IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v14y2024i4p21582440241305082.html
   My bibliography  Save this article

Working Memory Load, Automaticity, and Problem Solving in College Engineering Students: Two Applications

Author

Listed:
  • Yi Ding
  • Qian Wang
  • Ru-De Liu
  • Jolene Trimm
  • Jiayi Wang
  • Shu Feng
  • Wei Hong
  • Xian-Tong Yang

Abstract

The paper examined the relations among problem solving, automaticity, and working memory load (WML) by changing the difficulty level of task characteristics through two applications. In Study 1, involving 68 engineering students, a 2 (automaticity) × 2 (WML) design was utilized for arithmetic problems. In Study 2, involving 76 engineering students, a 2 (automaticity) × 2 (WML) design was used for linear algebra tasks. In both studies, there were statistically significant main effects and interaction effects of automaticity and WML on the variable of response time, concurring with the cognitive load theory. The simple effect of WML rendered a larger effect size under the conditions with low automaticity. When the testing condition was easy but contained more steps, the students were more accurate, and response times were faster. When the testing condition was difficult but contained fewer steps, the students were less accurate, and response times were slower. The findings underscore the important role of automaticity in helping engineering students bypass the limits of working memory.

Suggested Citation

  • Yi Ding & Qian Wang & Ru-De Liu & Jolene Trimm & Jiayi Wang & Shu Feng & Wei Hong & Xian-Tong Yang, 2024. "Working Memory Load, Automaticity, and Problem Solving in College Engineering Students: Two Applications," SAGE Open, , vol. 14(4), pages 21582440241, December.
  • Handle: RePEc:sae:sagope:v:14:y:2024:i:4:p:21582440241305082
    DOI: 10.1177/21582440241305082
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440241305082
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440241305082?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
    ---><---

    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:sae:sagope:v:14:y:2024:i:4:p:21582440241305082. 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: SAGE Publications (email available below). General contact details of provider: .

    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.