Open Access Peer-reviewed Research Article

Redefining student assessment in Nigerian tertiary institutions: The impact of AI technologies on academic performance and developing countermeasures

Main Article Content

Usman Abubakar corresponding author
Ayotunde Atanda Falade
Hussaini Aliyu Ibrahim

Abstract

Integrating artificial AI technologies in education has revolutionised teaching, learning, and assessment worldwide. In Nigerian tertiary institutions, students increasingly rely on AI tools for assignments, research, and exam preparation, raising concerns about the integrity of traditional assessment methods. This paper explores the impact of AI technologies on academic performance and the challenges they pose to accurately evaluating student capabilities. It argues for the urgent need to redefine assessment strategies in Nigerian higher education to preserve academic standards while harnessing the benefits of AI. The study highlights ethical concerns such as data privacy, access inequality, and over-reliance on AI tools, which can undermine critical thinking skills. It provides countermeasures and policy recommendations, including establishing AI usage guidelines, promoting equitable access to technology, and integrating assessments that prioritise critical thinking and problem-solving skills. By adopting these innovative policies, Nigerian tertiary institutions can enhance the quality of education and ensure that students develop genuine skills and academic excellence. This paper calls for immediate action to align education with the realities of the AI age, ensuring sustainable and authentic student outcomes.

Keywords
AI technologies, academic performance, student assessment, academic integrity

Article Details

How to Cite
Abubakar, U., Falade, A. A., & Ibrahim, H. A. (2024). Redefining student assessment in Nigerian tertiary institutions: The impact of AI technologies on academic performance and developing countermeasures. Advances in Mobile Learning Educational Research, 4(2), 1149-1159. https://doi.org/10.25082/AMLER.2024.02.009

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