Artificial Intelligence (AI) is reshaping various fields, including education, but its complexity often leads to questions about trust, fairness, and transparency. In response, two crucial concepts have emerged: Explainable AI (xAI) and Interpretable AI. These terms may sound similar, but they offer distinct affordances and are critical in educational contexts where understanding predictions can drive […]
Classification is a type of machine learning task where you predict a category (or label) rather than a continuous number. For example, classifying whether an email is spam or not is a classification task, because the output is categorical (spam or not spam), not a continuous number. Neural Networks: The Building Blocks Neural networks are a […]
In educational data mining, prediction models play a critical role in analyzing student data to infer specific outcomes, known as predicted variables, from a combination of other features, referred to as predictor variables. These models are applied in various contexts: sometimes to forecast future performance, and at other times to gain insights into current states […]
In today’s data-driven world, the field of education has not been left behind. Two key communities have been at the forefront of harnessing the potential of “big data” in education are: the Educational Data Mining Society (EDM) and the Society of Learning Analytics Research (SoLAR). These groups have been instrumental in advancing our understanding of […]
