Student Management System with Artiffical Intelligences

Authors: Assistant Professor Vivek Kumar, Pratham Bansal, Shraddha Rastogi, Nida Khan, Simran Michael

Abstract: The rapid digital transformation in the education sector has created a growing need for intelligent systems that can efficiently manage student information while supporting academic success. Traditional Student Management Systems (SMS) primarily focus on maintaining records such as attendance, examination results, course enrollment, and student profiles. However, these systems often lack the capability to analyze data and provide meaningful insights for decision-making. To address this limitation, this research proposes an AI-Based Student Management System that integrates Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics to improve educational administration and student performance monitoring. The proposed system is designed to automate routine administrative tasks, reduce human errors, and enhance the overall efficiency of educational institutions. It collects and processes data related to student attendance, academic performance, assignment submissions, and classroom activities. Using machine learning algorithms, the system can predict student performance, identify students who may be at academic risk, and generate personalized recommendations for improvement. The system also includes an AI-powered chatbot that provides instant responses to student queries regarding courses, schedules, attendance, and academic progress. In addition, the system offers advanced analytical dashboards and reporting tools that assist teachers, administrators, and parents in monitoring student development. Real-time notifications and alerts help ensure timely intervention when students show signs of poor performance or irregular attendance. By leveraging predictive analytics, the proposed solution enables institutions to make data-driven decisions and improve educational outcomes. The implementation of an AI-Based Student Management System contributes to creating a smart educational environment that promotes personalized learning, effective resource management, and proactive student support. Although challenges such as data privacy, security, and implementation costs exist, the benefits of improved efficiency, accuracy, and student engagement make this approach highly valuable. The proposed system represents a significant step toward the future of intelligent educational management and digital transformation in academic institutions.

DOI: http://doi.org/