IDEAS home Printed from https://ideas.repec.org/a/bjb/journl/v14y2025i5p678-684.html
   My bibliography  Save this article

Optimizing Engagement and Retention Through Data-Driven Personalization in Adaptive Multimedia Learning Systems

Author

Listed:
  • Ain Geuel E. Escober

    (Polytechnic University of the Philippines Quezon City Campus)

  • Demelyn E. Monzon

    (Polytechnic University of the Philippines Quezon City Campus)

Abstract

This study investigates the development of a personalized multimedia learning system designed to overcome the limitations of traditional content delivery methods, which often utilize a generic, one-size-fits-all approach. By tailoring educational materials to align with user preferences, such as content format and information density, as well as learning styles—like visual, auditory, and kinesthetic—this research seeks to enhance user engagement and improve knowledge retention. Recent studies by Feng and Yang (2023) and López-Morales and Rosado-Muñoz (2023) suggest that personalized approaches significantly increase user satisfaction and retention. Utilizing advancements in learning management systems (LMS) and user behavior analytics, this research gathers user preferences and learning style data to facilitate dynamic content adaptation. This customization promotes deeper engagement and highlights the importance of accessibility, inclusivity, and ethical considerations surrounding user data management (Papadopoulos & Tsoukalas, 2022; Hwang & Chang, 2021). The findings provide actionable insights for educators and content creators, advocating for the responsible development of multimedia platforms that empower users and optimize their learning experiences.

Suggested Citation

  • Ain Geuel E. Escober & Demelyn E. Monzon, 2025. "Optimizing Engagement and Retention Through Data-Driven Personalization in Adaptive Multimedia Learning Systems," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 14(5), pages 678-684, May.
    • Handle: RePEc:bjb:journl:v:14:y:2025:i:5:p:678-684
    as

    Download full text from publisher

    File URL: https://www.ijltemas.in/DigitalLibrary/Vol.14Issue5/678-684.pdf
    Download Restriction: no
    File URL: https://www.ijltemas.in/papers/volume-14-issue-5/678-684.html
    Download Restriction: no
    ---><---

    More about this item

    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:bjb:journl:v:14:y:2025:i:5:p:678-684. 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: Dr. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .

    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.