Specifying gestures by example
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Guidelines for usability testing with children
interactions
Children as our technology design partners
The design of children's technology
Visual similarity of pen gestures
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Sketched Symbol Recognition using Zernike Moments
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
GLADDER: combining gesture and geometric sketch recognition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
LADDER, a sketching language for user interface developers
Computers and Graphics
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
A lightweight multistroke recognizer for user interface prototypes
Proceedings of Graphics Interface 2010
Proceedings of the 2012 ACM international conference on Interactive tabletops and surfaces
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Sketching is one of the many valuable lifelong skills that children require in their overall development, and many educational psychologists manually analyze children's sketches to assess their developmental progress. The disadvantages of manual assessment are that it is time-consuming and prone to human error and bias, so intelligent sketching interfaces have strong potential in automating this process. Unfortunately, current sketch recognition techniques concentrate solely on recognizing the meaning of sketches, rather than the sketcher's developmental skill; and do not perform well on children's sketched input, as most are trained on and developed for adult's sketches. We introduce our proposed solution called KimCHI, a specialized sketch classification technique which utilizes a sketching interface for assessing the developmental skills of children from their sketches. Our approach relies on sketch feature selection to automatically classify the developmental progress of children's sketches as either developmental or mature. We evaluated our classifiers through a user study, and our classifiers were able to differentiate the users' development skill and gender with reasonable accuracy. We subsequently created an initial sketching interface utilizing our specialized classifier called EasySketch for demonstrating educational applications to assist children in developing their sketching skills.