The False-Positive Rate of Automated Plagiarism Detection for SQL Assessments-Reference-Cited by-同舟云学术

The False-Positive Rate of Automated Plagiarism Detection for SQL Assessments

Published:2019 Issue: Volume: Page:
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Container-title:Proceedings of the 1st UK & Ireland Computing Education Research Conference on - UKICER
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Author:

Kleerekoper Anthony¹,Schofield Andrew¹

Affiliation:

1. Manchester Metropolitan University, Manchester, UK

Publisher

ACM Press

Reference17 articles.

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2. Jess Bidgood and Jeremy B. Merrill. 2017. As Computer Coding Classes Swell, So Does Cheating. https://www.nytimes.com/2017/05/29/us/computer-science-cheating.htmlhttps://www.nytimes.com/2017/05/29/us/computer-science-cheating.html%0Ahttps://www.nytimes.com/2017/05/29/us/computer-science-cheating.html?smid=nytcore-ipad-share&smprod=nytcore-ipad&_r

3. Samuel Breese, Evan Maicus, Matthew Peveler, and Barbara Cutler. 2018. Correlation of a Flexible Late Day Policy with Student Stress and Programming Assignment Plagiarism. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education - SIGCSE '18. ACM Press, New York, New York, USA, 1089--1089. https://doi.org/10.1145/3159450.3162236

4. Georgina Cosma and Mike Joy. 2006. Source-code plagiarism: A UK academic perspective. Research Report No. 422 (2006), 1--74. https://www.dcs.warwick.ac.uk/report/pdfs/cs-rr-422.pdfhttp://eprints.dcs.warwick.ac.uk/52/

5. Robert Fraser. 2014. Collaboration, collusion and plagiarism in computer science coursework. Informatics in Education 13, 2 (2014), 179--195. https://doi.org/10.15388/infedu.2014.01

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2. University learning with anti-plagiarism systems;Accountability in Research;2020-09-23

3. Choosing Code Segments to Exclude from Code Similarity Detection;Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education;2020-06-17