Determinants of perceived e-learning usefulness in higher education: A case of Thailand
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DOIhttp://dx.doi.org/10.21511/im.18(4).2022.08
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Article InfoVolume 18 2022, Issue #4, pp. 86-96
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Perceived e-learning usefulness as a marketing element has significantly affected student satisfaction, which results in a high propensity to continue using the current e-learning services with their universities. Therefore, this study aims to examine the effects of perceived risk, confirmation, and student motivation on perceived e-learning usefulness. This paper employed a convenience sampling technique to collect opinions from 689 university students at different universities (e.g., Thaksin University, Hatyai University, Prince of Songkla University, and Rajabhat University) around Thailand. Those students were actively using e-learning to access their education. After checking data validity, only 527 valid responses were analyzed through the path analysis method. According to empirical findings, confirmation significantly influenced student motivation, while perceived risk did not significantly impact student motivation. Finally, perceived e-learning usefulness was significantly influenced by confirmation, student motivation, and perceived risk. Furthermore, although these factors significantly influenced perceived e-learning usefulness, attitudes toward perceived e-learning usefulness relied mainly on the degree of confirmation, as this factor highlighted the most substantial effect on perceived e-learning usefulness. Moreover, perceived e-learning usefulness as a marketing element is a promising topic in the e-learning service sector, which requires future studies to examine to which extent the current study findings could apply to other groups of students or practitioners.
- Keywords
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JEL Classification (Paper profile tab)I23, M30, M31
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References49
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Tables4
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Figures2
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- Figure 1. Conceptual framework
- Figure 2. Path analysis findings
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- Table 1. Reliability and convergent validity
- Table 2. Discriminant validity
- Table 3. Model fitness of path analysis
- Table 4. Findings and hypotheses testing
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