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Dataset . 2021
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Dataset: Evaluating Two Approaches to Assessing Student Progress in Cybersecurity Exercises

Authors: Valdemar Švábenský; Richard Weiss; Jack Cook; Jan Vykopal; Pavel Čeleda; Jens Mache; Radoslav Chudovský; +1 Authors

Dataset: Evaluating Two Approaches to Assessing Student Progress in Cybersecurity Exercises

Abstract

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).

Related Organizations
Keywords

learning analytics, educational data mining, assessment, cybersecurity education, modeling, command-line history

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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