Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
addClaim

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

Authors: Chenxiao Lyu, Kusuma Yamgate, Chananporn Areekul;

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

Abstract

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.

Keywords

Teaching Ability Assessment, Tourism Management Education, Outcome-Based Education, Collaborative Governance, Pedagogical Content Knowledge, Smart Tourism, Faculty Development, Wuhan

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average