Policy presence
University of Luxembourg has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
Alzette, Luxembourg
University of Luxembourg
University of Luxembourg is listed as QS 2026 rank =381. University of Luxembourg has 5 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
University of Luxembourg is listed as QS 2026 rank =381. University of Luxembourg has 5 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of Luxembourg as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 5 source-backed claims, including 5 reviewed claims, from 2 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-luxembourg.json. The entity-level confidence is 91%. 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.
Policy signals in this record
- Evidence includes Academic integrity claims.
- Evidence includes AI tool treatment claims.
- Named AI services detected in public claims: Microsoft Copilot.
- Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
- Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Review: Agent reviewed
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.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
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.
AI disclosure
University of Luxembourg has 3 source-backed public claims for ai disclosure; deterministic analysis status: recommended.
Coursework
University of Luxembourg has 5 source-backed public claims for coursework; deterministic analysis status: required.
Exams
University of Luxembourg has 5 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
No source-backed public claim about privacy or data-entry restrictions is present in this profile.
The current public tracker record does not contain claim evidence about personal, confidential, sensitive, regulated, or student data entry into AI tools.
Academic integrity
University of Luxembourg has 4 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
University of Luxembourg has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.
Named AI services
University of Luxembourg has 1 source-backed public claim for named ai services; deterministic analysis status: recommended.
Teaching guidance
No source-backed public claim about teaching guidance is present in this profile.
The current public tracker record does not contain claim evidence about instructor, classroom, assessment-design, or syllabus guidance.
Research guidance
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.
Security and procurement
No source-backed public claim about AI security review or procurement is present in this profile.
The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
5 reviewed evidence-backed public claim
Academic Integrity
University of Luxembourg guidance says generative AI use should be disclosed according to each course and assessment, with course guidelines serving as the primary point of reference.
Review: Agent reviewed
Normalized value: genai_disclosure_course_specific
Original evidence
Evidence 1The use of Generative AI must be disclosed in accordance with the specific guidelines communicated for each course and assessment.
Ai Tool Treatment
University of Luxembourg guidance identifies Microsoft Copilot as the official supported chatbot and notes that UniGPT access is currently limited to University staff.
Review: Agent reviewed
Normalized value: microsoft_copilot_supported_unigpt_staff
Original evidence
Evidence 1The University provides Microsoft Copilot as its official supported chatbot. Students are encouraged to prioritise this tool, as it is supported within the University environment and offers stronger institutional safeguards than other public platforms. In February 2026, the University of Luxembourg launched UniGPT... At present, access to UniGPT is limited to University staff.
Academic Integrity
University of Luxembourg guidance lists non-permitted AI practices, including undisclosed submission of AI output as one's own work, using AI to replace the central assessed intellectual contribution, fabricating data or citations, and trying to conceal AI involvement.
Review: Agent reviewed
Normalized value: non_permitted_ai_practices
Original evidence
Evidence 1Unless explicitly authorised by the course guidelines, the following uses are non-permitted and may constitute academic misconduct: Submitting text, code, images, or other outputs generated fully or partly by AI as if they were entirely one's own work... Generating or altering data to create fake datasets, results, quotes, references, or evidence... Citing non-existent sources supplied by AI... Running outputs through multiple AI tools to conceal AI involvement.
Academic Integrity
University of Luxembourg assessment guidance says chatbot use in assignments should align with academic integrity and scientific judgement, and students should disclose where and how the chatbot influenced the text.
Review: Agent reviewed
Normalized value: chatbot_assignment_disclosure
Original evidence
Evidence 1If you decide to use a chatbot for an assignment, be sure to adhere to the principles of academic integrity. This means properly citing the chatbot as a source and disclosing in which parts of the text it has been used and how it has influenced the text.
Academic Integrity
University of Luxembourg assessment guidance says a substantiated suspicion of unauthorized chatbot use triggers disciplinary procedure for academic fraud and plagiarism.
Review: Agent reviewed
Normalized value: unauthorized_chatbot_use_disciplinary_procedure
Original evidence
Evidence 1A substantiated suspicion of unauthorized chatbot use in an assignment will trigger the disciplinary procedure for academic fraud and plagiarism.
Candidate claims
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.
Official sources
2 source attribution
Chatbots and student assessment
uni.lu
Guidelines on the Use of Generative AI for Teaching and Learning
uni.lu
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.