Automated Feedback for Participants of Hands-on Cybersecurity Training
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00131829" target="_blank" >RIV/00216224:14330/23:00131829 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10639-023-12265-8" target="_blank" >https://link.springer.com/article/10.1007/s10639-023-12265-8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10639-023-12265-8" target="_blank" >10.1007/s10639-023-12265-8</a>
Alternative languages
Result language
angličtina
Original language name
Automated Feedback for Participants of Hands-on Cybersecurity Training
Original language description
Computer-supported learning technologies are essential for conducting hands-on cybersecurity training. These technologies create environments that emulate a realistic IT infrastructure for the training. Within the environment, training participants use various software tools to perform offensive or defensive actions. Usage of these tools generates data that can be employed to support learning. This paper investigates innovative methods for leveraging the trainee data to provide automated feedback about the performed actions. We proposed and implemented feedback software with four modules that are based on analyzing command-line data captured during the training. The modules feature progress graphs, conformance analysis, activity timeline, and error analysis. Then, we performed field studies with 58 trainees who completed cybersecurity training, used the feedback modules, and rated them in a survey. Quantitative evaluation of responses from 45 trainees showed that the feedback is valuable and supports the training process, even though some features are not fine-tuned yet. The graph visualizations were perceived as the most understandable and useful. Qualitative evaluation of trainees' comments revealed specific aspects of feedback that can be improved. We publish the software as an open-source component of the KYPO Cyber Range Platform. Moreover, the principles of the automated feedback generalize to different learning contexts, such as operating systems, networking, databases, and other areas of computing. Our results contribute to applied research, the development of learning technologies, and the current teaching practice.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Education and Information Technologies
ISSN
1360-2357
e-ISSN
1573-7608
Volume of the periodical
2023
Issue of the periodical within the volume
11
Country of publishing house
US - UNITED STATES
Number of pages
30
Pages from-to
1-30
UT code for WoS article
001091913600002
EID of the result in the Scopus database
2-s2.0-85175379464