Generative AI Usage and Information Literacy Skills among University Students in North-West Nigeria

Generative AI Usage and Information Literacy Skills among University Students in North-West Nigeria

Authors

  • Kayode Sunday John Dada University Library, Federal University of Education, Zaria, Kaduna State, Nigeria
  • Opeyemi Romoke Quadir

DOI:

https://doi.org/10.32734/jocai.v10.i1-24709

Keywords:

Artificial Intelligence tools, Information Literacy competencies, undergraduate education, academic integrity, North-West Nigeria

Abstract

This study examined the relationship between generative AI usage and information literacy skills among university students in North-West Nigeria. The research investigated awareness levels, evaluation practices, ethical considerations, and barriers affecting the integration of AI-powered tools in academic contexts. Employing a quantitative research design, the study surveyed 385 undergraduate students from federal, state, and private universities using the Generative AI and Information Literacy Impact Questionnaire (GAIL-IQ). Data analysis utilized descriptive statistics including means, standard deviations, and frequencies through SPSS version 26. The ACRL Framework for Information Literacy (2016) provided the theoretical foundation, emphasizing threshold concepts in information understanding. Findings revealed moderate awareness levels (M=3.42, SD=0.89) of AI-powered tools among students, with significant variations across institutional types. Students demonstrated limited capacity in evaluating AI-generated content credibility (M=2.78, SD=0.94), raising concerns about information accuracy assessment. Ethical practices regarding attribution and academic integrity showed moderate adherence (M=3.15, SD=1.02), though infrastructural constraints and inadequate training emerged as primary barriers (M=3.68, SD=0.87). The study concluded that while students increasingly engage with AI-powered tools, critical evaluation competencies and ethical awareness require substantial improvement. The study recommends that Universities in North-West Nigeria should integrate comprehensive information literacy training programs specifically addressing AI-powered content evaluation, ethical usage frameworks, and attribution practices into undergraduate curricula to enhance academic integrity and critical thinking capabilities.

Downloads

Download data is not yet available.

References

[1] M. Sullivan, A. Kelly, and P. McLaughlan, "ChatGPT in higher education: Considerations for academic integrity and student learning," J. Appl. Learn. Teach., vol. 6, no. 1, pp. 1-10, 2023. [Online]. Available: https://doi.org/10.37074/jalt.2023.6.1.17

[2] Association of College & Research Libraries, Framework for Information Literacy for Higher Education. American Library Association, 2016. [Online]. Available: http://www.ala.org/acrl/standards/ilframework

[3] D. Baidoo-Anu and L. Owusu Ansah, "Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning," J. AI, vol. 7, no. 1, pp. 52-62, 2023. [Online]. Available: https://doi.org/10.61969/jai.1337500

[4] Y. K. Dwivedi et al., "Opinion paper: 'So what if ChatGPT wrote it?' Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy," Int. J. Inf. Manage., vol. 71, Art. no. 102642, 2023. [Online]. Available: https://doi.org/10.1016/j.ijinfomgt.2023.102642

[5] X. Zhai, "ChatGPT user experience: Implications for education," SSRN Electron. J., 2022. [Online]. Available: https://doi.org/10.2139/ssrn.4312418

[6] C. K. Y. Chan and W. Zhou, "Deconstructing student perceptions of generative AI (GenAI) through a reflective learning approach: A case study of ChatGPT," Educ. Inf. Technol., 2023, Advance online publication. [Online]. Available: https://doi.org/10.1007/s10639-023-12174-9

[7] D. R. E. Cotton, P. A. Cotton, and J. R. Shipway, "Chatting and cheating: Ensuring academic integrity in the era of ChatGPT," Innov. Educ. Teach. Int., vol. 61, no. 2, pp. 228-239, 2023. [Online]. Available: https://doi.org/10.1080/14703297.2023.2190148

[8] E. Hargittai, "Second-level digital divide: Differences in people's online skills," First Monday, vol. 7, no. 4, 2002. [Online]. Available: https://doi.org/10.5210/fm.v7i4.942

[9] E. M. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell, "On the dangers of stochastic parrots: Can language models be too big?" in Proc. 2021 ACM Conf. Fairness, Accountability, Transparency, 2021, pp. 610-623. [Online]. Available: https://doi.org/10.1145/3442188.3445922

[10] K. Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven, CT, USA: Yale Univ. Press, 2021.

[11] D. N. Ocholla and T. Bothma, "Trends, challenges and opportunities for LIS education and training in Eastern and Southern Africa," New Library World, vol. 108, no. 1/2, pp. 55-78, 2007. [Online]. Available: https://doi.org/10.1108/03074800710722180

[12] A. A. Adeleke and K. I. N. Nwalo, "ICT and information literacy skills among students of colleges of health sciences in Oyo State, Nigeria," Qualitative Quantitative Methods Libraries, vol. 6, no. 1, pp. 79-89, 2017.

[13] O. S. Oyelekan, A. S. Olorundare, and A. A. Adeniran, "Constraints to effective use of information and communication technology for teaching in higher institutions in Nigeria," J. Educ. Pract., vol. 12, no. 13, pp. 45-52, 2021.

[14] J. W. Creswell and J. D. Creswell, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 5th ed. Thousand Oaks, CA, USA: SAGE Publications, 2018.

[15] T. Yamane, Statistics: An Introductory Analysis, 2nd ed. New York, NY, USA: Harper and Row, 1967.

[16] M. Tavakol and R. Dennick, "Making sense of Cronbach's alpha," Int. J. Med. Educ., vol. 2, pp. 53-55, 2011. [Online]. Available: https://doi.org/10.5116/ijme.4dfb.8dfd

Published

2026-01-31

How to Cite

Dada, K. S. J., & Quadir, O. R. (2026). Generative AI Usage and Information Literacy Skills among University Students in North-West Nigeria: Generative AI Usage and Information Literacy Skills among University Students in North-West Nigeria. Data Science: Journal of Computing and Applied Informatics, 10(1), 36–60. https://doi.org/10.32734/jocai.v10.i1-24709