Brain Dynamics in Second Language Acquisition: Comparing the Speakers of Different Languages using EEG

This study explores the neural foundations of second language acquisition in native Arabic and Hindi speakers, employing EEG data analysis techniques. EEG data, collected from six healthy adult participants with no prior proficiency in a second language, underwent preprocessing and power spectral density (PSD) analysis to investigate differences in theta, alpha, and beta frequency bands. Machine Learning (ML) models, such as Random Forest and CNN were utilized to classify EEG signals associated with native and second language processing, achieving remarkable accuracies of $93.9 \%$ and $\mathbf{9 2 . 1 7 \%}$. The PSD analysis unveiled significant distinctions between Arabic and Hindi participants, indicating the engagement of distinct neural mechanisms during second language processing. So, demographic comparisons, encompassing age, gender, and native language, highlighted the substantial influence of these factors on second language acquisition. The study’s findings contribute to growing understanding of the brain’s plasticity during language learning and its promising implications for the development of second effectively language teaching strategies.