Factors predicting the mathematics anxiety of adolescents: a structural equation modeling approach

Front Psychiatry. 2024 Dec 5:15:1484381. doi: 10.3389/fpsyt.2024.1484381. eCollection 2024.

Abstract

Introduction: Mathematics anxiety (MA) is a distinct negative emotional state or trait that individuals experience when confronted with mathematical problems in everyday life and academic contexts. This study aims to identify the key predictors of MA among secondary-level students in Bangladesh.

Methods: Utilizing a quantitative cross-sectional research design, data were collected from 486 students across 89 institutions. Later, the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Results: The findings revealed that math related negative past experiences (β = 0.241, t = 4.914, p < 0.001) and a perceived lack of teacher support (β = 0.234, t = 5.440, p < 0.001) significantly contribute to students' low self-efficacy in mathematics. This low self-efficacy is further influenced by negative attitudes and test anxiety, ultimately leading to increased MA (β = 0.694, t = 22.695, p < 0.001). Additionally, cognitive challenges, particularly working memory difficulties, directly affect MA (β = 0.110, t = 2.659, p = 0.008). The study also found that negative attitudes (β = 0.347, t = 9.063, p < 0.001) and test anxiety (β = 0.251, t = 5.913, p < 0.001) independently exacerbate MA. Moreover, a lack of motivation in learning mathematics is directly influenced by this elevated level of MA (β = 0.384, t = 9.939, p < 0.001).

Discussion: Taken together, the study proposes several key recommendations and policy implications to inform the development of synchronized policies by educational authorities aimed at combatting, reducing MA among secondary-level students in Bangladesh and similar contexts.

Keywords: adolescents in Bangladesh; factors of mathematics anxiety; mathematics anxiety; mathematics performance; partial least squares structural equation modeling (PLS-SEM).

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study received funding from Institute for Advanced Research (IAR), United International University (Grant Reference: UIU-IAR-02-2022-SE-15). The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.