Student Knowledge Representation

Student knowledge representation focuses on modeling how students learn and understand concepts, aiming to improve personalized education and assessment. Current research emphasizes creating more accurate and interpretable models by incorporating individual student characteristics and addressing class imbalances in educational data, often using deep neural networks and techniques like knowledge distillation. These advancements enable more precise predictions of student performance and offer insights into their learning processes, ultimately leading to more effective and tailored educational interventions.