User Satisfaction of E-Learning System Implementation for Training and Development Program in Organization

Disastra, Ganjar Mohamad; Wahyuningtyas, Ratri

doi:10.2991/aebmr.k.200410.038

Cited by 3 publications

(4 citation statements)

References 15 publications

(15 reference statements)

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“…The results of the sixth hypothesis testing reveal that user satisfaction lacks an impact on cloud-based e-learning when mediated by variable behavioral intentions. This suggests that, contrary to the findings of Disastra and Wahyuningtyas (2020), user satisfaction with cloudbased e-learning does not significantly influence the user's intention to continue using such systems [33].…”

contrasting

confidence: 93%

The Influence of Social Influence, Relative Advantage, User Satisfaction on Cloud-Based E-Learning with Behavioral Intention as a Mediating Variable

Muhammad Cevin Yunior,

Yvonne Augustine Sudibijo

2024

TSSJ

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This research investigates the influence of social influence, relative advantage, and user satisfaction on cloud-based e-learning adoption, with behavioral intention acting as a mediating variable. Drawing on existing literature, hypotheses are formulated to explore these relationships. The study integrates models such as DOI, TAM, and UTAUT to propose hypotheses, guided by empirical findings from Lebanon, the Philippines, and Indonesia. The hypotheses posit positive impacts of social influence (H1), relative advantage (H2), and user satisfaction (H3) on cloud-based e-learning adoption. Additionally, the study explores the mediating role of behavioral intention in the relationships between social influence (H4), relative advantage (H5), user satisfaction (H6), and cloud-based e-learning adoption. The operational model is presented, depicting the relationships among variables. The research adopts an explanatory approach, using questionnaires distributed to 143 university students engaging in cloud-based e-learning. Descriptive statistics and validity tests ensure data quality, and hypothesis testing involves Mediated Regression Analysis. Results indicate that relative advantage and user satisfaction positively impact cloud-based e-learning, while social influence's direct impact is inconclusive. Behavioral intention does not mediate the relationships as hypothesized, highlighting the nuanced nature of cloud-based e-learning adoption. The study provides insights into the interplay of factors influencing cloud-based e-learning adoption, contributing to the understanding of technology acceptance in educational contexts.

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contrasting

confidence: 93%

The Influence of Social Influence, Relative Advantage, User Satisfaction on Cloud-Based E-Learning with Behavioral Intention as a Mediating Variable

Muhammad Cevin Yunior,

Yvonne Augustine Sudibijo

2024

TSSJ

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“…It is a critical factor affecting students' use of ELS applications (Disastra and Wahyuningtyas, 2020). Satisfaction is characterized by a person's perception of how responsive the system is to their needs and expectations (Ghazal et al, 2018).…”

Section: User-perceived Satisfaction (Upsat)mentioning

confidence: 99%

“…Students' gratification appears to be a vital feature in the assessment of tutors, tutor courses, and the general quality of university education programs (Teo and Wong, 2013). In the context of ELS services, students are more prospective to practice the service again if they feel satisfied with the services provided (Disastra and Wahyuningtyas, 2020). User gratification is one indicator of the efficient use of an ELS to assist with their activities, such as extracting and publishing information and interacting with others (Seta et al, 2018).…”

Section: User-perceived Satisfaction (Upsat)mentioning

confidence: 99%

Evaluating E-learning system success in higher education during the Covid-19

Özdamlı

Noori

2022

CJES

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Human lives globally have been affected by the COVID-19 pandemic. The quantitative research method was followed to assess e-learning system success from students' perspectives during the pandemic. ISS and USAT model was adopted to measure it, and a survey was used to collect 632 voluntary students. The regression analysis method presented variations between the quality of factors that anticipate user-perceived satisfaction, system use, and individual performance. While the quality factors suggested the impact of the dependent variable was (collaboration, information, service, System, IATE, DIA, LCAx, and LPIWO). In students' opinion, the study found quality factors significantly positively influence the adopted model, except for the QSer and IATE. The study outcome is expected to help academic staff and learners with further research. Keywords: E-learning, distance education, students' opinion, DeL& McL model, USAT model

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“…Research shows that there are essential factors in increasing user satisfaction with technology-based learning models. Although it is true that, in practice, developing the implementation of technology-based learning requires costs and time to implement, Technologybased learning activities encourage someone to use them; therefore, user satisfaction is an essential factor for individuals when using technology (Disastra & Wahyuningtyas, 2020).…”

Section: Introductionmentioning

confidence: 99%

Acceptance of Distance Learning Technology in Technology-Based Learning Management

Rosita,

Fatmasari

2023

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The Technology Acceptance Model (TAM) describes the factors that influence the acceptance and adoption of technology by individuals. In education management, TAM is used to understand how educators, students, and administrative staff respond to the use of technology in the educational process. The application of the Technology Acceptance Model in education management is to help educational institutions plan, implement, and support the use of technology more effectively, taking into account psychological factors and user perceptions. The variables influencing technology acceptance are Perceived Ease of Use, Perceived Usefulness, Attitude Toward Technology, and Intention to Use. This study examines the factors that influence the acceptance of technology by UT postgraduate students toward using information technology in distance learning. The research results are used to develop distance education management, especially in developing internet technology-based learning. The results show that the variables measured have a significant effect on the use of distance learning technology. The Behavioral Intention to Use variable has the most significant influence on Actual Use (AU), followed by the influence of Perceived Ease of Use (PEU) on Attitude Toward Using (ATU) and Perceived Usefulness (PU) on Attitude Toward Using (ATU).Open University, Technology Acceptance Models, Technology Based Learning Management

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User Satisfaction of E-Learning System Implementation for Training and Development Program in Organization

Cited by 3 publications

References 15 publications

The Influence of Social Influence, Relative Advantage, User Satisfaction on Cloud-Based E-Learning with Behavioral Intention as a Mediating Variable

The Influence of Social Influence, Relative Advantage, User Satisfaction on Cloud-Based E-Learning with Behavioral Intention as a Mediating Variable

Evaluating E-learning system success in higher education during the Covid-19

Acceptance of Distance Learning Technology in Technology-Based Learning Management

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