Customer Feedback Management System for the Quality Assurance Office of the Pangasinan State University – Alaminos City Campus
Quality assurance serves as the foundation for educational excellence, empowering institutions to adapt and grow alongside the needs of their communities. By fostering a culture of continuous improvement, quality assurance ensures that educational services not only meet but anticipate the evolving expectations of students, faculty, and stakeholders. This study focuses on developing a Customer Feedback Management System (CFMS) to enhance quality assurance at Pangasinan State University Alaminos City Campus (PSU-ACC). To address inefficiencies in the university’s manual feedback processes, the developed system offers a centralized and automated solution designed to improve responsiveness and service quality. Located in Alaminos City, PSU-ACC implemented this system to streamline feedback collection from students, faculty, and stakeholders. The study examined current feedback practices and identified critical areas for improvement, guiding the design of targeted system features to address these needs. Developed through an iterative Agile process, the system integrates multi-channel feedback collection, real-time data analysis, and intuitive dashboards to streamline data handling. Results show that the system significantly enhances feedback processing efficiency, minimizing delays and improving data accuracy. By fostering a culture of continuous improvement and supporting data-driven decision-making, the developed system demonstrates the potential for quality-focused feedback systems to strengthen educational service delivery and stakeholder satisfaction.
Authors
- Govindasamy Bala (ORCID: https://orcid.org/0000-0002-3079-0600)
- Gomer C. Cabubas
- Aryel Jeremy M. Endaya
- Joana Rose T. Canlas
- Rodolfo Raborar
Publication Details
- Journal
- International Journal of Research and Innovation in Applied Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.51584/ijrias.2025.10030025
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00