AN ADMINISTRATIVE MODEL USING COLLABORATIVE NETWORKS TO PROMOTE STUDENTS' CONTINUATION TO VOCATIONAL EDUCATION UNDER THE OFFICE OF THE VOCATIONAL EDUCATION COMMISSION: A FACTOR ANALYSIS APPROACH

Abstract

This research aimed to: 1) Examine the components of the administrative conditions of collaborative network management for promoting students' continuation to vocational education, and 2) Develop a collaborative network management model for promoting students' continuation to vocational education. A mixed-methods research design was employed. The research instruments consisted of an expert interview form, a questionnaire for investigating the components, and a questionnaire for confirming the identified components. The participants included nine experts in network management, selected through purposive sampling, and respondents for the component analysis, selected using three-stage random sampling from 13 educational institutions under the Bangkok Institute of Vocational Education. The respondents were divided into two groups: 1) 219 administrators and teachers for the exploratory factor analysis (EFA), and 2) 234 administrators and teachers for the confirmatory factor analysis (CFA). The findings revealed that: 1) The document analysis and expert interviews yielded 107 preliminary items, which were subsequently refined into 79 questionnaire items; 2) The exploratory factor analysis indicated that the 79 indicators could be classified into seven components: work competency, administrative processes, increasing stakeholder participation through collaboration with enterprises in the practical implementation of vocational education management, alumni networks supporting student inspiration and educational facilities, modern instructional management, career orientation, and strategy implementation; and 3) The confirmatory factor analysis demonstrated that the factor structure was consistent with the conceptual framework, supporting a unidimensional model. Furthermore, the model showed a good fit with the empirical data, with all statistical indices meeting the established criteria, confirming the construct validity and the goodness-of-fit of all seven components.