⚡ Quick Summary
This study explored the integration of narrative simulation and visual AI in university teaching management to enhance mental health literacy and emotional resilience among students. The findings revealed significant improvements in students’ mental health scores (p < 0.01) and emotional awareness.
🔍 Key Details
- 📊 Participants: 332 undergraduate students and 15 faculty members
- 🧩 Methodology: Mixed-methods design with pre- and post-intervention surveys
- ⚙️ Technology: Narrative decision-making module and AI-powered emotion recognition tool
- 🏆 Key Findings: Statistically significant improvements in mental health scores and emotional awareness
🔑 Key Takeaways
- 📚 Innovative Approach: Combining narrative simulation with visual AI offers a unique method for teaching mental health.
- 💡 Emotional Insight: The AI tool provides real-time emotional data, enhancing classroom engagement.
- 👩🏫 Faculty Involvement: 15 faculty members participated, indicating a collaborative approach to mental health education.
- 🏆 Significant Results: Improvements in mental health scores were statistically significant (p < 0.01).
- 🌍 Scalability: The integrated system is suitable for institutions with AI-capable classrooms.
- 🧠 Focus on Resilience: The study emphasizes building emotional resilience among students.
- 📈 Data Collection: Usage logs and real-time emotional data were key components of the evaluation.
- 🔍 Ethical Oversight: Trained ethical oversight is essential for implementing such technologies.
📚 Background
University students are increasingly facing mental health challenges, including anxiety, depression, and stress. Unfortunately, many higher education environments lack proactive systems for emotional monitoring and support. This study aims to address these gaps by integrating innovative technologies into teaching management.
🗒️ Study
Conducted across multiple universities, this study involved 332 undergraduate students and 15 faculty members. The researchers designed a hybrid teaching management system that integrates a narrative decision-making module simulating stress scenarios with an AI-powered emotion recognition tool based on facial expression detection.
📈 Results
The results indicated that the integrated approach led to statistically significant improvements in students’ mental health scores (p < 0.01), emotional awareness, and decision-making confidence. This suggests that the combination of narrative simulation and visual AI can effectively enhance mental health literacy among students.
🌍 Impact and Implications
The implications of this study are profound. By integrating narrative simulation and visual AI into teaching management, universities can create a more supportive environment for students facing mental health challenges. This approach not only enhances emotional awareness but also equips students with the skills needed to navigate stress and anxiety effectively.
🔮 Conclusion
This research highlights the potential of integrating narrative simulation and visual AI in educational settings to build mental health capacity among university students. As institutions continue to face challenges related to student mental health, such innovative approaches could pave the way for more effective support systems. We encourage further exploration and implementation of these technologies in higher education.
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Research on Integrating Narrative Simulation and Visual AI into Teaching Management to Build Mental Health Capacity in Universities.
Abstract
University students increasingly face mental health challenges, including anxiety, depression, and stress, yet most higher education environments lack proactive systems for emotional monitoring and support. This study aimed to design, implement, and evaluate a hybrid teaching management system that integrates narrative simulation with visual artificial intelligence (AI) to promote mental health literacy and emotional resilience among students. The system includes a narrative decision-making module simulating stress scenarios and an AI-powered emotion recognition tool (based on facial expression detection) embedded in classroom settings. A mixed-methods design was employed with 332 undergraduate students and 15 faculty members from multiple universities. Pre- and post-intervention surveys, usage logs, and real-time emotional data from visual AI were collected. Quantitative data were analyzed using descriptive statistics, paired t-tests, ANOVA, and multiple linear regression. Results indicated statistically significant improvements in students’ mental health scores (p < 0.01), emotional awareness, and decision-making confidence. This integrated approach demonstrates both usability and scalability, offering instructors early emotional insight and students a reflective learning environment. The method is best suited for institutions equipped with AI-capable classrooms and trained ethical oversight.
Author: [‘Chen P’, ‘Xu C’]
Journal: J Vis Exp
Citation: Chen P and Xu C. Research on Integrating Narrative Simulation and Visual AI into Teaching Management to Build Mental Health Capacity in Universities. Research on Integrating Narrative Simulation and Visual AI into Teaching Management to Build Mental Health Capacity in Universities. 2025; (unknown volume):(unknown pages). doi: 10.3791/69016