IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i3p1057-d727079.html
   My bibliography  Save this article

A Path Model of University Dropout Predictors: The Role of Satisfaction, the Use of Self-Regulation Learning Strategies and Students’ Engagement

Author

Listed:
  • Ana B. Bernardo

    (Department of Psychology, University of Oviedo, 33003 Oviedo, Spain)

  • Celia Galve-González

    (Department of Psychology, University of Oviedo, 33003 Oviedo, Spain)

  • José Carlos Núñez

    (Department of Psychology, University of Oviedo, 33003 Oviedo, Spain)

  • Leandro S. Almeida

    (Department of Educational Psychology and Special Education (DPEEE), University of Minho, 4710-057 Braga, Portugal)

Abstract

University dropout is a phenomenon that is a concern in many countries all over the world. However, although there are studies in which the direct relationship of the personal and contextual variables is observed individually to predict dropout, there is little research to know whether any of these variables mediate each other in a more dynamic and complex model. Thus, the objective of this study was to analyze the extent to which the intention to drop out of university courses is predicted by (i) satisfaction and expectations with the course, (ii) engagement with the course, and (iii) by the use of Self-Regulated Learning (SRL) strategies. Eight hundred and seventy-seven students from two Spanish universities completed the CARE questionnaire. Path analyses were performed using Mplus 8.3. The data obtained indicate that the intention to drop out is directly and significantly explained by students´ engagement (in 17.8%) and indirectly explained by the use of SRL strategies through engagement. Changes in engagement and in the use of SRL strategies were seen to be associated with satisfaction. Finally, the effect of satisfaction and the use of SRL strategies explained a proportion of students’ engagement (53.6%). It is important for research or interventions focused on students’ intention to drop out to understand that there are multiple variables that both directly and indirectly influence those intentions.

Suggested Citation

  • Ana B. Bernardo & Celia Galve-González & José Carlos Núñez & Leandro S. Almeida, 2022. "A Path Model of University Dropout Predictors: The Role of Satisfaction, the Use of Self-Regulation Learning Strategies and Students’ Engagement," Sustainability, MDPI, vol. 14(3), pages 1-10, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1057-:d:727079
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/3/1057/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/3/1057/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nannan Yan, 2024. "An Exploratory Study on the Relationship between Language Learning Attitude, Engagement, and Communication Skills Among Chinese EFL Learners," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3), pages 1317-1336, March.

    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:jsusta:v:14:y:2022:i:3:p:1057-:d:727079. 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: 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.