Extended Technology Acceptance Model for Enhanced Distribution Strategies to Online Learning: Application of Phantom Approach
Purpose: This study is aimed to introduce the application of phantom approach with structural equation modelling method for online learning. By integrating these innovative methodologies, the research seeks to advance the understanding of how the phantom approach can effectively complement and augme...
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Veröffentlicht in: | Journal of distribution science 2024, Vol.22 (4), p.1-10 |
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Format: | Artikel |
Sprache: | kor |
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Zusammenfassung: | Purpose: This study is aimed to introduce the application of phantom approach with structural equation modelling method for online learning. By integrating these innovative methodologies, the research seeks to advance the understanding of how the phantom approach can effectively complement and augment structural equation modeling techniques. Research design, data and methodology: A theoretical framework of Technology Acceptance Model (TAM) was modified and updated. A questionnaire was developed and used to extract information from 189 instructors who used online learning as their primary medium. The Covariance Based Structural Equation Modelling (CBSEM) was applied to test the direct effects and the phantom approach is used to handle the 2 mediators in the model. Results:social influence, perceived usefulness, and perceived ease of use exerted discernible impacts on instructors' intentionsto engage in online learning. These findings illuminate the intricate dynamics influencing instructor behavior within the realm of online education, underscoring the significance of various factors in shaping their intentions. Conclusions: In additions, the perceived usefulness and perceived ease of use had mediated the effect of social influence and instructor intention using phantom approach. Therefore, one can have concluded that this modified model was also confirmed, thereby reinforcing distribution strategies to online learning and overall education presence. |
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ISSN: | 1738-3110 2093-7717 |