Understanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog
Date
2021
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Conference paper
Publisher
IOP Publishing Ltd
Journal Title
Understanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog
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Abstract
In reality, students learn via eLearning (electronic online learning) system in different ways depending on their learning needs, learning behaviours as well as eLearning system policy for users. However, most learning outcome prediction models of eLearning systems are still not stable and still cannot be applied in many situations as the use of eLearning is considered to be highly dynamic. Therefore, the objective of this work is understand if eLearning system can be predicted based eLearning usage by exploiting Moodle log data. To understand it, features from web log course-student in Moodle is being considered, a number of machine learning techniques also have been applied for benchmarking in this study. The result found that the current group doesn't give better understanding and significant groups of factors that could be able to predict the learning outcome. © Published under licence by IOP Publishing Ltd.
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Journal of Physics: Conference Series