International Journal of New Developments in Education, 2026, 8(5); doi: 10.25236/IJNDE.2026.080508.
Wang Haitao1,2,3
1Psychology, Sofia University, Palo Alto, USA
2Arts, City University of Macau, Macau, China
3Liaoyuan Vocational and Technical College, Liaoyuan, Jilin, China
As the academic burden grows, students' mental health problems are becoming more apparent. Music is a natural, safe and accepted art form, and is widely used in psychotherapy. The traditional assessment frameworks are however not suitable to measure the impact of music therapy (MT) on the mental health of students, accurately and efficiently. To compensate for this, an evaluation system of music therapy effectiveness based on support vector machine algorithms has been built. This system will automatically track and evaluate students psychological reactions to MT and adjust the MT therapy programme in real-time to provide optimal therapeutic outcomes. As experimental subjects, the students who participated in this study were students who took MT for the first time in the third year of junior high school, third year of senior high school and fourth year of college. MT sessions were held and students' psychological response data was regularly collected and compared with data from traditional evaluation methods. The final experimental outcomes showed that the AI-based MT evaluation system can attain an average evaluation accuracy of 91.25%, evaluation time of 9 minutes and 58 seconds, and cost of 42.46 USD. Overall, these findings are better than the traditional methods of evaluation for their accuracy, efficiency and cost-effectiveness.
Artificial Intelligence, Music Therapy, Student Mental Health, Efficacy Evaluation System
Wang Haitao. Music Therapy Based on Artificial Intelligence Technology for Students' Mental Health Response and Automatic Efficacy Evaluation System. International Journal of New Developments in Education (2026), Vol. 8, Issue 5: 55-63. https://doi.org/10.25236/IJNDE.2026.080508.
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