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.
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