E Learning

E-learning research focuses on optimizing the online learning experience through personalization and engagement enhancement. Current efforts involve developing methods to assess student attention and cognitive load using multimodal data (e.g., facial expressions, physiological signals) and machine learning algorithms like convolutional neural networks and mixture Markov models to analyze student behavior and predict outcomes such as procrastination. These advancements aim to improve learning outcomes and provide valuable insights for educators and platform developers by enabling tailored learning experiences and early identification of at-risk students.