DEVELOPMENT OF A COLLABORATIVE TEACHING ABILITY ASSESSMENT MODEL FOR TOURISM MANAGEMENT FACULTY IN WUHAN UNIVERSITIES: A MIXED-METHODS STUDY

China’s transition from higher-education expansion to quality-oriented development has intensified scrutiny of teaching competence in application-oriented disciplines. Tourism Management is particularly exposed to this shift because it must reconcile theoretical rigor with rapidly changing industry practices (e.g., smart tourism platforms, data-driven service design, and digital marketing). Against this backdrop, Wuhan—an educational and tourism hub in Central China—faces a practical governance problem: existing faculty evaluation systems remain administrative-heavy and classroom-performance oriented, while under-measuring outcome alignment, feedback-driven improvement, and the enabling role of institutional–industry collaboration. To address this gap, this study develops and validates a localized, theory-informed assessment model for the teaching ability of Tourism Management faculty in Wuhan universities. The model is grounded in a triangulation of (a) teaching competence theory (Pedagogical Content Knowledge and its technological extension), (b) Outcome-Based Education (OBE) and constructive alignment, and (c) collaborative governance. An exploratory mixed-method design was adopted. In Phase 1, an initial pool of indicators was generated from literature and refined through expert consultation; content validity was supported by an Item-Objective Congruence index of 0.87. In Phase 2, survey data from 113 faculty members across five universities were used to evaluate the psychometric properties of a 20-item instrument. Exploratory Factor Analysis (KMO = 0.803; Bartlett’s test p < .001) supported a five-factor structure explaining 75.14% of total variance: Instructional Design Ability, Teaching Evaluation and Feedback, Professional Development, Professional Knowledge and Teaching, and Information Literacy and Technology. The scale demonstrated strong internal consistency (Cronbach’s alpha = 0.904). The results reveal a dual-speed faculty profile: theoretical and professional knowledge are relatively robust, whereas digital competence is uneven and appears stratified by age. The study contributes a diagnostic tool for developmental evaluation and proposes a collaborative implementation pathway that integrates university governance, faculty development, and industry engagement.