IDEAS home Printed from https://ideas.repec.org/a/igg/jkss00/v13y2022i1p1-19.html
   My bibliography  Save this article

A Dual-Role Collaborative Learning Support System for Simultaneous Speaking Acquisition in English and Japanese

Author

Listed:
  • Anh Bui

    (Japan Advanced Institute of Science and Technology, Japan)

  • Kazushi Nishimoto

    (Japan Advanced Institute of Science and Technology, Japan)

Abstract

Learning a foreign language is becoming more vital in Japan as a result of globalization. It gives foreigners various reasons to study Japanese including working or living in Japan. They should exchange language and skills and generate opportunities for engagement. Assisting them in exchanging linguistic skills and knowledge is critical. This study first proposes a theoretical model of dual-role collaborative learning to improve second language learners' speaking skills. Learners will participate as facilitators in their native language and receivers in their second language. Some supporting features must be given, followed by a Computer-supported Collaborative Learning (CSCL) named BiTak which is a video chat system that allows strict turn-taking dual-lingual conversation. The learner’s progress is positively evaluated by language teachers using a Rubric scoring framework. Based on the experiment results, it was concluded that BiTak has turned users' perspectives of video chat programs into collaborative learning platforms, allowing them to act as facilitators and receivers.

Suggested Citation

  • Anh Bui & Kazushi Nishimoto, 2022. "A Dual-Role Collaborative Learning Support System for Simultaneous Speaking Acquisition in English and Japanese," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 13(1), pages 1-19, January.
  • Handle: RePEc:igg:jkss00:v:13:y:2022:i:1:p:1-19
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJKSS.298709
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jkss00:v:13:y:2022:i:1:p:1-19. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.