IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v10y2025i8p1275-1283.html

Personalized AI in Higher Education: Development and Evaluation of a Course-Specific Chatgpt Tutor

Author

Listed:
  • Navaratnam Vejaratnam

    (Department of Business Management, FAME, New Era University College)

  • Shamuni Kunjiapu

    (Department of Business Management, FAME, New Era University College)

  • Theepa Paramasivam

    (Department of Business Management, FAME, New Era University College)

  • Rajennd Muniady

    (Department of Business Management, FAME, New Era University College)

  • Shri Dayalam James Batumalay

    (Department of Business Management, FAME, New Era University College)

Abstract

The integration of artificial intelligence into education has opened new avenues for personalized and widespread learning assistance. This paper focuses on the design and development of a custom ChatGPT tailored for tertiary education settings. The main objective is to investigate how generative AI customized to align with subject materials, intended outcomes, and how to actively involve learners can be of benefit. For this study, a special chatbot was built with OpenAI’s GPT framework to work as a tutor available at any time for the subject International Business (IBUS 201D). The design and testing of this ChatGPT tutor followed a Design Science Research method. A quantitative study was done conducted with 35 undergraduate students, using a pre–post-test to see the effectiveness of new developed GPT for the specific subject. The findings show that this type of ChatGPT tutor can be a helpful support alongside normal teaching. The results indicate that the custom ChatGPT tutor can be a meaningful addition to traditional teaching methods.

Suggested Citation

  • Navaratnam Vejaratnam & Shamuni Kunjiapu & Theepa Paramasivam & Rajennd Muniady & Shri Dayalam James Batumalay, 2025. "Personalized AI in Higher Education: Development and Evaluation of a Course-Specific Chatgpt Tutor," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(8), pages 1275-1283, August.
    • Handle: RePEc:bjf:journl:v:10:y:2025:i:8:p:1275-1283
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrias/digital-library/volume-10-issue-8/1275-1283.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrias/articles/personalized-ai-in-higher-education-development-and-evaluation-of-a-course-specific-chatgpt-tutor/
    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:bjf:journl:v:10:y:2025:i:8:p:1275-1283. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    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.