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@inproceedings{1816366,
author = {Vykopal, Jan and Švábenský, Valdemar and Šeda, Pavel and Čeleda, Pavel},
address = {New York, NY, USA},
booktitle = {Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22)},
doi = {http://dx.doi.org/10.1145/3478431.3499420},
keywords = {summative assessment; automatic problem generation; networking; operating systems; cybersecurity; exercise; homework; case study},
howpublished = {elektronická verze "online"},
language = {eng},
location = {New York, NY, USA},
isbn = {978-1-4503-9070-5},
pages = {78-84},
publisher = {ACM},
title = {Preventing Cheating in Hands-on Lab Assignments},
url = {https://arxiv.org/abs/2201.01154},
year = {2022}
}
TY - JOUR
ID - 1816366
AU - Vykopal, Jan - Švábenský, Valdemar - Šeda, Pavel - Čeleda, Pavel
PY - 2022
TI - Preventing Cheating in Hands-on Lab Assignments
PB - ACM
CY - New York, NY, USA
SN - 9781450390705
KW - summative assessment
KW - automatic problem generation
KW - networking
KW - operating systems
KW - cybersecurity
KW - exercise
KW - homework
KW - case study
UR - https://arxiv.org/abs/2201.01154
N2 - Networking, operating systems, and cybersecurity skills are exercised best in an authentic environment. Students work with real systems and tools in a lab environment and complete assigned tasks. Since all students typically receive the same assignment, they can consult their approach and progress with an instructor, a tutoring system, or their peers. They may also search for information on the Internet. Having the same assignment for all students in class is standard practice efficient for learning and developing skills. However, it is prone to cheating when used in a summative assessment such as graded homework, a mid-term test, or a final exam. Students can easily share and submit correct answers without completing the assignment. In this paper, we discuss methods for automatic problem generation for hands-on tasks completed in a computer lab environment. Using this approach, each student receives personalized tasks. We developed software for generating and submitting these personalized tasks and conducted a case study. The software was used for creating and grading a homework assignment in an introductory security course enrolled by 207 students. The software revealed seven cases of suspicious submissions, which may constitute cheating. In addition, students and instructors welcomed the personalized assignments. Instructors commented that this approach scales well for large classes. Students rarely encountered issues while running their personalized lab environment. Finally, we have released the open-source software to enable other educators to use it in their courses and learning environments.
ER -
VYKOPAL, Jan, Valdemar ŠVÁBENSKÝ, Pavel ŠEDA and Pavel ČELEDA. Preventing Cheating in Hands-on Lab Assignments. Online. In \textit{Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22)}. New York, NY, USA: ACM, 2022, p.~78-84. ISBN~978-1-4503-9070-5. Available from: https://dx.doi.org/10.1145/3478431.3499420.
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