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Abstract
Mathematics education emphasizes Higher-Order Thinking Skills (HOTS) to enhance students’ problem-solving and analytical reasoning. However, students often struggle with HOTS-based mathematical tasks, and the cognitive mechanisms underlying these challenges remain unclear. This experimental study employs electroencephalography (EEG) to investigate the neural correlations of HOTS engagement by analyzing brainwave activity during mathematical problem-solving. A sample of 24 secondary school students, stratified into high, moderate, and low achievers, based on prior mathematics performance, assigned to either the experimental group (HOTS tasks) or the control group (non-HOTS tasks) to assess differences in cognitive engagement. Both groups completed tasks within 30 minutes while their brain activity was recorded using an 8-channel EEG system. The EEG data was analyzed using Neuron-Spectrum.NET to extract power spectral densities in beta (13 - 30Hz), alpha (8 - 12Hz), and theta (4 - 7Hz) frequency bands, with a focus on frontal, parietal and occipital regions. Findings reveal distinct neurocognitive patterns across achievement levels: high-achieving students exhibited strong beta wave activity in prefrontal cortex, suggesting efficient executive function and logical reasoning. Moderate achievers showed increased alpha and beta activity in occipital region, indicating reliance on visual-spatial processing. Low achievers demonstrated heightened frontal theta activity, associated with cognitive effort and working memory overload. The study’s integration of EEG methodology with educational research offers actionable insights into designing neuroscience-informed pedagogical interventions tailored to students’ cognitive profiles. These findings provide empirical, brain-based evidence that can inform personalized learning approaches, teacher training, and curriculum design-key priorities in modern education. This study not only advances the integration of neuroscience and education but also offers actionable insights for policymakers seeking to enhance 21st century competencies through evidence-based instruction.
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Article Type: Research Article
INT ELECT J MATH ED, Volume 20, Issue 4, November 2025, Article No: em0852
https://doi.org/10.29333/iejme/16889
Publication date: 01 Oct 2025
Online publication date: 07 Sep 2025
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