Student Affairs Merit System: A Digital Performance Assessment System Using Rule-Based Algorithm

digital merit system, student affairs, ISO/IEC 25010, web-based evaluation, AI chatbot, extracurricular assessment

Authors

  • Nathaniel Andrei Gonzales School of Science and Technology, Centro Escolar University – Manila, Philippines
  • Xyrus Lex Pajarillaga School of Science and Technology, Centro Escolar University – Manila, Philippines
  • Jhan Robin Sy School of Science and Technology, Centro Escolar University – Manila, Philippines
  • Rhugene Villegas School of Science and Technology, Centro Escolar University – Manila, Philippines
  • Eliza B. Ayo School of Science and Technology, Centro Escolar University – Manila, Philippines
April 30, 2026

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The digitalization of student affairs processes has become essential to promoting transparency, efficiency, and fairness in higher education. This study introduces and evaluates the Student Affairs Merit System (SAMS), a web-based platform developed to modernize the evaluation of co-curricular and extracurricular activities at Centro Escolar University (CEU) Manila. The system integrates an automated merit point computation engine, an artificial intelligence (AI)–powered chatbot for user guidance, a notification module, and a role-based authentication framework within a multi-tiered validation workflow. A descriptive-developmental research design was employed. System quality was assessed using the ISO/IEC 25010 framework across seven domains: Functionality Suitability, Performance Efficiency, Compatibility, Usability, Reliability, Security, and Maintainability. Survey data were gathered from 52 end-users who rated the system on a four-point Likert scale, and responses were analyzed using descriptive statistics. All seven domains yielded mean scores within the Strongly Agree range (M = 3.73–3.81). Compatibility recorded the highest mean (M = 3.81), while Usability recorded the lowest (M = 3.73), identifying interface navigation as the primary area for refinement. The findings indicate that SAMS is a reliable, efficient, and secure digital solution that is ready for broader institutional deployment, with targeted enhancements recommended to optimize the overall user experience. The study contributes to the growing literature on digital performance assessment by demonstrating how standardized evaluation frameworks and AI-assisted guidance can be combined to support equitable merit recognition in higher education.