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SEM-ANN-based approach to understanding students' academic-performance adoption of YouTube for learning during Covid.

Elareshi, M; Habes, M; Youssef, E; Salloum, S; Alfaisal, R; Ziani, A

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Authors

M Elareshi

M Habes

E Youssef

S Salloum

R Alfaisal

A Ziani



Abstract

A hybrid analysis of Structural Equation Modeling (SEM) and Artificial Neural Network (ANN), through SmartPLS and SPSS software, as well as the importance-performance map analysis (IPMA) were used to examine the impact of YouTube videos content on Jordanian university students' behavioral intention regarding eLearning acceptance, in Jordan. According to the evaluation of both ANN and IPMA, performance expectancy was the most important and, theoretically, several explanations were provided by the suggested model regarding the impact of intention to adopt eLearning from Internet service determinants at a personal level. The findings coincide greatly with prior research indicating that users' behavioral intention to adopt eLearning is significantly affected by their performance expectancy and effort expectancy. The paper contributed to technology adoption e.g., YouTube in academia, especially in Jordan. Respondents showed a willingness to employ and adopt the new technology in their education. Finally, the findings were presented and discussed through the UTAUT and TAM frameworks.

Citation

Elareshi, M., Habes, M., Youssef, E., Salloum, S., Alfaisal, R., & Ziani, A. (2022). SEM-ANN-based approach to understanding students' academic-performance adoption of YouTube for learning during Covid. Heliyon, 8(4), e09236. https://doi.org/10.1016/j.heliyon.2022.e09236

Journal Article Type Article
Acceptance Date Mar 30, 2022
Online Publication Date Apr 4, 2022
Publication Date Apr 4, 2022
Deposit Date Jul 29, 2022
Publicly Available Date Jul 29, 2022
Journal Heliyon
Print ISSN 2405-8440
Publisher Elsevier
Volume 8
Issue 4
Pages e09236
DOI https://doi.org/10.1016/j.heliyon.2022.e09236
Publisher URL https://doi.org/10.1016/j.heliyon.2022.e09236
Related Public URLs https://europepmc.org/articles/PMC9010636
https://europepmc.org/articles/PMC9010636?pdf=render

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