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 Associate Professor, Department of Development Studies, Daffodil International University https://orcid.org/0000-0002-6884-837X
  • Saida Mahamuda Rahman Department of Development Studies, Daffodil International University https://orcid.org/0000-0002-0068-6706
  • Samiha Khan Department of Development Studies, Daffodil International University
  • Md. Salman Sohel Department of Development Studies, Daffodil International University https://orcid.org/0000-0001-5448-8185
  • Maruf Ahmed Tamal Division of Research, Daffodil International University
  • Mohammad Marufur Rashid Khan Deputy Secretary, Dhaka North City Corporation, Government of Bangladesh
  • Md Kabirul Islam Faculty of Graduate Studies, Daffodil International University

DOI:

https://doi.org/10.3991/ijet.v18i13.38807

Keywords:

Online Education; COVID-19-induced Pandemic; Binary Logistic Regression Analysis; Students’ Perception and Preference; Bangladesh

Abstract


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.

Author Biographies

Md Fouad Hossain Sarker, Associate Professor, Department of Development Studies, Daffodil International University

Md Fouad Hossain Sarker is an Associate Professor in the Department of Development Studies, under the Faculty of Humanities and Social Science, at Daffodil International University (DIU), Bangladesh. He has received the "Teaching Practices Excellence Award (Chairman’s Award) in 2020 and the Vice Chancellor’s Award in 2016" for innovation in teaching and learning at DIU. His research interests focus on educational development, mentoring & counseling, corporate social responsibility, migration, and development. ORCID ID: https://orcid.org/0000-0002-6884-837X

Saida Mahamuda Rahman, Department of Development Studies, Daffodil International University

 

 

 

Samiha Khan, Department of Development Studies, Daffodil International University

 

 

Md. Salman Sohel, Department of Development Studies, Daffodil International University

 

 

Maruf Ahmed Tamal, Division of Research, Daffodil International University

 

 

Mohammad Marufur Rashid Khan, Deputy Secretary, Dhaka North City Corporation, Government of Bangladesh

 

 

Md Kabirul Islam, Faculty of Graduate Studies, Daffodil International University

 

 

Cover iJET – Vol 18, No 13, 2023

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Published

2023-07-07

How to Cite

Sarker, M. F. H., Rahman, S. M. ., Khan, S. ., Sohel, M. S. ., Tamal, M. A. ., Khan, M. M. R. ., & Islam, M. K. . (2023). Perception and Preference of the Students for Online Education during COVID-19 in Bangladesh: A Study Based on Binary Logistic Regression . International Journal of Emerging Technologies in Learning (iJET), 18(13), pp. 74–90. https://doi.org/10.3991/ijet.v18i13.38807

Issue

Vol. 18 No. 13 (2023)

Section

Papers

License

Copyright (c) 2023 Md Fouad Hossain Sarker, Saida Mahamuda Rahman, Samiha Khan, Md. Salman Sohel, Maruf Ahmed Tamal, Mohammad Marufur Rashid Khan, Md Kabirul Islam

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