article

Patterns of plagiarism

Authors:

Jane HorganAuthors Info & Claims

ACM SIGCSE Bulletin, Volume 37, Issue 1

Pages 383 - 387

https://doi.org/10.1145/1047124.1047473

Published: 23 February 2005 Publication History

Abstract

We used a new technique to analyse how students plagiarise programs in an introductory programming course. This involved placing a watermark on a student's program and monitoring programs for the watermark during assignment submission. We obtained and analysed extensive and objective data on student plagiarising behaviour. In contrast to the standard plagiarism detection approaches based on pair comparison, the watermark based approach allows us to distinguish between the supplier and the recipient of the code. This gives us additional insight into student behaviour. We found that the dishonest students did not perform significantly worse than the honest students in the exams. However, when dishonest students are further classified into supplier and recipient, it emerged that the recipient students performed significantly worse than the suppliers.

References

[1]

Aiken A. Moss: A system for detecting software plagiarism. Berkeley Computer Science Department. http://www.cs.berkeley.edu/~aiken/moss.html

[2]

Aiken A. Personal communication (2004).

[3]

Brassil, J. et al. Electronic Marking and Identification. IEEE Journal on Selected Areas in Communications V13 no 8 (1995), 1495--1504.

Digital Library

[4]

Carter J. Collaboration or Plagiarism: What happens when students work together? Proceedings of ITiCSE (June 1999), 52--55.

Digital Library

[5]

Culwin, F. MacLeod, A. and Lancaster, T. Source Code Plagiarism in UK HE Computing Schools, Issues, Attitudes and Tools, South Bank University Technical Report SBU-CISM-01-02. (2001).

[6]

Daly, C. RoboProf and an introductory programming course Proceedings of ITiCSE (June 1999), 155--158.

Digital Library

[7]

Daly, C., Horgan, J. Automatic Plagiarism Detection. Proceedings of the International Conference in Applied Informatics (February 2001), 255--259. http://www.computing.dcu.ie/~cdaly/publications/2001/automaticPlagiarismDetection.pdf

[8]

Daly C., Horgan J. M. An automated learning system for Java programming. IEEE Transactions on Education, (February 2004), 10--17.

Digital Library

[9]

Harris, J. Plagiarism in Computer Science Courses. Proceedings of the Conference on Ethics in the Computer Science Age. (November 1994), 133--135.

Digital Library

[10]

Lancaster T., Culwin F. Towards an Error Free Plagiarism Detection System. Proceedings of ITiCSE. (June 2001), 57--60.

Digital Library

[11]

Plauger, P. J. Fingerprints, Embedded Systems Programming. (June 1994), 84--87.

[12]

Prechelt, L., Malpohl, G., Philippsen M., JPlag: Finding Plagiarisms among a Set of Programs, Technical Report 2000-1, Fakultät für Informatik, Universität Karlsruhe, (2000).

[13]

Reilly, J. Understanding statistics and its application in business, science and engineering. Folens, 1997.

[14]

Roberts, E. Strategies for Promoting Academic Integrity in CS Courses. 32nd ASEE/IEEE Frontiers in Education (November 2002) http://fie.engrng.pitt.edu/fie2002/papers/1125.pdf

[15]

Sheard J. et al. Cheating and Plagiarism: Perceptions and Practices of First Year IT Students. Proceedings of ITiCSE (June 2002), 183--187.

Digital Library

[16]

Wagner, N. Plagiarism by Student Programmers, http://www.cs.utsa.edu/~wagner/pubs/plagiarism0.html

[17]

Zobel J. "Uni cheats racket": a case study in plagiarism investigation. Proceedings of the sixth conference on Australian Computing Education. (2004), 357--365.

Digital Library

Cited By

Hart KMano CEdwards JDoyle MStephenson BDorn BSoh LBattestilli L(2023)Plagiarism Deterrence in CS1 Through Keystroke DataProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569805(493-499)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569805
Cheers HLin Y(2022)Identifying plagiarised programming assignments based on source code similarity scoresComputer Science Education10.1080/08993408.2022.206063333:4(621-645)Online publication date: 19-Apr-2022
https://doi.org/10.1080/08993408.2022.2060633
Mason TGavrilovska AJoyner DHawthorne EPérez-Quiñones MHeckman SZhang J(2019)Collaboration Versus CheatingProceedings of the 50th ACM Technical Symposium on Computer Science Education10.1145/3287324.3287443(1004-1010)Online publication date: 22-Feb-2019
https://dl.acm.org/doi/10.1145/3287324.3287443
Show More Cited By

Index Terms

Patterns of plagiarism
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education

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Published In

cover image ACM SIGCSE Bulletin

ACM SIGCSE Bulletin Volume 37, Issue 1

2005

562 pages

ISSN:0097-8418

DOI:10.1145/1047124

Issue’s Table of Contents

SIGCSE '05: Proceedings of the 36th SIGCSE technical symposium on Computer science education
February 2005
610 pages
ISBN:1581139977
DOI:10.1145/1047344
Conference Chairs:
Wanda Dann
Ithaca College
,
Tom Naps
University of Wisconsin - Oshkosh
,
Program Chairs:
Paul Tymann
Rochester Institute of Technology
,
Doug Baldwin
SUNY Geneseo

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 February 2005

Published in SIGCSE Volume 37, Issue 1

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Cited By

Hart KMano CEdwards JDoyle MStephenson BDorn BSoh LBattestilli L(2023)Plagiarism Deterrence in CS1 Through Keystroke DataProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569805(493-499)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569805
Cheers HLin Y(2022)Identifying plagiarised programming assignments based on source code similarity scoresComputer Science Education10.1080/08993408.2022.206063333:4(621-645)Online publication date: 19-Apr-2022
https://doi.org/10.1080/08993408.2022.2060633
Mason TGavrilovska AJoyner DHawthorne EPérez-Quiñones MHeckman SZhang J(2019)Collaboration Versus CheatingProceedings of the 50th ACM Technical Symposium on Computer Science Education10.1145/3287324.3287443(1004-1010)Online publication date: 22-Feb-2019
https://dl.acm.org/doi/10.1145/3287324.3287443
Modiba PPieterse VHaskins B(2016)Evaluating plagiarism detection software for introductory programming assignmentsProceedings of the Computer Science Education Research Conference 201610.1145/2998551.2998558(37-46)Online publication date: 4-Jul-2016
https://dl.acm.org/doi/10.1145/2998551.2998558
Sheahen DJoyner DHaywood JAleven VKay JRoll I(2016)TAPSProceedings of the Third (2016) ACM Conference on Learning @ Scale10.1145/2876034.2893435(285-288)Online publication date: 25-Apr-2016
https://dl.acm.org/doi/10.1145/2876034.2893435
Ji JWoo GCho H(2009)Automated Detecting and Tracing for Plagiarized Programs using Gumbel Distribution ModelThe KIPS Transactions:PartA10.3745/KIPSTA.2009.16A.6.45316A:6(453-462)Online publication date: 31-Dec-2009
https://doi.org/10.3745/KIPSTA.2009.16A.6.453
Hickman HMcKeown PBell T(2023)Beyond Question Shuffling: Randomization Techniques in Programming Assessment2023 IEEE Frontiers in Education Conference (FIE)10.1109/FIE58773.2023.10342976(1-9)Online publication date: 18-Oct-2023
https://doi.org/10.1109/FIE58773.2023.10342976
Riese EBälter O(2022)A Qualitative Study of Experienced Course Coordinators’ Perspectives on Assessment in Introductory Programming Courses for Non-CS MajorsACM Transactions on Computing Education10.1145/351713422:4(1-29)Online publication date: 15-Sep-2022
https://dl.acm.org/doi/10.1145/3517134
Brennan KBlum-Smith SPeters LKang J(2021)Designing for Student-Directedness: How K–12 Teachers Utilize Peers to Support ProjectsACM Transactions on Computing Education10.1145/347651522:2(1-18)Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1145/3476515
Albluwi I(2019)Plagiarism in Programming AssessmentsACM Transactions on Computing Education10.1145/337115620:1(1-28)Online publication date: 9-Dec-2019
https://dl.acm.org/doi/10.1145/3371156
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