GradeBoardAgent: An AI-Driven Conversational System for Academic Performance Monitoring

Abstract: Academic performance monitoring plays a vital role in improving learning outcomes and supporting informed instructional decisions. Conventional grade management systems, such as spreadsheets and static digital registers, primarily focus on data storage and provide limited analytical insight or interactive feedback. As a result, educators spend considerable time interpreting academic records manually, while students receive minimal understanding of their performance trends. This paper presents GradeBoardAgent, an AI-driven academic performance monitoring system that integrates structured data management with conversational intelligence. The system enables educators and students to interact with academic records using both a visual dashboard and natural language queries. Built using FastAPI for backend services, SQLite for persistent storage, and a generative AI model for conversational interaction, the platform supports automated insights, performance visualization, and real-time academic queries. Experimental evaluation demonstrates that GradeBoardAgent improves accessibility, reduces manual workload, and enhances transparency in academic monitoring. The proposed system highlights the practical application of conversational AI in education and illustrates how intelligent dashboards can transform static academic data into actionable insights.

Keywords: Academic Performance Monitoring, Conversational AI, Learning Analytics, FastAPI, SQLite, Intelligent Education Systems