📄 Abstract
This study examined data-driven leadership based on multi-source evaluation for school improvement at World Citi Colleges. A quantitative descriptive-correlational research design was used, involving thirty (30) deans and program heads from the Antipolo, Quezon City, and Guimba campuses. A unified researcher-made questionnaire was utilized as the instrument. Descriptive statistics were used to describe the demography and data-driven decision-making based on multi-source evaluation, while Spearman rank-order correlation tested the relationship between these two. Results revealed that the demography of the respondents predominantly belonged to the 25–34 age group, was relatively balanced in terms of sex, specialized in diverse fields—specifically allied health—with 2–5 years of leadership service and engaged in 11–20 relevant trainings. The results also indicated that the respondent’s data-driven decision-making based on multi-source evaluation was utilized to a very great extent, with school organization and community extension receiving the highest average mean, followed by recognition, contracts, and promotion, teaching performance, and student progress. Accordingly, results showed that there was no significant relationship between the demographic profile of the respondents and their data-driven decision-making, as all computed p-values were greater than 0.05 and correlation coefficients ranged from rho = -0.293 to rho = 0.321, indicating a very weak association, thereby accepting the null hypothesis. Based on the findings, a school improvement plan was proposed, recommending that World Citi Colleges institutionalize a Standardized Feedback and Monitoring Framework, Data-Guided Instructional Communication Enhancement Program, Faculty Advanced Learning and Certification Program, Data-Based Organizational Alignment Framework, and Data-Driven Community Extension Planning and Evaluation Framework. Future research may examine the development of school leaders’ decision-making and the impact of data-driven practices on student learning outcomes and institutional performance using qualitative and longitudinal approaches, with organizational culture, leadership style, technological readiness, and data literacy as stronger predictors of effective data-driven decision-making.
🏷️ Keywords
📚 How to Cite:
Delio P. Reyes Jr , DATA-DRIVEN LEADERSHIP: LEVERAGING MULTI-SOURCE EVALUATION FOR SCHOOL IMPROVEMENT , Volume 12 , Issue 7, July 2026, EPRA International Journal of Multidisciplinary Research (IJMR) , Pages: 244 - 251 ,