Understanding the Growth of Artificial Intelligence in Educational Research through Bibliometric Analysis

Abstract

The purpose of this study was to investigate research trends in artificial intelligence studies related to education that were published in the Web of Science database. This review conducted a bibliometric analysis of 4673 articles published between 1975 and 2023 and explored trends in several areas, including the annual distribution of publications, frequently studied topics, top authors, top countries, top universities/departments, top journals and publishers, and top funders. The findings highlighted that the number of studies increased exponentially after 2010. The most often used terms in artificial intelligence research in education were machine learning, deep learning, and data mining. Studies in higher education have been more prevalent than studies in elementary and secondary education. The USA, mainland China, and Australia were the three most productive nations. Most productive authors were connected to academic institutions in Taiwan, Hong Kong, or mainland China. Furthermore, there was little cooperation among the most productive authors andcountries. In addition to the abundance of journals on educational technology, it is crucial to emphasize the dearth of publications on education across different disciplines. To understand how artificial intelligence can support new practices in educational research, interdisciplinary interest and support are needed.