IDEAS home Printed from https://ideas.repec.org/a/igg/jcallt/v15y2025i1p1-26.html
   My bibliography  Save this article

From Fragmentation to Integration: Optimizing Blended College English Teaching With a Production-Oriented Approach

Author

Listed:
  • Juan Wang

    (University Kebangsaan Malaysia, Malaysia & Chaohu University, Malaysia)

  • Hanita Hanim Ismail

    (University Kebangsaan, China)

  • Ahmad Zamri Mansor

    (University Kebangsaan, Malaysia)

Abstract

Blended teaching, which combines online resources with face-to-face instruction, has become the dominant pedagogical model in College English education. As a crucial form of computer-assisted language learning, blended teaching leverages digital technologies to enhance language learning experiences. However, current implementations often result in fragmented learning experiences due to poorly integrated online and offline components, leading to reduced learning outcomes and student dissatisfaction. This study developed and evaluated an optimized blended teaching model guided by the production-oriented approach, implemented through two iterative action research cycles involving 92 undergraduate students (44 experimental, 48 control) over one semester. Results show that this model significantly improved students' reading and writing performance compared to traditional blended teaching, with marked increases across all dimensions of course satisfaction, particularly in learning assessment.

Suggested Citation

  • Juan Wang & Hanita Hanim Ismail & Ahmad Zamri Mansor, 2025. "From Fragmentation to Integration: Optimizing Blended College English Teaching With a Production-Oriented Approach," International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), IGI Global Scientific Publishing, vol. 15(1), pages 1-26, January.
    • Handle: RePEc:igg:jcallt:v:15:y:2025:i:1:p:1-26
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCALLT.388707
    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:jcallt:v:15:y:2025:i:1:p:1-26. 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.