Designing a Curriculum Model Based on Artificial Intelligence and Purposeful Physical Activity to Enhance Learning Self-Regulation, Mental Health, and Psychological Well-Being among Students

Objective: The objective of this study was to design and validate a curriculum model based on artificial intelligence and purposeful physical activity with emphasis on enhancing learning self-regulation, mental health, and psychological well-being among students. Methods and Materials: This applied developmental study was conducted using an exploratory sequential mixed-methods design. In the qualitative phase, 20 experts in curriculum studies, educational technology, artificial intelligence in education, physical education, educational psychology, and student mental health were selected through purposive criterion-based sampling from Tehran and participated in semi-structured interviews. The interview data were analyzed using thematic analysis to extract the main dimensions, components, and indicators of the proposed curriculum model. In the quantitative phase, 384 secondary school students from Tehran were selected through multistage cluster sampling during the 2025–2026 academic year. Data were collected using a researcher-made curriculum model validation questionnaire, a learning self-regulation questionnaire, the General Health Questionnaire, and a psychological well-being scale. Data were analyzed using descriptive statistics, reliability analysis, confirmatory factor analysis, and structural equation modeling. Findings: The inferential findings showed that the final curriculum model had acceptable empirical fit. The final modified model demonstrated favorable fit indices, including χ²/df = 2.14, GFI = 0.917, AGFI = 0.901, CFI = 0.951, TLI = 0.944, RMSEA = 0.054, and SRMR = 0.043. Artificial intelligence-based curriculum components had significant direct effects on learning self-regulation, mental health, and psychological well-being. Purposeful physical activity also had significant direct effects on learning self-regulation, mental health, and psychological well-being. Learning self-regulation and mental health significantly predicted psychological well-being. The model explained 48% of the variance in learning self-regulation, 43% of the variance in mental health, and 57% of the variance in psychological well-being. Conclusion: The findings indicate that an integrated curriculum model based on artificial intelligence and purposeful physical activity can provide an effective educational framework for strengthening students’ self-regulated learning, supporting mental health, and promoting psychological well-being.