Keywords
institutional regulation
Kano model
higher education
AI-based services
intellectual activity
How to Cite
Abstract
The rapid advancement of artificial intelligence technologies has fundamentally transformed higher education, encouraging universities to develop comprehensive institutional policies for AI implementation across academic and administrative processes. This study presents Kherson State University's institutional experience developing regulatory frameworks for implementing AI-based services.
The research employs the Kano model methodology to assess user satisfaction and prioritize AI-based services among university participants. A comprehensive survey involving 502 students, 141 academic staff members, and 61 non-academic staff members was conducted to determine preferences and satisfaction levels with the 13 most demanded worldwide AI-based services, including ChatGPT, Google Gemini, Gamma, and others.
The study introduces a conceptual distinction between routine and creative intellectual activities, establishing a framework for appropriate AI utilization. Based on survey results, a four-tier typology of AI-based services usage was developed: mandatory use, recommended use, not recommended use, and prohibited use. This classification system addresses different participant groups and activity types within educational, scientific, administrative, and management domains.
Key findings reveal that ChatGPT (35.1%), students consider Gamma (21.1%), and Google Gemini (19.7%) most functional, while academic staff prioritize ChatGPT (55.3%), Google Gemini (46.1%), and Gamma (38.3%). Notable differences emerged between natural science and humanities students regarding specific AI tool preferences.
The research resulted in comprehensive institutional regulations that define ethical principles, security requirements, and implementation guidelines for AI-based services. The study provides practical recommendations for enterprise-level AI tools, including security protocols for confidential data processing and integration with university authentication systems.
This institutional model offers valuable insights for other universities developing AI governance frameworks, contributing to responsible AI adoption in higher education while maintaining academic integrity and educational quality standards.
References
[1] J. P. W. De Azevedo, F. H. Rogers, S. E. Ahlgren, M.-H. Cloutier, B. Chakroun, G.-C. Chang, S. Mizunoya, N. J. Reuge, M. Brossard, and J. L. Bergmann, The State of the Global Education Crisis: A Path to Recovery, vol. 1. Washington, D.C.: World Bank Group, 2021, [Online]. Available: http://documents.worldbank.org/curated/en/416991638768297704 (in English).
[2] A. El Galad, D. H. Betts, and N. Campbell, “Flexible learning dimensions in higher education: Aligning students’ and educators’ perspectives for more inclusive practices,” Front. Educ., vol. 9, p. 1347432, Apr. 2024, doi.org/10.3389/feduc.2024.1347432. (in English).
[3] O. V. Spivakovsky, S. A. Omelchuk, V. V. Kobets, N. V. Valko, and D. S. Malchykova, “Institutional Policies on Artificial Intelligence in University Learning, Teaching and Research”, ITLT, vol. 97, no. 5, pp. 181–202, Oct. 2023, doi:10.33407/itlt.v97i5.5395. (in English).
[4] A. Aldoseri, K. N. Al-Khalifa, and A. M. Hamouda, “AI-powered innovation in digital transformation: Key pillars and industry impact,” Sustainability, vol. 16, no. 5, p. 1790, 2024, doi.org/10.3390/su16051790 (in English).
[5] D. Blanuša Trošelj, S. Maričić, and A. Ćurić, “Growing interest in AI in education: Systematic literature review,” in Proc. Int. Conf. Research in Education and Science (ICRES), Antalya, Turkiye: ISTES, 2024, pp. 2410–2427 (in English).
[6] H. Crompton and D. Burke, “Artificial intelligence in higher education: The state of the field,” Int. J. Educ. Technol. High. Educ., vol. 20, no. 1, p. 22, 2023, doi.org/10.1186/s41239-023-00392-8. (in English).
[7] O. Spivakovsky, D. Malchykova, and V. Yatsenko, “Digitalisation of Crisis Management and Resource Balancing for Educational Quality Assurance at a Displaced University”, ITLT, vol. 102, no. 4, pp. 130–147, Sep. 2024, doi: 10.33407/itlt.v102i4.5761. (in English).
[8] M. D. Lytras, A. Alkhaldi, S. Malik, A. C. Șerban, and T. Aldosemani, Eds., The Evolution of Artificial Intelligence in Higher Education: Challenges, Risks, and Ethical Considerations, 1st ed. Bingley, UK: Emerald Publishing Limited, 2024, doi/10.1108/9781835494868. (in English).
[9] R. Luckin, “Towards artificial intelligence-based assessment systems,” Nat. Hum. Behav., vol. 1, p. 0028, 2017. doi: 10.1038/s41562-016-0028. (in English).
[10] W. Holmes, M. Bialik, and C. Fadel, Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston, MA: Center for Curriculum Redesign, 2019 (in English).
[11] A. Kaplan and M. Haenlein, “Rulers of the world, unite! The challenges and opportunities of artificial intelligence,” Business Horizons, vol. 63, no. 1, pp. 37–50, 2020, doi.org/10.1016/j.bushor.2019.09.003. (in English).
[12] A. Kumar, M. M. Salim, D. Camacho, and J. H. Park, “A comprehensive survey on large language models for multimedia data security: Challenges and solutions”, vol. 267, p. 111379, 2025, doi.org/10.1016/j.comnet.2025.111379. (in English).
[13] H. Xiao, F. Zhou, X. Liu, T. Liu, Z. Li, X. Liu, and X. Huang, “A comprehensive survey of large language models and multimodal large language models in medicine,” Information Fusion, vol. 117, p. 102888, 2024, doi.org/10.1016/j.inffus.2024.102888. (in English).
[14] O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education – where are the educators?” International Journal of Educational Technology in Higher Education, vol. 16, no. 1, pp. 1–27, 2019, doi.org/10.1186/s41239-019-0171-0. (in English).
[15] H. Crompton and D. Burke, “Artificial intelligence in higher education: the state of the field,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, p. 22, 2023, doi.org/10.1186/s41239-023-00392-8. (in English).
[16] Ministry of Education and Science of Ukraine, Recommendations on the Responsible Implementation and Use of Artificial Intelligence Technologies in Higher Education Institutions, Apr. 24, 2025. [Online]. Available: https://mon.gov.ua/static-objects/mon/sites/1/news/2025/04/24/shi-v-zakladakh-vyshchoi-osvity-24-04-2025.pdf [Accessed: Jun. 7, 2025] (in Ukrainian).
[17] Kherson State University, General Policies on the Use of Artificial Intelligence in Teaching, Learning, and Research at Kherson State University, Ivano-Frankivsk, Ukraine, Jun. 29, 2023. [Online]. Available: https://www.kspu.edu/FileDownload.ashx/281-%D0%94.pdf?id=6e2f1e1f-f267-4da6-859f-096168e2a70f [Accessed: Jun. 7, 2025] (in Ukrainian).
[18] National University "Zaporizhzhia Polytechnic", Declaration on the Principles of Using Generative Artificial Intelligence in the Educational Process and Scientific Activity, 2023. [Online]. Available: https://zp.edu.ua/uploads/pubdocs/2023/Dekl_pro_pryn_vykor_heneratyvnoho_shtuchnoho_intelektu.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[19] National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Policy on the Use of Artificial Intelligence for Academic Activities at KPI, approved by the Academic Council on Dec. 11, 2023 (Protocol No. 11). [Online]. Available: https://ela.kpi.ua/server/api/core/bitstreams/70b895b5-1339-4d51-975b-a6114035c950/content [Accessed: Jun. 17, 2025] (in Ukrainian).
[20] National University of Water and Environmental Engineering, Policy on the Use of Artificial Intelligence in the Activities of the University, [Online]. Available: https://ep3.nuwm.edu.ua/31987/. [Accessed: Feb. 20, 2025] (in Ukrainian).
[21] Ivano-Frankivsk National Technical University of Oil and Gas, Regulation on General Policies for the Use of Generative Artificial Intelligence Tools in the Educational Process, approved by the Academic Council on Jan. 31, 2024, enacted by Order No. 82 on Mar. 15, 2024. [Online]. Available: https://drive.google.com/file/d/17bBDaJKlhZPr1R5RAYD__-xCANQLvZUe/view [Accessed: Jun. 17, 2025] (in Ukrainian).
[22] H.S. Skovoroda Kharkiv National Pedagogical University, Regulation on the Use of Generative Artificial Intelligence Tools in the Educational and Research Process, approved by the Academic Council on Nov. 25, 2024 (Minutes No. 11), enacted by Order No. 247-od on Dec. 5, 2024. [Online]. Available: http://hnpu.edu.ua/sites/default/files/files/Normat_dokum/Pol/Pol_vykorystannia_shi.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[23] National University of Life and Environmental Sciences of Ukraine, Regulation on the Policy of Artificial Intelligence Use at NULES of Ukraine, Order No. 940 dated Aug. 16, 2024. [Online]. Available: https://qms.nubip.edu.ua/wp-content/uploads/2024/08/СУ-СМЯ-НУБіП-України-7.5-021-011.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[24] National Technical University “Kharkiv Polytechnic Institute”, Policies on the Use of Artificial Intelligence at the University, 2024. [Online]. Available: http://library.kpi.kharkov.ua/files/Seminars/04-12-2024-chatgpt.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[25] Simon Kuznets Kharkiv National University of Economics, Policy on the Use of Artificial Intelligence in Academic Activities at Simon Kuznets KhNUE, Mar. 25, 2025. [Online]. Available: https://hneu.edu.ua/content/documents/158/15768/Attaches/politika-vikoristannya-shi-v-hneu.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[26] Alfred Nobel University, Policy on the Use of Artificial Intelligence at the Higher Educational Institution "Alfred Nobel University", Jan. 21, 2025. [Online]. Available: https://duan.edu.ua/wp-content/uploads/2025/01/polityka-vykorystannya-shtuchnoho-intelektu.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[27] Kyiv School of Economics, Policy on the Use of Generative Artificial Intelligence Tools and/or Models in the Educational Process at the Private Institution "Kyiv School of Economics University", Mar. 21, 2025. [Online]. Available: https://kse.ua/wp-content/uploads/2025/03/Politika-SHI.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[28] Ministry of Digital Transformation of Ukraine, Guidelines on the Responsible Use of Artificial Intelligence by Public Servants. [Online]. Available: https://cms.thedigital.gov.ua/storage/uploads/files/page/community/docs/Porady_z_vykorystannya_AI.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[29] Ministry of Education and Science of Ukraine, Instructional and Methodological Recommendations for the Implementation and Use of Artificial Intelligence Technologies in General Secondary Education Institutions. [Online]. Available: https://mon.gov.ua/static-objects/mon/sites/1/news/2024/05/21/Instruktyvno.metodychni.rekomendatsiyi.shchodo.SHI.v.ZZSO-22.05.2024.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[30] Ministry of Education and Science of Ukraine, Recommendations on the Responsible Implementation and Use of Artificial Intelligence Technologies in Higher Education Institutions, Apr. 2025. [Online]. Available: https://mon.gov.ua/static-objects/mon/sites/1/news/2025/04/24/shi-v-zakladakh-vyshchoi-osvity-24-04-2025.pdf [Accessed: Jun. 17, 2025] (in Ukrainian).
[31] D. Ravšelj et al., “Higher education students’ perceptions of ChatGPT: A global study of early reactions,” PLoS ONE, vol. 20, no. 2, 2025 (in English).
[32] A. M. Abdo-Salloum and H. Y. Al-Mousawi, “Accounting students’ technology readiness, perceptions, and digital competence toward artificial intelligence adoption in accounting curricula,” Journal of Accounting Education, vol. 70, p. 100951, 2025, doi:10.1016/j.jaccedu.2025.100951. (in English).
[33] M. Nurtanto, S. Nawanksari, V. L. P. Sutrisno, H. Syahrudin, N. Kholifah, D. Rohmantoro, et al., “Determinants of behavioral intentions and their impact on student performance in the use of AI technology in higher education in Indonesia: A SEM-PLS analysis based on TPB, UTAUT, and TAM frameworks,” Social Sciences & Humanities Open, vol. 11, p. 101638, 2025, doi:10.1016/j.ssaho.2025.101638. (in English).
[34] R. S. K. Yeung, R. Tian, D. K. W. Chiu, and S. P.-M. Choi, “University students’ perceptions on how generative artificial intelligence shape learning and research practices: A case study in Hong Kong,” The Journal of Academic Librarianship, vol. 51, no. 5, p. 103082, 2025, doi.org/10.1016/j.acalib.2025.103082. (in English).
[35] D. Tbaishat, G. Amoudi, and M. Elfadel, “Adapting teaching and learning with existing generative AI by higher education students: Comparative study of Zayed University and King Abdulaziz University,” Computers and Education: Artificial Intelligence, vol. 2025, p. 100421, 2025, doi: 10.1016/j.caeai.2025.100421. (in English).
[36] A. C. Niloy, R. Hafiz, B. M. T. Hossain, F. Gulmeher, N. Sultana, K. F. Islam, et al., “AI chatbots: A disguised enemy for academic integrity?” International Journal of Educational Research Open, vol. 7, p. 100396, 2024, doi: 10.1016/j.ijedro.2024.100396. (in English).
[37] I. Levkovich, E. Rabin, R. H. Farraj, and Z. Elyoseph, “Attributional patterns toward students with and without learning disabilities: Artificial intelligence models vs. trainee teachers,” Research in Developmental Disabilities, vol. 160, p. 104970, 2025, doi: 10.1016/j.ridd.2025.104970. (in English).
[38] O. P. Barus, A. N. Hidayanto, E. Y. Handri, D. I. Sensuse, and C. Yaiprasert, “Shaping generative AI governance in higher education: Insights from student perception,” International Journal of Educational Research Open, vol. 8, p. 100452, 2025, doi: 10.1016/j.ijedro.2025.100452. (in English).
[39] N. Kano, F. Seraku, F. Takahashi, and S. Tsuji, “Attractive Quality and Must-Be Quality,” J. Jpn. Soc. Qual. Control, vol. 14, no. 2, pp. 39–48, Apr. 1984. [Online]. Available: https://ci.nii.ac.jp/naid/110003158895 (in English).
[40] G. Grunwald, A. Kara, and J. E. Spillan, “Application of the Kano Model for Insights into Business Students’ Sustainability Transformation Expectations from Higher Educational Institutions: A Cross-country Study,” J. Clean. Prod., vol. 464, p. 142748, 2024. doi: 10.1016/j.jclepro.2024.142748. (in English).
[41] M. Wang, C. Zeng, L. Xu, and H. Sun, “Meeting the digital literacy education needs of college students: A two-stage study in China,” J. Acad. Librarianship, vol. 51, no. 5, p. 103084, 2025. doi: 10.1016/j.acalib.2025.103084. (in English).
[42] P. Gupta, B. Ding, C. Guan, and D. Ding, “Generative AI: A systematic review using topic modelling techniques,” Data and Information Management, vol. 8, no. 2, p. 100066, 2024, doi.org/10.1016/j.dim.2024.100066. (in English).
[43] K. Illeris and C. Ryan, “Contemporary theories of learning: Learning theorists... in their own words,” Australian Journal of Adult Learning, vol. 60, no. 1, pp. 138–143, 2020 (in English).
[44] ”Zoom Inc: Introducing Zoom AI Companion” [Online]. Available: https://www.zoom.com/en/blog/zoom-ai-companion/?cms_guid=false&lang=null [Accessed: Jun. 7, 2025] (in English).
[45] MorphCast, “Emotion AI and Face Recognition” [Online]. Available: https://www.morphcast.com/ [Accessed: Jun. 7, 2025] (in English).
[46] A. Spivakovsky, M. Poltoratskyi, O. Lemeshchuk, V. Denysenko, I. Karpov, and Y. Revenko, “Algorithms for using online tutoring as a tool for personalization of learning in an online educational environment,” in Proc. Int. Conf. on Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2024), V. Ermolayev et al., Eds., Cham: Springer, 2025, pp. 178–193, doi: 10.1007/978-3-031-81372-6_13. (in English).
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright (c) 2025 Oleksandr Spivakovsky , Serhii Omelchuk, Vitaliy Kobets , Maksym Poltoratskyi, Daria Malchykova, Oleksandr Lemeshchuk