Abstract
This study explores the implementation of the DeepPsy framework at a university in Hebei, China, assessing its impact on student mental health and ethical behavior. By integrating a 2D convolutional neural network (2D-CNN) with long short-term memory (LSTM) networks, DeepPsy analyzes complex online behavior patterns and academic performance data. The methodology involves diverse data collection techniques, providing a comprehensive understanding of students' mental health. Results indicate improved identification of at-risk students, leading to timely interventions and enhanced mental health outcomes. This study highlights the potential of advanced data analytics in fostering supportive educational environments that promote student mental health and ethical decision making.
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