DEVELOPMENT OF AN AI-POWERED STUDENT PERFORMANCE ANALYSIS SYSTEM USING PHP

Аннотация:

The rapid expansion of educational web applications has resulted in the continuous generation of large volumes of learner-related data, including interaction logs, assessment results, and engagement indicators. While these data provide valuable insights into learning processes, many PHP-based educational platforms lack advanced analytical mechanisms capable of transforming raw data into actionable knowledge. As a result, learning analytics in such systems often remain limited to descriptive statistics and basic reporting tools. This article explores the application of artificial intelligence–supported learning analytics in educational web applications developed using PHP. The proposed approach integrates AI-based analytical components into a PHP-based platform to enable automated analysis of learner behavior, performance trends, and engagement patterns. By leveraging machine learning–driven analytics, the system aims to support data-informed instructional decisions and enhance academic monitoring without requiring substantial modifications to existing web infrastructures. The findings indicate that AI-supported learning analytics significantly enhance the analytical depth of PHP educational applications by enabling dynamic pattern detection and early identification of learning issues. The proposed framework demonstrates that artificial intelligence can be effectively combined with traditional PHP-based systems to deliver scalable and intelligent learning analytics solutions. This research contributes to educational technology by presenting a practical model for integrating AI-driven learning analytics into widely used educational web applications.