Indrajith Ekanayake
Data visualization using augmented reality for education: a systematic review.
Ekanayake, Indrajith; Gayanika, Shashini
Authors
Shashini Gayanika
Abstract
Current education systems use data visualization to present the data in a more comprehensible format. Augmented data visualization is an extended version to present the data in a 2D or 3D form in our field of vision. This study conducted a systematic literature review to identify the current state-of-the-art research in augmented reality and potential future research. Research paid especial attention towards the effective use of augmented reality for data visualization to offer a better pedagogical experience. A total of 39 studies have been filtered between 2017 to 2021 from two recognized databases, IEEE Xplore and ScienceDirect. Three research questions are designed for further analysis. Finally, the paper concludes with a future projection and uncovers research gaps that need to be addressed.
Citation
EKANAYAKE, I. and GAYANIKA, S. 2022. Data visualization using augmented reality for education: a systematic review. In Proceedings of the 7th International conference on business and industrial research (ICBIR 2022), 19-20 May 2022, Bangkok, Thailand. Bangkok: Thai-Nichi Institute of Technology, pages 533-537. Hosted on IEEE Xplore [online]. Available from: https://doi.org/10.1109/ICBIR54589.2022.9786403
Conference Name | 7th International conference on business and industrial research (ICBIR 2022) |
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Conference Location | Bangkok, Thailand |
Start Date | May 19, 2022 |
End Date | May 20, 2022 |
Acceptance Date | Apr 10, 2022 |
Online Publication Date | Jun 8, 2022 |
Publication Date | Dec 31, 2022 |
Deposit Date | Jun 24, 2022 |
Publicly Available Date | Jun 24, 2022 |
Publisher | Thai-Nichi Institute of Technology |
Pages | 533-537 |
ISBN | 9781665494748; 9781665494762 |
DOI | https://doi.org/10.1109/ICBIR54589.2022.9786403 |
Keywords | Data visualisation; Augmented reality; Education; Human computer interaction; Systematic review |
Public URL | https://rgu-repository.worktribe.com/output/1688225 |
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