An Analysis of the Use of Machine Learning to Enhance Online Digital Learning

Academic institutions’ interest in online learning is rising at an exponential rate due to the rapid advancement of expertise. The Learning Management System (LMS) is a key component of the online learning architecture and is also used to mine student data. This study reviews and analyses the literature on machine learning (ML) in online education and machine learning integrated learning management systems (LMS). The goal of this study is to comprehend the different efforts made to employ different ML techniques to lessen the difficulties associated with online learning environments, or online LMSs. Increasing student performance by projecting future grades is just one of several obstacles. Other issues that can be resolved using machine learning include student retention and behavior analysis for performance enhancement. The paper presents the research that different authors have done in the relevant topic. The chosen time frame for the project remains close to the Covid19 years.