Evaluating E-learning systems success: An empirical study. Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. Computers in Human Behavior, 102:67–86, January, 2020. ![Evaluating E-learning systems success: An empirical study [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex E-learning, as a direct result of the integration of technology and education, has emerged as a powerful medium of learning particularly using Internet technologies. The undeniable significance of e-learning in education has led to a massive growth in the number of e-learning courses and systems offering different types of services. Thus, evaluation of e-learning -systems is vital to ensure successful delivery, effective use, and positive impacts on learners. Based on an intensive review of the literature, a comprehensive model has been developed which provides a holistic picture and identifies different levels of success related to a broad range of success determinants. The model has been empirically validated by fitting the model to data collected from 563 students engaged with an e-learning system in one of the UK universities through a quantitative method of Partial Least Squares - Structural Equation Modelling (PLS-SEM). The determinants of e-learning perceived satisfaction are technical system quality, information quality, service quality, support system quality, learner quality, instructor quality, and perceived usefulness, which together explain 71.4% of the variance of perceived satisfaction. The drivers of perceived usefulness are technical system quality, information quality, support system quality, learner quality, and instructor quality, and these explain 54.2% of the variance of perceived usefulness. Four constructs were found to be the determinants of e-learning use, namely educational system quality, support system quality, learner quality, and perceived usefulness, and together they account for 34.1%. Finally, 64.7% of the variance of e-learning benefits was explained by perceived usefulness, perceived satisfaction, and use.
@article{al-fraihat_evaluating_2020,
title = {Evaluating {E}-learning systems success: {An} empirical study},
volume = {102},
issn = {0747-5632},
shorttitle = {Evaluating {E}-learning systems success},
url = {https://www.sciencedirect.com/science/article/pii/S0747563219302912},
doi = {10.1016/j.chb.2019.08.004},
abstract = {E-learning, as a direct result of the integration of technology and education, has emerged as a powerful medium of learning particularly using Internet technologies. The undeniable significance of e-learning in education has led to a massive growth in the number of e-learning courses and systems offering different types of services. Thus, evaluation of e-learning -systems is vital to ensure successful delivery, effective use, and positive impacts on learners. Based on an intensive review of the literature, a comprehensive model has been developed which provides a holistic picture and identifies different levels of success related to a broad range of success determinants. The model has been empirically validated by fitting the model to data collected from 563 students engaged with an e-learning system in one of the UK universities through a quantitative method of Partial Least Squares - Structural Equation Modelling (PLS-SEM). The determinants of e-learning perceived satisfaction are technical system quality, information quality, service quality, support system quality, learner quality, instructor quality, and perceived usefulness, which together explain 71.4\% of the variance of perceived satisfaction. The drivers of perceived usefulness are technical system quality, information quality, support system quality, learner quality, and instructor quality, and these explain 54.2\% of the variance of perceived usefulness. Four constructs were found to be the determinants of e-learning use, namely educational system quality, support system quality, learner quality, and perceived usefulness, and together they account for 34.1\%. Finally, 64.7\% of the variance of e-learning benefits was explained by perceived usefulness, perceived satisfaction, and use.},
language = {en},
urldate = {2021-02-20},
journal = {Computers in Human Behavior},
author = {Al-Fraihat, Dimah and Joy, Mike and Masa'deh, Ra'ed and Sinclair, Jane},
month = jan,
year = {2020},
keywords = {DeLone and McLean information systems success model, E-Learning, E-learning evaluation, E-learning satisfaction, E-learning success, TAM},
pages = {67--86},
}
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