Development of an AI-Based Digital Report Card Information System for Automated Student Progress Description Generation Using the Waterfall Method

Abstract

The preparation of early childhood student report cards is still predominantly performed manually, resulting in time-consuming administrative processes, inconsistent narrative assessments, and increased teacher workload. Despite the growing adoption of educational information systems, limited studies have integrated Generative Artificial Intelligence (AI) to automate developmental narrative generation in early childhood education. This study aims to develop a web-based Digital Report Card Information System that integrates the Gemini API to automatically generate individualized developmental narratives based on teachers' assessment data. The system was developed using the Waterfall software development methodology, encompassing requirements analysis, system design, implementation, and testing. PHP and MySQL were used to develop the application, while the Gemini API generated narrative evaluations according to predefined developmental assessment indicators. The resulting system provides comprehensive functionalities, including student, teacher, and class management, developmental assessment, anecdotal records, principal approval, parent access, and automated digital report card generation. System implementation demonstrates that the proposed solution streamlines report preparation, facilitates assessment data management, and produces more consistent developmental narratives, thereby supporting academic administrative services at PAUD Terpadu Restu 2. These findings demonstrate the potential of integrating Generative AI into educational information systems to support digital transformation and improve assessment practices in early childhood education.