The document discusses educational data mining and a proposed Student-Staff-Tutor (SST) framework. It summarizes that: 1) Educational data mining uses techniques like predictive modeling, clustering, and relationship mining to analyze educational data and better understand student performance, behavior, and the learning process. 2) The proposed SST framework models relationships between students, staff, and tutors in higher education. 3) An experiment applied social network analysis and k-means clustering to educational data and found that tutor-student interactions and relationships improved student performance and outcomes.