
3. Guilbault M. Students as customers in higher education: the (controversial) debate needs to end // Journal of Retailing and Consumer Services. 2018. No. 40. Pp. 295–298. doi:10.1016/j.jretconser.2017.03.006.
4. Lyz N.A., Golubeva E.V., Istratova O.N. Students' educational experience: conceptualization and development of an educational quality assessment tool // Education issues. 2022. No. 3. Pp. 67–98. doi:10.17323/1814-9545-2022-3-67-98.
5. Definitions of quality in higher education: a synthesis of the literature / L. Schindler, S. Puls-Elvidge, H. Welzant, L. Crawford // Higher Learning Research Communications. 2015. No. 5 (3). Pp. 3–13. doi:10.18870/hlrc.v5i3.244.
6. Understanding student satisfaction and dissatisfaction: an interpretive study in the UK higher education context / J.A. Douglas, A. Douglas, R. McClelland, J. Davies // Studies in Higher Education. 2015. No. 40 (2). Pp. 329–349. doi:10.1080/03075079.2013.842217.
7. Marques F., Hernández-Leo D., Castillo C. Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design // Journal of New Approaches in Educational Research. 2025. No. 14. doi:10.1007/s44322-025-00030-3.
8. Sun Y., Yan W. Using topic modeling to understand comments in student evaluations of teaching // Studies in Educational Evaluation. 2023. No. 78. doi:10.1016/j.stueduc.2023.101252.
9. Aznar-Mas L.E., Atarés-Huerta L., Marin-Garcia J.A. Effectiveness of the use of open-ended questions in student evaluation of teaching in an engineering degree // Journal of Industrial Engineering and Management. 2023. No. 16 (3). Pp. 521–534. doi:10.3926/jiem.5620.
10. Paricio J. Students as customers: a paradigm shift in higher education // Debats. Journal on Culture, Power and Society. 2017. No. 131 (3). Pp. 137–149. doi:10.28939/iam.debats-en.2017-11.
11. Lubicz-Nawrocka T., C. Bovill Do students experience transformation through co-creating curriculum in higher education? // Teaching in Higher Education. 2021. No. 28 (7). Pp. 1744–1760. doi:10.1080/13562517.2021.1928060.
12. Towards a comprehensive student satisfaction model / M. Haverila, K. Haverila, C. McLaughlin, M. Arora // The International Journal of Management Education. 2021. No. 19 (3). doi:10.1016/j.ijme.2021.100558.
13. Matus N., Rusu C., Cano S. Student eXperience: a systematic literature review // Applied Sciences. 2021. No. 11 (20). doi:10.3390/app11209543.
14. Understanding the multidimensional nature of student engagement during the first year of higher education / V. Korhonen, M. Mattsson, M. Inkinen, A. Toom // Frontiers in Psychology. 2019. No. 10. doi:10.3389/fpsyg.2019.01056.
15. Ammigan R., Dennis J.L., Jones E. The differential impact of learning experiences on international student satisfaction and institutional recommendation // Journal of International Students. 2021. No. 11 (2). Pp. 299–321. doi:10.32674/jis.v11i2.2038.
16. Than W.W., Khaing N.N. A meta-analysis on factors influencing student satisfaction in higher education // Journal of the Myanmar Academy of Arts and Science. 2021. No. XVIII (9B). Pp. 393–404.
17. Danilova K.A., Sandler D.G., Shavrin V.S. A marketing perspective on the interrelation of key factors affecting student satisfaction with university activities // Economics of education. 2024. No. 3 (142). Pp. 91– 103.
18. Parasuraman A., Zeithaml V.A., Berry L.L. SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality // Journal of Retailing. 1988. No. 64 (1). Pp. 12–40.
19. Potential bias factors that affect the course evaluation of students in preclinical courses / S.J. Chae, M. Kim, K.H. Chang, Y.S. Chung // Korean Journal of Medical Education. 2017. No. 29 (2). Pp. 73–80. doi:10.3946/kjme.2017.54.
20. Langan A.M., Harris W.E. Metrics of student dissatisfaction and disagreement: longitudinal explorations of a national survey instrument // Higher Education. 2023. Pp. 1–21. doi:10.1007/s10734-023-01004-0.
21. Learning analytics methods, benefits, and challenges in higher education: a systematic literature review / J.T. Avella, M. Kebritchi, S.G. Nunn, T. Kanai // Online Learning. 2016. No. 20 (2). Pp. 13–29. doi:10.24059/olj.v20i2.790.
22. Advances in learning analytics and educational data mining / M. Vahdat, A. Ghio, L. Oneto [et al.] // Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Belgium, 2015.
23. Kostina S.N., Bannykh G.A. Regional university development programs: goals in the field of digital maturity and tools for assessing their achievement // University management: practice and analysis. 2023. No. 27 (4). Pp. 103–115. doi:10.15826/umpa.2023.04.036.
24. Liu H., Zhang J., Wang C. Research on students’ satisfaction of intelligent learning based on text mining // Frontiers in Psychology. 2022. No. 13. doi:10.3389/fpsyg.2022.897125.
25. Nemo H., Rahman M.M. Student feedback analysis using Natural Language Processing // 2021 ASEE Annual Conference & Exposition Proceedings. ASEE. 2021.
26. Shaik S., Rosalind R., Suguna S. Sentiment analysis and opinion mining on educational data // Materials Today : proceedings. 2022. No. 62. Pp. 3984–3990. doi:10.1016/j.matpr.2022.03.540.
27. Zhu Y., Wu B., Wang Q. Modeling student satisfaction in online learning using a Random Forest– based framework // Scientific Reports. 2023. No. 13 (1). doi:10.1038/s41598-023-43076-8.
28. Improving the international competitiveness of universities in the global digital space / V.V. Bondarenko, K.S. Taisheva, T.V. Tampey, D.P. Penzina // University Bulletin. 2023. No. 9. Pp. 21– 29. doi:10.26425/1816-4277-2023-9-21-29.
29. Sá M.J. A Multidimensional model of analysis of students’ global experience in higher education // Education Sciences. 2023. No. 13 (3). doi:10.3390/educsci13030232.
30. Fass-Holmes B. survey fatigue – literature search and analysis of implications for student affairs policies and practices // Journal of Interdisciplinary Studies in Education. 2022. No. 11 (1). Pp. 56–73.
31. Porter S.R., Whitcomb M.E., Weitzer W.H. Multiple surveys of students and survey fatigue // New Directions for Institutional Research. 2004. No. 121. Pp. 63–73. doi:10.1002/ir.101.
32. Watson S. Closing the feedback loop: ensuring effective action from student feedback // Tertiary Education and Management. 2003. No. 9 (2). Pp. 145–157. doi:10.1080/13583883.2003.9967099.
33. Barker M., Pinard M. Closing the feedback loop? Iterative feedback between tutor and student in coursework assessments // Assessment & Evaluation in Higher Education. 2014. No. 39 (8). Pp. 899–915. doi:10.1080/02602938.2013.875985.
34. Grimmer J., Stewart B.M. Text as data: the promise and pitfalls of automatic content analysis methods for political texts // Political Analysis. 2013. No. 21 (3). Pp. 267–297. doi:10.1093/pan/mps028.
Review
For citations:
Danilova K.A., Sandler D.G., Zorina A.D., Sosnin M.S. Multidimensional educational experience as the basis for student satisfaction. Vestnik of Samara State University of Economics. 2026;(5):119-131. (In Russ.) https://doi.org/10.46554/1993-0453-2026-5-259-119-131
Views:
73
JATS XML
Email this article 