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Factors affecting digital education during COVID-19: A statistical modeling approach
Proceedings of the 2020 5th International Conference on Computing, Communication and Security ; 2020.
Article in English | Web of Science | ID: covidwho-1271166
ABSTRACT
Worldwide governments have decided to temporarily closures of educational institutions in an attempt to minimize the spread of the COVID-19 Pandemic, which has forged significant challenges for the education community. The present study is from the digital education scenario during the COVID-19 lockdown to find out the factors affecting online learning. This study is exploratory from 1218 students who have been collected based on a structured questionnaire having a 5-point linear scale. Jamovl software has been used for data analysis and results demonstrate that there are three major factors like affordability, infrastructural, and training that affect online learning during the COVID-19. Besides, correlation analysis between these factors highlights the relationship among them. Linear regression has applied to know the impact of affordability and infrastructure on the training factor. Outcomes suggested that infrastructure has a negative impact but affordability has a positive impact on the training factor. In the present scenario, this study highlighted the importance of social distancing and digital education tools that should he adopted by schools and colleges.
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Collection: Databases of international organizations Database: Web of Science Language: English Journal: Proceedings of the 2020 5th International Conference on Computing, Communication and Security Year: 2020 Document Type: Article

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Collection: Databases of international organizations Database: Web of Science Language: English Journal: Proceedings of the 2020 5th International Conference on Computing, Communication and Security Year: 2020 Document Type: Article