Sustainable artificial intelligence-driven classroom assessment in higher institutions: Lessons from Estonia, China, the USA, and Australia for Nigeria
Usani Joseph Ofem 1 * , Ginika Chukwujama 2
More Detail
1 Alex Ekwueme Federal University, Ikwo, Ebonyi State, NIGERIA2 University of Calabar, Calabar, Cross River State, NIGERIA* Corresponding Author

Abstract

The advent of artificial intelligence (AI) in higher education presents unprecedented opportunities for enhancing teaching methodologies, assessment systems, and administrative efficiencies. As Nigerian higher education institutions consider integrating AI-driven assessments, this study explores the potential benefits, challenges, and strategic approaches necessary for successful implementation. Drawing from global case studies in Estonia, China, the USA, and Australia, we analyze how AI has been employed to personalize learning, streamline assessment processes, and enhance educational outcomes. The findings highlight not only the transformative potential of AI in education but also the significant challenges related to fairness, privacy, and security. The study proposes a comprehensive framework involving policy reform, infrastructure development, multi-stakeholder collaboration, and ethical considerations. By adopting these strategies, Nigerian higher education institutions can harness the benefits of AI to foster an inclusive, efficient, and innovative educational environment. This study offers insights into how AI can be strategically implemented to enhance educational systems in Nigeria, ensuring that they are sustainable, equitable, and aligned with global technological advancements.

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EUR J INTERACT MULTIMED ED, Volume 5, Issue 2, July 2024, Article No: e02403

https://doi.org/10.30935/ejimed/15265

Publication date: 03 Oct 2024

Article Views: 4139

Article Downloads: 1983

Open Access References How to cite this article