Strategies for the Synergistic Development of University Governance Systems and Students’ Social-Emotional Competencies Based on Multimodal Learning Analysis

Against the backdrop of higher education governance shifting from “hierarchical control” to “networked co-governance,” students’ social-emotional competencies (SEC) are no longer merely individual psychological variables but have become a core indicator for measuring governance resilience. This paper proposes an “emotion–governance” coupling analysis framework. Utilizing multimodal learning analytics (MLA) technology, it integrates text, speech, facial expressions, body language, interactive behaviors, and physiological signals to construct a dynamic profile of students’ social-emotional competencies, which is then fed back into higher education governance decision-making. Through a quasi-experimental design, the study tracked 1,240 undergraduate students over one academic year. Using a cross-modal attention fusion model and multilevel linear regression, the study found that: 1) The relationship between governance rule density and SEC growth follows an inverted U-shape (inflection point λ = 0.62); 2) The emotional bond between faculty and students significantly promotes SEC development through two pathways: “emotional support → relational skills” and “academic efficacy → self-management” (β = 0.34, p < 0.01); 3) A multimodal early warning mechanism increased the identification and recall rate of high-risk students to 86.7%, representing a 19.2% improvement over a single-modal approach. Based on these findings, this paper proposes the “Adaptive Emotional Governance Network” model, providing an actionable pathway for the synergistic evolution of university governance and student development.