Plagiarism Detection: A Comparison of Teaching Assistants and a Software Tool in Identifying Cheating in a Psychology Course

Abstract

Essays that are assigned as homework in large classes are prone to cheating via unauthorized collaboration. In this study, we compared the ability of a software tool based on Latent Semantic Analysis (LSA) and student teaching assistants to detect plagiarism in a large group of students. To do so, we took two approaches: the first approach was in vivo; that is, we observed whether LSA and the teaching assistants could detect plagiarism during the term. The second approach was in vitro; that is, we had 14 teaching assistants and LSA evaluate, after the term had ended, a sample of N = 60 essays of which two essays were identical. Results showed that the responsible teaching assistant did not detect the duplicates during the term (in vivo) and that the majority of the teaching assistants did not notice that they had read two identical essays (in vitro). Some of them even scored the duplicates in markedly different ways. However, the duplicates were easily identified and evaluated as equally good by LSA. We conclude that using LSA can improve assessment at universities in terms of detecting plagiarism.