Dealing with Plagiarism in Introductory Programming

Louw, Daniel J.; Pieterse, Vreda

doi:10.5176/2251-2195_cseit15.7

Cited by 4 publications

(3 citation statements)

References 0 publications

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“…The institution may also choose to use a reactive method like plagiarism detection combined with disciplinary action to limit future plagiarism. Both proactive and reactive approaches and their respective techniques applied to prevent or detect plagiarism, present problems that need to be examined and addressed (Ganguly et al, 2018;Haskins & Pieterse, 2016;Louw & Pieterse, 2015;Portillo-Dominguez et al, 2017).…”

Section: Research Problemmentioning

confidence: 99%

Systematic Literature Review to Identify and Rank the Most Common Reasons for Plagiarism

2020

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Aim/Purpose: In this paper the authors explore and analyse the literature to determine the common reasons why a student may choose to plagiarise. The predominant purpose of the research formed part of a larger study to develop metrics and methods to identify potential plagiarism within coding-based assignments. Methodology: A systematic literature review with the objective to identify and rank the most common reasons for plagiarism was conducted. This was achieved by identi-fying primary studies conducted on the reasons for plagiarism. The identified studies were subsequently subjected to a top down quality assessment with a number of criteria. In total, 37 studies made it through the selection process. The results of the selected studies were synthesized to obtain a ranked list of reasons why students plagiarise. Contribution: This paper contributes a ranked list of reasons that may influence a student’s decision to plagiarise, based on a set of categories emerging from the literature. Findings: Eleven possible categories indicating the common reasons behind a student’s decision to plagiarise are identified. The literature revealed that aspects such as the external values of the student and attitudes towards academia and teaching styles are significant factors that impact a student’s willingness and decision to plagiarise. Impact on Society: Instructors may gain a better understanding on why their students decided to plagiarise.

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Section: Research Problemmentioning

confidence: 99%

Systematic Literature Review to Identify and Rank the Most Common Reasons for Plagiarism

2020

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“…The authors suggest that students who have highly similar submissions may be those who are carefully following exemplars [38]. Louw and Pieterse [37] propose that similarity between submissions is more likely in the context of introductory courses with large enrolments since it is more likely that two students will arrive at the same solution independently. However, the authors do not justify this proposition.…”

Section: Why Is Computing Different?mentioning

confidence: 99%

“…In view of the specific characteristics of the programming domain raised above, and of prevailing industry practice, students may find it difficult to understand the justification for the design of such assessment tasks. Louw and Pieterse [37] note that because the industry promotes code reuse, students should learn the skills required for responsible and effective reuse of code without being accused of plagiarism.…”

Section: Differences Between Industry and Academiamentioning

confidence: 99%

Negotiating the Maze of Academic Integrity in Computing Education

Simón

Sheard

Morgan

et al. 2016

Proceedings of the 2016 ITiCSE Working Group Reports

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Academic integrity in computing education is a source of much confusion and disagreement. Studies of student and academic approaches to academic integrity in computing indicate considerable variation in practice along with confusion as to what practices are acceptable. The difficulty appears to arise in part from perceived differences between academic practice in computing education and professional practice in the computing industry, which lead to challenges in devising a consistent and meaningful approach to academic integrity. Coding practices in industry rely heavily on teamwork and use of external resources, but when computing educators seek to model industry practice in the classroom these techniques tend to conflict with standard academic integrity policies, which focus on assessing individual achievement.We have surveyed both industry professionals and computing academics about practices relating to academic integrity, and can confirm the uncertainty and variability that permeates the field. We find clear divergence in the views of these two groups, and also a broad range of practices considered acceptable by the academics.Our findings establish a clear need to clarify academic integrity issues in the context of computing education. Educators must carefully consider how academic integrity issues relate to their learning objectives, teaching approaches, and the industry practice for which they are preparing students. To this end we propose a process that fulfils two purposes: to guide academics in the consideration of academic integrity issues when designing assessment items, and to effectively communicate the resulting guidelines to students so as to reduce confusion and improve educational practice.

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