Abstract
Artificial Intelligence (AI) has brought unprecedented growth and productivity to every socioeconomic sector. The application of AI in education is transformational, encompassing the reduction of teacher workload, individualized learning, intelligent tutoring, profiling and prediction, high-precision education, collaboration, and learner tracking. This paper highlights the directions of AI research in higher education (HE) through bibliometric analysis. We adhered to the PRISMA guidelines to select 1610 articles published in the Scopus database between 2014 and 2023. VOSviewer was employed for visualization, and text mining was utilized to identify hotspots in the field. Spain, the United States, the United Kingdom, China, and India dominate the publications. Articles on this topic are predominantly published in conference proceedings and journals. Four themes emerge: data as a catalyst, AI development, AI implementation in higher education, emerging trends, and the future of AI in higher education. This research contributes to the literature by synthesizing opportunities for AI adoption in higher education, topic modeling, and future research areas.
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