Development of an Intelligent Learning Evaluation System Based on Big Data

Abstract

The increasing need for effective learning evaluation in higher education is driving the development of big data-based systems to provide comprehensive insights. This research aims at developing an Intelligent Learning Evaluation System (ILES) to support team teaching and monitor the effectiveness of the learning process through pre-tests, post-tests and periodic evaluations. The system was developed using the Agile methodology, including iterative stages of requirements gathering, design, development, testing and implementation. Codeigniter is used for backend development, PostgreSQL as database. This system enables dynamic monitoring and evaluation of teaching performance and student learning outcomes. The finding showed that the Real-time data visualization and user-friendly dashboards improve decision making for faculty and administrators. Testing shows increased engagement and actionable insights for performance improvement. ILES demonstrates the potential of big data in higher education by enabling data-based decision making and driving continuous improvement in teaching and learning. Future research will explore integration with broader institutional systems and its scalability.