Policy presence
National University of Singapore (NUS) has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
Singapore, Singapore
National University of Singapore (NUS) has 8 source-backed AI policy claims from 3 official source attributions. Review state: agent reviewed; 8 reviewed claims. Last checked May 6, 2026.
v1 public contract
National University of Singapore (NUS) has 8 source-backed AI policy claims from 3 official source attributions, including 8 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 6, 2026. Discovery context: National University of Singapore (NUS) is listed as QS 2026 rank 8.
As of this public record, University AI Policy Tracker lists National University of Singapore (NUS) as an agent-reviewed AI policy record last checked on May 6, 2026 and last changed on May 6, 2026. The record contains 8 source-backed claims, including 8 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/national-university-of-singapore.json. The entity-level confidence is 96%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Deterministic source-backed dimensions derived from this record's public claims.
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
National University of Singapore (NUS) has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
National University of Singapore (NUS) has 3 source-backed public claims for ai disclosure; deterministic analysis status: required.
National University of Singapore (NUS) has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
National University of Singapore (NUS) has 5 source-backed public claims for exams; deterministic analysis status: restricted.
National University of Singapore (NUS) has 2 source-backed public claims for privacy and data entry; deterministic analysis status: recommended.
National University of Singapore (NUS) has 3 source-backed public claims for academic integrity; deterministic analysis status: required.
National University of Singapore (NUS) has 3 source-backed public claims for approved tools; deterministic analysis status: restricted.
National University of Singapore (NUS) has 1 source-backed public claim for named ai services; deterministic analysis status: restricted.
National University of Singapore (NUS) has 4 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
No source-backed public claim about research AI use is present in this profile.
The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.
National University of Singapore (NUS) has 2 source-backed public claims for security and procurement; deterministic analysis status: restricted.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
8 reviewed evidence-backed public claim
Academic Integrity
Bukti asal
Evidence 1The verdicts of current AI tools purported to determine whether an analyzed input has been generated by AI are not admissible as conclusive evidence in a disciplinary process to charge a student with academic dishonesty or as justification to penalize student work.
Academic Integrity
Bukti asal
Evidence 1Representing an AI's output as your own work, without any acknowledgement that you have used such a tool, is plagiarism. A student found to have submitted work generated by AI but failed to acknowledge their use of AI can still be sanctioned for plagiarism, assuming the case can be made.
Teaching
Bukti asal
Evidence 1Instructors should be transparent about where and how they deploy AI in NUS courses. This is especially important where AI is deployed to generate course content (including assessment questions), to function as virtual tutors to answer student queries, or to help with assessment feedback and grading.
Teaching
Bukti asal
Evidence 1The use of AI tools to provide instruction to learners in the form of responses, feedback and/or marks, whether as virtual tutors or as markers, requires prior approval by Head of Department or relevant Deanery, under the oversight of Chair of the AI-COP. Approval must be sought through submission of an AI Risk Assessment.
Teaching
Bukti asal
Evidence 1Conversely, the default assumption for any unsupervised (e.g., 'take home') assessment task is that the use of AI tools is permitted so long as the use is duly acknowledged. ... If the decision is that students should be forbidden from using AI tools for an assessment (for pedagogical reasons), then crucial aspects of that assessment should be conducted in-person and instructor-supervised.
Procurement
Bukti asal
Evidence 1Wherever NUS data is involved, use NUS approved AI tools (see the list here).
Source Status
Bukti asal
Evidence 1NUS's Policy for Use of AI in Teaching and Learning; THE1005 on AI Use for Students on the NUSOne page
Academic Integrity
Bukti asal
Evidence 1Important! Always check your assignment guidelines for specific instructions on use of AI in your assignment. ... If you intend to publish your work, do note that in addition to style guides for citation, you may need to consult publishers' policies for using AI tools or including AI-generated content in writing.
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
3 source attribution
libguides.nus.edu.sg
libguides.nus.edu.sg
ctlt.nus.edu.sg
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