Authors : John Phillip M. Medina; Jet C. Aquino

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/yc25mbpd

Scribd : https://tinyurl.com/52w5yh98

DOI : https://doi.org/10.38124/ijisrt/26feb807

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Recognition systems play a vital role in strengthening institutional culture, motivation, and accountability in higher education institutions. However, many universities continue to rely on manual and paper-based processes, resulting in inefficiencies, data inconsistencies, and limited transparency. This study evaluates the system quality and implementation acceptability of HEI Parangal: An AI-Assisted Recognition and Awards Platform developed to centralize nomination submission, document validation, evaluation workflows, and reporting processes at the Nueva Ecija University of Science and Technology (NEUST). A quantitative descriptive-evaluative research design was employed involving IT experts and end-users from key university offices. The system was assessed using the ISO/IEC 25010 Software Product Quality Model and a structured Likert-scale instrument to measure implementation acceptability. Descriptive statistical analysis was used to interpret the evaluation results. Findings indicate that the system demonstrated high compliance with established software quality standards across key attributes, including functional suitability, performance efficiency, usability, reliability, security, compatibility, maintainability, and portability. End-users also expressed strong acceptance of the platform, particularly in terms of usability, workflow efficiency, and transparency features. The results confirm that HEI Parangal is technically robust, highly acceptable to stakeholders, and ready for institutional deployment. The study contributes empirical evidence on the evaluation of AI-assisted administrative systems in higher education and supports the use of structured quality assessment frameworks in digital transformation initiatives.

Keywords : AI-Assisted Systems, Recognition Management, Awards Platform, System Quality Evaluation, ISO/IEC 25010, Implementation Acceptability, Higher Education Institutions, Digital Transformation, Software Quality Assessment, Institutional Automation.

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