ABSTRACT
We analyzed 6 semesters of data from a large enrollment data structures course to identify instances of plagiarism in 4 assignments. We find that the majority of the identified plagiarism instances involve cross-semester cheating and are performed by students for whom the plagiarism is an isolated event (in the studied assignments). Second, we find that providing students an opportunity to work with a partner doesn't decrease the incidence of plagiarism. Third, while plagiarism on a given assignment is correlated with better than average scores on that assignment, plagiarism is negatively correlated with final grades in both the course that the plagiarism occurred and in a subsequent related course. Finally, we briefly describe the Algae open-source suite of plagiarism detectors and characterize the kinds of obfuscation that students apply to their plagiarized submissions and observe that no single algorithm appears to be sufficient to detect all of the cases.
- C/C+ Obfuscator. http://stunnix.com/prod/cxxo/.Google Scholar
- Clang: A C language family frontend for LLVM. http://clang.llvm.org/index.html.Google Scholar
- K. W. Bowyer and L. O. Hall. Experience using "MOSS" to detect cheating on programming assignments. In Frontiers in Education Conference, 1999. FIE'99. 29th Annual, volume 3, pages 13B3--18. IEEE, 1999. Google ScholarCross Ref
- S. Burrows, S. M. Tahaghoghi, and J. Zobel. Efficient plagiarism detection for large code repositories. Software: Practice and Experience, 37(2):151--175, 2007. Google ScholarDigital Library
- C. Collberg, C. Thomborson, and D. Low. A taxonomy of obfuscating transformations. Technical report, Department of Computer Science, The University of Auckland, New Zealand, 1997.Google Scholar
- J. L. Donaldson, A.-M. Lancaster, and P. H. Sposato. A plagiarism detection system. SIGCSE Bull., 13(1):21--25, Feb. 1981. Google ScholarDigital Library
- S. Engels, V. Lakshmanan, and M. Craig. Plagiarism detection using feature-based neural networks. SIGCSE Bull., 39(1):34--38, Mar. 2007. Google ScholarDigital Library
- M. Freire, M. Cebrián, and E. Del Rosal. AC: An integrated source code plagiarism detection environment. arXiv preprint cs.IT/0703136, 2007.Google Scholar
- D. Gitchell and N. Tran. Sim: A utility for detecting similarity in computer programs. SIGCSE Bull., 31(1):266--270, Mar. 1999. Google ScholarDigital Library
- S. Grier. A tool that detects plagiarism in pascal programs. SIGCSE Bull., 13(1):15--20, Feb. 1981. Google ScholarDigital Library
- C. J. Hwang and D. E. Gibson. Using an effective grading method for preventing plagiarism of programming assignments. SIGCSE Bull., 14(1):50--59, Feb. 1982. Google ScholarDigital Library
- Y.-C. Jhi, X. Wang, X. Jia, S. Zhu, P. Liu, and D. Wu. Value-based program characterization and its application to software plagiarism detection. In Proceedings of the 33rd International Conference on Software Engineering, ICSE '11, pages 756--765, New York, NY, USA, 2011. ACM. Google ScholarDigital Library
- J. Pierce. Algae, 2015. http://www.github.com/JonathanPierce/Algae.Google Scholar
- L. Prechelt, G. Malpohl, and M. Philippsen. Finding plagiarisms among a set of programs with jplag. J. UCS, 8(11):1016, 2002.Google Scholar
- S. Schleimer, D. S. Wilkerson, and A. Aiken. Winnowing: Local algorithms for document fingerprinting. In Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, SIGMOD '03, pages 76--85, New York, NY, USA, 2003. ACM. Google ScholarDigital Library
- J. Sheard, M. Dick, S. Markham, I. Macdonald, and M. Walsh. Cheating and plagiarism: Perceptions and practices of first year it students. SIGCSE Bull., 34(3):183--187, June 2002. Google ScholarDigital Library
- G. Whale. Software metrics and plagiarism detection. Journal of Systems and Software, 13(2):131--138, 1990. Google ScholarDigital Library
- M. Zeidner. Test Anxiety The State of the Art. Plenum Press, 1998.Google Scholar
Index Terms
- Investigating Student Plagiarism Patterns and Correlations to Grades
Recommendations
Electronic media, creativity and plagiarism
This article provides an introduction to plagiarism and the numerous negative aspects associated with it. Some examples from history have also been provided along with their outcomes. There are different types of plagiarism with varying legal and social ...
Turnitin is not the primary weapon in the campaign against plagiarism
CompSysTech '10: Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and TechnologiesThe Turnitin plagiarism detection system allows individual student assignments to be uploaded and matched for similarity with content on the web, all other assignments uploaded by institutions using the system and numerous journals. There is much ...
Computer-based plagiarism detection methods and tools: an overview
CompSysTech '07: Proceedings of the 2007 international conference on Computer systems and technologiesThe paper is dedicated to plagiarism problem. The ways how to reduce plagiarism: both: plagiarism prevention and plagiarism detection are discussed. Widely used plagiarism detection methods are described. The most known plagiarism detection tools are ...
Comments