Integrating Artificial Intelligence in Computer Education to Enhance Psychological Well-being: A Study on Deep Fusion of Teaching and Mental Health Support
Zhihong LiangAbstract
Objective
This study aims to develop and evaluate a deep fusion teaching model that integrates artificial intelligence (AI) technology with computer science instruction to proactively support student mental health. The research investigates how an AI-enhanced learning environment can simultaneously improve technical skill acquisition and mitigate academic stress and anxiety.
Subjects and Methods
A mixed-methods quasi-experimental study was conducted over one academic semester with 200 undergraduate computer science majors. The experimental group (n=100) used an AI-powered platform featuring emotion-aware adaptive learning, real-time stress detection via interaction patterns, and embedded psycho-educational nudges. The control group (n=100) used a standard digital learning platform. Data were collected through pre-post surveys (measuring anxiety, self-efficacy, and engagement), system interaction logs, and focus group interviews.
Results
Students in the experimental group showed a 30% greater reduction in learning-related anxiety (p < 0.01) and a 25% higher increase in programming self-efficacy (p < 0.01) compared to controls. The AI system demonstrated 82% accuracy in identifying distress signals, triggering timely supportive interventions. Course completion rates and final exam scores were significantly higher in the experimental group. Qualitative data highlighted students' appreciation for the responsive and psychologically attuned learning environment.
Conclusions
The deep integration of AI within computer science education effectively creates a dual-focused environment that enhances both technical learning and psychological well-being. This model provides a scalable, evidence-based framework for educational institutions to address the growing mental health needs of students in high-demand STEM disciplines.
Acknowledgement
Vocational Education Teaching Reform Research Project of Gansu Province 2025 Research on the Talent Training Model of “School-Enterprise Collaboration and Integration of Learning and Performance” in Higher Vocational Performing Art Major from the Perspective of Integration of Production and Education (2025GSZYJY-074).
Corresponding Author
Zhihong Liang, Jiuquan Vocational Technical University, Jiuquan 735000, China.