The Future of Distance Education: Exploring the Potential of Adaptive Learning Systems

Adaptive learning technologies are used in many areas of education, including online distance learning. This study investigates the applications of Adaptive Learning technology in distance education environments. Following the steps of systematic literature review and using bibliometric analysis, the study examines a total of 1071 publications. Accordingly, time trend analysis has increased steadily within recent years, and Educational Research, Computer Science, and Engineering are the leading subject areas in research on Adaptive Learning in distance education. China and USA are the countries that make the most of the contribution, followed by Taiwan, Spain, and India. Kinshuk is the author who contributed the most, followed by Caballé and Santi. The most collaborative authors are Capuano and Nicola, Ritrovato and Pierluigi, Cabelle and Santi, and Gaeta and Matteo. Pierri and Anna hold central positions in the co-authoring network. The top three journals with the most publications are Computers & Education, International Journal of Distance Education, and Academic Medicine, all with significant citation counts. The most frequently used keywords are “e-learning”, followed by “adaptive learning”, and “online learning”. Integrating artificial intelligence and machine learning techniques presents significant potential for enhancing adaptive learning technologies. Utilizing frameworks such as learning analytics and the Technology Acceptance Model can help identify effective strategies to increase system acceptability.