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Concept maps are a well-known pedagogical tool for organizing and representing knowledge and developing a deep understanding of concepts. Unfortunately, the grading of concept maps tends to be manual and tedious thereby, posing serious limitation for an instructor to use them in class efficiently. To automate the assessment and grading, the topology and structural features of concept maps are utilized. However, they have never been explored for cybersecurity education. This paper evaluates the effectiveness of topological scoring of the concept maps for two cybersecurity courses: digital forensics, and SCADA system security. We create a dataset of 41 high-quality concept maps developed with expert knowledge. We utilize waterloo rubric to manually validate the quality of the concept maps based-on their contents and further compare the rubric outcome (obtained via manual analysis) with the automated topological scoring of the maps. The evaluation results show that the topological scoring is promising. However, it is not equally effective and warrants for advanced techniques to better utilize the topology of the maps. The dataset is made publicly available for further research on this topic.

Topological Scoring of Concept Maps for Cybersecurity Education