A detection process to create awareness of source-code plagiarism among students using it to pass introductory programming

Authors

  • Imelda Smit North-West University
  • Eduan Naudé North-West University
  • Busisiwe Zulu North-West University

DOI:

https://doi.org/10.17159/ijtl.v19i1.18854

Keywords:

introductory programming, source-code plagiarism, source-code plagiarism detection tool, source-code plagiarism awareness, source-code plagiarism categories

Abstract

The COVID-19 pandemic restrained the academic environment and changed the rules of the educational game; contact classes were restricted, and online assessments had to be introduced. This situation opened an opportunity for some students to use source-code plagiarism to pass coding assessments in the Introduction to Programming subject module. The focus of this paper is on making sense of this environment to establish a process to ensure that students obtain the skills they need to build on in subsequent modules. This is necessary to reach the outcomes of a computing course. Four aspects were used in establishing this source-code plagiarism awareness process in focusing on one class of students. Qualitative data were gathered by firstly requesting the class to supply feedback on their understanding of source-code plagiarism, and secondly inviting students identified as guilty of Python source-code plagiarism to start a conversation with the lecturer, which was triangulated with quantitative data regarding the success of the latter group in terms of their pass rate. Although the Measure of Software Similarity tool was instrumental in establishing a source-code plagiarism detection process, it is cumbersome and time consuming. Hence fourthly, it was compared to other available tools to determine their suitability in comparison. A refined source-code plagiarism awareness process is the resultant finding of this paper. 

Author Biographies

Imelda Smit, North-West University

Imelda Smit is a senior lecturer who works in Computing at North-West University in South Africa. Current responsibilities include lecturing Python programming to first year students, coordinating honours research projects, management of the Computer Science and Information Technology honours programme, guiding honours, master’s and doctoral post-graduate research, as well as acting as subprogramme leader of the research unit of Data Science and Computing (Vanderbijlpark Campus). Postdoctoral research interests include Reflective Practice, the philosophy of Dooyeweerd, and using technology to teach technology. The management of source code plagiarism is linked to being the guardian of promoting the ethical use of code and text in the academic computing environment of the School of Computer Science and Information Systems. 

Eduan Naudé, North-West University

Eduan Naudé graduated from North-West University, South Africa with an undergraduate degree in Information Technology, the pursuit of an honour’s degree in Computer Science & Information Technology allowed furthering academic computing knowledge which included a research study to analyse different plagiarism detection techniques. This knowledge was viewed from the perspective of an introductory Python programming class. It formed part of a larger study on academic honesty and the difficulties associated with code plagiarism in the classroom environment. Currently he is working as a full-stack web developer based in Cape Town. 

Busisiwe Zulu, North-West University

Busisiwe Zulu is a data and analytics technical consultant, she incorporates the love for technology with
the love for art and creativity – to produce unique data analysis reports. This love for data and analytics
stem from a desire to showcase artistic inspiration with a career in technology. Through this work she can
combine storytelling with trends in data – by developing reports that are smart and convenient for clients.
By studying and learning the associated skills, she obtained an undergraduate degree in Information
Technology and an honours degree in Computer Science & Information Technology. The honours course
included a research project which focused on the impact of source code copying practices used by
students to pass an introductory programming course, on student progress.

References

Bhosale, U. (2022). Best Plagiarism Checker Tool for Researchers- Top 4 to Choose From! Retrieved 2 February 2024 from https://www.enago.com/academy/best-plagiarism-checker-tool-for-researchers/

Cheers, H., Lin, Y., & Smith, S. P. (2021). Academic Source-code Plagiarism Detection by Measuring Program Behavioural Similarity. School of Electrical Engineering & Computing, 1-18.

Codequiry. (2021). The effectiveness of Codequiry's code plagiarism checking tool. Retrieved 2 February 2024 from https://codequiry.com/code-plagiarism-checker

CopyLeaks. (2021). Origin of CopyLeaks. Retrieved 2 February 2024 from https://copyleaks.com/about-copyleaks

Cosma, G. & Joy, M. (2008). Towards a definition of source-code plagiarism. IEEE Transactions on Education, 51(2), 195-200.

Erkaya, O. R. (2009). Plagiarism by Turkish students: Causes and solutions. Asian EFL journal, 11(2), 86-103.

Erlingsson, C. & Brysiewicz, P. (2017). A hands-on guide to doing content analysis. African journal of emergency medicine, 7(3), 93-99.

Gomes, A. & Mendes, A. J. (2007). Learning to program - difficulties and solutions. International Conference on Engineering Education – ICEE, 7, 1-5.

Hage, J., Rademaker, P., & Vugt, N. (2010). A comparison of plagiarism detection tools. Department of Information and Computing Sciences, Utrecht University. Utrecht, The Netherlands, 28(1), 1-10.

Helminen, J. & Malmi, L. (2010). Jype-a program visualization and programming exercise tool for Python. Paper presented at the Proceedings of the 5th international symposium on Software visualization. Salt Lake City, Utah, USA. 25 October.

Joy, M., Cosma, G., Yau, J. Y.-K. & Sinclair, J. (2010). Source-code plagiarism—a student perspective. IEEE Transactions on Education, 54(1), 125-132.

Joy, M., Cosma, G., Yau, J. Y.-K. & Sinclair, J. (2011). Source-code Plagiarism—A Student Perspective. IEEE Transactions on Education, 54(1), 124-132.

Karnalim, O. (2017). Python source-code plagiarism attacks on introductory programming course assignments. Themes in Science Technology Education, 10(1), 17-29.

Lambert, K. A. (2018). Fundamentals of Python: first programs: Cengage Learning.

Maharajh, L. R. (2020). Exploring university students’ perceptions of plagiarism: a focus group study. Proceedings of the International Conference on Multidisciplinary Research, Moka, Mauritius.

Martins, V. T., Fonte, D., Henriques, P. R. & Cruz, D. d. (2014). Plagiarism Detection: A Tool Survey and Comparison. 144-158. https://doi:

Maryono, D., Yuana, R. & Hatta, P. (2019). The analysis of source-code plagiarism in basic programming course. Paper presented at the Journal of Physics: Conference Series 1193 https://iopscience.iop.org/article/10.1088/1742-6596/1193/1/012027/pdf

Miller, D. T., Visser, P. S. & Staub, B. D. (2005). How surveillance begets perceptions of dishonesty: the case of the counterfactual sinner. Journal of Personality Social Psychology, 89(2), 117.

Myers, M. D. (1997). Qualitative Research in IS. MIS quarterly, 21(2), 241-242.

Newton, D. (2020). Another problem with shifting education online: A rise in cheating. The Washington Post. Retrieved 2 February 2024 from https://www.washingtonpost.com/local/education/another-problem-with-shifting-education-online-a-rise-in-cheating/2020/08/07/1284c9f6-d762-11ea-aff6-220dd3a14741_story.html

Newton, P. M. & Essex, K. (2023). How common is cheating in online exams and did it increase during the pandemic? A Systematic Review. Journal of Academic Ethics, 2023, 1-21.

Ngo, M. N. (2016). Eliminating plagiarism in programming courses through assessment design. International Journal of Information Education Technology, 6(11), 873.

Shahabi, M. (2012). Comparing Three Plagiarism Tools (Ferret, Sherlock, and Turnitin). Mitra Shahabi International Journal of Computational Linguistics (IJCL), 3(1), 53-66.

Smit, I. (2022). The Value of the Measure of Software Similarity Tool in the Assessment of Introductory Programming-Making Sense of a Changing World. Proceedings of the International Conference on Teaching, Assessment and Learning in the Digital Age, Durban, South Africa.

Thurmond, V. A. (2001). The point of triangulation. Journal of nursing scholarship, 33(3), 253-258.

Vom Brocke, J., Hevner, A., Maedche, A. (2020). Introduction to Design Science Research. In: Vom Brocke, J., Hevner, A., Maedche, A. (Eds) Design Science Research. Cases. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-030-46781-4_1

Yang, D. (2019). How MOSS works. Retrieved 2 February 2024 from https://yangdanny97.github.io/blog/2019/05/03/MOSS

Younas, R. (2021). List Of Best Code Plagiarism Checkers In 2021. Retrieved 2 February 2024 from https://ssiddique.info/list-of-best-code-plagiarism-checkers.html

Zarfsaz, E. & Ahmadi, R. (2017). Investigating some main causes and reasons of writing plagiarism in an EFL context. International Journal of Applied Linguistics and English Literature, 6(5), 214-223.

Downloads

Published

21-05-2024

How to Cite

Smit, I., Naudé, E., & Zulu, B. (2024). A detection process to create awareness of source-code plagiarism among students using it to pass introductory programming. The Independent Journal of Teaching and Learning, 19(1), 79–92. https://doi.org/10.17159/ijtl.v19i1.18854

Issue

Vol. 19 No. 1 (2024): The Independent Journal of Teaching and Learning

Section

Articles

License

Copyright (c) 2024 The Independent Journal of Teaching and Learning

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.