IDEAS home Printed from https://ideas.repec.org/a/epw/ejedu0/v5y2024i2id30799.html

The Impact of Cognitive Load Theory on the Effectiveness of Microlearning Modules

Author

Listed:
  • Sandeep Lopez

    (QA Instructional Designer, University of the People, USA; Research Scholar, Regional Institute of Education, India)

Abstract

This study explores how Cognitive Load Theory (CLT) impacts microlearning effectiveness in the Indian educational context. CLT, introduced by John Sweller in the late 1980s, suggests that cognitive capacity influences information processing. The research aims to assess cognitive load in microlearning, gauge its perceived effectiveness, examine the relationship between cognitive load and effectiveness, and explore demographic influences. A structured survey, conducted over 4 weeks with 300 participants from educational institutions and online platforms in India, revealed moderate intrinsic and extraneous cognitive load, with higher germane load. Microlearning modules were highly effective, improving knowledge retention, engagement, and learning outcomes. The study emphasizes managing cognitive engagement and minimizing extraneous load. Demographic factors, such as prior microlearning experience, also influence effectiveness. These findings underscore the importance of balanced instructional design aligned with cognitive load principles, with microlearning emerging as a potent tool for efficient learning.

Suggested Citation

  • Sandeep Lopez, 2024. "The Impact of Cognitive Load Theory on the Effectiveness of Microlearning Modules," European Journal of Education and Pedagogy, European Open Science, vol. 5(2), pages 29-35, March.
    • Handle: RePEc:epw:ejedu0:v:5:y:2024:i:2:id:30799
    DOI: 10.24018/ejedu.2024.5.2.799
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejedu/article/view/30799
    File Function: Abstract page
    Download Restriction: no
    File URL: https://eu-opensci.org/index.php/ejedu/article/download/30799/6200
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.24018/ejedu.2024.5.2.799?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:epw:ejedu0:v:5:y:2024:i:2:id:30799. 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: Support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejedu .

    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.