Integration of School Leaders and Student Preferences in Determining the Best Teachers

Abstract

This research integrates the preferences of school leaders and students in assessing teacher performance using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) and Multi-Attributive Border Approximation Area Comparison (MABAC) methods. Conducted at SMK YADIKA 5, this quantitative study evaluated teacher performance based on various criteria, including attendance, teaching innovation, leadership, pedagogical skills, and personality. Data collection involved questionnaires for students and school leaders, interviews for deeper insights, and documentation such as attendance records and academic reports to support the evaluation. The MOORA method facilitated decision matrix normalization, criteria weighting, and optimization score calculation, while the MABAC method analyzed alternatives by measuring their distances from ideal and anti-ideal solutions. Both methods consistently identified teacher A7 as the top performer, showcasing their effectiveness in providing objective, fair, and transparent evaluations. The results highlight the practicality of these methods in educational settings to enhance teacher motivation and improve overall teaching quality. This study contributes to advancing performance evaluation frameworks in schools by integrating diverse preferences and offering actionable recommendations. Future research could expand this approach by including additional stakeholders, such as parents or administrative staff, or applying these methods to different educational institutions to further validate and refine the framework for broader use.