A Study of Technologies Used in Learning Management Systems and Evaluation of New Trend Algorithms

Abstract

Distance education is a completely different way of learning, separated from traditional face-to-face education, independent of time and place. The journey of distance education that started with communication tools such as letters, radio, and television continues to evolve based on the use of web-based technologies such as social media and learning management systems (LMSs), depending on the developments in technology today. In this study, a review has been carried out to outline the technologies used in LMS, first. In particular, the developments of the widely used advanced algorithms and LMSs have been taken into consideration in the study by examining web based technologies and standards. Then, an investigation on new trends algorithms in this field has been performed. In this scope, five supervised (linear regression, logistic regression, 𝑘�-nearest neighbors, decision tree and Naïve Bayes), two unsupervised (Apriori and principal component analysis) and lastly one ensemble learning algorithm (Adaptive Boosting) have been examined. Consequently, the new algorithms have been proposed to be used in LMSs for different purposes, such as analyzing of users' hidden behaviors, performance prediction, producing automatic recommendations as well.