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BRIEF RESEARCH REPORT article

Front. Psychol.
Sec. Educational Psychology
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1414563
This article is part of the Research Topic Fostering self-regulated learning View all 17 articles

Using the Fused Graphical Lasso to Explore the Motivational Self-System After a Multimedia Self-Regulated Learning Training: A Brief

Provisionally accepted
Sarah M Wolff Sarah M Wolff 1*Jonathan Hilpert Jonathan Hilpert 1Matthew L Bernacki Matthew L Bernacki 2Jeff Greene Jeff Greene 2Christy Strong Christy Strong 1
  • 1 University of Nevada, Las Vegas, Las Vegas, United States
  • 2 University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States

The final, formatted version of the article will be published soon.

    The purpose of this study is to explore the effects of a randomized control trial designed to test the effect of a brief intervention used to improve self-regulated learning (SRL) in gateway biology courses using joint estimation of graphical models. Methods: Students (N = 265; n = 136) from three sections of a hybrid-format introductory biology course were randomly assigned to participate in the multimedia science of learning to learn or a multimedia control condition. All participants completed a self-report battery of motivational measures. Course performance data was also collected. Results: Network structures of motivation variables were estimated in two sub-groups (Treatment and Control). These networks showed a high level of correspondence in the relative magnitudes of the edge weights, however there were non-trivial differences in the edge weights between groups that may be attributed to the treatment and differences in predictability. While these findings suggest meaningful differences in motivational structures, the relatively small sample size may limit the stability of the estimated network models. The SRL strategy based interventions may have positioned the students motivationally to approach the challenging exam through activating the role of value and self-efficacy in their learning. Discussion: Many of the ways analyses of typical intervention studies are conducted ignore the underlying complexity of what motivates individuals. This study provides preliminary evidence how Gaussian Graphical Modeling may be valuable in preserving the integrity of complex systems and examining relevant shifts in variations between motivational systems between groups and individuals.

    Keywords: Gaussian graphical modeling, fused graphical lasso, Motivation, self-regulated learning, Complexity

    Received: 09 Apr 2024; Accepted: 07 Feb 2025.

    Copyright: © 2025 Wolff, Hilpert, Bernacki, Greene and Strong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Sarah M Wolff, University of Nevada, Las Vegas, Las Vegas, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.