Preventing Cheating in Hands-on Lab Assignments

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This publication doesn't include Faculty of Arts. It includes Institute of Computer Science. Official publication website can be found on muni.cz.
Authors

VYKOPAL Jan ŠVÁBENSKÝ Valdemar ŠEDA Pavel ČELEDA Pavel

Year of publication 2022
Type Article in Proceedings
Conference Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22)
MU Faculty or unit

Institute of Computer Science

Citation
Web Preprint on ArXiv.org
Doi http://dx.doi.org/10.1145/3478431.3499420
Keywords summative assessment; automatic problem generation; networking; operating systems; cybersecurity; exercise; homework; case study
Attached files
Description 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.
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