Explores the impact of skipping activities on student success and the use of transition matrices and learning analytics cubes to predict student states.
Explores mastery learning, behaviorism, and instructional design, emphasizing personalized instruction and the effectiveness of Intelligent Tutoring Systems.
Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.
