Md. Fouad Hossain Sarker, Saida Mahamuda Rahman, Samiha Khan, M. Sohel, Maruf Ahmed Tamal, Mohammad Marufur Rashid Khan, Md. Kabirul Islam
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The results of the study showed that while students faced a range of challenges while participating in online classes, including technical issues and limited access to study materials, they still preferred to participate in online courses due to the ongoing pandemic and the support of their teachers. Furthermore, the study revealed that there were differences in students’ attitudes toward online learning based on gender, geographic location, and type of university. The findings of this study are of great significance to governments, policymakers, technology developers, and university administrators, as they provide valuable information for the development of effective policies for online education in the future. These findings should be taken into consideration as a crucial guide to making in-formed decisions in the area of online education.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Perception and Preference of the Students for Online Education during COVID-19 in Bangladesh: A Study Based on Binary Logistic Regression\",\"authors\":\"Md. Fouad Hossain Sarker, Saida Mahamuda Rahman, Samiha Khan, M. Sohel, Maruf Ahmed Tamal, Mohammad Marufur Rashid Khan, Md. Kabirul Islam\",\"doi\":\"10.3991/ijet.v18i13.38807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The COVID-19 pandemic has had a significant impact on both public health, and the global educational system. 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Perception and Preference of the Students for Online Education during COVID-19 in Bangladesh: A Study Based on Binary Logistic Regression
The COVID-19 pandemic has had a significant impact on both public health, and the global educational system. In response to the concerns surrounding the spread of the disease, many educational institutions, including those in Bangladesh, have shifted to online learning. This study aimed to investigate the perceptions and preferences of university students in Bangladesh towards online classes during the COVID-19 pandemic. The research was based on Binary Logistic Regression (BLR) and was conducted on a sample of 1116 university students in Bangladesh. The results of the study showed that while students faced a range of challenges while participating in online classes, including technical issues and limited access to study materials, they still preferred to participate in online courses due to the ongoing pandemic and the support of their teachers. Furthermore, the study revealed that there were differences in students’ attitudes toward online learning based on gender, geographic location, and type of university. The findings of this study are of great significance to governments, policymakers, technology developers, and university administrators, as they provide valuable information for the development of effective policies for online education in the future. These findings should be taken into consideration as a crucial guide to making in-formed decisions in the area of online education.
期刊介绍:
This interdisciplinary journal focuses on the exchange of relevant trends and research results and presents practical experiences gained while developing and testing elements of technology enhanced learning. It bridges the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Fields of interest include, but are not limited to: -Software / Distributed Systems -Knowledge Management -Semantic Web -MashUp Technologies -Platforms and Content Authoring -New Learning Models and Applications -Pedagogical and Psychological Issues -Trust / Security -Internet Applications -Networked Tools -Mobile / wireless -Electronics -Visualisation -Bio- / Neuroinformatics -Language /Speech -Collaboration Tools / Collaborative Networks