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Cited by 237Academic integrity and plagiarismOnline Learning and AnalyticsBenford’s Law and Fraud Detection

The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.

A systematic review of research on cheating in online exams from 2010 to 2021

Open access
Noorbehbahani, Fakhroddin, Mohammadi, Azadeh, Aminazadeh, Mohammad·2022·Education and Information Technologies
DOI 10.1007/s10639-022-10927-7PMC PMC8898996
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Abstract

In recent years, online learning has received more attention than ever before. One of the most challenging aspects of online education is the students' assessment since academic integrity could be violated due to various cheating behaviors in online examinations. Although a considerable number of literature reviews exist about online learning, there is no such review study to provide comprehensive insight into cheating motivations, cheating types, cheating detection, and cheating prevention in the online setting. The current study is a review of 58 publications about online cheating, published from January 2010 to February 2021. We present the categorization of the research and show topic trends in the field of online exam cheating. The study can be a valuable reference for educators and researchers working in the field of online learning to obtain a comprehensive view of cheating mitigation, detection, and prevention.

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Research works printed but not linked: 7

  1. Arnautovski, L. (2019). Face recognition technology in the exam identity authentication system - implementation concept. In 2nd International Scientific Conference MILCON’19 (pp. 51–56). Olsztyn, Poland.
  2. Bawarith, R., Basuhail, A., Fattouh, A., & Gamalel-din, P. S. (2017). E-exam Cheating Detection System. International Journal of Advanced Computer Science and Applications, 8(4), 176–181. · DOI
  3. Cluskey, G. R. C. Jr, Ehlen, C. R., & Raiborn, M. H. (2011). Thwarting Online Exam Cheating without Proctor Supervision, 4, 1–7.
  4. Idemudia, S., Rohani, M. F., Siraj, M., & Othman, S. H. (2016). A Smart Approach of E-Exam Assessment Method Using Face Recognition to Address Identity Theft and Cheating. International Journal of Computer Science and Information Security, 14(10), 515–522. Retrieved from https://sites.google.com/site/ijcsis/
  5. Jalali, K., & Noorbehbahani, F. (2017). An Automatic Method for Cheating Detection in Online Exams by Processing the Students Webcam Images. In 3rd Conference on Electrical and Computer Engineering Technology (E-Tech 2017), Tehran, Iran (pp. 1–6). Tehran, Iran.
  6. Kigwana, I., & Venter, H. (2016). Proposed high-level solutions to counter online examination fraud using digital forensic readiness techniques. Proceedings of the 11th International Conference on Cyber Warfare and Security, ICCWS 2016, 407–414.
  7. Weiner, J. A., & Hurtz, G. M. (2017). A comparative Study of Online Remote Proctored Vs Onsite Proctored. Journal of Applied Testing Technology, 18(1), 13–20.

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Metadata

Authors
Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M.
Affiliations
University of Isfahan (IR)
Corresponding author
Noorbehbahani, Fakhroddin
ORCID
Venue
Education and Information Technologies
Publisher
Springer Science and Business Media LLC
Published
2022-03-07
Volume
27
Issue
6
Pages
8413-8460
ISSN
  • 1360-2357 (ISSN-L)
  • 1573-7608
DOI
10.1007/s10639-022-10927-7
PMC
PMC8898996
OpenAlex
W4220695000
Cited by
236
References
65
Citations by year
2026: 42 · 2025: 47 · 2024: 66 · 2023: 61 · 2022: 20
FWCI
9.25
Type
journal article
Language
en
Open access
Licence
Locations
  • Education and Information Technologies (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Education › Academic integrity and plagiarism
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Mathematics › Statistics and Probability › Benford’s Law and Fraud Detection
Keywords
academic integrity, online learning, cheating detection, cheating prevention, student assessment

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