Discovering Bloom Taxonomic Relationships between Knowledge Units Using Semantic Graph Triangularity Mining

摘要

Inferring Bloom's Taxonomy among knowledge units is important and challenging. This paper proposes a novel method that can identify the revised Bloom's Taxonomy levels among knowledge units in the semantic cognitive graph (SCG) by using a graph triangularity. The method determines significant relationships among knowledge units by utilizing triangularity of knowledge units in the computer science domain. We share an experiment that evaluates and validates the method on three textbooks. The performance analysis shows that the method succeeds in discovering the hidden associations among knowledge units and classifying them.