Medori, JDM, Atwell, ES, Gent, JP et al. (1 more author) (2002) Customising a copying-identifier for biomedical science student reports: comparing simple and smart analyses. In: O'Neill, M, Sutcliffe, R, Ryan, C, Eaton, M and Griffith, N, (eds.) Artificial Intelligence and Cognitive Science: 13th Irish International Conference, AICS 2002, Limerick, Ireland, September 12-13, 2002. Proceedings Series: Lecture Notes in Computer Science, Vol. 2464. Springer Berlin Heidelberg , 228 - 233. ISBN 978-3-540-45750-3
Abstract
The aim of our project is to develop a system for detecting student copying in Biomedical Science laboratory practical reports. We compare contrasting approaches: “simple” methods Zipping, based on a standard file-compression tool, and Bigrams, a basic comparison of frequent bigrams; and “smart” methods using commercial-strength plagiarism-checking systems Turnitin, Copycatch, and Copyfind. Both approaches successfully flag examples of copying in our Test Corpus of 218 student courseworks, but Copycatch provides more user-friendly batch-processing mechanism. Human experts go beyond word-based pattern matching, and take account of knowledge specific to our domain: methods and questions can legitimately be copied, whereas originality is more important in the Discussion section.
Metadata
Item Type: | Book Section |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Dec 2014 12:27 |
Last Modified: | 19 Dec 2022 13:29 |
Published Version: | http://www.springer.com/computer/ai/book/978-3-540... |
Status: | Published |
Publisher: | Springer Berlin Heidelberg |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:82240 |