IDEAS home Printed from https://ideas.repec.org/a/aoj/asjoet/v10y2024i3p146-153id5885.html
   My bibliography  Save this article

Using machine learning techniques to study of stress, depression, and academic performance of grade 12th students

Author

Listed:
  • Wudhijaya Philuek

Abstract

The objectives of this research were 1) to study the problems of stress and depression among Grade 12 students; 2) to investigate the machine learning technique in analyzing and predicting stress, depression, and academic performance among Grade 12 students; and 3) to evaluate the stress and depression prediction platform. Students from schools in the Secondary Educational Service Areas of Nakhon Sawan, Uthai Thani, Chainat, and Pichit in Thailand comprised the sampling group, which the researchers recruited through simple random sampling. A total of 510 students volunteered to participate in the questionnaire, while 117 students served as the group for the evaluation platform. The researcher employed a total of three assessments: 1) the Stress Assessment Scale (SPST-20), 2) the Depression Assessment Form 9 Questions (9Q), and 3) the Death Assessment Form (8Q) to gather data and develop the platform. The data analytics process incorporates all assessment results, comparing five techniques to yield the most accurate results. The article presents the research results, which will guide the development of a system and tools for future student monitoring in schools.

Suggested Citation

  • Wudhijaya Philuek, 2024. "Using machine learning techniques to study of stress, depression, and academic performance of grade 12th students," Asian Journal of Education and Training, Asian Online Journal Publishing Group, vol. 10(3), pages 146-153.
  • Handle: RePEc:aoj:asjoet:v:10:y:2024:i:3:p:146-153:id:5885
    as

    Download full text from publisher

    File URL: http://www.asianonlinejournals.com/index.php/EDU/article/view/5885/2858
    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:aoj:asjoet:v:10:y:2024:i:3:p:146-153:id:5885. 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: Sara Lim (email available below). General contact details of provider: http://asianonlinejournals.com/index.php/EDU/ .

    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.