Educational Data

Educational data mining (EDM) leverages computational methods to analyze large datasets from educational settings, aiming to improve learning outcomes and pedagogical practices. Current research heavily utilizes machine learning, particularly deep learning architectures like Long Short-Term Memory networks (LSTMs) and transformers (e.g., BERT, GPT), for tasks such as student performance prediction, learning style identification, and the detection of engagement patterns from various data sources (e.g., text, time series). This field is significant because it offers data-driven insights to personalize learning, optimize instruction, and ensure fairness in educational systems, impacting both research and practical applications in education.