IDEAS home Printed from https://ideas.repec.org/a/prg/jnlaip/v2024y2024i3id235p460-489.html
   My bibliography  Save this article

Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning

Author

Listed:
  • Manel Guettala
  • Samir Bourekkache
  • Okba Kazar
  • Saad Harous

Abstract

The integration of generative artificial intelligence (AI) into adaptive and personalized learning represents a transformative shift in the educational landscape. This research paper investigates the impact of incorporating generative AI into adaptive and personalized learning environments, with a focus on tracing the evolution from conventional artificial intelligence methods to generative AI and identifying its diverse applications in education. The study begins with a comprehensive review of the evolution of generative AI models and frameworks. A framework of selection criteria is established to curate case studies showcasing the applications of generative AI in education. These case studies are analysed to elucidate the benefits and challenges associated with integrating generative AI into adaptive learning frameworks. Through an in-depth analysis of selected case studies, the study reveals tangible benefits derived from generative AI integration, including increased student engagement, improved test scores and accelerated skill development. Ethical, technical and pedagogical challenges related to generative AI integration are identified, emphasizing the need for careful consideration and collaborative efforts between educators and technologists. The findings underscore the transformative potential of generative AI in revolutionizing education. By addressing ethical concerns, navigating technical challenges and embracing human-centric approaches, educators and technologists can collaboratively harness the power of generative AI to create innovative and inclusive learning environments. Additionally, the study highlights the transition from Education 4.0 to Education 5.0, emphasizing the importance of social-emotional learning and human connection alongside personalization in shaping the future of education.

Suggested Citation

  • Manel Guettala & Samir Bourekkache & Okba Kazar & Saad Harous, 2024. "Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2024(3), pages 460-489.
  • Handle: RePEc:prg:jnlaip:v:2024:y:2024:i:3:id:235:p:460-489
    DOI: 10.18267/j.aip.235
    as

    Download full text from publisher

    File URL: http://aip.vse.cz/doi/10.18267/j.aip.235.html
    Download Restriction: free of charge

    File URL: http://aip.vse.cz/doi/10.18267/j.aip.235.pdf
    Download Restriction: free of charge

    File URL: https://libkey.io/10.18267/j.aip.235?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:prg:jnlaip:v:2024:y:2024:i:3:id:235:p:460-489. 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: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.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.