BibTex Citation Data :
@article{JSINBIS64559, author = {Arya Krizna Nawanda and Johan Jimmy Carter Tambotoh}, title = {Evaluating the Success of Learning Management Systems using the EESS Model and Expected Confirmation Theory}, journal = {Jurnal Sistem Informasi Bisnis}, volume = {14}, number = {4}, year = {2024}, keywords = {E-learning; LMS; EESS; PLS-SEM; ECT}, abstract = { E-learning and LMS (Learning Management Systems) have been implemented in most universities to modernize learning and assist in the learning process of university students. This study aims to explore the factors that can be used to measure e-learning system success using the EESS (Evaluating E-learning System Success) model and Expectation and Confirmation Theory (ECT). A quantitative research method was employed, using questionnaires to collect data on users’ perceptions of LMS. The collected data were then statistically analyzed using the PLS-SEM method with SmartPLS 3.2.9. Results revealed that out of 29 hypotheses, 16 were accepted and 13 were rejected. A novel discovery was that ECT can be implemented in the EESS model. Three hypotheses involving expectation confirmation had p-values of 0.001, 0.000, and 0.000, indicating significant roles. The study concluded that incorporating expectation confirmation quality into the EESS model enhances its effectiveness by providing a comprehensive perspective. }, issn = {2502-2377}, pages = {337--352} doi = {10.21456/vol14iss4pp337-352}, url = {https://ejournal.undip.ac.id/index.php/jsinbis/article/view/64559} }
Refworks Citation Data :
E-learning and LMS (Learning Management Systems) have been implemented in most universities to modernize learning and assist in the learning process of university students. This study aims to explore the factors that can be used to measure e-learning system success using the EESS (Evaluating E-learning System Success) model and Expectation and Confirmation Theory (ECT). A quantitative research method was employed, using questionnaires to collect data on users’ perceptions of LMS. The collected data were then statistically analyzed using the PLS-SEM method with SmartPLS 3.2.9. Results revealed that out of 29 hypotheses, 16 were accepted and 13 were rejected. A novel discovery was that ECT can be implemented in the EESS model. Three hypotheses involving expectation confirmation had p-values of 0.001, 0.000, and 0.000, indicating significant roles. The study concluded that incorporating expectation confirmation quality into the EESS model enhances its effectiveness by providing a comprehensive perspective.
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