Online cheating amid COVID-19
Open accessAbstract
We present evidence of cheating that took place in online examinations during COVID-19 lockdowns and propose two solutions with and without a camera for the cheating problem based on the experience accumulated by online chess communities over the past two decades. The best implementable solution is a uniform online exam policy where a camera capturing each students computer screen and room is a requirement. We recommend avoiding grading on a curve and giving students less time but simpler questions on tests.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Bilen and Matros (2021) argued that fears about widespread cheating often exceed documented cases.
“Bilen and Matros (2021) also argued that fears about widespread cheating often exceed documented cases.”
From A cross-sectional look at teacher reactions, worries, and professional development needs related to generative AI in an urban school district (2025) · cites this paper as Bilen and Matros (2021)
The Introduction (page unavailable) argues that, without action, online exams will see widespread cheating and that the chance of obtaining definitive evidence is close to zero. The Related literature section (page unavailable) also cautions that self-reported cheating rates may miss cases. The authors do not argue that fears exceed documented cheating; they warn that documented cases may understate it. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Crime and Punishment: An Economic Approach
Becker, G. S. (1968) · Journal of Political Economy · doi:10.1086/259394 · Cited by 13,999 · see citing works
Deception: The Role of Consequences
Uri Gneezy, B. (2005) · American Economic Review · doi:10.1257/0002828053828662 · Cited by 1,676 · see citing works
LIES IN DISGUISE-AN EXPERIMENTAL STUDY ON CHEATING
Fischbacher, U., & Föllmi-Heusi, F. (2013) · Journal of the European Economic Association · doi:10.1111/jeea.12014 · Cited by 1,289 · see citing works
Rotten Apples: An Investigation of the Prevalence and Predictors of Teacher Cheating
Jacob, B. A., & Levitt, S. D. (2003) · The Quarterly Journal of Economics · doi:10.1162/00335530360698441 · Cited by 878 · see citing works
Erat, S., & Gneezy, U. (2011) · Management Science · doi:10.1287/mnsc.1110.1449 · Cited by 728 · see citing works
Intrinsic honesty and the prevalence of rule violations across societies
Gächter, S., & Schulz, J. F. (2016) · Nature · doi:10.1038/nature17160 · Cited by 551 · see citing works
Winning Isn't Everything: Corruption in Sumo Wrestling
Duggan, M., & Levitt, S. D. (2000) · American Economic Review · doi:10.1257/000282802762024665 · Cited by 372 · see citing works
Freakonomics: a rogue economist explores the hidden side of everything
Dinardo, J., Journalist, T., & Dubner, S. (2005) · Choice Reviews Online · doi:10.5860/choice.43-1689 · Cited by 358 · see citing works
Cheating in the Digital Age: Do Students Cheat More in Online Courses?.
Watson, G., & Sottile, J. (2010) · Online journal of distance learning administration · Cited by 242 · see citing works
Karim, M. N., Kaminsky, S. E., & Behrend, T. S. (2014) · Journal of Business and Psychology · doi:10.1007/s10869-014-9343-z · Cited by 126 · see citing works
Rational Ignorance in Education: A Field Experiment in Student Plagiarism
Dee, T. S., & Jacob, B. A. (2010) · National Bureau of Economic Research · doi:10.3386/w15672 · Cited by 92 · see citing works
PageFocus: Using paradata to detect and prevent cheating on online achievement tests
Diedenhofen, B., & Musch, J. (2016) · Behavior Research Methods · doi:10.3758/s13428-016-0800-7 · Cited by 73 · see citing works
Cheating, incentives, and money manipulation
Charness, G. B., Jimenez, C. B., Ezquerra, L., & Rodríguez-Lara, I. (2018) · Experimental Economics · doi:10.1007/s10683-018-9584-1 · Cited by 61 · see citing works
Rational Ignorance in Education: A Field Experiment in Student Plagiarism
Dee, T. S., & Jacob, B. A. (2012) · The Journal of Human Resources · doi:10.1353/jhr.2012.0012 · Cited by 59 · see citing works
Cheating and incentives in a performance context: Evidence from a field experiment on children
Alan, Ş., Ertaç, S., & Gümren, M. (2019) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2019.03.015 · Cited by 44 · see citing works
Cheating and Incentives: Learning from a Policy Experiment
Martinelli, C., Parker, S. W., Pérez-Gea, A. C., & Rodrigo, R. (2018) · American Economic Journal Economic Policy · doi:10.1257/pol.20150066 · Cited by 34 · see citing works
Clever little lies: Math performance and cheating in primary schools in Congo
Maggioni, M. A., & Rossignoli, D. (2020) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2019.12.021 · Cited by 24 · see citing works
Vanberg, C. (2016) · Experimental Economics · doi:10.1007/s10683-016-9491-2 · Cited by 18 · see citing works
Fask, A., Englander, F., & Wang, Z.-B. (2014) · Journal of Academic Ethics · doi:10.1007/s10805-014-9207-1
Flagged first, then by citations
Cited by
Sorted by citations
A Systematic Review on AI-based Proctoring Systems: Past, Present and Future
Nigam, A., Pasricha, R., Singh, T., & Churi, P. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10597-x · Cited by 267 · see citing works
A systematic review of research on cheating in online exams from 2010 to 2021
Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10927-7 · Cited by 236 · see citing works
Zooming to Class? Experimental Evidence on College Students’ Online Learning during COVID-19
Kofoed, M. S., Gebhart, L., Gilmore, D., & Moschitto, R. (2024) · American Economic Review: Insights · doi:10.1257/aeri.20230077 · Cited by 125 · see citing works
Chat or cheat? Academic dishonesty, risk perceptions, and ChatGPT usage in higher education students
Ortiz-Bonnin, S., & Blahopoulou, J. (2025) · Social Psychology of Education · doi:10.1007/s11218-025-10080-2 · Cited by 40 · see citing works
Chen, R., Lee, V. R., & G Lee, M. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13350-w · Cited by 43 · see citing works
“Bilen and Matros (2021) also argued that fears about widespread cheating often exceed documented cases.”
It's Bad but It's Good: An Exploration of AI Cheating on Higher Educational Students Perspectives
Sholikhah, Z., Pramuka, B. A., Adawiyah, W. R., Yanuar, I., Respati, Y. A., & Pramuka, M. F. (2024) · 2024 IEEE Technology & Engineering Management Conference - Asia Pacific (TEMSCON-ASPAC) · doi:10.1109/temscon-aspac62480.2024.11024673 · Cited by 4 · see citing works
- Authors
- Bilen, E., & Matros, A.
- Affiliations
- University of South Carolina (US)
- Corresponding author
- Matros, Alexander
- Venue
- Journal of Economic Behavior & Organization
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 182
- Pages
- 196-211
- ISSN
- 0167-2681 (ISSN-L)
- PMC
- PMC9754215
- OpenAlex
- W3091616849
- Cited by
- 237
- References
- 19
- Citations by year
- 2026: 27 · 2025: 16 · 2024: 41 · 2023: 58 · 2022: 62 · 2021: 32 · 2020: 1
- FWCI
- 52.06
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Journal of Economic Behavior & Organization (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Munich Personal RePEc Archive (Ludwig Maximilian University of Munich) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Education › Education during COVID-19 pandemic
- Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
- Keywords
- online cheating, online examinations, COVID-19 lockdown, academic integrity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review