Generative artificial intelligence in higher education learning: A review based on academic databases

Abstract

Objective. The rapid integration of Generative Artificial Intelligence (AI), especially tools like ChatGPT, into educational sectors has spurred significant academic interest. This review article provides a systematic examination of the current scholarly landscape concerning the use of ChatGPT within higher education. Design/Methodology/Approach. Drawing from a range of academic databases between 2022 and 2024, we meticulously adhere to PRISMA guidelines, evaluating a final set of 28 out of 1740 initial articles based on predetermined inclusion and exclusion criteria. Results/Discussion. Our analysis reveals diverse global contributions predominantly from Asia and identifies a prevalent quantitative research approach among the studies. We delve into the selected articles' geographical distribution, methodologies, and thematic outcomes, highlighting a notable lack of research from Latin America. The review critically assesses the validity, utility, and time optimization aspects of ChatGPT in educational settings, uncovering a positive impact on student learning and time management. However, we pinpoint a significant gap in rigorous experimental research, underscoring the need for studies with random sampling and controlled settings to enhance the external validity of findings. Additionally, we call attention to the ethical considerations and the necessity for higher education institutions to adapt teaching methodologies to incorporate AI effectively. Conclusion. The article concludes with recommendations for future research to address the identified gaps and optimize the educational use of generative AI technologies like ChatGPT.

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