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PreprintCited by 3,079Academic integrity and plagiarismArtificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT

Open access
Cotton, Debby, Cotton, Peter, Shipway, J. Reuben·2023·Innovations in Education and Teaching International
DOI 10.35542/osf.io/mrz8h

Preprint — published as 10.1080/14703297.2023.2190148 · Paper page

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Abstract

The use of artificial intelligence in academia is a hot topic in the education field. The use of chatAPIs and GPT-3 in higher education has the potential to offer a range of benefits, including increased student engagement, collaboration, and accessibility. However, these tools also raise a number of challenges and concerns, particularly in relation to academic honesty and plagiarism. This paper examines the opportunities and challenges of using chatAPIs and GPT-3 in higher education, with a focus on the potential risks and rewards of these tools and the ways in which universities can address the challenges they pose. The paper discusses the main features and capabilities of chatAPIs and GPT-3 and provides examples of their use in higher education. It also considers the potential for these tools to be used for academic dishonesty and the difficulties of detecting and preventing such abuses. Finally, the paper suggests a range of strategies that universities can adopt to ensure that chatAPIs and GPT-3 are used ethically and responsibly, including developing policies and procedures, providing training and support, and using a variety of methods to detect and prevent cheating.

Integrity signals

Registry

Crossref · 10.35542/osf.io/mrz8h

Cites

24 of 24 references verified0 citation errors · 0 not checkable

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Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • Use of ChatGPT can exacerbate fairness issues by putting non-users at a disadvantage and ultimately reinforcing digital inequality.

    “Thus, use of ChatGPT can exacerbate fairness issues by putting non-users at disadvantage (Cotton et al., 2023), and ultimately reinforcing digital inequality (Fui-Hoon Nah et al., 2023; Mhlanga, 2023).”

    From College students’ literacy, ChatGPT activities, educational outcomes, and trust from a digital divide perspective (2026) · cites this paper as Cotton et al., 2023

  • The need to rethink and revise current assessment tools in health care education comes in light of ChatGPT's ability to pass reputable exams (e.g., USMLE) and the possibility of ChatGPT misuse resulting in academic dishonesty.

    “The need to rethink and revise the current assessment tools in health care education comes in light of ChatGPT’s ability to pass reputable exams (e.g., USMLE) and possibility of ChatGPT misuse, which would result in academic dishonesty [24,34,58,59,62,76,85,86,87].”

    From ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns (2023) · cites this paper as [62]

  • AI-generated content challenges traditional definitions of authorship and originality.

    “As Cotton, Cotton, & Shipway (2024) note, AI-generated content challenges traditional definitions of authorship and originality, a concern echoed by Perkins (2023).”

    From Generative AI-Enhanced Oral Exams in Economics Education (2026) · cites this paper as Cotton, Cotton, & Shipway (2024)

  • Incorporating real-time elements into assessments can safeguard against unauthorized GenAI use and ensure a more accurate reflection of each student's understanding.

    “Incorporating real-time elements into assessments in the form of oral responses or monitored discussions can safeguard against unauthorized GenAI use and ensure a more accurate reflection of each student's understanding (Cotton, Cotton, & Shipway 2024).”

    From Generative AI-Enhanced Oral Exams in Economics Education (2026) · cites this paper as Cotton, Cotton, & Shipway 2024

  • Large language models excel at synthesizing domain-specific technical concepts and mimicking natural linguistic fluency, making traditional written tasks increasingly vulnerable to unearned authorship and cognitive shortcut.

    “Because large language models (LLMs) excel at synthesizing domainspecific technical concepts and mimicking natural linguistic fluency, traditional written tasksuch as take-home assignments, reflective reports, or online language modules-are increasingly vulnerable to unearned authorship and cognitive shortcut (Cotton et al., 2023;Perkins, 2023).”

    From Navigating Academic Integrity and Student Rationalisations of Generative AI in Vocational Online Learning Environments (2026) · cites this paper as Cotton et al., 2023

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Authors
Cotton, D., Cotton, P., & Shipway, J. R.
Affiliations
  • Plymouth Marjon University (GB)
  • University of Plymouth (GB)
Corresponding author
Cotton, Peter
ORCID
Venue
Innovations in Education and Teaching International
Publisher
Center for Open Science
Published
2023-01-10
Volume
61
Issue
2
Pages
228-239
ISSN
1470-3297 (ISSN-L)
DOI
10.35542/osf.io/mrz8h
OpenAlex
W4324046518
Cited by
3,079
References
24
Citations by year
2026: 1105 · 2025: 801 · 2024: 789 · 2023: 381 · 2022: 1 · 2021: 1
FWCI
769.67
Type
journal article
Language
en
Open access
Licence
Locations
  • Innovations in Education and Teaching International (publishedVersion, cc-by-nc-nd)
  • Plymouth Marjon University Repository (Plymouth Marjon University) (acceptedVersion)
  • PEARL (University of Plymouth) (submittedVersion)
  • EdArXiv (OSF Preprints) (submittedVersion)
  • EdArXiv (OSF Preprints) (submittedVersion, cc-by)
Topics
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
ChatGPT, academic integrity, academic dishonesty, cheating detection, plagiarism, artificial intelligence in higher education, AI ethics, university policy

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