Understanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog

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dc.contributor.authorS. Chayanukro
dc.contributor.authorM. Mahmuddin
dc.contributor.authorH. Husni
dc.contributor.correspondenceS. Chayanukro; Suan Dusit Rajabhat University, Mueang Trang, Trang, 92130, Thailand; email: songsakda@gmail.com
dc.date.accessioned2025-03-10T07:35:29Z
dc.date.available2025-03-10T07:35:29Z
dc.date.issued2021
dc.description.abstractIn 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.
dc.identifier.citationJournal of Physics: Conference Series
dc.identifier.doi10.1088/1742-6596/1869/1/012087
dc.identifier.issn17426588
dc.identifier.scopus2-s2.0-85104781681
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/4712
dc.languageEnglish
dc.publisherIOP Publishing Ltd
dc.rightsAll Open Access; Gold Open Access
dc.rights.holderScopus
dc.titleUnderstanding and assembling user behaviours using features of Moodle data for eLearning usage from performance of course-student weblog
dc.typeConference paper
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85104781681&doi=10.1088%2f1742-6596%2f1869%2f1%2f012087&partnerID=40&md5=68b7e0601f134e55310da107abae8865
oaire.citation.issue1
oaire.citation.volume1869
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