Evaluation of the Index of Similarity Detected by Turnitin® in Research Projects of a Master's Degree in Higher Education

Arias-Chávez D.; Ramos-Quispe T.; Lanchipa-Ale A.P.; Rivera-Mansilla E.B.; Vela J.E.Q. · CEUR Workshop Proceedings (2020)

Resumen

The objective of this study is to compile samples of errors extracted from research papers that illustrate the different conflicts in the theoretical sections after the application of the Turnitin® software. To do this, 28 theoretical sections were selected, drawn from research projects written by students of a master's degree in Higher Education at a private university in southern Peru in 2020. The design is non-experimental, cross-sectional with a quantitative approach. Descriptive statistics were used to analyze the data. The results show that with regard to the level of similarity found the documents analyzed are at level IV (50-74%), while the types of plagiarism with the greatest presence are “copy and paste” and “search and replace”. Among the sources with a high coincidence index are theses and articles from scientific journals, while the section with the highest percentage of similarity and the highest number of cases of plagiarism is the theoretical framework. In this sense, the Turnitin software® is suitable for reporting the degree of similarity in research papers as it helps to detect signs of possible cases of plagiarism.

Instituciones: Universidad Nacional de San Agustín de Arequipa; Universidad Continental; Universidad del Pacífico; Universidad Nacional Jorge Basadre Grohmann