@ARTICLE{26543116_623228600_2022, 
	author = {Joanna Ejdys}, 
	keywords = {, e-learning, consumer satisfaction, future intension to use, computer self-efficacyuniversity students},
	title = {Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level},
	journal = {Foresight and STI Governance},
	year = {2022},
	volume = {16},
	number = {2},
	pages = {52-64},
	url = {https://foresight-journal.hse.ru/en/2022-16-2/623228600.html},
	publisher = {},
	abstract = {With the growing interest in e-education, particularly in the context of the pandemic, more scientific studies have been undertaken recently to analyze and identify factors influencing e-learning acceptance. Indeed, e-learning acceptance depends on many different factors, but no consensus has been reached on factors that contribute most to the acceptance of e-learning solutions. Consequently, this article ascertains the factors and their relationships behind the satisfaction and the future intention to use e-learning among Polish university students. From among the factors analyzed in the literature, the author examined the relationship between computer self-efficacy (CSE), facilitating conditions (FC), satisfaction (S) and the future intention to use e-learning (FI). Data were gathered using structured questionnaires and computer-assisted web interviewing (CAWI). Students at Bialystok University of Technology (Poland) were sent an electronic link to the questionnaires using the internal e-mail system. Eight hundred three forms were returned fully filled out. Aiming to ascertain the extent to which measured variables describe the number of constructs, the author made the Confirmatory Factor Analysis (CFA). The Generalized Least Squares (GLS) estimator was used to calculate the values of model parameters.The results confirmed that higher computer self-efficacy and better facilitation conditions result in greater user satisfaction with e-learning. However, facilitating conditions impact user satisfaction more than computer self-efficacy construct variables. Based on the findings, user satisfaction is a strong anticedents of the future intention to use e-learning.},
	annote = {With the growing interest in e-education, particularly in the context of the pandemic, more scientific studies have been undertaken recently to analyze and identify factors influencing e-learning acceptance. Indeed, e-learning acceptance depends on many different factors, but no consensus has been reached on factors that contribute most to the acceptance of e-learning solutions. Consequently, this article ascertains the factors and their relationships behind the satisfaction and the future intention to use e-learning among Polish university students. From among the factors analyzed in the literature, the author examined the relationship between computer self-efficacy (CSE), facilitating conditions (FC), satisfaction (S) and the future intention to use e-learning (FI). Data were gathered using structured questionnaires and computer-assisted web interviewing (CAWI). Students at Bialystok University of Technology (Poland) were sent an electronic link to the questionnaires using the internal e-mail system. Eight hundred three forms were returned fully filled out. Aiming to ascertain the extent to which measured variables describe the number of constructs, the author made the Confirmatory Factor Analysis (CFA). The Generalized Least Squares (GLS) estimator was used to calculate the values of model parameters.The results confirmed that higher computer self-efficacy and better facilitation conditions result in greater user satisfaction with e-learning. However, facilitating conditions impact user satisfaction more than computer self-efficacy construct variables. Based on the findings, user satisfaction is a strong anticedents of the future intention to use e-learning.}
}