IDEAS home Printed from https://ideas.repec.org/a/gam/jscscx/v13y2024i9p479-d1474416.html
   My bibliography  Save this article

Constructing a Socio-Legal Framework Proposal for Governing Large Language Model Usage and Application in Education

Author

Listed:
  • Mirela Mezak Matijevic

    (Faculty of Tourism and Rural Development, Josip Juraj Strossmayer University of Osijek, 34000 Pozega, Croatia)

  • Barbara Pisker

    (Faculty of Tourism and Rural Development, Josip Juraj Strossmayer University of Osijek, 34000 Pozega, Croatia)

  • Kristian Dokic

    (Faculty of Tourism and Rural Development, Josip Juraj Strossmayer University of Osijek, 34000 Pozega, Croatia)

Abstract

Due to the fast-changing environments caused by artificial intelligence development, the socio-technical challenge in contemporary educational systems focuses on the need for more regulative measures guiding system stakeholders’ behavior. In fulfilling the present legal gap, enacted soft law regulation has been laid out, and a detailed systematic literature review was conducted in the paper presented. The specific methodological approach was selected to deal with two crucial research tasks: to reveal and recommend fundamental governing mechanisms regarding the use and application of generative artificial intelligence; more precisely, large language models in educational systems. Three systematically guided layers of quantitative and qualitative content analysis of central policy, legislation, and regulatory mechanisms in governing AI in education were extracted from the 142 Scopus Database and Web of Science research papers analyzed and presented. These research findings benefit policymakers, regulatory and legislative bodies, and agencies in constructing governing frames for using and applying generative artificial intelligence in education.

Suggested Citation

  • Mirela Mezak Matijevic & Barbara Pisker & Kristian Dokic, 2024. "Constructing a Socio-Legal Framework Proposal for Governing Large Language Model Usage and Application in Education," Social Sciences, MDPI, vol. 13(9), pages 1-19, September.
  • Handle: RePEc:gam:jscscx:v:13:y:2024:i:9:p:479-:d:1474416
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2076-0760/13/9/479/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2076-0760/13/9/479/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jason Hung & Jackson Chen, 2023. "The Benefits, Risks and Regulation of Using ChatGPT in Chinese Academia: A Content Analysis," Social Sciences, MDPI, vol. 12(7), pages 1-15, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lian, Ying & Tang, Huiting & Xiang, Mengting & Dong, Xuefan, 2024. "Public attitudes and sentiments toward ChatGPT in China: A text mining analysis based on social media," Technology in Society, Elsevier, vol. 76(C).

    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:gam:jscscx:v:13:y:2024:i:9:p:479-:d:1474416. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.