IDEAS home Printed from https://ideas.repec.org/a/rfa/smcjnl/v13y2025i3p248-259.html
   My bibliography  Save this article

Developing a Phenomenon-Based Learning Model Utilizing Digital Media on the LINE OA Application

Author

Listed:
  • Suwannee Thammaratthara
  • Surapon Boonlue
  • Sorakrich Maneewan
  • Kuntida Thamwipat

Abstract

This research aimed 1) to develop and evaluate the quality of a phenomenon-based learning model with a digital learning companion to enhance commercial law competency for the entrepreneurship of Thai vocational students; and 2) to study the competence in knowledge of commercial law, skills, and attributes for the entrepreneurship of students after learning with the develop learning model and media. Data were collected from a sample group using a cluster sampling method from 25 vocational students in the business computer program in 2024. The research results found that the phenomenon-based learning model, “aCHIC model†, was developed with the digital learning companion “brain lump†on the LINE OA application. The quality of the content was found to be very good ( =4.98, SD = 0.03), as was the quality of the teaching media ( =4.94, SD = 0.08). It was found that the knowledge competency (K) of commercial law in entrepreneurship after studying was higher than before studying at a statistical significance level of .05 (t-test = 12.71). In terms of the skills (S) competency of entrepreneurship, it was found that students were able to create a business plan by applying commercial law for eight businesses at a good competency level (80.40%). They had a competency of attributes (A) of entrepreneurship at a good attributes level (81.80%). The aCHIC model used with the brain lump that was developed can be applied in practice. It is a challenge to overcome cross-disciplinary skills and integrate students in commercial law to have an entrepreneurial mindset.

Suggested Citation

  • Suwannee Thammaratthara & Surapon Boonlue & Sorakrich Maneewan & Kuntida Thamwipat, 2025. "Developing a Phenomenon-Based Learning Model Utilizing Digital Media on the LINE OA Application," Studies in Media and Communication, Redfame publishing, vol. 13(3), pages 248-259, September.
  • Handle: RePEc:rfa:smcjnl:v:13:y:2025:i:3:p:248-259
    as

    Download full text from publisher

    File URL: https://redfame.com/journal/index.php/smc/article/download/7635/6913
    Download Restriction: no

    File URL: https://redfame.com/journal/index.php/smc/article/view/7635
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:rfa:smcjnl:v:13:y:2025:i:3:p:248-259. 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: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.