Plagiarism prevention or detection? The contribution of text-matching software to education about academic integrity

Abstract

Developing an understanding of academic integrity within students is one of the core objectives of many Academic Language and Learning (ALL) advisers, and the perceived rise of plagiarism suggests that this will continue to demand our attention. A recently available tool to assist advisers in this role is text-matching software (TMS). Routinely promoted on the basis of its capabilities for “plagiarism detection”, TMS also offers students educative opportunities which appropriately are web-based, given the increasing “web-dependency” of students. This paper examines how TMS can contribute to the role ALL advisers play in developing students’ understanding of academic integrity. Students from across one university were invited to submit their assignments to a TMS program called SafeAssignment™, offered as part of the university’s academic integrity policy. Text-matching reports generated from 21 students were analysed to identify the extent and nature of identifiable plagiarism, and how the software communicated this to students. Overall percentages of text-matching were low, with many students’ texts matching purely on information that was bibliographical, appropriately quoted, generic or technical. However, the quantitative information reported to the students by the software offered less assistance in determining if plagiarism had occurred than the more detailed information to be found in careful interpretation of the text-matching reports. A guide is presented for ALL advisers involved with interpreting reports with students.