Intelligent Student Activity and Performance Monitoring System for Online Education

As online education grows, new challenges emerge in understanding and improving student engagement. Traditional methods, such as attendance or task completion, fail to provide detailed, real time insights, especially in virtual classrooms where teachers cannot observe students directly. This research introduces an intelligent classroom management system that tracks and analyzes engagement by monitoring interactions with learning materials (e.g., videos, notes) and recording the time spent. Using custom middleware and artificial intelligence (AI), the system classifies students into performance categories poor, average, or good based on activity levels. This enables educators to identify struggling students early and provide timely support. The AI integration improves accuracy and delivers actionable insights into student productivity. User studies confirm its usefulness for online teaching and learning.