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E-Learning Satisfaction Analysis of the Support Factors

E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and...

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Main Authors: Siswanto, Boby, Alamsyah, Doni Purnama, Morika, Doni, Othman, Norfaridatul Akmaliah, Wijaya, Billiam Christofer, Adinda, Putri Giyan
Format: Conference or Workshop Item
Language:English
Published: 2023
Online Access:http://eprints.utem.edu.my/id/eprint/28050/1/E-Learning%20Satisfaction%20Analysis%20of%20the%20Support.pdf
http://eprints.utem.edu.my/id/eprint/28050/
https://ieeexplore.ieee.org/document/10276458
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spelling my.utem.eprints.280502024-10-17T12:26:36Z http://eprints.utem.edu.my/id/eprint/28050/ E-Learning Satisfaction Analysis of the Support Factors Siswanto, Boby Alamsyah, Doni Purnama Morika, Doni Othman, Norfaridatul Akmaliah Wijaya, Billiam Christofer Adinda, Putri Giyan E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and the factors that can increase student e-learning satisfaction. This study uses a quantitative survey method with a questionnaire as a data collection tool. The research respondents were randomly selected e-learning students from several educational institutions that use Big Data technology in their e-learning platforms. There are 663 data collected through online questionnaires, then the data is processed through SmartPLS to test the research hypothesis. The results of the study show that the use of Big Data technology in an e-learning environment has a positive impact on student satisfaction. Several factors determine e-learning satisfaction including usability requirements, quality level, learning competence, and material relatedness. Relatedness to e-learning is more important in increasing student motivation in learning, as can be seen from the correlation value which is more dominant in forming student satisfaction. The e-learning platform must have navigation that is easy for users to understand and use. Learning content must be well-designed and follow established learning standards. The use of Big Data technology in e-learning can have a significant impact on student satisfaction and the quality of learning. Future research can develop a more personal and adaptive e- learning platform, using Big Data technology as the basis for its development. 2023 Conference or Workshop Item PeerReviewed text en http://eprints.utem.edu.my/id/eprint/28050/1/E-Learning%20Satisfaction%20Analysis%20of%20the%20Support.pdf Siswanto, Boby and Alamsyah, Doni Purnama and Morika, Doni and Othman, Norfaridatul Akmaliah and Wijaya, Billiam Christofer and Adinda, Putri Giyan (2023) E-Learning Satisfaction Analysis of the Support Factors. In: 10th International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2023, 31 August 2023 through 1 September 2023, Virtual, Online. https://ieeexplore.ieee.org/document/10276458
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and the factors that can increase student e-learning satisfaction. This study uses a quantitative survey method with a questionnaire as a data collection tool. The research respondents were randomly selected e-learning students from several educational institutions that use Big Data technology in their e-learning platforms. There are 663 data collected through online questionnaires, then the data is processed through SmartPLS to test the research hypothesis. The results of the study show that the use of Big Data technology in an e-learning environment has a positive impact on student satisfaction. Several factors determine e-learning satisfaction including usability requirements, quality level, learning competence, and material relatedness. Relatedness to e-learning is more important in increasing student motivation in learning, as can be seen from the correlation value which is more dominant in forming student satisfaction. The e-learning platform must have navigation that is easy for users to understand and use. Learning content must be well-designed and follow established learning standards. The use of Big Data technology in e-learning can have a significant impact on student satisfaction and the quality of learning. Future research can develop a more personal and adaptive e- learning platform, using Big Data technology as the basis for its development.
format Conference or Workshop Item
author Siswanto, Boby
Alamsyah, Doni Purnama
Morika, Doni
Othman, Norfaridatul Akmaliah
Wijaya, Billiam Christofer
Adinda, Putri Giyan
spellingShingle Siswanto, Boby
Alamsyah, Doni Purnama
Morika, Doni
Othman, Norfaridatul Akmaliah
Wijaya, Billiam Christofer
Adinda, Putri Giyan
E-Learning Satisfaction Analysis of the Support Factors
author_facet Siswanto, Boby
Alamsyah, Doni Purnama
Morika, Doni
Othman, Norfaridatul Akmaliah
Wijaya, Billiam Christofer
Adinda, Putri Giyan
author_sort Siswanto, Boby
title E-Learning Satisfaction Analysis of the Support Factors
title_short E-Learning Satisfaction Analysis of the Support Factors
title_full E-Learning Satisfaction Analysis of the Support Factors
title_fullStr E-Learning Satisfaction Analysis of the Support Factors
title_full_unstemmed E-Learning Satisfaction Analysis of the Support Factors
title_sort e-learning satisfaction analysis of the support factors
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/28050/1/E-Learning%20Satisfaction%20Analysis%20of%20the%20Support.pdf
http://eprints.utem.edu.my/id/eprint/28050/
https://ieeexplore.ieee.org/document/10276458
_version_ 1814061453998555136
score 13.211869

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