Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level

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...

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Main Author: Joanna Ejdys
Format: Article
Language:English
Published: National Research University Higher School of Economics 2022-06-01
Series:Foresight and STI Governance
Subjects:
Online Access:https://foresight-journal.hse.ru/article/view/19242
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author Joanna Ejdys
author_facet Joanna Ejdys
author_sort Joanna Ejdys
collection DOAJ
description 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.
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spelling doaj-art-70bcbed53b31420e87509ae49f37c4552025-08-20T02:08:43ZengNational Research University Higher School of EconomicsForesight and STI Governance2500-25972022-06-0116210.17323/2500-2597.2022.2.52.64Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University LevelJoanna Ejdys0Bialystok University of Technology, 45A, Wiejska Street, 15-351 Bialystok, Poland 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. https://foresight-journal.hse.ru/article/view/19242e-learningconsumer satisfactionfuture intension to usecomputer self-efficacyuniversity students
spellingShingle Joanna Ejdys
Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level
Foresight and STI Governance
e-learning
consumer satisfaction
future intension to use
computer self-efficacy
university students
title Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level
title_full Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level
title_fullStr Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level
title_full_unstemmed Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level
title_short Factors Influencing Satisfaction and Future Intention to Use E-Learning at the University Level
title_sort factors influencing satisfaction and future intention to use e learning at the university level
topic e-learning
consumer satisfaction
future intension to use
computer self-efficacy
university students
url https://foresight-journal.hse.ru/article/view/19242
work_keys_str_mv AT joannaejdys factorsinfluencingsatisfactionandfutureintentiontouseelearningattheuniversitylevel