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AI-Based Active Teaching Competency Model for Digital Business Education and Tech-Startup Ecosystem Development in Private Colleges |
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| รหัสดีโอไอ | |
| Creator | Ntapat Worapongpat |
| Title | AI-Based Active Teaching Competency Model for Digital Business Education and Tech-Startup Ecosystem Development in Private Colleges |
| Publisher | DR.KET INSTITUTE OF ACADEMIC DEVELOPMENT AND PROMOTION |
| Publication Year | 2569 |
| Journal Title | Journal of Social Sciences Innovations |
| Journal Vol. | 3 |
| Journal No. | 3 |
| Page no. | 19-42 |
| Keyword | AI-Based Active Teaching, Teaching Competency Model, Digital Business Education, Tech-Startup Ecosystem, Private Colleges |
| URL Website | https://so13.tci-thaijo.org/index.php/jssi/about |
| Website title | https://so13.tci-thaijo.org/index.php/jssi/about |
| ISSN | 3057-0948 |
| Abstract | This study aimed to 1) identify the components of AI-based active teaching competencies among academic staff in digital business faculties at private higher education institutions, 2) develop and validate a Buddhist-integrated AI-based Active Learning competency model for Tech-Startup education, and 3) propose practical guidelines for applying the model to interdisciplinary curricula and integrated degree programs. This quantitative study employed a survey research design. The sample consisted of 380 academic staff members from digital business faculties in private higher education institutions, selected using multi-stage sampling. Data were collected through a five-point Likert-scale questionnaire covering six competency dimensions: AI-based instructional design, AI-supported facilitation and assessment, AI literacy and ethics, Buddhist learning competency, entrepreneurial learning design, and readiness for interdisciplinary curriculum development. Descriptive statistics, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) were employed for data analysis.The findings indicated that all six competency dimensions were rated at a high level. Structural Equation Modeling demonstrated that AI-based instructional design, AI-supported facilitation and assessment, AI literacy and ethics, Buddhist learning competency, and entrepreneurial learning design significantly influenced the proposed competency model. Among these factors, Buddhist learning competency exerted the strongest effect. Furthermore, the competency model significantly enhanced readiness for interdisciplinary curriculum development, including integrated Bachelor's–Master's and Master's–Doctoral programs. The proposed model demonstrated satisfactory goodness-of-fit with the empirical data based on established model fit indices. |
