DocumentCode :
2870045
Title :
An Extendible Software for Learning to Write Chinese Characters in Correct Stroke Sequences on Smartphones
Author :
Tam, Vincent ; Huang, Chao
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China
fYear :
2011
fDate :
6-8 July 2011
Firstpage :
118
Lastpage :
119
Abstract :
With the fast economic development in China, learning to understand Chinese becomes very crucial and popular worldwide. To most foreigners and even native Chinese students, one of the major challenges in learning Chinese is to write Chinese characters in correct stroke sequences since the correct stroke sequences of writing any Chinese character is regarded as crucial in the Chinese culture. Intrinsically, there were very few available character recognition techniques that can tackle the complexity of structures of Chinese characters together with their stroke sequences. In this paper, we propose an extendible and intelligent e-learning software based on learning objects to facilitate the learning of writing Chinese characters in correct stroke sequences. To demonstrate the feasibility of our proposal, a prototype of our proposed e-learning software was built on smart phones. Our proposal represents the first attempt to reduce the complexity while increasing the extendibility of the e-learning software to learn Chinese through learning objects. More importantly, it opens up numerous opportunities for further investigations.
Keywords :
character recognition; computer aided instruction; mobile computing; mobile handsets; software prototyping; China; Chinese character writing; Chinese learning; character recognition techniques; correct stroke sequences; economic development; intelligent e-learning software prototype; smartphones; Electronic learning; Periodic structures; Proposals; Prototypes; Smart phones; Software; Writing; Chinese characters; e-learning systems; learning objects; stroke sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies (ICALT), 2011 11th IEEE International Conference on
Conference_Location :
Athens, GA
ISSN :
2161-3761
Print_ISBN :
978-1-61284-209-7
Electronic_ISBN :
2161-3761
Type :
conf
DOI :
10.1109/ICALT.2011.40
Filename :
5992279
Link To Document :
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