Putjorn, Pruet, Siriaraya, Panote, Deravi, Farzin, Ang, Chee Siang (2018) Investigating the use of sensor-based IoET to facilitate learning for children in rural Thailand. PLOS ONE, 13 (8). Article Number 201875. ISSN 1932-6203. (doi:10.1371/journal.pone.0201875) (KAR id:68918)
PDF
Publisher pdf
Language: English
This work is licensed under a Creative Commons Attribution 4.0 International License.
|
|
Download this file (PDF/7MB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1371/journal.pone.0201875 |
Abstract
A novel sensor-based Internet of Educational Things (IoET) platform named OBSY was iteratively designed, developed and evaluated to support education in rural regions in Thailand. To assess the effectiveness of this platform, a study was carried out at four primary schools located near the Thai northern border with 244 students and 8 teachers. Participants were asked to carry out three science-based learning activities and were measured for improvements in learning outcome and learning engagement. Overall, the results showed that students in the IoET group who had used OBSY to learn showed significantly higher learning outcome and had better learning engagement than those in the control condition. In addition, for those in the IoET group, there was no significant effect regarding gender, home location (Urban or Rural), age, prior experience with technology and ethnicity on learning outcome. For learning engagement, only age was found to influence interest/enjoyment. The study demonstrated the potential of IoET technologies in underprivileged area, through a co-design approach with teachers and students, taking into account the local contexts.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1371/journal.pone.0201875 |
Subjects: |
L Education > L Education (General) T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Jim Ang |
Date Deposited: | 04 Sep 2018 12:20 UTC |
Last Modified: | 05 Nov 2024 12:30 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/68918 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):