IDEAS home Printed from https://ideas.repec.org/a/igg/jitn00/v18y2026i1p1-19.html

Exploration of AI-Based English Translation Teaching Models

Author

Listed:
  • Mengli He

    (Zhongyuan Institute of Science and Technology, China)

Abstract

AI's rapid advancement in foreign language education introduces new opportunities and challenges for English translation teaching. Traditional methods often fail to provide deep interaction and instant feedback, limiting student engagement. This study integrates AI-assisted tools into teaching to foster multidimensional teacher-student interactions, using selected cases and novel evaluation schemes. It highlights AI's pivotal role in translation, advocating for teachers to evolve from knowledge providers to learning facilitators, aiding students in mastering language nuances and critical thinking. The research combines theoretical insights with empirical evidence, showcasing how AI empowers flexible, personalized learning environments. Findings suggest that appropriate use of AI optimizes translation processes, boosts motivation, and supports continuous development, offering valuable references for future practices. Emphasizing the integration of theory and practice, this study proposes fresh perspectives for educational reforms.

Suggested Citation

  • Mengli He, 2026. "Exploration of AI-Based English Translation Teaching Models," International Journal of Interdisciplinary Telecommunications and Networking (IJITN), IGI Global Scientific Publishing, vol. 18(1), pages 1-19, January.
    • Handle: RePEc:igg:jitn00:v:18:y:2026:i:1:p:1-19
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJITN.415340
    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:jitn00:v:18:y:2026: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.