Muhammad Nurhusain
STKIP YPUP Makassar, Indonesia

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Linking mathematical literacy to teaching competence through creative thinking: evidence from prospective mathematics teachers Nur Asrawati; Andi Tenriawaru; Sirwanti; Muhammad Nurhusain
Journal of Advanced Sciences and Mathematics Education Vol. 6 No. 3 (2026): Journal of Advanced Sciences and Mathematics Education
Publisher : CV. FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/jasme.v6i3.1516

Abstract

Background: Teaching competence among prospective mathematics teachers requires not only mathematical understanding but also the ability to transform such knowledge into flexible and context-responsive pedagogical decisions. Creative thinking may provide a critical pathway connecting mathematical literacy with teaching competence. Aims: This study investigated the mediating role of creative thinking in the relationship between mathematical literacy and teaching competence among prospective mathematics teachers. Method: An explanatory cross-sectional survey involved 149 sixth-semester prospective mathematics teachers. Data were collected through five-point Likert-scale measures and analyzed using partial least squares structural equation modeling (PLS-SEM) with 3,000 bootstrap resamples. Results: Mathematical literacy was strongly associated with creative thinking (β = 0.907, p < .001), which was significantly associated with teaching competence (β = 0.762, p < .001). The direct relationship between mathematical literacy and teaching competence was nonsignificant (β = 0.178, p = .077), whereas the indirect relationship through creative thinking was significant (β = 0.691, 95% CI [0.523, 0.851]). The model demonstrated substantial explanatory and predictive capacity (R² = 0.823–0.858; Q² > .80; SRMR = 0.052). Conclusion: Creative thinking represents an important statistical pathway linking mathematical literacy with teaching competence. Given the cross-sectional and self-reported data, these findings indicate predictive associations rather than causal relationships.