Influence of Personality Traits on Plagiarism Through Collusion in Programming Assignments

Fuente: arXiv
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Autori principali: PD, Parthasarathy, Kapoor, Ishaan, Joshi, Swaroop, Thomas, Sujith
Natura: Preprint
Pubblicazione: 2024
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author PD, Parthasarathy
Kapoor, Ishaan
Joshi, Swaroop
Thomas, Sujith
author_facet PD, Parthasarathy
Kapoor, Ishaan
Joshi, Swaroop
Thomas, Sujith
contents Educating students about academic integrity expectations has been suggested as one of the ways to reduce malpractice in take-home programming assignments. We test this hypothesis using data collected from an artificial intelligence course with 105 participants (N=105) at a university in India. The AI course had two programming assignments. Plagiarism through collusion was quantified using the Measure of Software Similarity (MOSS) tool. Students were educated about what constitutes academic dishonesty and were required to take an honor pledge before the start of the second take-home programming assignment. The two programming assignments were novel and did not have solutions available on the internet. We expected the mean percentage of similar lines of code to be significantly less in the second programming assignment. However, our results show no significant difference in the mean percentage of similar lines of code across the two programming assignments. We also study how the Big-five personality traits affect the propensity for plagiarism in the two take-home assignments. Our results across both assignments show that the extraversion trait of the Big Five personality exhibits a positive association, and the conscientiousness trait exhibits a negative association with plagiarism tendencies. Our result suggests that the policy of educating students about academic integrity will have a limited impact as long as students perceive an opportunity for plagiarism to be present. We explain our results using the Fraud triangle model.
format Preprint
id arxiv_https___arxiv_org_abs_2407_15014
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Influence of Personality Traits on Plagiarism Through Collusion in Programming Assignments
PD, Parthasarathy
Kapoor, Ishaan
Joshi, Swaroop
Thomas, Sujith
Computers and Society
Educating students about academic integrity expectations has been suggested as one of the ways to reduce malpractice in take-home programming assignments. We test this hypothesis using data collected from an artificial intelligence course with 105 participants (N=105) at a university in India. The AI course had two programming assignments. Plagiarism through collusion was quantified using the Measure of Software Similarity (MOSS) tool. Students were educated about what constitutes academic dishonesty and were required to take an honor pledge before the start of the second take-home programming assignment. The two programming assignments were novel and did not have solutions available on the internet. We expected the mean percentage of similar lines of code to be significantly less in the second programming assignment. However, our results show no significant difference in the mean percentage of similar lines of code across the two programming assignments. We also study how the Big-five personality traits affect the propensity for plagiarism in the two take-home assignments. Our results across both assignments show that the extraversion trait of the Big Five personality exhibits a positive association, and the conscientiousness trait exhibits a negative association with plagiarism tendencies. Our result suggests that the policy of educating students about academic integrity will have a limited impact as long as students perceive an opportunity for plagiarism to be present. We explain our results using the Fraud triangle model.
title Influence of Personality Traits on Plagiarism Through Collusion in Programming Assignments
topic Computers and Society
url https://arxiv.org/abs/2407.15014