IDEAS home Printed from https://ideas.repec.org/a/aac/ijirss/v8y2025i1p1188-1195id4550.html
   My bibliography  Save this article

Development of an intelligent platform for predicting curriculum management in higher education under the AUN-QA framework

Author

Listed:
  • Suwut Tumthong
  • Nichanun Samakthai
  • Pinyaphat Tasatanattakool

Abstract

This research aims to study and define the user requirements and operational capabilities required to develop an intelligent platform for forecasting and managing higher education courses under the AUN-QA framework using documentary research, platform design, and technology suitability assessment. The samples studied include personnel, instructors, course administrators, and IT specialists selected by the purposive method. Data were analyzed using statistics and standard deviation calculations. The results show that the developed platform should have five main components: user data control with AWS IAM and React, access security, SmartEduQA system for data storage and analysis, data presentation with Microsoft Power BI, and a serverless storage system. The platform is designed to meet the needs of administrators in forecasting the labor market and managing courses, instructors in analyzing data according to AUN-QA standards, and staff in managing data quickly and supporting interactive display. This platform can help make higher education course management efficient and aligned with AUN-QA standards.

Suggested Citation

  • Suwut Tumthong & Nichanun Samakthai & Pinyaphat Tasatanattakool, 2025. "Development of an intelligent platform for predicting curriculum management in higher education under the AUN-QA framework," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(1), pages 1188-1195.
    • Handle: RePEc:aac:ijirss:v:8:y:2025:i:1:p:1188-1195:id:4550
    as

    Download full text from publisher

    File URL: https://ijirss.com/index.php/ijirss/article/view/4550/667
    Download Restriction: no
    ---><---

    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:aac:ijirss:v:8:y:2025:i:1:p:1188-1195:id:4550. 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: Natalie Jean (email available below). General contact details of provider: https://ijirss.com/index.php/ijirss/ .

    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.