IDEAS home Printed from https://ideas.repec.org/a/igg/jcallt/v15y2025i1p1-19.html
   My bibliography  Save this article

Revolutionising Essay Evaluation: A Cutting-Edge Rubric for AI-Assisted Writing

Author

Listed:
  • Hassan Saleh Mahdi

    (Arab Open University, Saudi Arabia)

  • Ahmed Alkhateeb

    (King Faisal University, Saudi Arabia)

Abstract

This study aims to develop a robust rubric for evaluating artificial intelligence (AI)–assisted essay writing in English as a Foreign Language (EFL) contexts. Employing a modified Delphi technique, we conducted a comprehensive literature review and administered Likert scale questionnaires. This process yielded nine key evaluation criteria, forming the initial rubric. The rubric was applied to evaluate 33 AI-assisted essays written by students as part of an intensive course assignment. Statistical analysis revealed significant inter-rater reliability and convergent validity coefficients, supporting the adoption and further development of such rubrics across higher education institutions. The developed rubric was subsequently used to evaluate these essays using two AI tools: ChatGPT and Claude. The results indicated that both AI tools evaluated the essays with similar scores, demonstrating consistency in their assessment capabilities.

Suggested Citation

  • Hassan Saleh Mahdi & Ahmed Alkhateeb, 2025. "Revolutionising Essay Evaluation: A Cutting-Edge Rubric for AI-Assisted Writing," International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), IGI Global, vol. 15(1), pages 1-19, January.
    • Handle: RePEc:igg:jcallt:v:15:y:2025:i:1:p:1-19
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCALLT.368226
    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:1-19. 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.