Preventing Cheating in Hands-on Lab Assignments

TL;DR

This paper presents an automatic problem generation method for hands-on lab assignments to personalize tasks, detect potential cheating, and improve scalability in large classes, supported by a case study with 207 students.

Contribution

It introduces software for generating personalized lab tasks, demonstrating its effectiveness in detecting cheating and its scalability for large courses.

Findings

Seven suspicious submissions identified as potential cheating

Students and instructors favored personalized assignments

Software scalable for large classes and easy to use

Abstract

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.