Application research of psychological feedback monitored by biosensors in ideological and political education intervention for college students
Abstract
In many countries, a core component of academic instruction is ideological and political education (IPE), which aims to comprehend important political ideas, social ideals, moral reasoning, and civic responsibilities. College students’ mental health is deteriorating due to increased academic demands, social expectations, and maturity adjustment, impacting their personal growth and potential societal contributions. This research explores applying psychological feedback systems, monitored by biosensors, as an intervention tool in IPE for college students. A novel refined hippopotamus-optimized adaptive deep recurrent neural network (HO-ADRNN) is proposed to evaluate the psychological feedback. To collect information on students’ emotional and cognitive states during educational sessions by using biosensors, such as heart rate variability (HRV) monitors and electroencephalography (EEG) monitors. The data was preprocessed using data cleaning to remove noise from the obtained data. Short-Time Fourier Transform (STFT) was used to extract the features of biosensor data. The ADRNN and HO algorithms are designed for assessing psychological feedback, while RNNs offer strong skills for processing sequential data and identifying temporal correlations. The results demonstrate the proposed method allows educators to tailor their teaching methods and content delivery in response to students’ psychological conditions, fostering a more engaging and supportive learning environment. The proposed method of HO-ADRNN has achieved 98.89% in Accuracy, 94.91% in Precision, 93.96% in Recall, and 94.05% in F1 score. The HO-ADRNN model demonstrates that technology can improve students’ understanding of ideological concepts while also addressing their mental health needs.
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