Knowledge, Attitude, and Perception of Learners Towards the Use of ChatGPT in the University of Ibadan, Nigeria

Authors

https://doi.org/10.17583/rise.15313

Keywords:


Downloads

Abstract

ChatGPT has acquired a global audience due to its widespread integration into educational practices and the rapid advancement of technology, particularly in the innovative artificial intelligence tool. Hence, a growing need exists to understand how students interact with and perceive such writing tools within the academic landscape. This study aims to provide valuable insights into integrating AI technologies into higher education. The study used a mixed-method approach guided by the social constructivism theory. Through the multi-stage sampling, 402 students were selected for quantitative analysis, while qualitative insights were gathered through ten (10) In-depth interviews with the University academics. Quantitative data was analysed using descriptive statistics and the Independence Sample T-test in IBM-SPSS Version 23. Qualitative data underwent thematic and content analysis. The study findings indicate a high level of awareness among students on ChatGPT, with most obtaining knowledge about the tool from recommendations by friends and colleagues. Despite its high level of awareness among students, the study found that some academics reported a lack of familiarity with ChatGPT. Based on the findings, several recommendations are proposed, which include organising seminars on technology, specifically AI, for lecturers and students and integrating them into the curriculum to create awareness.

Downloads

Download data is not yet available.

References

Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., ... & Sallam, M. (2023). Factors influencing attitudes of university students towards ChatGPT and its usage: a multi-national study validating the TAME-ChatGPT survey instrument.

Google Scholar Crossref

Abejide, O. J. (2023). Diagnosis of pleural mesothelioma using machine learning (Doctoral dissertation, Laurentian University Library & Archives). Diagnosis of pleural mesothelioma using machine learning

Google Scholar Crossref

Adebayo, A., Oluwaseun, B., Gboyega, A. & Ebenezer, B. (2021). University Students’ Awareness of Access to and Use of Artificial Intelligence for Learning in Kwara State. Indonesian Journal of Teaching in Science 1(2):91-104. https://ejournal.upi.edu/index.php/IJoTis/article/view/38014.

Google Scholar Crossref

Adetayo, A. J. (2021). Leveraging bring your own device for the mobility of library reference services: The Nigerian perspective. The Reference Librarian, 62(2), 106-125.

Google Scholar Crossref

Anderson, J. & Rainie, L. (2018). Artificial Intelligence and the Future of Humans. Pew Research Centre: Internet, Science & Tech.

Google Scholar Crossref

Ajlouni, A. O., Almahaireh, A. S. & Wahba, F.A. (2023). Students’ Perception of Using ChatGPT in Counseling and Mental Health Education: The Benefits and

Google Scholar Crossref

Challenges. International Journal of Emerging Technologies in Learning (iJET), 18(20), pp. 199–218. https://doi.org/10.3991/ijet.v18i20.42075.

Google Scholar Crossref

Alburger, J. (2018). Rule-based chatbots vs. AI chatbots: Key differences. Hubtype. https://www.hubtype.com/blog/rule-based-chatbots-vs-ai-chatbots. BML Munjal University (2023). A Hero Group Initiative.

Google Scholar Crossref

Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440.

Google Scholar Crossref

Baker, M. A. (2021). Educational distancing: A mixed-methods study of student perceptions in the time of coronavirus. Journal of Hospitality & Tourism Education, 33(3), 207–221.

Google Scholar Crossref

Choi, Y., Cordova, C., Hsin, P. S., Lam, H. T., & Shao, S. H. (2023). Non-invertible condensation, duality, and triality defects in 3+ 1 dimensions. Communications in Mathematical Physics, 402(1), 489–542.

Google Scholar Crossref

Creswell, J. W. (2011). Controversies in mixed methods research. The SAGE.

Google Scholar Crossref

Deng, J., & Lin, Y. (2022). The benefits and challenges of ChatGPT: An overview. Frontiers in Computing and Intelligent Systems, 2(2), 81-83. 2911cbc3bc24e43a910477a90363225bed95.pdf

Google Scholar Crossref

Dhawan, S., Singh, K., & Batra, A. (2021). Defining and Evaluating Network. Recent Innovations in Computing: Proceedings of ICRIC 2020, 701, 151.

Google Scholar Crossref

El Khodr, M., Gide, E., Wu, M., & Darwish, O. (2023). ICT students’ perceptions towards ChatGPT: An experimental, reflective lab analysis.

Google Scholar Crossref

Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in education and teaching international, 61(3), 460–474.

Google Scholar Crossref

Haggart, B. (2023). ChatGPT strikes at the heart of the scientific worldview. Centre for International Governance Innovation.

Google Scholar Crossref

Ibrahim, H., Liu, F., Asim, R., Battu, B., Benabderrahmane, S., Alhafni, B., ... & Zaki, Y. (2023). Perception, performance, and detectability of conversational artificial intelligence across 32 university courses. Scientific Reports, 13(1), 12187.

Google Scholar Crossref

Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Artificial intelligence applications for industry 4.0: A literature-based study. Journal of Industrial Integration and Management, 7(01), 83–111.

Google Scholar Crossref

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274.

Google Scholar Crossref

Kılınç, S. (2023). Embracing the future of distance science education: Opportunities and challenges of ChatGPT integration. Asian Journal of Distance Education 18(1). ISSN 1347-9008

Google Scholar Crossref

Khojah, R., Mohamad, M., Leitner, P., & de Oliveira Neto, F. G. (2024). Beyond code generation: An observational study of ChatGPT usage in software engineering practice. Proceedings of the ACM on Software Engineering, 1(FSE), 1819-1840.

Google Scholar Crossref

King, M. R., & ChatGPT. (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and molecular bioengineering, 16(1), 1-2.

Google Scholar Crossref

Krittanawong, C., Zhang, H., Wang, Z., Aydar, M. & Kitai, T. (2017). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, pp. 69, 2657–2664. https://doi.org/10.1016/j.jacc.2017.03.571.

Google Scholar Crossref

Lodge, J. M., de Barba, P., & Broadbent, J. (2023). Learning with generative artificial intelligence within a network of co-regulation. Journal of University Teaching and Learning Practice, 20(7), 1–10.

Google Scholar Crossref

Masters, K. (2023). Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Medical Teacher, 45(6), 574–584.

Google Scholar Crossref

Mascolo, M. F., Fischer, K. W., & Fischer, K. W. (2005). Constructivist theories. Cambridge encyclopedia of child development, 49-63.

Google Scholar Crossref

Matthew, U. O., Oyekunle, D. O., Akpan, E. E., Oladipupo, M. A., Chukwuebuka, E. S., Adekunle, T. S., ... & Onumaku, V. C. (2024). Generative Artificial Intelligence (AI) on Sustainable Development Goal 4 for Tertiary Education: Conversational AI With User-Centric ChatGPT-4. In Impacts of Generative AI on Creativity in Higher Education (pp. 259–288). IGI Global.

Google Scholar Crossref

Memarian, B., & Doleck, T. (2023). ChatGPT in education: Methods, potentials, and limitations. Computers in Human Behavior: Artificial Humans, 1(2), 100022.

Google Scholar Crossref

Michel, G. F. & Rochat, P. (Eds.). Cambridge encyclopedia of child development. Cambridge, U.K.: Cambridge University Press. https://www.academia.edu/8906476/Constructivist_Theories.

Google Scholar Crossref

McCarthy, J. (1987). Generality in artificial intelligence. Communications of the ACM, 30(12), 1030–1035. Generality in artificial intelligence | Communications of the ACM

Google Scholar Crossref

McCarthy, J., Minsky, M. L., Rochester, N. & Shannon, C. E. (1955). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. Dartmouth College. https://doi.org/10.1609/aimag.v27i4.1904.

Google Scholar Crossref

Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023). Impact of the implementation of ChatGPT in education: A systematic review. Computers, 12(8), 153.

Google Scholar Crossref

Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., ... & Sandison, C. (2023). ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559-614.

Google Scholar Crossref

OpenAI, & ChatGPT. (2022). ChatGPT: Optimizing language models for dialogue. https://openai.com/blog/chatgpt/.

Google Scholar Crossref

Ondáš, S., Pleva, M., & Hládek, D. (2019, November). How chatbots can be involved in the education process. In 2019 17th international conference on emerging elearning technologies and applications (ICETA) (pp. 575-580). IEEE.

Google Scholar Crossref

Pavlik, J. V. (2023). Collaborating with ChatGPT: Considering the implications of generative artificial intelligence for journalism and media education. Journalism & mass communication educator, 78(1), 84-93.

Google Scholar Crossref

Qadir, J. (2023, May). Engineering education in the era of ChatGPT: Promise and pitfalls of generative AI for education. In 2023 IEEE Global Engineering Education Conference (EDUCON) (pp. 1-9). IEEE.

Google Scholar Crossref

Raghu, K., S, T., S Devishamani, C., Rajalakshmi, R., & Raman, R. (2023). The utility of ChatGPT in diabetic retinopathy risk assessment: a comparative study with clinical diagnosis. Clinical Ophthalmology, 4021-4031.

Google Scholar Crossref

Sanders, N. R., & Wood, J. D. (2024). The Humachine: AI, Human Virtues, and the Superintelligent Enterprise. Taylor & Francis.

Google Scholar Crossref

Sedaghat, S. (2023). Early applications of ChatGPT in medical practice, education and research. Clinical Medicine, 23(3), 278–279.

Google Scholar Crossref

Shoufan, A. (2023). Exploring students’ perceptions of ChatGPT: Thematic analysis and follow-up survey. IEEE Access, 11, 38805–38818.

Google Scholar Crossref

Spennemann, H. R. (2023). Exhibiting the Heritage of COVID-19—A Conversation with ChatGPT, Gulbali Institute. Charles Sturt University, P.O. Box 789, Albury, NSW 2640, Australia. https://doi.org/10.3390/heritage6080302.

Google Scholar Crossref

Sun, G. H., & Hoelscher, S. H. (2023). The ChatGPT storm and what faculty can do. Nurse Educator, 48(3), 119-124.

Google Scholar Crossref

Surameery, N. M. S., & Shakor, M. Y. (2023). Use chatGPT to solve programming bugs. International Journal of Information Technology and Computer Engineering, (31), 17-22.

Google Scholar Crossref

Rahman, M., Harold, J., Terano, M., Nafizur, R. & Aidin, S. (2023). ChatGPT and Academic Research: A Review and Recommendations Based on Practical Examples. doi: 10.52631/jemds.v3i1.175.

Google Scholar Crossref

Tancredi, L. (2023). Understanding ChatGPT: The Promise and Nuances of Large Language

Google Scholar Crossref

Models.

Google Scholar Crossref

Thi, T. A. (2023). The Perception by University Students of the Use of ChatGPT in Education. DOI: https://doi.org/10.3991/ijet.v18i17.39019

Google Scholar Crossref

Tiwari, C. K., Bhat, M. A., Khan, S. T., Subramaniam, R., & Khan, M. A. I. (2024). What drives students toward ChatGPT? An investigation of the factors influencing the adoption and usage of ChatGPT. Interactive Technology and Smart Education, 21(3), 333-355.

Google Scholar Crossref

Turing, A. (1936). Turing machine. Proc London Math Soc, 242, 230–265. 2001S13Week9.ppt

Google Scholar Crossref

Uzunboylu, H., Prokopyev, A. I., Kashina, S. G., Makarova, E. V., Chizh, N. V. & Sakhieva, R. G. (2022). Determining the opinions of university students on the education they receive with technology during the pandemic process. International Journal of Engineering Pedagogy (iJEP), 12(2), 48–61. https://doi.org/10.3991/ijep.v12i2.29329.

Google Scholar Crossref

Yigci, D., Eryilmaz, M., Yetisen, A. K., Tasoglu, S., & Ozcan, A. (2024). Large Language Model‐Based Chatbots in Higher Education. Advanced Intelligent Systems, 2400429.

Google Scholar Crossref

Yu, H. (2024). The application and challenges of ChatGPT in educational transformation: New demands for teachers' roles. Heliyon, 10(2).

Google Scholar Crossref

Zheng, W. (2024). AI vs. Human: A Comparative Study of Cohesion and Coherence in Academic Texts between Human-Written and ChatGPT-Generated Texts.

Google Scholar Crossref

Zohery, M. (2023). Artificial Intelligence in Academia, Research and Science: ChatGPT as a Case Study. pp.10-61, Achtago Publishing. http://dx.doi.org/10.5281/zenodo.7803703

Google Scholar Crossref

Downloads

Published

2025-06-25

Almetric

Dimensions

How to Cite

Shittu, O. I. ., Busari, D. A. ., & Olonade, O. Y. . (2025). Knowledge, Attitude, and Perception of Learners Towards the Use of ChatGPT in the University of Ibadan, Nigeria. International Journal of Sociology of Education, 14(2), 146–168. https://doi.org/10.17583/rise.15313

Issue

Section

Articles