Measurement factors model for e-learning systems success

Hagos, Yonas; Garfield, Monica J.; Anteneh, Salehu

doi:10.1109/rcis.2016.7549361

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…Similarly, in the context of e-learning, the relationship between SRQ and satisfaction was found significant in the Roca et al (2006) and Ozkan and Koseler (2009) models. The relationship between SRQ and perceived usefulness proposed in the conceptual model developed by Hagos et al (2016) and Lwoga (2014) was shown empirically to be significant in the study conducted by Al-Sabawy (2014) and Ngai et al (2007). Accordingly, the following hypotheses are proposed: H3a: Service Quality positively influences the perceived satisfaction with the e-learning system; H3b: Service Quality positively influences the perceived usefulness of the e-learning system; H3c: Service Quality positively influences the use of the e-learning system.…”

Section: Service Quality (Srq)mentioning

confidence: 99%

Evaluating E-learning systems success: An empirical study

Al-Fraihat

Joy

Masa’deh

et al. 2020

Computers in Human Behavior

815

599

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Section: Service Quality (Srq)mentioning

confidence: 99%

Evaluating E-learning systems success: An empirical study

Al-Fraihat

Joy

Masa’deh

et al. 2020

Computers in Human Behavior

815

599

View full text Add to dashboard Cite

show abstract

“…In addition to the long-term educational purpose of adopting an e-learning system (Poulova and Simonova, 2014 ; Xu et al, 2014 ), in this investigation, SEQ is anticipated to have a favorable impact on both person satisfaction and intention to utilize it. The investigation demonstrated the empirical importance of the relationship between SEQ and PU stated in the conceptual model of Hagos et al ( 2016 ). As a result, the following hypotheses emerged from this study.…”

Section: Research Model and Hypotheses Developmentmentioning

confidence: 62%

Investigating Students' Perceptions of Online Learning Use as a Digital Tool for Educational Sustainability During the COVID-19 Pandemic

et al. 2022

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Previous research on e-learning in underdeveloped countries has seldom taken a comprehensive approach. A literature review of recent published research in the field of e-learning use during the COVID-19 epidemic is also included in this study. Therefore, the aim of this study is to look at the technology acceptance model (TAM) and information systems (IS) performance models to see how system quality (SYQ), service quality (SEQ), and quality of life (QoL) are related, as well as the mediating impact of perceived ease of use (PEU) and perceived usefulness (PU), affect students' behavioral intention to use (BIU), and actual use of an e-learning system (AUE) as sustainability for education during the COVID-19 pandemic. Path analysis and structural equation modeling (SEM) were used to evaluate the research model, using the data from e-learning users obtained through a survey. Participants were e-learning users from two Saudi Arabian public universities. The findings revealed that PU and ease of use were positively correlated and influenced by SYQ, SEQ, and QoL in education, and that PEU and PU were positively influenced by students' BIU and AUE system. In the sense of e-learning in developing countries, previous studies rarely looked at an integrated model. This paper also attempts to provide a recently published study in the area of the use of an e-learning system as sustainability for education during the COVID-19 pandemic. There is a lot of ongoing research.

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“…However, studies have shown that the most popular way of delivering teaching and learning practices in Ethiopia is the face-to-face method. Ketema & Nirmala (2015) and Hagos et al (2016)have listed Ethiopian universities that have adopted Moodle as their learning management system to enhance their teaching and learning practices. However, the integration of this system to support teachinglearning practice within HEI faces numerous challenges.…”

Section: Related Workmentioning

confidence: 99%

Factors predicting knowledge sharing behavior of academic staff

Gebreyohans,

T. Croasdell,

Meshesha

2023

SEJS

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The main objective of this paper is to identify the factors that influence academic staff's knowledge-sharing intentions and behaviors in Ethiopian higher education. A structural equation model was used to validate the research framework using survey data from 256 respondents. The collected data has been analyzed using Smart PLS software. The result indicates that the factors that affect knowledge-sharing intention include social interaction, reciprocity, management support, reward systems, and reputation. Systems integrated into teaching-learning practice, availability of information technology infrastructure, perceived ease of use, and perceived usefulness are among the technological factors affecting the intention to use web technology for knowledge sharing toward knowledge-sharing behavior. It has also been concluded that management support had the greatest influence, but the reward system did not affect the knowledge-sharing intention. On the other hand, the availability of IT infrastructure has the largest effect on the intention to use web technology, while perceived ease of use has the least. The contributions of this study are twofold. The framework may serve as a roadmap for future researchers and managers considering their strategy to enhance knowledge sharing in HEI. The findings will benefit academic staff, university administrations, and higher education institutions. This study gives managers a solid foundation to promote and support academic staff's usage of web technology for knowledge sharing. The study will also help academic staff enhance their current knowledge-sharing practices.

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Measurement factors model for e-learning systems success

Cited by 9 publications

References 23 publications

Evaluating E-learning systems success: An empirical study

Evaluating E-learning systems success: An empirical study

Investigating Students' Perceptions of Online Learning Use as a Digital Tool for Educational Sustainability During the COVID-19 Pandemic

Factors predicting knowledge sharing behavior of academic staff

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