• 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