An intelligent model to enhance user experience in E-learning systems

E-learning systems improve day by day. Therefore, it is important to monitor and evaluate student performance to provide targeted content. This paper focuses on a model for intelligent E-learning systems that can identify student behaviors and provide personalized content recommendations. Data mining is used to analyze user interactions and patterns in E-learning systems. This analysis helps identify areas for improvement and personalize the learning experience. The paper highlights the benefits of personalized learning, increased satisfaction, early intervention, and improved content recommendation within an E-learning system. These concepts form a model for student interaction and content recommendation aspects.