Cited by 237Academic integrity and plagiarismEducation during COVID-19 pandemicEducational Technology and Assessment

Online cheating amid COVID-19

Open access
Bilen, Eren, Matros, Alexander·2021·Journal of Economic Behavior & Organization

Abstract

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jebo.2020.12.004

Cites

19 of 19 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Flagged first, then by citations

Cited by

Sorted by citations

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)
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
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