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Topological Scoring of Concept Maps for Cybersecurity Education

Published:22 February 2019Publication History

ABSTRACT

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.

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    • Published in

      cover image ACM Conferences
      SIGCSE '19: Proceedings of the 50th ACM Technical Symposium on Computer Science Education
      February 2019
      1364 pages
      ISBN:9781450358903
      DOI:10.1145/3287324

      Copyright © 2019 ACM

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      Publication History

      • Published: 22 February 2019

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      SIGCSE '19 Paper Acceptance Rate169of526submissions,32%Overall Acceptance Rate1,595of4,542submissions,35%

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