Plagiarism in Take-home Exams: Help-seeking, Collaboration, and Systematic Cheating
Open accessAbstract
Due to the increased enrollments in Computer Science education programs, institutions have sought ways to automate and streamline parts of course assessment in order to be able to invest more time in guiding students' work.
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There has been some success in using changelogs and behavioral detectors to monitor for plagiarism in programming.
“There has been some success in using changelogs and behavioral detectors to monitor for plagiarism in programming [26], but it is unclear how successful this could be in other areas of the curriculum, or whether it could be effective in detecting the use of LLM-generated content.”
From Bob or Bot: Exploring ChatGPT's Answers to University Computer Science Assessment (2024) · cites this paper as [26]
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References 29 · Cited by 50
- Authors
- Hellas, A., Leinonen, J., & Ihantola, P.
- Affiliations
- University of Helsinki (FI)
- Tampere University of Technology (FI)
- Venue
- Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education
- Publisher
- ACM
- Published
- 2017-06-28
- Pages
- 238-243
- OpenAlex
- W2728842346
- Cited by
- 50
- References
- 29
- Citations by year
- 2025: 3 · 2024: 8 · 2023: 4 · 2022: 11 · 2021: 10 · 2020: 4 · 2019: 4 · 2018: 3 · 2017: 3
- FWCI
- 9.54
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) (publishedVersion)
- Työväentutkimus Vuosikirja (submittedVersion, other-oa)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Keywords
- plagiarism, take-home exams, computer science education, automated assessment, course evaluation, academic integrity
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