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Mathematical critical thinking ability through Brain based learning model in view of self-regulated learning Sahidun, Muh; Suyitno, Amin; Pujiastuti, Emi
International Journal of Trends in Mathematics Education Research Vol 6, No 2 (2023)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ijtmer.v6i2.213

Abstract

The method used is quantitative with a quasi-experimental design. Data collection techniques using tests and questionnaires. Data analysis techniques by testing the increase in mathematical critical thinking skills and learning independence. The results showed that there were 23 students in the control class with a moderately critical category with a percentage of 71.875%. The critical category consists of 9 students with a percentage of 28.125%. In the experimental class there are 3 students in the critical category with a percentage of 9.375%. For the very critical category there are 29 students with a percentage of 90.625%. The results of the t test show that the P-value is 0.000 0.05, there is an increase in the ability to think critically mathematically through the brain based learning model. The results of the control class self-regulated learning were 5108 with a mean value of 63.85 in the fairly independent category. The experimental class is 6114 with an average value of 76.43 in the independent category. Test results with the t test show a P-value of 0.000 0.05, meaning that the class has independent learning in the experimental class.
Optimizing Mathematical Problem-Solving Skills through Brain-Based Learning: A Neuro-Pedagogical Perspective Sahidun, Muh
Journal of Multidisciplinary Sustainability Asean Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v3i1.3413

Abstract

Background. Mathematical problem-solving requires complex cognitive processes that integrate reasoning, executive function, and emotional regulation. Persistent gaps in students’ performance suggest that conventional instructional approaches often fail to align with the brain’s natural learning mechanisms. Purpose. This study aims to examine the effectiveness of Brain-Based Learning (BBL) in optimizing mathematical problem-solving skills from a neuro-pedagogical perspective. Method. A quasi-experimental pretest–posttest control group design was employed involving 64 Grade 8 students divided into experimental and control groups. The intervention was conducted over eight weeks and integrated neuroscience-informed strategies emphasizing emotional safety, multisensory engagement, distributed practice, and metacognitive reflection. Data were collected through validated problem-solving tests, working memory assessments, and mathematics anxiety questionnaires. Results. Inferential statistical analyses revealed significant improvements in problem-solving performance in the experimental group compared to the control group (p < 0.001), with large effect sizes. Working memory capacity increased and mathematics anxiety significantly decreased among students exposed to Brain-Based Learning strategies. The findings indicate that neuro-aligned instructional design enhances both cognitive processing and affective readiness, leading to substantial gains in higher-order mathematical reasoning. Conclusion. The study concludes that Brain-Based Learning provides an evidence-based pedagogical framework capable of optimizing mathematical problem-solving performance in contemporary classrooms.