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ChatGPT in higher education: Considerations for academic integrity and student learning
Open accessAbstract
The release of ChatGPT has sparked significant academic integrity concerns in higher education. However, some commentators have pointed out that generative artificial intelligence (AI) tools such as ChatGPT can enhance student learning. Consequently, academics should adapt their teaching and assessment practices to embrace the new reality of living, working, and studying in a world where AI is freely available. Despite this important debate, very little academic literature has been published on ChatGPT and other generative AI tools. This article uses content analysis to examine news articles (N=100) about how ChatGPT is disrupting higher education, concentrating specifically on Australia, New Zealand, the United States, and the United Kingdom. It explores several key themes, including university responses, academic integrity concerns, the limitations and weaknesses of AI tool outputs, and opportunities for student learning. The data reveals mixed public discussion and university responses, with a focus mainly on academic integrity concerns and opportunities for innovative assessment design. There has also been a lack of public discussion about the potential for ChatGPT to enhance participation and success for students from disadvantaged backgrounds. Similarly, the students’ voice is poorly represented in media articles to date. This article considers these trends and the impact of AI tools on student learning at university.
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“research emerging from late 2022 to early 2023 began to reflect significant concerns about academic dishonesty and the threat to traditional modes of assessment (Sullivan et al., 2023).”
From The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment (2024) · cites this paper as Sullivan et al., 2023
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Sullivan et al. (2023) identified systemic marginalization of student voices in favor of institutional integrity narratives.”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Sullivan et al. (2023)
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“while research on generative AI adoption in higher education has grown rapidly, most studies focus on Western or East Asian institutional contexts [1, 6, 7], leaving African higher education settings substantially underexplored.”
From Generative AI Usage and Information Literacy Skills among University Students in North-West Nigeria (2026) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Whilst chatbots can be responsive pedagogical tools [41], educators have raised the alarm about students using chatbots to compose essays, write computer code, and complete other homework assignments [56].”
From New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023) · cites this paper as [56]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In 2023, ChatGPT (OpenAI, San Francisco, USA) became the most well-known aid for written assignments in universities (Dwivedi et al., 2023; Sullivan et al., 2023).”
From Using version control to document genuine effort in written assignments: a protocol with examples for universities (2023) · cites this paper as Sullivan et al., 2023
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“Despite the evolving levels of nuance in our understanding of these technologies in HE, to date, there has been little discussion of the student perspectives of GenAI in HE in both media and research (Sullivan et al., 2023).”
From The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment (2024) · cites this paper as Sullivan et al., 2023
The cited source says what the claim attributes to it.
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“Other authors see the benefits of GenAI to enhance student learning through innovative assessment designs [41], potentially addressing such student concerns in the long term.”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [41]
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“However, the release of ChatGPT and other free-touse generative AI tools have provided a new and distinct method for cheating.”
From Bob or Bot: Exploring ChatGPT's Answers to University Computer Science Assessment (2024) · cites this paper as [48]
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“yet questions persist regarding their capacity to critically evaluate such resources [1].”
From Generative AI Usage and Information Literacy Skills among University Students in North-West Nigeria (2026) · cites this paper as [1]
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“The emergence of generative AI has sparked discussions about academic integrity and the possible exploitation of such technology in student assignments (Sullivan et al., 2023).”
From Assessment design through co-creation (2025) · cites this paper as Sullivan et al., 2023
In the citing paper
“Nonetheless, this unprecedented level of support also raises concerns about academic integrity and the role of course instructors [26].”
From Exploring ChatGPT’s impact on post-secondary education: A qualitative study (2023) · cites this paper as [26]
In the citing paper
“The public discourse surrounding GenAI has been mostly positive, but in the education sector there is serious concern about academic integrity and plagiarism (Dehouche, 2021;Lampropoulos et al., 2023;Sullivan et al., 2023;Yeo, 2023).”
From Not quite eye to A.I.: student and teacher perspectives on the use of generative artificial intelligence in the writing process (2023) · cites this paper as Sullivan et al., 2023
In the citing paper
“The findings from previous studies indicate the importance of rethinking, improving, and redesigning innovative assessment methods in the era of chatbots [14, 20, 64, 75]”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [75]
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Citations
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“…reviews focused on AI in higher education highlight that studies tend to frame AI principally as a tool for improving assignment feedback and assisting with administrative duties rather than exploring concerns relating to academic integrity (Ouyang et al., 2022; Zawacki-Ricther et al., 2019).”
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GenAI Usage in Higher Education: The Evolution of Students’ Perceptions
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FROM ASSIGNMENT TO AFFECTION: WHAT DRIVES UNIVERSITY STUDENTS TO KEEP USING CHATGPT?
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Critical Thinking and Artificial Intelligence
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Conversational intra-drama: a posthumanist methodology for researching human–AI dialogue
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Reimagining assessment design in higher education through Design Thinking
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“Survey evidence gathered during the first year of availability showed a consistent pattern: majority student use alongside majority institutional restriction (Sullivan et al., 2023; Chan, 2023).”
Exploring ChatGPT Through Bloom’s Taxonomy: A Systematic Literature Review
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Assessing Graduate Students’ Perceptions in Exploring Generative AI for Scientific Writing
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“Analyses of AI-generated responses to academic writing prompts indicate that, while the outputs are generally original and relevant, they often include inappropriate references and lack personal perspectives that artificial intelligence is unable to produce [13].”
Culturally Responsive AI-Mediated Feedback
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Metadata
- Authors
- Sullivan, M., Kelly, A., & McLaughlan, P.
- Affiliations
- Edith Cowan University (AU)
- Venue
- Journal of Applied Learning & Teaching
- Publisher
- Open Access Publishing Association
- Published
- 2023-03-21
- Volume
- 6
- Issue
- 1
- ISSN
- 2591-801X (ISSN-L)
- OpenAlex
- W4327918021
- Cited by
- 853
- References
- 25
- Citations by year
- 2026: 192 · 2025: 255 · 2024: 284 · 2023: 122
- FWCI
- 199.83
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Journal of Applied Learning & Teaching (publishedVersion, cc-by)
- Australasian Journal of Paramedicine (submittedVersion, cc-by)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- ChatGPT, generative AI, academic integrity, higher education, student learning, assessment design, student participation, disadvantaged students, news media coverage
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.
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