A Method for Cheating Indication in Unproctored On-Line Exams

Simple item page
dc.contributor.authorKomosný, Dancs
dc.contributor.authorRehman, Saeedcs
dc.coverage.issue2cs
dc.coverage.volume22cs
dc.date.accessioned2022-01-18T11:54:40Z
dc.date.available2022-01-18T11:54:40Z
dc.date.issued2022-01-15cs
dc.description.abstractCOVID-19 has disrupted every field of life and education is not immune to it. Student learning and examinations moved on-line on a few weeks notice, which has created a large workload for academics to grade the assessments and manually detect students’ dishonesty. In this paper, we propose a method to automatically indicate cheating in unproctored on-line exams, when somebody else other than the legitimate student takes the exam. The method is based on the analysis of the student’s on-line traces, which are logged by distance education systems. We work with customized IP geolocation and other data to derive the student’s cheating risk score. We apply the method to approx. 3600 students in 22 courses, where the partial or final on-line exams were unproctored. The found cheating risk scores are presented along with examples of indicated cheatings. The method can be used to select students for knowledge re-validation, or to compare student cheating across courses, age groups, countries, and universities. We compared student cheating risk scores between four academic terms, including two terms of university closure due to COVID-19.en
dc.formattextcs
dc.format.extent1-18cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationSENSORS. 2022, vol. 22, issue 2, p. 1-18.en
dc.identifier.doi10.3390/s22020654cs
dc.identifier.issn1424-8220cs
dc.identifier.other175956cs
dc.identifier.urihttp://hdl.handle.net/11012/203341
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofSENSORScs
dc.relation.urihttps://www.mdpi.com/1424-8220/22/2/654cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1424-8220/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectnetworken
dc.subjectend deviceen
dc.subjectlocationen
dc.subjectIP addressen
dc.subjectcheatingen
dc.subjecte-learningen
dc.subjectexamen
dc.subjectMoodleen
dc.subjectCOVID-19en
dc.subjectlockdownen
dc.titleA Method for Cheating Indication in Unproctored On-Line Examsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-175956en
sync.item.dbtypeVAVen
sync.item.insts2022.05.04 16:55:33en
sync.item.modts2022.05.04 16:14:13en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
sensors2200654v2.pdf
Size:
561.9 KB
Format:
Adobe Portable Document Format
Description:
sensors2200654v2.pdf
Download
Collections
Ústav telekomunikací