Emotion monitoring and feedback system for ideological and political education using biosensor technology
Abstract
The use of technology to enhance educational experiences has gained significant attention, particularly in the field of emotional engagement monitoring. Active student participation can promote a greater knowledge of values, ethics, and social duties, which is particularly crucial in university ideological and political education. The research objective is to establish a biosensor-based emotional monitoring and feedback system for university ideological and political education. This research proposed a novel Battle Royale fine-tuned Deep Bidirectional Long Short-Term Memory (BR-DBiLSTM) to detect both cognitive and emotional engagement in students. The system uses a combination of biosensors to monitor physiological and behavioral indicators and collect emotional data. The feedback system uses an instructor dashboard to display emotional states and engagement levels and alerts to trigger responses if students show disengagement or stress. The data was preprocessed using Z-score normalization to reduce noise from the obtained data. Feature extraction was implemented using the Fast Fourier Transform (FFT), BR is to optimize and select the features and DBiLSTM model to improve its classification accuracy. The experimental findings show that the suggested model has a high degree of reliability in identifying cognitive and emotional involvement, with a Micro-F1 of 90.62%, Micro-P of 89.95%, and Micro-R of 88.34%. This system demonstrates the potential for enhancing engagement in ideological and political education through adaptive feedback mechanisms based on biosensor data.
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