Who’s Cheating?

Mining Patterns of Collusion from Text and Events in Online Exams

verfasst von

Catherine Cleophas, Christoph Hönnige, Frank Meisel, Philipp Meyer

Abstract

As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams’ digital output also enables computer-aided detection of collusion patterns. This paper presents two simple data-driven techniques to analyze exam event logs and essay-form answers. Based on examples from exams in social sciences, we show that such analyses can reveal patterns of student collusion. We suggest using these patterns to quantify the degree of collusion. Finally, we summarize a set of lessons learned about designing and analyzing online exams.

Organisationseinheit(en)

Institut für Politikwissenschaft

Externe Organisation(en)

Christian-Albrechts-Universität zu Kiel (CAU)

Typ

Artikel

Journal

INFORMS Transactions on Education

Band

23

Seiten

84-94

Anzahl der Seiten

11

ISSN

1532-0545

Publikationsdatum

01.10.2021

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Ausbildung bzw. Denomination, Management-Informationssysteme, Managementlehre und Operations Resarch

Elektronische Version(en)

https://doi.org/10.1287/ited.2021.0260 (Zugang: Offen)