Predicting Mathematical Performance Based on Positive and Negative Emotions with the Mediating Role of Mathematical Self-Efficacy in Students

Abstract

Purpose: The present study aimed to predict students' mathematical performance based on positive and negative emotions, with the mediating role of mathematical self-efficacy.

Methodology: This study employed a correlational design using structural equation modeling. The statistical population included all second-grade high school students in Tehran during the 2023–2024 academic year. A multi-stage cluster sampling method was used, and 341 students were selected as the final sample. Data collection instruments included a general mathematics achievement test developed by teachers, the Positive and Negative Affect Schedule (Watson et al., 1988), and the Mathematics Self-Efficacy Scale (Midgley & Middleton, 1997). Data analysis was conducted in two stages (descriptive and inferential) using SPSS-27 and AMOS-27.

Findings: Structural equation modeling results revealed that positive emotions had a significant direct effect on mathematical performance (β=0.16, p<0.001), and also an indirect effect through mathematical self-efficacy (β=0.15, p<0.001). In contrast, negative emotions had a significant direct negative effect on mathematical performance (β=-0.17, p<0.001), as well as an indirect negative effect mediated by reduced self-efficacy (β=-0.12, p=0.009). Model fit indices, including RMSEA (0.05) and CFI (0.95), indicated a satisfactory fit.

Conclusion: Enhancing positive emotions and strengthening mathematical self-efficacy can significantly improve students' math performance. In contrast, negative emotions reduce performance by undermining self-efficacy. These findings provide an empirical foundation for designing effective instructional strategies in mathematics education.