Fifteen Years of Recommender Systems Research in Higher Education: Current Trends and Future Direction

Abstract

Artificial intelligence applications have revolutionized business, industry, and education. Applications developed for other sectors are being adapted for education. The amount of data being generated by educational institutions is used to make recommendations for a wide range of areas. The study uses bibliometric analysis to evaluate the development and growth of recommender systems in higher education. Two hundred seventy-two (272) articles published between 2007 and 2021 in the Scopus database were utilized to collect data. The study examines the different patterns such as publication trends, the relative growth rate (RGR) and doubling time (DT) for publications. Results show a steady increase in publications, with 2017 recording the highest number of publications. China, Spain and the United States have the highest publications. The mean RGR decreased, and the mean doubling time increased in the three-five-year periods. The study identified sixteen themes covered by the research articles analyzed. Most articles focused on e-learning, followed by classroom activities and, thirdly, those focusing on course selection. The study provides essential insights into current and future research on recommender systems in higher education. This analysis helps researchers, policymakers, and practitioners better understand the development of recommender systems in higher education and possible practice implications.