A Systematic Review of Generative AI in Education

Nzenwata U. J.¹, Barn-Nzekwe C. L.^1, , Ojelabi E. O¹, Oduware O.¹, Atalor. P. E.¹, Yisau Y.¹, Adeyela A. T.¹, Nwanguma E. C.¹, Emokiniovo E.¹ and Osisanya O. A¹

¹Computer Science Department, School of Computing and Engineering Sciences, Babcock University, Ilisan Remo, Ogun state, Nigeria

Cite this paper:
Nzenwata U. J., Barn-Nzekwe C. L., Ojelabi E. O, Oduware O., Atalor. P. E., Yisau Y., Adeyela A. T., Nwanguma E. C., Emokiniovo E. and Osisanya O. A. A Systematic Review of Generative AI in Education. Journal of Computer Sciences and Applications. 2024; 12(1):25-30. doi: 10.12691/jcsa-12-1-4

Abstract

The integration of Generative Artificial Intelligence (AI) in education presents a transformative frontier, shaping teaching, learning, and research practices in higher education institutions. This systematic review explores recent studies on the application of Generative AI in education, examining its benefits, challenges, and implications. Through an analysis of literature from prominent databases, key themes emerge surrounding Generative AI's multifaceted applications. These include personalized learning, academic integrity policy development, multimodal writing enhancement, and research innovation. While Generative AI offers promising benefits such as enhanced teaching methodologies, accessibility, and efficiency, challenges persist regarding academic integrity, algorithmic bias, and equitable distribution of resources. Additionally, the review identifies areas lacking sufficient exploration within education research, emphasizing the need for interdisciplinary collaboration, ethical guidelines, and innovative pedagogical approaches to harness Generative AI's transformative potential responsibly.

Keywords:
Artificial Intelligence (AI) Generative artificial intelligence (GAI) Education systematic review

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