Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/8281
Title: | Web-based training platform with AR games for dyslexic children |
Authors: | Ng, Ka-Fai Yung, Chi-Wai Muppala, Jogesh K. Lok, Cheuk-Hong Zhou, Senrui Lau, Hoi-Chung Dr. YUEN Man-Ching, Connie |
Issue Date: | 2023 |
Publisher: | IEEE |
Source: | Yuen, Man-Ching, Ng, Ka-Fai, Yung, Chi-Wai, Muppala, Jogesh K., Lok, Cheuk-Hong, Zhou, Senrui & Lau, Hoi-Chung (2023 Jan 3-8). Web-based training platform with AR games for dyslexic children. In COMSNETS (Ed.). 2023 15th International Conference on COMmunication Systems & NETworkS (COMSNETS).2023 15th International Conference on COMmunication Systems & NETworkS (COMSNETS), Bangalore, India (pp. 1-6). IEEE. |
Conference: | 2023 15th International Conference on COMmunication Systems & NETworkS (COMSNETS) |
Abstract: | Dyslexia could greatly hinder one's ability to read and write if it has not been remedied at a young age. Training games can provide an interactive environment for dyslexic children to learn in gameplay. This paper presents the design, implementation, system testing and evaluation of (Writing Fun), a web-based training and gaming platform for Hong Kong dyslexic children aged 4–6 to learn Chinese. (Writing Fun) offers one AR games for writing testing and four non-AR games to help preschool dyslexic children improve their Chinese literacy and to train the children in visual, auditory, and kinaesthetic movement. We evaluate the system with different browsers on various operating systems to ensure our application could be accessed by different devices and software. We also conducted an internal testing session and carried out a questionnaire to assess whether the system could deliver the desired outcomes. The results show that our project could help dyslexic children strengthen their reading and writing skills and improve their handwriting while keeping them entertained. |
Type: | Conference Paper |
URI: | http://hdl.handle.net/20.500.11861/8281 |
ISBN: | 978-1-6654-7706-2 978-1-6654-7707-9 |
ISSN: | 2155-2509 2155-2487 |
DOI: | 10.1109/COMSNETS56262.2023.10041268 |
Appears in Collections: | Applied Data Science - Publication |
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