Honors Theses and Capstones

Date of Award

Spring 2023

Project Type

Senior Honors Thesis

College or School



Electrical and Computer Engineering

Program or Major

Electrical Engineering

Degree Name

Bachelor of Science

First Advisor

Ronald Croce

Second Advisor

Wayne Smith

Third Advisor

Mauricio Pulecio


Second language proficiency may be predicted with electrophysiological techniques. In a machine learning application, this electrophysiological data may be used for language instructors and language students to assess their language learning. This study identifies how electroencephalogram (EEG) power spectrum and cross spectrum data of the brain cortex relates to Spanish second language (L2) proficiency of 20 Spanish language students of varying proficiency levels at the University of New Hampshire. The two metrics for assessing cortical power and processing were event-related desynchronization (ERD)—a measure of relative change in power—of the alpha (8-12 Hz) brain frequency band, and alpha and beta (13-30Hz) brain frequency band coherence—a relative measure of spectral correlation between two cortical areas, respectively. Alpha ERD and alpha and beta coherence were calculated from EEG data collected on participants of ACTFL Spanish L2 proficiency levels Novice, Intermediate, and Advance while listening to three audio conditions of varying Spanish language difficulty. Significant differences in both alpha and beta coherence were found between proficiency groups. Higher proficiency Spanish L2 students exhibited more bilateral alpha and beta coherence dominance in the frontal and central cortices while the lower proficiency Spanish L2 students demonstrated greater unilateral alpha and beta coherence between the posterior cortices and Broca and Wernicke’s Area. This suggests that higher proficiency simultaneous bilinguals utilize the frontoparietal and fronto-occipital networks for achieving language comprehension and focus.