Optimizing Mathematical Problem-Solving Skills through Brain-Based Learning: A Neuro-Pedagogical Perspective - Muh Sahidun (Yayasan Adra Karima Hubbi, 2026)
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.