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Criminal Minds: A Plagiarism Study about Getting Away With It (for Science)

Maisch, Robin ORCID iD icon 1,2; Schmid, Larissa ORCID iD icon; Glassey, Richard
1 Karlsruher Institut für Technologie (KIT)
2 Institut für Informationssicherheit und Verlässlichkeit (KASTEL), Karlsruher Institut für Technologie (KIT)

Abstract:

Can we benefit from students cheating? We think so. In the Criminal Minds study, first-year students are tasked with plagiarizing code and evading detection, choosing from a variety of strategies. What began as a collaboration between researchers at KIT (Germany) and KTH (Sweden) to address the shortage of open plagiarism datasets also proved to be a highly engaging pedagogical activity, creating a safe space for students to experience and discuss plagiarism from a radically different perspective. We present the study design and the controlled lab setting. We plan to repeat the study in Fall 2026 and use this poster to encourage educators to collaborate with us on future installments of the Criminal Minds study.


Verlagsausgabe §
DOI: 10.5445/IR/1000193196
Veröffentlicht am 13.05.2026
Originalveröffentlichung
DOI: 10.1145/3803401.3812035
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2026
Sprache Englisch
Identifikator ISBN: 979-8-4007-2633-0
KITopen-ID: 1000193196
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Erschienen in Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2 (ITiCSE 2026), Madrid, 13th-15th July 2026
Veranstaltung 31st Conference on Innovation and Technology in Computer Science Education (ITiCSE 2026), Madrid, Spanien, 13.07.2026 – 15.07.2026
Verlag Association for Computing Machinery (ACM)
Bemerkung zur Veröffentlichung Poster Abstract
Schlagwörter Plagiarism Detection, Large Language Models, LLMs, Software Engineering Education, SE Education, Computer Science Education
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