IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p2872-d1058418.html
   My bibliography  Save this article

Supporting Speaking Practice by Social Network-Based Interaction in Artificial Intelligence (AI)-Assisted Language Learning

Author

Listed:
  • Bin Zou

    (Department of Applied Linguistics, Xi’an Jiaotong Liverpool University, Suzhou 215123, China)

  • Xin Guan

    (Department of Applied Linguistics, Xi’an Jiaotong Liverpool University, Suzhou 215123, China)

  • Yinghua Shao

    (Department of Applied Linguistics, Xi’an Jiaotong Liverpool University, Suzhou 215123, China)

  • Peng Chen

    (Department of Applied Linguistics, Xi’an Jiaotong Liverpool University, Suzhou 215123, China)

Abstract

In recent decades, the rapid development of artificial intelligence (AI) technology has led to the increasing use of AI speaking apps in foreign language learning. This research investigates the impact of social network-based interaction on students’ English speaking practice with the assistance of AI speaking apps in China. During the summer vacation, 70 students from different Chinese universities and majors were recruited for the experiment. They were required to practice speaking skills with AI apps for five weeks and were divided into two groups. Participants in the experimental group were encouraged to engage in various interactive activities when practicing speaking with AI apps, while those in the control group were asked to use AI speaking apps without interaction. Data were collected through questionnaires and semi-structured interviews as well as pre-and post-tests. The results indicated that students generally held positive attitudes towards interactive activities when using AI apps to practice their spoken English. The finding also showed that social network-based interaction can effectively improve learners’ speaking skills in the AI context. This study contributes to the research on the implementation and promotion of AI speaking apps with social networking and extends the previous studies on network-based interaction to the AI-assisted learning environment. An investigation of interactions based on Chinese social network-based platforms such as WeChat can be further applied to other social networking platforms such as Facebook or WhatsApp in different cultural contexts for AI-assisted speaking practice.

Suggested Citation

  • Bin Zou & Xin Guan & Yinghua Shao & Peng Chen, 2023. "Supporting Speaking Practice by Social Network-Based Interaction in Artificial Intelligence (AI)-Assisted Language Learning," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:2872-:d:1058418
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/2872/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/4/2872/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joy Egbert & Omran Akasha & Leslie Huff & HyunGyung Lee, 2011. "Moving Forward: Anecdotes and Evidence Guiding the Next Generation of CALL," International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), IGI Global, vol. 1(1), pages 1-15, January.
    2. Halima Bahi & Khaled Necibi, 2020. "Fuzzy Logic Applied for Pronunciation Assessment," International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), IGI Global, vol. 10(1), pages 60-72, January.
    3. Murad Abdu Saeed & Mohammed Abdullah Alharbi & Amr Abdullatif Yassin, 2021. "Sustaining Synchronous Interaction Effectiveness in Distance Writing Courses: A Mixed Method Study in a KSA University," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bin Zou & Yiran Du & Zhimai Wang & Jinxian Chen & Weilei Zhang, 2023. "An Investigation Into Artificial Intelligence Speech Evaluation Programs With Automatic Feedback for Developing EFL Learners’ Speaking Skills," SAGE Open, , vol. 13(3), pages 21582440231, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bin Zou & Yiran Du & Zhimai Wang & Jinxian Chen & Weilei Zhang, 2023. "An Investigation Into Artificial Intelligence Speech Evaluation Programs With Automatic Feedback for Developing EFL Learners’ Speaking Skills," SAGE Open, , vol. 13(3), pages 21582440231, August.
    2. Jaeseok Yang, 2013. "Mobile Assisted Language Learning: Review of the Recent Applications of Emerging Mobile Technologies," English Language Teaching, Canadian Center of Science and Education, vol. 6(7), pages 1-19, July.
    3. Tong Zhou & Wei Zhang, 2022. "Effectiveness Study on Online or Blended Language Learning Based on Student Achievement: A Systematic Review of Empirical Studies," Sustainability, MDPI, vol. 14(12), pages 1-29, June.

    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:gam:jsusta:v:15:y:2023:i:4:p:2872-:d:1058418. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.