Abstract :

This study presents results of a systematic literature review (SLR) of the responsible use of artificial intelligence (AI) tools in higher education, identify patterns of ethical and irresponsible use, and propose a conceptual framework for predicting ethical AI adoption. Following PRISMA guidelines, was conducted on 60 peer-reviewed studies published between 2022 and 2026, sourced from Google Scholar. Studies were mapped against four research questions addressing AI tools used, their applications, reported unethical practices, and predictive modelling approaches. Results reveal that general AI, generative AI tools, and large language models dominate higher education contexts, primarily deployed for personalized learning, academic work, and teaching. Irresponsible practices were documented in one-third of studies, including academic integrity breaches (13.33%), algorithmic bias,  and privacy violations. Critically, no existing study developed a real-time predictive model capable of monitoring ethical AI use, despite four studies demonstrating predictive modelling capabilities for other purposes. This study addresses a significant gap by proposing a novel conceptual framework that integrates AI tool deployment, user behaviour, governance measures, and predictive analytics to forecast ethical outcomes. The framework provides higher education institutions with a pathway toward data-informed, proactive governance of AI technologies.

---

Keywords :

Artificial Intelligence, Ecosystem, Ethical and Responsible AI, Higher Education, systematic literature review

---

References :

1. Ajayi, V.O., 2023. A review on primary sources of data and secondary sources of data. Available SSRN 5378785.
2. Al Ka’bi, A., 2023. Proposed artificial intelligence algorithm and deep learning techniques for the development of higher education. Int. J. Intel. Netw. 4, 68–73.
3. Aler Tubella, A., Mora-Cantallops, M., Nieves, J.C., 2023. How to teach responsible AI in Higher Education: challenges and opportunities. Ethics Inf. Technol. 26, 3. https://doi.org/10.1007/s10676-023-09733-7
4. Crompton, H., Burke, D., 2023. Artificial intelligence in higher education: the state of the field. Int. J. Educ. Technol. High. Educ. 20, 22. https://doi.org/10.1186/s41239-023-00392-8
5. Diallo, R., Edalo, C., Awe, O.O., 2024. Practical Statistical Learning and Data Science Methods: Case Studies from LISA 2020 Global Network, USA. Springer Nature.
6. Dube, S, Madzore, A, Dube, S.P, Mpande, B (2026). Enhancing Personalized E-Learning Systems in Higher Education Through Artificial Intelligence: A Rapid Systematic Literature Revie, 10(2), https://doi.org/10.47772/IJRISS.2026.10200008.

7. Dube, S, Mpande, B, Chazuza, T, Siwela, T, Moyo, M Dube, S. P, (2026). A Systematic Literature Review of Data Privacy in AI-Driven Educational Platforms. , 10(26), https://doi.org/10.47772/IJRISS.2026.1026EDU0078.
8. Erdmann, A., Toro-Dupouy, L., 2025. The influence of the institutional environment on AI adoption in universities: identifying value drivers and necessary conditions. Eur. J. Innov. Manag. 28, 4365–4398. https://doi.org/10.1108/EJIM-04-2024-0407
9. Francis, N.J., Jones, S., Smith, D.P., 2025. Generative AI in higher education: Balancing innovation and integrity. Br. J. Biomed. Sci. 81, 14048.
10. Hall, P., Curtis, J., Pandey, P., 2023. Machine Learning for High-risk Applications: Approaches to Responsible AI. O’Reilly Media, Inc.
11. Han, B., Coghlan, S., Buchanan, G., McKay, D., 2025. Who is Helping Whom? Student Concerns about AI-Teacher Collaboration in Higher Education Classrooms. Proc ACM Hum-Comput Interact 9, CSCW206:1-CSCW206:32. https://doi.org/10.1145/3711104
12. Hasan, A., 2021. Ethical considerations in the use of secondary data for built environment research, in: Secondary Research Methods in the Built Environment. Routledge.
13. Ifenthaler, D., Gibson, D., Prasse, D., Shimada, A., Yamada, M., 2021. Putting learning back into learning analytics: actions for policy makers, researchers, and practitioners. Educ. Technol. Res. Dev. 69, 2131–2150. https://doi.org/10.1007/s11423-020-09909-8
14. Iranzad, R., Liu, X., 2025. A review of random forest-based feature selection methods for data science education and applications. Int. J. Data Sci. Anal. 20, 197–211. https://doi.org/10.1007/s41060-024-00509-w
15. Li, Z., Dhruv, A., Jain, V., 2024. Ethical Considerations in the Use of AI for Higher Education: A Comprehensive Guide, in: 2024 IEEE 18th International Conference on Semantic Computing (ICSC). Presented at the 2024 IEEE 18th International Conference on Semantic Computing (ICSC), pp. 218–223. https://doi.org/10.1109/ICSC59802.2024.00041
16. Melnyk, Y.B., Pypenko, I.S., 2025. Implementing of artificial intelligence in a higher educational ecosystem. Int. J. Sci. Ann. 8, 13–20. https://doi.org/10.26697/ijsa.2025.1.1
17. Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D.E., Thierry-Aguilera, R., Gerardou, F.S., 2023. Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Educ. Sci. 13, 856.
18. Mishra, V. and Mishra, M.P., 2023. PRISMA for review of management literature–method, merits, and limitations–an academic review.
19. Mrabti, L., Alaoui, Z.B., 2024. Balancing Qualitative and Quantitative Research Methods: Insights and Applications, in: Data Collection and Analysis in Scientific Qualitative Research. IGI Global Scientific Publishing, pp. 87–118. https://doi.org/10.4018/979-8-3693-8689-7.ch004
20. Mumtaz, S., Carmichael, J., Weiss, M., Nimon-Peters, A., 2025. Ethical use of artificial intelligence based tools in higher education: are future business leaders ready? Educ. Inf. Technol. 30, 7293–7319. https://doi.org/10.1007/s10639-024-13099-8
21. Nagy, A.S., Tumiwa, J.R., Arie, F.V., Erdey, L., 2024. An exploratory study of artificial intelligence adoption in higher education. Cogent Educ. 11, 2386892. https://doi.org/10.1080/2331186X.2024.2386892
22. Pacheco-Mendoza, S., Guevara, C., Mayorga-Albán, A., Fernández-Escobar, J., 2023. Artificial intelligence in higher education: A predictive model for academic performance. Educ. Sci. 13, 990.
23. Rahiman, H.U., Kodikal, R., 2024. Revolutionizing education: Artificial intelligence empowered learning in higher education. Cogent Educ. 11, 2293431. https://doi.org/10.1080/2331186X.2023.2293431
24. Salman, H.A., Kalakech, A., Steiti, A., 2024. Random forest algorithm overview. Babylon. J. Mach. Learn. 2024, 69–79.
25. Shimaoka, A.M., Ferreira, R.C., Goldman, A., 2024. The evolution of CRISP-DM for data science: Methods, processes and frameworks. SBC Rev. Comput. Sci. 4, 28–43.
26. Slimi, Z., Carballido, B.V., 2023. Navigating the Ethical Challenges of Artificial Intelligence in Higher Education: An Analysis of Seven Global AI Ethics Policies. TEM J. 12.
27. Sova, R., Tudor, C., Tartavulea, C.V., Dieaconescu, R.I., 2024. Artificial Intelligence Tool Adoption in Higher Education: A Structural Equation Modeling Approach to Understanding Impact Factors among Economics Students. Electronics 13, 3632. https://doi.org/10.3390/electronics13183632
28. Statham, W., 2025. Facilitating Faculty Engagement with AI: Practical Insights from the Frontline of Higher Education, in: INTED2025 Proceedings. IATED, pp. 6015–6024.
29. Taherdoost, H., 2022. What are Different Research Approaches? Comprehensive Review of Qualitative, Quantitative, and Mixed Method Research, Their Applications, Types, and Limitations. J. Manag. Sci. Eng. Res. 5, 53–63. https://doi.org/10.30564/jmser.v5i1.4538
30. Towfek, S.K., Khodadadi, N., Abualigah, L., Rizk, F.H., 2024. AI in higher education: insights from student surveys and predictive analytics using PSO-guided WOA and linear regression. J. Artif. Intell. Eng. Pract. 1, 1–17.
31. Yu, J., 2021. Academic Performance Prediction Method of Online Education using Random Forest Algorithm and Artificial Intelligence Methods. Int. J. Emerg. Technol. Learn. 15, 45. https://doi.org/10.3991/ijet.v16i05.20297
32. Azoulay, R., Hirst, T. and Reches, S., 2025. Large language models in computer science classrooms: Ethical challenges and strategic solutions. Applied Sciences, 15(4), p.1793.
33. Ganai, P.A. and Naikoo, I.A., 2025. The Ethical Paradox of AI-Generated Texts: Investigating the Moral Responsibility in Generative Models.
34. Njee, L.C., 2025. Online Professors’ Experience With Students Misusing Artificial Intelligence (AI) in Higher Education: An Exploratory Case Study (Doctoral dissertation, National University).
35. Prather, J., Denny, P., Leinonen, J., Becker, B.A., Albluwi, I., Craig, M., Keuning, H., Kiesler, N., Kohn, T., Luxton-Reilly, A. and MacNeil, S., 2023. The robots are here: Navigating the generative ai revolution in computing education. In Proceedings of the 2023 working group reports on innovation and technology in computer science education (pp. 108-159).
36. Vyortkina, D., 2023. AI in Education: Good, Bad, and Ugly. In ICERI2023 Proceedings (pp. 956-966). IATED.
37. Abdennour, O., Kemouss, H. and Khaldi, M., 2025. Integrating AI Education in Non-Technical Disciplines: Bridging the Gap Between Theory and Practice. In Ethics and AI Integration Into Modern Classrooms (pp. 117-146). IGI Global Scientific Publishing.
38. Ariza, E.N.W. and Mountford, M., 2025. Global Leadership and Artificial Intelligence (AI) Literacies: A Fulbright Perspective. Journal of Literacy and Technology, 26(3).
39. Deckker, D. and Sumanasekara, S., 2025. Student-centric ethical frameworks for AI-driven education: Participatory consent and data ownership in a global perspective. International Journal of Science and Research Archive, 15(3), pp.1491-1503.
40. FENGRUI, Z., 2025. Artificial Intelligence and Business Education: Transformation, Challenges, and Future Prospects. In International Conference on Fundamental and Applied Research (I-CFAR) (Vol. 2, pp. 601-608).
41. Harwood, A.E., 2025. AI in Academia: Faculty Perspectives at the Crossroads of Technology and Education (Doctoral dissertation, California State University, Los Angeles).
42. Huang, D., 2025. How teachers perceive AI in their profession and classroom: professional visions and practical problems (Doctoral dissertation, Boston University).
43. Istrate, O. and Velea, S., 2024. Guidelines for Online and Blended Learning: Design, Delivery, Assessment, Evaluation of Study Programmes Premises of Academic Curriculum Digitalisation.
44. Khan, T., 2025. AI in Education-A Primer for Educators. Available at SSRN 5528959.
45. Mistry, H.M., 2024. Need for Artificial Intelligence (AI) Tools in Educational Institutions (Doctoral dissertation, University of the Cumberlands).
46. Nartgün, Z. and Kennedy, E., 2024. Artificial Intelligence (AI) and education: Contributions opportunities and challenges. Political Economy and Management of Education, 5(2), pp.24-46.
47. Niazai, H. and Monib, W.K., 2025. AI for Personalized Learning in Medical Education. In Teaching in the Age of Medical Technology (pp. 91-122). IGI Global Scientific Publishing.
48. Ortiz, E.A., Vergara, N.C., Pabón, T.F., Gambi, G.D.N., Giambruno, C., Alfaro, M.P. and Segura, D.R., 2025. AI and education: Building the future through digital transformation.
49. Rothera, S. and Macdonald, M.A., 2025. Understanding the emerging use of artificial intelligence (AI) in social work education and practice in England.
50. Series, I.I.P., 2024. Teaching in the Artificial Intelligence Era: Empowering Educators for the Future.
51. Shukla, S., 2024. Principles governing ethical development and deployment of AI. International Journal of Engineering, Business and Management, 8(2), pp.26-46.
52. Singleton, J.L., 2025. Unlocking Student Success: Exploring the Impact of AI-Driven Tools within the LMS on Improving Student Academic Success (Doctoral dissertation).
53. Venkatesh, R. and Preethi, D.M.D., 2025. Innovations in Education: The Influence of Artificial Intelligence and Data Science on Teaching, Learning, and Assessments. In Driving Quality Education Through AI and Data Science (pp. 25-50). IGI Global Scientific Publishing.
54. Yazdandoust, Y., 2025. Public Health Students’ Perceptions of AI Technology in Education and Practice.
55. Alawneh, Y.J., 2025. Graduate Students’ Perceptions at An-Najah National University Regarding the Role of Artificial Intelligence in Enhancing Interaction in E-Learning Environments.
56. Masters, K., MacNeil, H., Benjamin, J., Carver, T., Nemethy, K., Valanci-Aroesty, S., Taylor, D.C., Thoma, B. and Thesen, T., 2025. Artificial intelligence in health professions education assessment: AMEE guide no. 178. Medical Teacher, 47(9), pp.1410-1424.
57. Mishra, D.R. and Varshney, D., 2024. Comprehensive analysis of human and AI task allocation in the education sector: Defining futuristic roles and responsibilities. World Journal of Advanced Research and Reviews, 22(3), pp.10-30574.
58. Ali Khan, U., Kauttonen, J., Aunimo, L. and V Alamäki, A., 2024. A system to ensure information trustworthiness in artificial intelligence enhanced higher education.
59. Kapoor, S.K., Sankhla, K. and Syed, S., 2026. Ethical Digital Twin: A Framework for AI-Powered Moral Reasoning Simulations in Education. In AI-Powered Transformations for Ethical Education (pp. 21-54). IGI Global Scientific Publishing.
60. Siddiqui, M.T., Mansoori, M.V., Siddiqui, M.A. and Yadav, A., 2025. AI-enabled pedagogy: Advancing education through innovative teaching tools and the AITEACH model. Journal of Informatics Education and Research, 5(1), pp.2526-2539.
61. Kronqvist, S., 2025. Ethics in AI usage.
62. Balthazaar, D., 2025, July. AI-Powered Pedagogy: A Model For Innovation In Teaching And Learning. In International e-Conference Proceeding (p. 38).
63. Khojah, R., Werth, A., Broadhead, K.W., Dobrucki, L.W., Geiger, C. and Rubenstein, D.A., 2025. Integrating Generative Artificial Intelligence Tools and Competencies in Biomedical Engineering Education: R. Khojah et al. Biomedical Engineering Education, 5(2), pp.135-151.
64. Miller, T.M., 2025. Adjunct Faculty Experiences of Students Using Generative Artificial Intelligence Content in Class: A Narrative Inquiry (Doctoral dissertation, University of Phoenix).
65. Noviandy, T.R., Maulana, A., Idroes, G.M., Zahriah, Z., Paristiowati, M., Emran, T.B., Ilyas, M. and Idroes, R., 2024. Embrace, don’t avoid: reimagining higher education with generative artificial intelligence. Journal of Educational Management and Learning, 2(2), pp.81-90.
66. Akbar, M.S., 2025. Beyond detection: designing AI-resilient assessments with automated feedback tool to foster critical thinking. arXiv preprint arXiv:2503.23622.
67. Baker, N., 2025. Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice. Education Sciences.
68. Echeverria-Caicedo, K., Vázquez-Meza, J.A., Llacsa-Puma, L.J., Gutiérrez-Izquierdo, M.A., Quirino-Rodríguez, L.G., Rengifo-Lozano, R.A., Chipana Peceros, C.N., Sabando-García, Á.R. and Moreira-Choez, J.S., 2026. Responsible practices and ethical behaviors in the use of artificial intelligence among university students. F1000Research, 15, p.16.
69. Fitas, R., Ghosh, K. and Maity, S., 2025. Leveraging AI in education: benefits, responsibilities, and trends. In AI Roles and Responsibilities in Education (pp. 129-169). Cham: Springer Nature Switzerland.
70. Frieary, A., 2025. The Integration of Artificial Intelligence Into Curriculum Design in Higher Education (Doctoral dissertation).
71. Sarkam, N.A., Mohammad, N.H., Jamil, N.I., Razi, N.F.M. and Ahmad, S., 2025, September. Analyzing the Impact of ChatGPT on Student Over-Reliance and Plagiarism using Artificial Neural Network (ANN). In 2025 6th International Conference on Artificial Intelligence and Data Sciences (AiDAS) (pp. 552-558). IEEE.
72. Vorobyeva, K.I., Belous, S., Savchenko, N.V., Smirnova, L.M., Nikitina, S.A. and Zhdanov, S.P., 2025. Personalized Learning through AI: Pedagogical Approaches and Critical Insights. Contemporary Educational Technology, 17(2).
73. Eze, C.A., 2024. The role of educators in upholding academic integrity in an ai-driven era. AI and ethics, academic integrity and the future of quality assurance in higher education.
74. Freeman, K., 2025. Perceptions of Artificial Intelligence in Higher Education (Doctoral dissertation, Seton Hall University).
75. Hagsér, E. and Rademacher, T., 2025. Generative AI Chatbots in Higher Education: ATAM-Based Analysis of Discipline-Specific Adoption Patterns for Students at the University of Borås.
76. Lamrabet, M., Fakhar, H., Echantoufi, N., El Khattabi, K. and Ajana, L., 2026. Exploring the Potential of Generative AI in Initial Teacher Training: A Motivational Analysis. International Journal of Information and Education Technology, 16(1).
77. Quang Sang, N., Thao, N., Tam, D. and Ly Duc, M., 2025. Evaluating Gpt-Enabled Learning: Challenges and Opportunities for Academic Performance in a Global Context. Nguyen and Tam, Do and Ly Duc, Minh, Evaluating Gpt-Enabled Learning: Challenges and Opportunities for Academic Performance in a Global Context.
78. Paullet, K., Pinchot, J., Kinney, E. and Stewart, T., 2025. Utilizing GPTZero to Detect AI-Generated Writing. Information Systems Education Journal, 23(6), pp.44-52.
79. Wadhwani, A. and Mohadeb, P., 2025 Harnessing Artificial Intelligence for Transforming Education and Accelerating Research: Opportunities, Challenges, and Future Directions.
80. Kaushik, A., Yadav, S., Browne, A., Lillis, D., Williams, D., Donnell, J.M., Grant, P., Kernan, S.C., Sharma, S. and Arora, M., 2025. Exploring the impact of generative artificial intelligence in education: a thematic analysis. arXiv preprint arXiv:2501.10134.
81. Bulut, O., Beiting-Parrish, M., Casabianca, J.M., Slater, S.C., Jiao, H., Song, D., Ormerod, C.M., Fabiyi, D.G., Ivan, R., Walsh, C. and Rios, O., 2024. The rise of artificial intelligence in educational measurement: Opportunities and ethical challenges. arXiv preprint arXiv:2406.18900.
82. PrajapatI, M.A.B., 2024. Artificially Intelligent in Education:” Redefining Learning in the 21st Century”. Educational Resurgence Journal.
83. Singh, M.V.K. and Sinha, K., 2025. How AI Is Reshaping Recruitment, Personalized Learning, Performance Tracking and Workforce Planning. International Journal of Engineering Development and Research, 13(4), pp.294-317.
84. Ogwueleka, F.N., 2025. Plagiarism detection in the age of artificial intelligence: current technologies and future directions. AI and ethics, academic integrity and the future of quality assurance in higher education, 10.
85. Jokhan, A., Chand, A.A., Singh, V. and Mamun, K.A., 2022. Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance. Sustainability, 14(4), p.2377.
86. Tariq, M.U., 2026. AI-Driven Curriculum Design in Higher Education: Frameworks for Future-Ready Learning Ecosystems. In AI Education Strategies for Future-Proofing Curriculum Design (pp. 21-46). IGI Global Scientific Publishing.
87. Omirali, A., Kozhakhmet, K. and Zhumaliyeva, R., 2025. Digital Trust in Transition: Student Perceptions of AI-Enhanced Learning for Sustainable Educational Futures. Sustainability, 17(17), p.7567.
88. Abdelaal, R.M., 2026. Integrating Artificial Intelligence Into the Industrial Engineering Discipline: Bridging Theory and Classroom Practice. In AI-Powered Pedagogy, Academic Transformation, and Faculty Empowerment (pp. 239-264). IGI Global Scientific Publishing.
89. Juárez, R., Hernández-Fernández, A., Camargo, C.B. and Molero, D., 2026. Nested Learning in Higher Education: Integrating Generative AI, Neuroimaging, and Multimodal Deep Learning for a Sustainable and Innovative Ecosystem. Sustainability, 18(2), p.656.
90. Nwozor, A., 2025. Artificial intelligence (AI) and academic honesty-dishonesty nexus: Trends and preventive measures. AI and ethics, academic integrity and the future of quality assurance in higher education, 27(3).