Posted: Sep 22, 2023
This research introduces a paradigm shift in financial literacy education by developing and evaluating a neuro-adaptive learning system that dynamically adjusts educational content based on real-time cognitive and emotional responses. Traditional financial literacy programs have demonstrated limited effectiveness due to their one-size-fits-all approach and inability to account for individual cognitive differences, emotional barriers, and learning preferences. Our methodology integrates multimodal biometric feedback, including electroencephalography (EEG) for cognitive engagement measurement, galvanic skin response for emotional arousal detection, and eye-tracking for attention monitoring, to create personalized learning pathways. The system employs a hybrid artificial intelligence framework combining deep learning architectures for pattern recognition with reinforcement learning for adaptive content delivery. We conducted a six-month longitudinal study with 450 participants across three banking institutions, comparing our neuro-adaptive system against conventional educational approaches. Results demonstrate a 67
Downloads: 30
Abstract Views: 403
Rank: 18292