IDEAS home Printed from https://ideas.repec.org/a/ibn/eltjnl/v18y2025i6p46.html
   My bibliography  Save this article

Research on the Construction of an AI-Empowered Adaptive Ecological Teaching Model for College Foreign Language Education

Author

Listed:
  • Chao Wang
  • Ying Zuo

Abstract

This study takes the "Artificial Intelligence + Education" theory as the starting point and constructs a theoretical model of adaptive ecological teaching for foreign languages in higher education within the framework of language ecological teaching theory. The proposed model has been applied to the teaching practice of foreign language general education courses. The article analyzes critical factors influencing the ecological foreign language classroom environment in the AI context, introduces construction pathways for the ecological teaching model based on AI technology, and demonstrates its positive significance for creating harmonious, efficient, and symbiotic ecological classrooms tailored to China's specific educational context. This research contributes to promoting intelligent transformation of foreign language teaching models in higher education and helps comprehensively enhance the pedagogical effectiveness of foreign language general education courses at the practical level.

Suggested Citation

  • Chao Wang & Ying Zuo, 2025. "Research on the Construction of an AI-Empowered Adaptive Ecological Teaching Model for College Foreign Language Education," English Language Teaching, Canadian Center of Science and Education, vol. 18(6), pages 1-46, June.
    • Handle: RePEc:ibn:eltjnl:v:18:y:2025:i:6:p:46
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/elt/article/download/0/0/51721/56253
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/elt/article/view/0/51721
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:eltjnl:v:18:y:2025:i:6:p:46. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.