Artificial Intelligence is one of the most researched areas of interest in recent years. A significant amount of research has been scoped toward the use of artificial intelligence in education (AIEd). In this research paper, much of the emphasis will be focused on artificial intelligence from a higher education perspective. The research in this area would conduct a thorough systematic review of the Web of Science (WoS) database and deeply analyze it to extract useful and relevant information, using text analysis and text mining software like Cite Space and Vos Viewer. By performing document co-citation analysis, a research pattern was identified that closely correlated with AI applications. The findings derived from this research paved the way to perform a thorough systematic review of AI applications in higher education using the Google Scholar database. It also gave me an opportunity to analyze relevant literature using Vos Viewer to extract useful and relevant information. The conclusion sheds light on the current research status of AI in higher education as well as AI applications in higher education. Furthermore, this paper has helped us to uncover potential research areas that can be used as a baseline to perform further research and derive state-of-art AI applications used in higher education.
Gayathri Sivasubramanian, University of North Florida, United States