Quantitative and Qualitative Research on the Use of Artificial Intelligence in Higher Education: A Systematic Literature Review

Abstract

The development of artificial intelligence has demonstrated remarkable progress over the past five years, particularly with the emergence of generative artificial intelligence. Higher education is one of the sectors that has intensively implemented this cutting-edge technology in learning process, research, and other educational functions, particularly in the acquisition and dissemination of information and knowledge. This study aims to explore the opportunities and challenges in the implementation of artificial intelligence in higher education based on research findings, with the subjects of the study comprising lecturers, university students, or university personnels. A systematic review was conducted on 30 selected open-access articles published between 2020 and 2025, consisting of 12 qualitative studies, 14 quantitative studies, and 4 mixed-method studies. The review results revealed various factors influencing the successful implementation of artificial intelligence based on user perceptions. The findings of this review can serve as best practices or lessons learned in formulating strategies for integrating artificial intelligence into educational governance and processes in a manner that aligns with the fundamental objectives of education. Future research may further develop qualitative, quantitative, or mixed-method approaches, particularly multi-disciplinary studies that integrate learning theories or models with technological, human, social, institutional, and environmental factors.

Keywords: Artificial Intelligence, Generative AI, Quantitative Method, Qualitative Method, Mixed Method

DOI: 10.7176/JEP/16-13-09

Publication date: December 30th 2025