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http://dx.doi.org/10.22937/IJCSNS.2022.22.2.19

Predicting the Saudi Student Perception of Benefits of Online Classes during the Covid-19 Pandemic using Artificial Neural Network Modelling  

Beyari, Hasan (Applied College Umm Al-Qura University)
Publication Information
International Journal of Computer Science & Network Security / v.22, no.2, 2022 , pp. 145-152 More about this Journal
Abstract
One of the impacts of Covid-19 on education systems has been the shift to online education. This shift has changed the way education is consumed and perceived by students. However, the exact nature of student perception about online education is not known. The aim of this study was to understand the perceptions of Saudi higher education students (e.g., post-school students) about online education during the Covid-19 pandemic. Various aspects of online education including benefits, features and cybersecurity were explored. The data collected were analysed using statistical techniques, especially artificial neural networks, to address the research aims. The key findings were that benefits of online education was perceived by students with positive experience or when ensured of safe use of online platforms without the fear cyber security breaches for which recruitment of a cyber security officer was an important predictor. The issue of whether perception of online education as a necessity only for Covid situation or a lasting option beyond the pandemic is a topic for future research.
Keywords
Online learning; Saudi Arabia; benefits; artificial neural network modelling;
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