A Bibliometric Analysis of Artificial Intelligence Applications in Higher Education Technology

Abstract

This study analyzes Scopus-indexed publications and documents from 2000 to 2023 on AI-HETT. We investigated publishing trends, identified key articles, and analyzed the most active AI-HETT research participants and funding institutions. A bibliometric analysis of coauthorships, keywords, and citations was done in artificial intelligence and higher education research. Scopus yielded 2,736 AI-HET publications. Trend study showed a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{4 2, 4 5 0 \%}$</tex> increase in publications from 2000 to 2023. Most publications are conference papers, 1,430. The Computer Science Lecture Notes, Subseries Lecture Notes in Artificial Intelligence and Bioinformatics, with 116 papers, are the main source. Salas Rueda is the leading higher education AI researcher with nine papers. The National Science Foundation, the largest US funding agency, has contributed to 42 publications and is responsible for creating the nation's active interest in the subject. A keyword co-occurrence analysis highlighted six main study domains with the important tools, concepts, methodologies, and socioeconomic and financial elements of AI in higher education. Artificial intelligence research in higher education will focus on deep learning, machine learning, and neural network methods. The study aims to accurately predict student learning habits.