Name
Title | ||
|---|---|---|
Detecting handwriting errors with visual feedback in early childhood for Chinese characters |
Abstract | ||
|---|---|---|
This paper presents KID, an interactive app on a smart device, designed to facilitate and encourage young children to learn and practice Chinese characters. It relies on pen dynamics to extract the strokes and map the written character to the proper one. The stroke orientation is also analyzed for ordering and spatial alignment features that pinpoint common errors. A visual pictorial feedback is then provided to motivate children and to arouse their interest. We iterate the prototype design and implementation upon collecting feedback from focus group interviews, from where the system is greeted with positive comments. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2593968.2610470 | IDC |
Keywords | Field | DocType |
stroke alignment,software psychology,pictographic feedback,human factors,learning to write,human information processing,stroke analysis | Chinese characters,Smart device,Handwriting,Computer science,Human–computer interaction,Early childhood,Multimedia,Focus group | Conference |
Citations | PageRank | References |
2 | 0.40 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Will Tang | 1 | 12 | 2.33 |
| Hong Va Leong | 2 | 1099 | 173.04 |
| Grace Ngai | 3 | 882 | 89.27 |
| Stephen C. F. Chan | 4 | 168 | 15.78 |