Ranking the Difficulty Level of the Knowledge Units Based on Learning Dependency

Abstract

Assigning difficulty level indicators to the knowledge units helps the learners plan their learning activities more efficiently. This paper focuses on how to use the topology of a knowledge map to compute and rank the difficulty levels of knowledge units. Firstly, the authors present the hierarchical structure and properties of the knowledge map. Then they propose three hypotheses of factors influencing difficulty based on the correlation between the difficulty level of knowledge units and the learning dependency. Finally, the authors provide algorithms for ranking the knowledge units with objective and subjective difficulty scores. The experiment on the knowledge map of the “plane geometry” course shows that our algorithm can precisely calculate the difficulty level of knowledge units.