The functioning of higher education in the network society: findings from a student survey
The article examines the impact of information-network transformations on the sphere of higher education in Ukraine. The author analyses the social and educational consequences of digitalisation, distance and hybrid learning, and the integration of artificial intelligence into the educational process. The study provides a comprehensive analysis of how information-network transformations shape the experiences and perceptions of higher education students, and offers recommendations for improving educational quality in the context of digitalisation. The empirical basis of the article consists of data from a nationwide survey of 2,552 higher education students conducted in 2025 using an online questionnaire. The research employs descriptive statistics as well as comparative and interpretative analytical methods. The article examines how digitalisation has become an integral part of the educational process considering the proportion of students studying in blended or fully online formats, the level of digital proficiency among learners, and the extent to which they use artificial intelligence tools. Among the most common challenges identified are technical difficulties, a lack of live interaction, decreased motivation, and manifestations of digital fatigue. While students generally have a positive view of technological tools, they emphasise the need for pedagogical support and the development of digital culture within higher educational institutions. Artificial intelligence is primarily perceived as a useful educational instrument, yet it raises concerns related to academic integrity. The article demonstrates that the effectiveness of digital transformation depends not only on technological infrastructure but above all on the readiness of instructors and students to assume new roles within the learning environment. It also provides recommendations for universities regarding the development of hybrid learning models, the ethical integration of artificial intelligence, and supporting student motivation. Ultimately, the study contributes to a deeper understanding of how digitalisation reshapes the social functions of higher education in the context of war and the formation of a networked society.
Information and Analytical Report on the Organisation of Educational Process in Vocational Pre-higher and Higher Education Institutions in Ukraine under Martial Law (based on the results of a quarterly online survey, II quarter, 2023). (2023). The State Service of Education Quality of Ukraine. URL: https://sqe.gov.ua/wp-content/uploads/2023/08/IAD_II_kvartal_2023.pdf [in Ukrainian]
Areshonkov, V.Yu. (2020). Digitalization of higher education: challenges and answers. Herald of the National Academy of Educational Sciences of Ukraine, 2 (2), 1-6 [in Ukrainian]
Pasichnyi, R., Serhieiev, V., Shevchenko, S., Petrukha, N., Hryvnak, B. (2024). Digital transformation of higher education as a driver of Ukraine’s integration into the European educational space. Cadernos de Educação Tecnologia e Sociedade, 17 (4), 232-245.
Gomes, A., Dias, J.G. (2024). Digital divide in the European Union: A typology of EU citizens. Social Indicators Research, 176, 149-172.
Akpen, C.N., Asaolu, S., Atobatele, S., Okagbue, H., Sampson, S. (2024). Impact of online learning on student’s performance and engagement: a systematic review. Discover Education, 3, 205.
Konstantinidou, A., Nisiforou, E.A. (2022). Assuring the quality of online learning in higher education: Adaptations in design and implementation. Australasian Journal of Educational Technology, 38 (4), 127-142.
Martin, F., Sun, T., Westine, C., Ritzhaupt, A. (2022). Examining research on the impact of distance and online learning: A second-order meta-analysis study. Educational Research Review, 36, 100438.
Marchuk, A. (2023). Quality of higher education in emergency situations: educational losses and dysfunctions of digitalization in higher education and distance learning. Socio-Economic Relations in the Digital Society, 1 (47), 80-89 [in Ukrainian]
Child, F., Frank, M., Law, J., Sarakatsannis, J. (2023). What do higher education students want from online learning? McKinsey Insights. URL: https://www.mckinsey.com/industries/public-sector/our-insights/what-do-higher-education-students-want-from-online-learning
Olaguer, V.R.F., Marcos, S.M.M., Solayao, R.A., Pelaez, E.R.B., Lagat, K.T. (2024). Blended learning in higher education: correlating teaching presence student engagement and satisfaction. Ho Chi Minh city open University journal of Science – Social Sciences, 16 (2), 79-97.
Williams, A. (2025). Integrating Artificial Intelligence Into Higher Education Assessment. Intersection: A Journal at the Intersection of Assessment and Learning, 6 (1), 128-154.
Sharples, M. (2022). Automated Essay Writing: An AIED Opinion. International Journal of Artificial Intelligence in Education, 32, 1119-1126.
Cotton, D.R.E., Cotton, P.A., Shipway, J.R. (2024). Chatting and Cheating: Ensuring Academic Integrity in the Era of ChatGPT. Innovations in Education and Teaching International, 61 (2), 228-239.
Dempere, J., Modugu, K., Hesham, A., Ramasamy, L.K. (2023). The impact of ChatGPT on higher education. Frontiers in Education, 8, 1206936.
Dergaa, I., Chamari, K., Zmijewski, P., Saad, H.B. (2023). From human writing to artificial intelligence generated text: examining the prospects and potential threats of ChatGPT in academic writing. Biology of Sport, 40 (2), 615-622.
Zhai, C., Wibowo, S., Li, L. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11 (28).
De Angelis, L., Baglivo, F., Arzilli, G., Privitera, G., Ferragina, P., Tozzi, A., Rizzo, C. (2023). ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health. Frontiers in Public Health, 11, 1166120.
Gao, C.A., Howard, F.M., Markov, N.S., Dyer, E., Ramesh, S., Luo, Y., Pearson, A.T. (2022). Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers. bioRxiv.
Mbalaka, B. (2023). Epistemically violent biases in artificial intelligence design: the case of DALLE-E 2 and Starry AI. Digital Transformation and Society, 2 (4), 376-402.
Yang, H.H., Yin, Z., Zhu, S. (2024). Examining students’ acceptance of the large-scale HyFlex course: An empirical study. British Journal of Educational Technology, 56 (1), 42-60.
Foucault, M. (1977). Discipline and Punish: The Birth of the Prison. New York: Vintage Books.
Baudrillard, J. (1994). Simulacra and Simulation. Ann Arbor: University of Michigan Press.
Readings, B. (1996). The University in Ruins. Cambridge: Harvard University Press.
Bok, D. (2003). Universities in the Marketplace: The Commercialization of Higher Education. Princeton: Princeton University Press.
Giroux, H.A. (2014). Neoliberalism’s War on Higher Education. Chicago: Haymarket Books.
Bourdieu, P. (1991). Language and Symbolic Power. Cambridge MA: Harvard University Press.
Beck, U. (1992). Risk Society: Towards a New Modernity. London: Sage.
Bourdieu, P. (1996). The State Nobility: Elite Schools in the Field of Power. Stanford: Stanford University Press.
Goffman, E. (1967). Interaction Ritual: Essays on Face-to-Face Behavior. New York: Anchor Books.
Du, J., Hew, K. F., Li, L. (2023). Do Direct and Indirect Recommendations Facilitate Students’ Self-Regulated Learning in Flipped Classroom Online Activities? Findings from Two Studies. Education Sciences, 13 (4), 400.
Shi, J., Zhang, X. (2023). Integration of AI with Higher Education Innovation: Reforming Future Educational Directions. International Journal of Science and Research, 12 (10), 1727-1731.
Holmes, W., Bialik, M., Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign.