Artificial Intelligence (AI) Analytics to Enhance EdPEx Self-Assessment Quality and DataDriven Strategic Decision Making
Abstract
The research on the Study of the quality of self-assessment according to the criteria for developing educational quality towards excellence (EdPEx) has the objectives 1) to study the factors related to the quality assurance operation and the self-assessment process according to the criteria for developing educational quality towards excellence (EdPEx) 2) to find the formats, concepts, and main issues that affect the self-assessment according to the criteria for developing educational quality towards excellence (EdPEx) using a mixed research methodology. The research collected data from the sample group, including administrators, lecturers, and staff of Suan Sunandha Rajabhat University.
The quantitative findings revealed that the overall level of quality assurance system implementation and self-assessment was "high" (mean 4.02, SD = 0.48). The highest-scoring categories were organizational leadership and strategic planning, while the lowest-scoring categories were measurement, analysis, and knowledge management and implementation. A Pearson correlation analysis revealed a significant positive relationship between administrator commitment and staff engagement and the level of quality assurance system implementation (r = 0.68, p < 0.01). Multiple regression analysis indicated that administrator commitment and internal communication were key factors positively influencing quality assurance system implementation (p < 0.05) and accounted for 55% of the variance.
The qualitative findings from in-depth interviews indicated that Respondents have a basic understanding of EdPEx principles but lack a systematic understanding. Organizational leadership and governance play a crucial role in driving educational quality. Strategic planning is clear but lacks the use of evidence-based data to support decision-making. Regarding customer focus and knowledge management, there are still developments to include a central tracking system and database. Meanwhile, personnel have positive attitudes toward quality assurance but require further knowledge development.
Zenodo Doi:-10.5281/zenodo.19498912
Keywords
Education, Excellence, Self-Assessment, Artificial IntelligenceHow to Cite
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