Artificial Intelligence (AI) has revolutionized the world in all spheres of life. Starting with the fundamentals, AI has altered key areas in the industry and is now poised to encroach upon the realm of education, most notably in higher education. Undoubtedly, the reliance on AI has been steadily rising in the past few years, and the University of Nizwa, in the Sultanate of Oman has been taken as a case study to establish the link between student performance and the usage of AI. Being exploratory research, this article attempts to shed light on the perspectives of AI being used to bolster students’ motivation and the extent of their involvement in the learning process. The main aim of this study is to observe the moderating factors, such as academic specialization and academic level, which may impact the relationship between the use of AI technologies and the students’ academic performance at the University of Nizwa. In doing so, this study seeks to answer questions on how educational specialization influences students’ gains from AI technologies. What are the challenges students encounter in utilizing AI technologies in their learning? For the research methodology, this study employed a quantitative approach based on a structured questionnaire analyzed using statistical procedures (descriptive statistics, correlation, regression and t-test) for the 115 random samples.
KeywordsAIAdaptive Learning PlatformsAutomated Assisted ProgramsChat GPTIntelligent Learning Systems
García-Martínez, I., Fernández-Batanero, J.M., Fernández-Cerero, J. and León, S.P. (2023) Analysing the Impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and Meta-Analysis. Journal of New App roaches in Educational Research , 12, 171-197. https://doi.org/10.7821/naer.2023.1.1240
Dong, L., Tang, X. and Wang, X. (2025) Examining the Effect of Artificial Intelligence in Relation to Students’ Academic Achievement: A Meta-Analysis. Computers and Education: Artificial Intelligence , 8, Article 100400. https://doi.org/10.1016/j.caeai.2025.100400
Jiao, J., Wang, J. and Liu, X. (2022) The Impact of Artificial Intelligence on Students’ Academic Performance: A Focus on Interaction Level. Educational Technology Re-search and Development , 70, 415-428.
Guidoum, S. and Saadi, E. (2024) The Impact of Artificial Intelligence on Students’ Academic Performance from University Teachers’ Perspectives. ATRAS journal , 5, 381-395. https://doi.org/10.70091/atras/ai.24
Shahzad, M.F., Xu, S., Lim, W.M., Yang, X. and Khan, Q.R. (2024) Artificial Intelligence and Social Media on Academic Performance and Mental Well-Being: Student Perceptions of Positive Impact in the Age of Smart Learning. Heliyon , 10, e29523. https://doi.org/10.1016/j.heliyon.2024.e29523
Shahzad, M.F., Xu, S. and Javed, I. (2024) ChatGPT Awareness, Acceptance, and Adoption in Higher Education: The Role of Trust as a Cornerstone. International Journal of Educational Technology in Higher Education , 21, Article No. 46. https://doi.org/10.1186/s41239-024-00478-x
Adewale, M.D., Azeta, A., Abayomi-Alli, A. and Sambo-Magaji, A. (2024) Impact of Artificial Intelligence Adoption on Students’ Academic Performance in Open and Distance Learning: A Systematic Literature Review. Heliyon , 10, e40025. https://doi.org/10.1016/j.heliyon.2024.e40025
Abdulhajar, E., Wahyusari, A., Nevrita, N., Irawan, D., Zaitun, Z., Sartika, D., et al . (2024) Students’ Acceptance of ChatGPT Technology: A Study of Its Positive and Negative Impacts on Academic Ethics and Learning Performance. SHS Web of Conferences , 205, Article ID: 07003. https://doi.org/10.1051/shsconf/202420507003
Ma’amor, H., Achim, N., Ahmad, N.L., Roszaman, N.S., Kamarul Anuar, N.N., Khairul Azwa, N.C.A., et al . (2024) The Effect of Artificial Intelligence (AI) on Students’ Learning. Information Management and Business Review , 16, 856-867. https://doi.org/10.22610/imbr.v16i3s(i)a.4178
Strazda, A., Dehtjare, J., Mironova, J., Kinderis, R. and Vveinhardt, J. (2025) The Role of AI Tools in Improving Practices in E-Learning Environment: A Pilot Study. TEM Journal , 14, Article 2972. https://doi.org/10.18421/tem144-08
Hamadneh, A.S., Saade, R.G. and Azzam, R. (2022) The Impact of Artificial Intelligence Tools on Academic Performance in Higher Education. Journal of Educational Technology Development and Exchange , 15, 45-67.
Ijiga, O.M., Ifenatuora, G.P. and Olateju, M. (2022) AI-Powered E-Learning Platforms for STEM Education: Evaluating Effectiveness in Low-Bandwidth and Remote Learning Environments. International Journal of Scientific Research in Computer Science, Engineering and Information Technology , 8, 455-475. https://doi.org/10.32628/cseit23902187
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T. and Du, Z. (2024) Artificial Intelligence in Education: A Systematic Literature Review. Expert Systems with Applica tions , 252, Article 124167. https://doi.org/10.1016/j.eswa.2024.124167
Altememy, H.A., Neamah, N.R., Mazhair, R., Naser, N.S., Fahad, A.A., Al-Sammarraie, N.A., Sharif, H.R., Alseidi, M.A. and Al-Muttar, M.Y.O. (2023) AI Tools’ Impact on Student Performance: Focusing on Student Motivation & Engagement in Iraq. Przestrzeń Społeczna ( Social Space ), 23, 143-165. https://socialspacejournal.eu/menu-script/index.php/ssj/article/view/217
Ben, A., Zhang, L. amnd Liu, H. (2024) The Role of Academic Discipline in the Adoption of Artificial Intelligence Tools: An Empirical Study. Journal of Educational Computing Research , 56, 133-150.
Coursera Staff (2024) AI in Education: Approaches and Strategies for Educators. https://www.coursera.org/articles/ai-in-education
Vieriu, A.M. and Petrea, G. (2025) The Impact of Artificial Intelligence (AI) on Students’ Academic Development. Education Sciences , 15, Article 343. https://doi.org/10.3390/educsci15030343
Klimova, B. and Pikhart, M. (2025) Exploring the Effects of Artificial Intelligence on Student and Academic Well-Being in Higher Education: A Mini-Review. Frontiers in Psychology , 16, Article 1498132. https://doi.org/10.3389/fpsyg.2025.1498132
Yang, M., et al . (2025). Analysing Nontraditional Students’ ChatGPT Interaction. British Journal of Educational Technology , 56, 1973-2000. https://doi.org/10.1111/bjet.13588 https://bera-journals.onlinelibrary.wiley.com/doi/full/10.1111/bjet.13588
Tanveer, I., Iqbal, S. and Hussain, A. (2024) Examining the Impact of AI-Based Chatbots on Academic Self-Efficacy and Self-Regulation among University Students. Journal of Development and Social Sciences , 5, 468-477. https://www.researchgate.net/publication/381551089
Pacheco-Mendoza, J., Rodríguez-Hernández, R. and Ramírez-Carrillo, D. (2023) The Increase in Study Time in Response to the Need to Adapt to Virtual Environments and Its Impact on Academic Performance. Journal of Educational Technology & Society , 26, 45-58.
Ward, B., Bhati, D., Neha, F. and Guercio, A. (2024) Analyzing the Impact of AI Tools on Student Study Habits and Academic Performance. arXiv: 2412.02166. https://arxiv.org/abs/2412.02166
Deci, E.L. and Ryan, R.M. (1985) Intrinsic Motivation and Self-Determination in Human Behavior. Springer Science & Business Media.
Davis, F.D. (1989) Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly , 13, 319-340. https://doi.org/10.2307/249008
Vallerand, R.J. (1997) Toward a Hierarchical Model of Intrinsic and Extrinsic Motivation. Advances in Experimental Social Psychology , 29, 271-360. https://doi.org/10.1016/s0065-2601(08)60019-2
Venkatesh, V. and Davis, F.D. (2000) A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science , 46, 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926