Abstract: Understanding the relationship between cognitive load and brain activity is essential for enhancing learning outcomes, particularly in complex subjects such as calculus. Despite its significance, empirical research examining the manifestation of cognitive load in brain activity patterns remains sparse, indicating a notable gap in the literature. This study aims to investigate the correlation between brain activity and cognitive load in a cohort of 30 mathematics education students enrolled in a calculus course, utilizing electroencephalogram (EEG) recordings. A quantitative descriptive research design was employed, integrating cluster analysis and data visualization techniques to facilitate an in-depth examination. EEG recordings of theta, alpha, and beta wave activity were collected during calculus sessions, followed by the administration of a cognitive load questionnaire. Descriptive statistics were utilized to analyze the distribution of cognitive load and brain activity, while correlation analysis was conducted to explore the relationships between cognitive load and EEG parameters across the different brainwave bands. The results revealed that higher cognitive load was positively correlated with increased frequency and amplitude in the alpha and beta bands, while a negative correlation was observed with theta frequency. Furthermore, cluster analysis effectively categorized participants based on distinct EEG signal patterns associated with varying levels of cognitive load. These findings offer valuable insights for the development of personalized learning interventions tailored to individual brain activity profiles, providing a foundation for future research on adaptive learning environments.
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