Abstract

TAs learning analytics is getting maturity, higher educational institutions worldwide are becoming more interested in practicing learning analytics. Over the last decade, learning management systems (LMSs) such as Moodle, Canvas, Blackboard, Sakai were the primary sources for interaction data. This paper reviewed LAK, EDM, and ACM proceedings and associate journals to shed light on Sakai LMS's potential as it offers flexible tools for teaching, learning, and dynamic collaboration. In comparison with other LMSs, Sakai was less explored by the learning analytics community. This paper also discusses Sakai-generated data's potential to cope with future research trends in learning analytics where AI would be used to make a broader impact on education. The findings lead to- with the advances of AI in education, Sakai data could leverage in designing new methods and tools for decision making, augment learners' productivity, regulate self-learning and knowledge extraction. Sakai and sophisticated learning systems could show promises in conventional learning research, including at-risk detection, drop-out prediction, student modeling, behavior analysis, and the human learning process.

Keywords: learning analytics, learning management system, Sakai,survey.