REVOLUTION OR DISTRACTION? ANALYZING GENERATIVE AI’S IMPACT ON UNDERGRADUATE STUDENT PERFORMANCE

Abdulrashid Abdulrauf; Omolara Busayo Abodunrin; Oluwatoyin Omoloba

doi:10.33003/fjs-2025-0904-3574

Authors

Abdulrashid Abdulrauf
talk2arrash@gmail.com

Federal Polytechnic Kaltungo, Gombe
Omolara Busayo Abodunrin
Federal School of Surveying Oyo
Oluwatoyin Omoloba
Federal School of Surveying Oyo

Keywords:

AI, ChatGPT, Generative AI, Impact, Performance, Student, Undergraduate

Abstract

Using ChatGPT regularly produces academic success, plus it develops moral critical thinking abilities and problem-solving capabilities. The use of ChatGPT creates ongoing concerns for stakeholders regarding system dependency and ethical implications that surface when users implement it. However, stakeholders continue to raise multiple concerns about both dependence on ChatGPT and the moral ramifications that come from using it. This study aims to analyze the impact of generative AI, particularly ChatGPT, on the academic performance of undergraduate students in five federal leading universities in Nigeria. A statistical analysis using Chi-square tests together with independent t-tests discovered meaningful relationships connecting academic achievements to ChatGPT usage. The study reveals that educational institutions can achieve effective results when combining AI tools like ChatGPT with conventional methods under strategic circumstances and need continuous ethical monitoring. Academic liability and the sustained advancement of critical thinking competence remain unharmed when ChatGPT use is implemented correctly.

Dimensions

REFERENCES

Abedi, M., Alshybani, I., Shahadat, M. R., & Murillo, M. (2023). Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education. Qeios, 1-45.

Ayman, S. E., El-Seoud, S. A., Nagaty, K., & Karam, O. H. (2023, November). The influence of ChatGPT on student learning and academic performance. In 2023 International Conference on Computer and Applications (ICCA) (pp. 1-5). IEEE.

Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62.

Banh, L., & Strobel, G. (2023). Generative artificial intelligence. Electronic Markets, 63.

Bharani Kumar. (2023). GPT-1, GPT-2 and GPT-3 models explained https://360digitmg.com/blog/types-of-gpt-in-artificial-intelligence.

Chiu, T. K. (2024). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187-6203.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., & Wright, R. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 102642, 71. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Ghojogh, B. &. (2020). Attention mechanism, transformers, BERT, and GPT: tutorial and survey.

Godde, D., Nohl, S., Wolf, C., Rupert, Y., Rimkus, L., Ehlers, J., Breuckmann, F., & Sellmann, T. (2023). A SWOT (strengths, weaknesses, opportunities, and threats) analysis of ChatGPT in the medical literature: Concise review. Journal of Medical Internet Research, 25, Article e49368. https://doi.org/10.2196/49368

Gregorcic, B., & Pendrill, A. M. (2023). ChatGPT and the frustrated Socrates. Physics Education, 58(3), Article 035021. https://doi.org/10.1088/1361-6552/acc299

Hagendorff, T., Fabi, S., & Kosinski, M. (2022). Machine intuition: Uncovering human-like intuitive decision-making in GPT-3.5. arXiv preprint arXi.

Hou, W., & Ji, Z. (2023). GeneTuring tests GPT models in genomics. BioRxiv.

Hwang, G. J., & Chang, C. Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 40994112. https://doi.org/10.1080/10494820.2021.1952615

Jaboob, M., Hazaimeh, M., & Al-Ansi, A. M. (2025). Integration of generative AI techniques and applications in student behavior and cognitive achievement in Arab higher education. International journal of humancomputer interaction, 41(1), 353-366.

Janiesch, C., Zschech, P., & Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 685695.

Katz, D. M., Bommarito, M. J., & Gao, S. &. (2024). Gpt-4 passes the bar exam. Philosophical Transactions of the Royal Society, 382(2270), 20230254.

Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2022). Impacts of an AI-based cha bot on college students after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational technology research and development, 70(5), 1843-1865.

Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarok or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), Article 100790. https://doi.org/10.1016/j.ijme.2023.100790

Liu, J., Shen, D., Zhang, Y., Dolan, B., Carin, L., & Chen, W. (2021). What Makes Good In-Context Examples for GPT-$3. arXiv preprint arXiv.

Liu, Z., Huang, Y., Yu, X., Zhang, L., Wu, Z., Cao, C., & Li, X. (2023). Deid-gpt: Zero-shot medical text de-identification by gpt-4. arXiv preprint arXiv.

Lo, C. K. (2023). What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Education Science, 13(410), 1-15. https://doi.org/https://doi.org/10.3390/educsci13040410

Lo, C. K., Hew, K. F., & Jong, M. S. Y. (2024). The influence of ChatGPT on student engagement: A systematic review and future research agenda. Computers & Education, 105100.

Malinka, K., Peresni, M., Firc, A., et al. (2023). On the Educational Impact of ChatGPT: Is Artificial Intelligence Ready to Obtain a University Degree? Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1. https://doi.org/10.1145/3587102.3588827

Meckler, L., & Verma, P. (2023). Teachers are on alert for inevitable cheating after the release of ChatGPT. The Washington Post. https://www.washingtonpost.com/education/2022/12/28/chatbot-cheating-ai-chatbotgpt-teachers/

Mhlanga, D. (2023). Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning. SSRN, 4354422.

Nguyen, M. T., Nguyen, P. T., Nguyen, V. V., & Nguyen, Q. M. (2021). Generating product description with generative pre-trained transformer 2. In 2021 6th international conference on innovative technology in intelligent system and industrial applications (CITISIA) (pp. 1-7). IEEE.

Patil, M. M., Rekha, P. M., Solanki, A., Nayyar, A., & Qureshi, B. (2022). Big Data Analytics Using Swarm-Based Long Short-Term Memory for Temperature Forecasting. Computers, Materials & Continua.

Sallam, M. (2023). The utility of ChatGPT as an example of large language models in healthcare education, research and practice: Systematic review on the future perspectives and potential limitations. MedRxiv, 2023, 1-34. https://doi.org/https://doi.org/10.1101/2023.02.19.23286155

Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887

Spitale, G., Biller-Andorno, N., & Germani, F. (2023). AI model GPT-3 (dis) informs us better than humans. Science Advances, 1850.

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x

Vargas-Murillo, A. R., de la Asuncion, I. N. M., & de Jess Guevara-Soto, F. (2023). Challenges and opportunities of AI-assisted learning: A systematic literature review on the impact of ChatGPT usage in higher education. International Journal of Learning, Teaching and Educational Research, 22(7), 122135. https://doi.org/10.26803/ijlter.22.7.7

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., & Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems. Advances in neural information processing systems.

Williams, N., Ivanov, S., & Buhalis, D. (2023). Algorithmic ghost in the research shell: Large language models and academic knowledge creation in management research. arXiv preprint arXiv.

Yenduri, G., Ramalingam, M., Selvi, G. C., Supriya, Y., Srivastava, G., Maddikunta, P. K., & Gadekallu, T. R. (2024). GPT (generative pre-trained transformer)a comprehensive review on enabling technologies, potential applications, emerging challenges, and future directions. IEEE Access, 1-39.

Zhang, P., & Tur, G. (2023). A systematic review of ChatGPT use in K-12 education. European Journal of Education. https://doi.org/10.1111/ejed.12599. Advance online publication.

REVOLUTION OR DISTRACTION? ANALYZING GENERATIVE AI’S IMPACT ON UNDERGRADUATE STUDENT PERFORMANCE

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