Development of an Online Academic Staff Evaluation System for Quality Assurance in Tertiary Institutions

Abstract

This study aims to develop an Online Academic Staff Evaluation System to enhance quality assurance in tertiary institutions. The system was designed using a multi-tier architecture, with HTML5, CSS3, JavaScript, and Bootstrap for the frontend, and Python (Django framework) with MySQL for backend processing and data management. The system was evaluated over three months using 120 participants, including students and academic staff, utilizing System Usability Scale (SUS) metrics, functional testing, and performance analysis. The system significantly improved evaluation efficiency, ensured data confidentiality, enhanced transparency in performance assessment, and improved user satisfaction. It achieved a high usability score (SUS = 78.7) and demonstrated strong reliability under synchronized user conditions. The proposed system offers a scalable, secure, and efficient solution for academic staff evaluation, with strong potential to enhance data-driven decision-making and contributing to institutional quality assurance practices.