CONSTRUCTION AND EMPIRICAL VALIDATION OF THE “FACULTY-STUDENT-AI-ENVIRONMENT-CULTURE” FIVE-ELEMENT SYNERGISTIC MODEL IN HIGHER EDUCATION: EVIDENCE FROM THE INTEGRATION OF SDG 4 AND ARTIFICIAL INTELLIGENCE

Against the backdrop of the United Nations Sustainable Development Goal 4 (SDG 4) and the rapid advancement of artificial intelligence (AI), higher education is undergoing an urgent transformation towards sustainability. To address the limitations of traditional educational models in the AI era, this study constructs a “Faculty-Student-AI-Environment-Culture” five-element synergistic model based on complex systems theory, Education for Sustainable Development (ESD) principles, and multiple interdisciplinary theories (e.g., self-determination theory, technology acceptance model). A sequential explanatory mixed-methods research design was adopted, including 431 valid questionnaires (covering 3 socio-economic regions, 6 universities, and 3 discipline categories) and 42 semi-structured interviews with faculty and students from Chinese universities. Hierarchical multiple regression, correlation analysis, interaction effect testing, mediating effect analysis, and multi-group comparison were used to verify the model's validity. The results show that: (1) The five elements collectively explain 38.5% of the variance in teaching effectiveness (Adj. R²=0.385), with Environmental Support (β=0.207, p<0.001) and AI Synergy (β=0.197, p<0.001) as the most critical drivers, followed by Student Agency Activation (β=0.169, p<0.001), Faculty Role Adaptation (β=0.167, p<0.001), and Cultural Adaptability (β=0.115, p=0.008); (2) AI Synergy significantly moderates the relationship between Environmental Support and teaching effectiveness (β=0.103, p=0.012), and partially mediates the effect of Environmental Support on teaching effectiveness (indirect effect=0.087, 95% CI=[0.042, 0.141]); (3) Faculty Role Adaptation positively moderates the relationship between Student Agency Activation and teaching effectiveness (β=0.092, p=0.023); (4) There are significant differences in the five-element scores across regions (F=3.217, p=0.041) and teacher age groups (F=2.895, p=0.036), but no significant differences across disciplines or institution types; (5) Group differences exist between faculty and students: faculty attach more importance to Cultural Adaptability (β=0.223, p=0.021), while students focus more on AI Synergy (β=0.215, p<0.001). The study verifies the theoretical innovation and practical applicability of the five-element synergistic model, provides evidence-based guidance for global higher education institutions to promote AI-integrated sustainable transformation, and enriches the theoretical system of human-machine collaborative education aligned with SDG 4.