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SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010636/ https://www.ncbi.nlm.nih.gov/pubmed/35434400 http://dx.doi.org/10.1016/j.heliyon.2022.e09236 |
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author | Elareshi, Mokhtar Habes, Mohammed Youssef, Enaam Salloum, Said A. Alfaisal, Raghad Ziani, Abdulkarim |
author_facet | Elareshi, Mokhtar Habes, Mohammed Youssef, Enaam Salloum, Said A. Alfaisal, Raghad Ziani, Abdulkarim |
author_sort | Elareshi, Mokhtar |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9010636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90106362022-04-16 SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid Elareshi, Mokhtar Habes, Mohammed Youssef, Enaam Salloum, Said A. Alfaisal, Raghad Ziani, Abdulkarim Heliyon Research Article 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. Elsevier 2022-04-04 /pmc/articles/PMC9010636/ /pubmed/35434400 http://dx.doi.org/10.1016/j.heliyon.2022.e09236 Text en © 2022 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Elareshi, Mokhtar Habes, Mohammed Youssef, Enaam Salloum, Said A. Alfaisal, Raghad Ziani, Abdulkarim SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid |
title | SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid |
title_full | SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid |
title_fullStr | SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid |
title_full_unstemmed | SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid |
title_short | SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid |
title_sort | sem-ann-based approach to understanding students’ academic-performance adoption of youtube for learning during covid |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010636/ https://www.ncbi.nlm.nih.gov/pubmed/35434400 http://dx.doi.org/10.1016/j.heliyon.2022.e09236 |
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