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Reinventing The Future Online Education Using Emerging Technologies

Author(s): Regina Reine 1 , Filbert H. Juwono 2 , W. K. Wong 2
Author(s) information:
1 Twigx Research, 71 – 75 Shelton Street, London WC2H 9JQ, United Kingdom
2 Department of Electrical and Computer Engineering, Curtin University Malaysia, Miri 98009, Sarawak, Malaysia

Corresponding author

The pandemic of Coronavirus Disease 2019 (COVID-19) has forced the teaching and learning activities to be conducted remotely. Before the pandemic, many academic institutions had offered online distance learning for selected courses. However, in practice, most of these programs were delivered as blended learning programs instead of full-fledged distance learning programs. Distance learning programs faced challenges and limitations in terms of communication, integrity, and interactions compared to the traditional face-to-face teaching and learning method. Despite the challenges and limitations in distance teaching and learning, academic staff is expected to accomplish the same (or better) outcomes than traditional face-to-face teaching and learning. Hence, the distance learning method was not popular with many academic staff and students before the pandemic time. In order to improve the quality of the full distance learning delivery, emerging technologies and more interactive platforms are being developed rapidly. This article discusses the emerging technologies and strategies to make full distance learning or remote education competitive compared to the traditional teaching and learning method. The future potential teaching and learning technology, i.e., digital twins, is also briefly presented.
About this article

SUBMITTED: 14 November 2021
ACCEPTED: 23 November 2021
PUBLISHED: 29 November 2021
SUBMITTED to ACCEPTED: 10 days
DOI: https://doi.org/10.53623/gisa.v1i1.42

Cite this article
Reine, R., Juwono, F. H., & Wong, W. K. (2021). Reinventing The Future Online Education Using Emerging Technologies. Green Intelligent Systems and Applications, 1(1), 26–36. https://doi.org/10.53623/gisa.v1i1.42
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