Collected Data for KG in RDF Triples

This dataset contains RDF triples generated from student responses to the FSLSM (Felder-Silverman Learning Style Model) questionnaire, along with Python scripts for knowledge graph construction and clustering analysis. The RDF data models individual learners' preferences, enabling semantic representation for adaptive learning systems. The Python code includes modules for generating heatmaps, dendrograms, and silhouette score visualizations to compare clustering performance. This dataset supports research in educational data mining, semantic web technologies, and personalized learning environments.