Automated grading system with student performance analytics
DOI:
https://doi.org/10.47577/technium.v30i.12871Abstract
Introduction. The Automated Grading System with Student Performance Analytics was developed to address the challenges and inefficiencies in traditional grading systems at educational institutions. The system aims to automate the grading process while offering robust analytics to track student performance, helping educators make data-driven decisions to enhance teaching strategies and improve student outcomes.
Product Description. This system operates through a web-based platform that ensures accessibility for both teachers and students, regardless of the device used. It automates the grading of assignments, quizzes, exams, and other academic assessments, significantly reducing administrative workload and enhancing grading accuracy. Additionally, the system incorporates performance analytics, allowing educators to generate comprehensive reports and track student progress over time. This functionality is essential in providing real-time insights into areas where students may need additional support, contributing to a more personalized learning experience.
System Features. The key features of the system include an intuitive user interface, automated grading based on customizable criteria, role-based access control, and offline-online integration. It supports both online and offline modes to ensure consistent access, even in areas with limited internet connectivity. Data security is prioritized with encrypted storage and secure communication protocols, ensuring the privacy of student information.
External Interface Requirements. The user interface of the Automated Grading System for Colegio De Santa Rita is designed to be intuitive, responsive, and accessible through any modern web browser, ensuring ease of use for teachers, administrators, and students. Developed using HTML, CSS, JavaScript, and Bootstrap, the system includes essential modules such as secure login with role-based access, student enrollment management, teacher profile administration, and subject load assignments. These modules streamline academic operations by ensuring accurate data handling, efficient teaching assignments, and secure access to relevant information. To support optimal system performance and reliability, the server hardware requirements include a multi-core 64-bit processor, a minimum of 4GB RAM, SSD storage, and an LED monitor with high resolution, ensuring smooth functionality and responsiveness of the system across all user tasks.
Other Nonfunctional Requirements. The Automated Grading System with Student Performance Analytics emphasizes performance, safety, security, and software quality to ensure seamless functionality and user satisfaction. Performance requirements ensure the system responds efficiently, supports multiple users, and maintains functionality across various platforms. Safety and security are reinforced through data protection measures, including regular backups and role-based access controls, while a built-in data backup feature allows users to download SQL copies to prevent data loss. The installation process includes deploying XAMPP, Composer, and Git to support smooth system management and updates. Software quality attributes such as operability, simplicity, modularity, and communicativeness were rated highly, confirming a user-friendly and adaptable system. Comprehensive testing functional, usability, performance, and security further ensure system reliability, scalability, and secure operations across user groups.
Project Management. The Automated Grading System with Student Performance Analytics incorporates recommended hardware and software to ensure system efficiency and reliability. These include Windows-based servers with SSD storage and sufficient RAM, modern client devices with internet access, and development tools such as XAMPP, Visual Studio Code, Git, and MariaDB. Key user roles registrar, teachers, and students are defined with role-based access to ensure security, usability, and data integrity. A comprehensive feasibility assessment confirms the system's technical, operational, economic, legal, and sustainability viability, highlighting benefits such as improved grading efficiency, cost-effectiveness through open-source tools, and secure data handling. Time management follows a structured timeline encompassing planning, design, development, testing, deployment, and maintenance, ensuring timely and quality implementation. Communication and coordination are sustained through consistent collaboration between the researchers, developers, and school stakeholders, ensuring the system meets institutional requirements and educational objectives.
Summary. The Automated Grading System with Student Performance Analytics streamlines academic evaluation by automating grade computation, enabling efficient performance tracking, and offering a user-friendly interface for educators and students. The system reduces manual grading efforts, improves data accuracy, and supports real-time feedback. With role-based access control and integrated performance reports, it enhances academic decision-making and fosters personalized learning experiences. The implementation proved effective in addressing traditional grading inefficiencies and elevating the institution’s academic management processes.
Recommendation. To further enhance system effectiveness, future development should focus on integrating advanced analytics features such as predictive modeling and trend analysis to support data-driven educational strategies. Comprehensive training for educators and students, along with a dedicated technical support team, is essential for optimal system use. Regular upgrades to hardware and software infrastructure are recommended to ensure scalability and sustained performance. Continuous system monitoring, periodic audits, and adherence to evolving data privacy regulations are crucial for maintaining security and compliance. Establishing a user feedback loop will ensure the system remains responsive to the evolving needs of its users, and exploring regional scalability can expand its impact across other educational institution
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Copyright (c) 2025 Brittaney E. Bato, Jake R. Pomperada
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