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

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

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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Crossref · 10.1007/s10639-022-10927-7

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  • Cheating on written assignments has amplified by tailored online services.

    “Cheating on written assignments has also amplified by tailored online services (Noorbehbahani1 et al., 2022; Yazici et al., 2022)”

    From Using version control to document genuine effort in written assignments: a protocol with examples for universities (2023) · cites this paper as Noorbehbahani et al., 2022

    The Results sections on cheating detection and cheating types describe written work produced by someone else for a student and contract workers supplying answers. They do not say that tailored online services have amplified cheating on written assignments; the discussion is primarily about online exams. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

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Flagged first, then by citations

Research works printed but not linked: 5

  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. 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/
  3. 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.
  4. 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.
  5. Weiner JA Hurtz GM A comparative Study of Online Remote Proctored Vs Onsite Proctored Journal of Applied Testing Technology 2017 18 1 13 20

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Authors
Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M.
Affiliations
University of Isfahan (IR)
Corresponding author
Noorbehbahani, Fakhroddin
Venue
Education and Information Technologies
Published
2022-03-07
Volume
27
Issue
6
Pages
8413-8460
ISSN
  • 1360-2357 (ISSN-L)
  • 1573-7608
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
Locations
  • Education and Information Technologies (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Safety Research › 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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