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Generative AI tools and assessment: Guidelines of the world's top-ranking universities
Open accessAbstract
The public release of generative artificial intelligence (GAI) tools (e,g. ChatGPT) has had a disruptive effect on the assessment practices of higher education institutions (HEIs) worldwide. Concerns have largely been associated with academic integrity, cheating and plagiarism. HEIs have had to develop guidelines in response to GAI. As many of these guidelines were developed in haste and could affect a large number of instructors and students, there is a need to examine their content, coverage and suitability. This review examines the extent to which the world's 50 top-ranking HEIs have developed or modified their assessment guidelines to address GAI use and, where guidelines exist, the primary content and advice given to guide instructors in their GAI assessment design and practices. The findings show that just under half of the institutions have developed publicly available guidelines. The guidelines cover three main areas: academic integrity, advice on assessment design, and communicating with students. Among the suggestions for teachers on assessment design, two appear particularly pertinent in helping develop effective assessment tasks and developing learners’ AI-literacy: first, running assessment tasks through GAI to check the extent to which the tool can accomplish the task and, second, having students use GAI as part of the assessment process. Overall, the review suggests that HEIs have come to accept the use of GAI and drafted assessment guidelines to advise instructors on its use. In the article, we argue that it may be beneficial to embrace GAI as a part of the assessment process since this is the reality of today's educational and job landscape. This will require instructors to develop a new competence - generative artificial intelligence assessment literacy - which is conceptualised in this article.
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In the citing paper
“Despite these technological advancements, a growing body of evidence indicates that the Integration of AI into language pedagogy remains superficial and inconsistent (Chan & Tsi, 2024;Moorhouse et al., 2023).”
From Adoption and Integration of Artificial Intelligence in Foreign Language Teaching: Multi-Institutional Analysis of Higher Education (2026) · cites this paper as Moorhouse et al., 2023
In the citing paper
“Moorhouse et al. (2023) examined institutional AI policies at leading universities and found that most frameworks concentrated on regulatory responses (e.g., academic integrity policies) rather than pedagogical enablement.”
From Adoption and Integration of Artificial Intelligence in Foreign Language Teaching: Multi-Institutional Analysis of Higher Education (2026) · cites this paper as Moorhouse et al. (2023)
In the citing paper
“aligning with recent studies that have reported limited faculty adoption of AI tools in higher education (Chan & Tsi, 2023;Moorhouse et al., 2023).”
From Adoption and Integration of Artificial Intelligence in Foreign Language Teaching: Multi-Institutional Analysis of Higher Education (2026) · cites this paper as Moorhouse et al., 2023
In the citing paper
“Moorhouse, Yeo, and Wan (2023) analysed 50 leading global higher education institutions and found that 57% had guidelines for AI use, primarily advising students to acknowledge AI use or cite AI-generated content.”
From Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education (2025) · cites this paper as Moorhouse, Yeo, and Wan 2023
In the citing paper
“Moorhouse et al.'s (2023) findings indicate that nearly half of the world's top 50 universities have published guidelines focusing on academic integrity, assessment design advice, and student communication.”
From Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania (2024) · cites this paper as Moorhouse et al., 2023
In the citing paper
“However, the authors pointed out that as these guidelines have been developed rapidly, it is likely that many of the suggestions have not been sufficiently tested.”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [12]
In the citing paper
“For example, the early review conducted by Moorhouse et al. [12] found that 23 out of the 50 top-ranking universities have developed publicly available guidelines by June 2023, which addressed the potential influence of GenAI on three main areas: academic integrity, advice on assessment design, and communicating with students.”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [12]
In the citing paper
“Despite significant uncertainty about the pros and cons of incorporating GenAI in education, many universities have published policies and guidelines, aiming to promote responsible and beneficial AI usage.”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [12]
In the citing paper
“English-speaking countries in the Global North tend to be ranked higher in various university rankings [12].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [12]
In the citing paper
“Concerns over AI-generated misinformation and its potential misuse in assessments underscore the need for updated academic policies and enhanced detection mecha -nisms [ 30-32 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [31]
In the citing paper
“Studies have revealed that traditional plagiarism detection tools, such as Turnitin, are ineffective in identifying AI-gen -erated content, often yielding false positives or negatives [ 31, 60, 85, 89, 90 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [31]
In the citing paper
“Without such policies, institutions risk ethical violations, academic dishonesty, and a lack of uniformity in AI integration within education [ 31 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [31]
In the citing paper
“One approach involves improving AI detec -tion tools to accurately identify AI-generated content while reducing false positives and negatives that may affect aca -demic integrity enforcement [ 31, 54, 57, 66, 91, 106].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [31]
In the citing paper
“Moorhouse, Yeo [38] found that less than half of the reviewed universities have developed publicly accessible guidelines addressing GenAI use.”
From Generative AI in Higher Education: Balancing Innovation and Integrity (2025) · cites this paper as Moorhouse, Yeo [38]
In the citing paper
“Prior empirical audits of university AI governance have focused on policy presence among elite or researchintensive samples [47, 50, 76, 80] (Table 2, Appendix B), examining primarily the pedagogical dimension: how universities communicate expectations about AI use in coursework.”
From The Due Process Deficit: Auditing AI Governance in U.S. Higher Education (2026) · cites this paper as [50]
In the citing paper
“Most recently, an investigation similar to this one was done of the GenAI policies of the world's 50 top-ranking HEIs [33] and found that guidance generally covers 'academic integrity, advice on assessment design and communicating with students.'”
From Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines (2025) · cites this paper as [33]
In the citing paper
“Moorhouse et al also find that HEIs have largely come to embrace GenAI, a position which the authors themselves advocate.”
From Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines (2025) · cites this paper as [33]
In the citing paper
“Perhaps, partly as a consequence, there seems to be somewhat of a shift away from this combative approach to GenAI [33].”
From Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines (2025) · cites this paper as [33]
In the citing paper
“Following the public release of ChatGPT, many universities initially adopted a cautious, wait-and-see approach (Wang, Dang, Wu and Mac, 2023; Moorhouse, Yeo and Wan, 2023; Cheng and YIM, 2024).”
From Generative AI in higher education: A global perspective of institutional adoption policies and guidelines (2025) · cites this paper as Moorhouse, Yeo and Wan, 2023
In the citing paper
“While previous studies have examined the roles of faculty and students in GAI adoption (Moorhouse et al., 2023; Wang et al., 2023), our research provided a more detailed perspective by also considering administrators' roles, offering insights into the comprehensive stakeholder responsibilities in GAI's context.”
From Generative AI in higher education: A global perspective of institutional adoption policies and guidelines (2025) · cites this paper as Moorhouse et al., 2023
In the citing paper
“Our findings highlighted a universal concern for academic integrity and the ethical use of AI, underscoring institutions' dedication to maintaining core educational values amidst technological progress (Moorhouse et al., 2023; Wang et al., 2023).”
From Generative AI in higher education: A global perspective of institutional adoption policies and guidelines (2025) · cites this paper as Moorhouse et al., 2023
In the citing paper
“Recent research suggests that tools like ChatGPT can aid college students in completing tasks such as essay and proposal writing and take-home examinations, raising concerns about increased risks of cheating and undermining academic integrity (Chiu et al, 2023; Moorhouse et al., 2023).”
From A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education (2024) · cites this paper as Moorhouse et al., 2023
In the citing paper
“GenAI placed a big challenge on academic integrity in student learning and development (Chiu, 2024; Moorhouse et al., 2023; Gou & Wang, 2023).”
From A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education (2024) · cites this paper as Moorhouse et al., 2023
In the citing paper
“The primary concern lies in the potential compromise to academic integrity presented by AI essay-writing systems, particularly ChatGPT.”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [4]
In the citing paper
“Recent studies have brought to light the potential for students to exploit ChatGPT for academic dishonesty.”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [4]
In the citing paper
“There is an apprehension that students might submit essays that do not authentically represent their work, thus contravening ethical standards within educational institutions [4,6].”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [4]
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Metadata
- Authors
- Moorhouse, B. L., Yeo, M. A., & Wan, Y.
- Affiliations
- Hong Kong Baptist University (HK)
- SEAMEO Regional Language Centre (SG)
- Corresponding author
- Moorhouse, Benjamin Luke
- Venue
- Computers and Education Open
- Publisher
- Elsevier BV
- Published
- 2023-12
- Volume
- 5
- Pages
- 100151
- ISSN
- 2666-5573 (ISSN-L)
- OpenAlex
- W4387873511
- Cited by
- 461
- References
- 39
- Citations by year
- 2026: 192 · 2025: 170 · 2024: 98 · 2023: 1
- FWCI
- 108.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Open (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Academic integrity and plagiarism
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- generative AI, ChatGPT, evaluation guidelines, higher education, academic integrity, cheating, plagiarism, assessment design, AI literacy, student communication
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 ›
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