Meta-Analysis: The Effectiveness of the Realistic Problem-Based Learning Model on Elementary Students’ Critical Thinking and Mathematical Problem-Solving Skills
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965-983
Digital Object Identifier:
10.58578/ijemt.v3i3.7935
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Authors:
Ibnu Hadi1*, Sariyasa Sariyasa2, I Gusti Putu Suharta3 
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Abstract
Although realistic and context-based approaches to mathematics instruction have garnered increasing attention, empirical syntheses evaluating the overall effectiveness of the Realistic Problem-Based Learning Model (PBMR) in elementary education remain scarce. This study conducts a quantitative meta-analysis to assess the impact of PBMR on students’ critical thinking and mathematical problem-solving abilities. Guided by the PRISMA framework, a systematic review and random-effects meta-analytic model were applied to 18 eligible studies involving a total of 1,234 elementary students across various regions in Indonesia. Data were extracted using a structured coding protocol and analyzed through effect size computation (Hedges’ g), heterogeneity testing, and publication bias assessment. The results reveal that PBMR has a significant and substantial effect on critical thinking (g = 0.74) and mathematical problem-solving skills (g = 0.68), consistently outperforming conventional teaching methods. These findings support the theoretical foundation of constructivist pedagogy and Realistic Mathematics Education (RME), affirming the role of contextualized learning in facilitating both horizontal and vertical mathematization and in enhancing higher-order cognitive functions. Practically, the study positions PBMR as a pedagogical model that aligns with Indonesia’s Merdeka Curriculum and other competency-based educational reforms. It concludes that the integration of authentic, context-rich problem scenarios fosters meaningful mathematical understanding and metacognitive development. The study recommends the incorporation of extended PBMR learning cycles into instructional design and curriculum planning. Future research directions include conducting larger-scale randomized controlled trials, employing standardized assessment tools, and exploring the implementation of PBMR in digital and hybrid learning settings.
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