Investigating Predictors of Academic Plagiarism among University Students

2020 
Academic plagiarism is increasingly becoming a challenge to academic integrity worldwide, owing to the ease of access to free information online. The aim of this paper was twofold; first, to ascertain the perceptions of transport and logistics management university students regarding academic plagiarism, and second, to determine the predictors of university students’ plagiarism practices. A self-designed structured questionnaire was developed to collect information from the students of their understanding of plagiarism (UP), the plagiarism practices (PP), the understanding of the university plagiarism policy (UPP), the understanding of the departmental plagiarism policy (DPP), the awareness of the university and departmental training workshops (TOP), and the adequacy of the university and departmental training workshops (AOT). Independent t- tests were computed for the differences in plagiarism, based on home language and gender. Also, a one-way ANOVA was computed to test if the year of study, the degree enrolled for, and race, had an impact on plagiarism practices. Lastly, a regression model was computed to determine the impact of the plagiarism predictors on the plagiarism practices. The results of this study revealed high-levels of the understanding of plagiarism, and an awareness of the university and departmental plagiarism policies. However, an analysis of the plagiarism practices revealed moderate levels of plagiarism, indicating a likelihood of intentional plagiarism among students. Two significant predictors of plagiarism practices among university students were identified as; the understanding of plagiarism and the understanding of the university-wide plagiarism policy. University instructors and education managers are informed through the findings of this study that clear plagiarism policies are important in reducing academic dishonesty among students. It is important to continuously train students on what plagiarism entails and how to avoid academic dishonesty. https://doi.org/10.26803/ijlter.19.12.14
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