A Method for Cheating Indication in Unproctored On-Line Exams

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU143059" target="_blank" >RIV/00216305:26220/22:PU143059 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1424-8220/22/2/654" target="_blank" >https://www.mdpi.com/1424-8220/22/2/654</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s22020654" target="_blank" >10.3390/s22020654</a>

Result language

angličtina

Original language name

A Method for Cheating Indication in Unproctored On-Line Exams

Original language description

COVID-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.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20202 - Communication engineering and systems

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

SENSORS

ISSN

1424-8220

e-ISSN

1424-3210

Volume of the periodical

22

Issue of the periodical within the volume

2

Country of publishing house

CH - SWITZERLAND

Number of pages

18

Pages from-to

1-18

UT code for WoS article

000758439600001

EID of the result in the Scopus database

2-s2.0-85123654856