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This lecture covers the concept of Knowledge Tracing, focusing on Bayesian Knowledge Tracing (BKT) and Learning Curves. It explores the prediction of student knowledge over time, the use of latent variables, and the application of BKT models in educational settings, using the ASSISTments platform as a case study. The lecture delves into the inference process in BKT models, the training and prediction tasks, and the importance of measuring student performance accurately.