Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/15626
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dc.contributor.authorVeguru, Hemanth Sravan Kumar-
dc.contributor.authorNaren, J-
dc.contributor.authorSingam, Yasasree-
dc.date.accessioned2024-05-29T08:51:24Z-
dc.date.available2024-05-29T08:51:24Z-
dc.date.issued2024-
dc.identifier.citationVol. 233; pp. 590-596en_US
dc.identifier.issn1877-0509-
dc.identifier.urihttp://dx.doi.org/10.1016/j.procs.2024.03.248-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/15626-
dc.description.abstractThe paper presents a study of the interest and opinions of students regarding online learning using a machine learning approach, as well as the evolution of different e-learning platforms based on education following the pandemic period. The study uses student data from a questionnaire-based survey of college students to improve the learning environment from the perspective of the students. The survey and questionnaire were designed with students' needs, requirements, and preferred level of quality for online learning. Survey data was subjected to data analysis and classification to gain a deeper understanding of the learner in a virtual learning environment. Through data preparation, analysis, visualization, and machine learning algorithm accuracy, machine learning classification algorithms and analysis are used to examine the collected data. The research study will illustrate the expectations and enhancement of online learning education patterns according to the requirements of students. With a 93% accuracy evaluation, the Random Forest algorithm has the best accuracy among the several classification algorithms. © 2024 The Authors. Published by Elsevier B.V.en_US
dc.language.isoenen_US
dc.publisherProcedia Computer Scienceen_US
dc.publisherElsevier B.V.en_US
dc.subjectClassification Analysisen_US
dc.subjectMachine Learningen_US
dc.subjectOnline Educationen_US
dc.subjectStudent'S Perspectiveen_US
dc.subjectVirtual Learning Environmenten_US
dc.titleStudent'S Interest and Opinion Towards Online Educationen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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