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This repository contains supplementary materials for the following conference paper: V. Švábenský, R. Weiss, J. Cook, J. Vykopal, P. Čeleda, J. Mache, R. Chudovský, A. Chattopadhyay. Evaluating Two Approaches to Assessing Student Progress in Cybersecurity Exercises. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE 2022). https://doi.org/10.1145/3478431.3499414 Preprint available at: https://arxiv.org/abs/2112.02053 How to cite If you use or build upon the materials, please use the BibTeX entry below to cite the original paper (not only this web link). @inproceedings{Svabensky2022evaluating, author = {\v{S}v\'{a}bensk\'{y}, Valdemar and Weiss, Richard and Cook, Jack and Vykopal, Jan and \v{C}eleda, Pavel and Mache, Jens and Chudovský, Radoslav and Chattopadhyay, Ankur}, title = {{Evaluating Two Approaches to Assessing Student Progress in Cybersecurity Exercises}}, booktitle = {Proceedings of the 53rd ACM Technical Symposium on Computer Science Education}, series = {SIGCSE '22}, location = {Providence, RI, USA}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, month = {03}, year = {2022}, pages = {787--793}, numpages = {7}, isbn = {978-1-4503-9070-5}, url = {https://doi.org/10.1145/3478431.3499414}, doi = {10.1145/3478431.3499414}, } Attached content The materials include the research dataset, source code, and graphs. See the README.md file inside the attached ZIP file for more details.
This research was supported by ERDF project CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence (No. CZ.02.1.01/0.0/0.0/16_019/0000822).
learning analytics, educational data mining, assessment, cybersecurity education, modeling, command-line history
learning analytics, educational data mining, assessment, cybersecurity education, modeling, command-line history
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