The current education systems in elementary schools are usually using traditional teaching methods such as paper and pencil or drawing on the board. The benefit of paper and pencil is their ease of use. Researchers have tried to bring this ease of use to computer-based educational systems through the use of sketch-recognition. Sketch-recognition allows students to draw naturally while at the same time receiving automated assistance and feedback from the computer.
There are many sketch-based educational systems for children. However, current sketch-based educational systems use the same sketch recognizer for both adults and children. The problem of this approach is that the recognizers are trained by using sample data drawn by adults, even though the drawing patterns of children and adults are markedly different. We propose that if we make a separate recognizer for children, we can increase the recognition accuracy of shapes drawn by children.
By creating a separate recognizer for children, we improved the recognition accuracy of children’s drawings from 81.25% (using the adults’ threshold) to 83.75% (using adjusted threshold for children).
Additionally, we were able to automatically distinguish children’s drawings from adults’ drawings. We correctly identified the drawer’s age (age 3, 4, 7, or adult) with 78.3%. When distinguishing toddlers (age 3 and 4) from matures (age 7 and adult), we got a precision of 95.2% using 10-fold cross validation. When we removed adults and distinguished between toddlers and 7 year olds, we got a precision of 90.2%. Distinguishing between 3, 4, and 7 year olds, we got a precision of 86.8%.
Furthermore, we revealed that there is a potential gender difference since our recognizer was more accurately able to recognize the drawings of female children (91.4%) than the male children (85.4%).
Finally, this paper introduces a sketch-based teaching assistant tool for children,
EasySketch, which teaches children how to draw digits and characters. Children can learn how to draw digits and characters by instructions and feedback.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/148207 |
| Date | 14 March 2013 |
| Creators | Kim, Hong-Hoe |
| Contributors | Hammond, Tracy |
| Source Sets | Texas A and M University |
| Detected Language | English |
| Type | Thesis, text |
| Format | application/pdf |
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