Guelph, Canada

University of Guelph

University of Guelph is listed as QS 2026 rank =504. University of Guelph has 6 source-backed AI policy claim records from 5 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 Guelph is listed as QS 2026 rank =504. University of Guelph has 6 source-backed AI policy claim records from 5 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 Guelph as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 6 source-backed claims, including 6 reviewed claims, from 5 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-guelph.json. The entity-level confidence is 97%. 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.

Claim coverage6 reviewedSource languageenPublic JSON/api/public/v1/universities/university-of-guelph.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Privacy claims.
  • Evidence includes Source status claims.
  • Evidence includes Teaching claims.
  • No specific AI service name is highlighted by the current public claim text.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
  • Privacy, sensitive-data, or security language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims6Reviewed6Candidate0Official sources5

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.

Coverage score85/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence81%

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

No source-backed public claim about AI disclosure or acknowledgement is present in this profile.

The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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

6 reviewed evidence-backed public claim

Academic Integrity

The University of Guelph states that submitting AI-completed materials without instructor permission constitutes an offence under its academic misconduct policies.

Review: Agent reviewedConfidence97%

Normalized value: unauthorized_ai_submission_academic_misconduct

Original evidence

Evidence 1
Submission of materials completed by AI, without permission of the instructor, constitutes an offence under the University’s academic misconduct policies, either as a form of plagiarism or the use of unauthorized aids.

Ai Tool Treatment

For University of Guelph courses, acceptable student use of AI is determined by the course instructor and may vary by discipline, program, and assessment type.

Review: Agent reviewedConfidence96%

Normalized value: course_instructor_determines_acceptable_ai_use

Original evidence

Evidence 1
Acceptable use of AI should be determined by the course instructor and may vary across disciplines, programs and types of assessments.

Academic Integrity

The University of Guelph Office of Teaching and Learning says generative AI plagiarism detection software is not currently approved for use at U of G and instructors should not submit student work to generative AI detection tools while more is being understood.

Review: Agent reviewedConfidence95%

Normalized value: genai_detection_software_not_currently_approved

Original evidence

Evidence 1
Generative AI plagiarism detection software is not currently approved for use at UofG. This software will continue to be reviewed and may be available in the future.

Privacy

University of Guelph information-security guidance says staff and faculty should not enter Internal, Confidential, or Restricted University data into public AI tools, and should avoid entering PII into generative AI tools not reviewed and approved by Information Security.

Review: Agent reviewedConfidence94%

Normalized value: sensitive_university_data_and_pii_restricted_in_public_or_unapproved_ai_tools

Original evidence

Evidence 1
Internal (S2), Confidential (S3) and Restricted (S4) University data should never be entered into a public AI tool (e.g., ChatGPT), such as including sensitive information in a generative AI prompt.

Source Status

The University of Guelph has public official guidance pages for generative AI in teaching and learning, including an AVPA resource page and Office of Teaching and Learning provisional recommendations.

Review: Agent reviewedConfidence93%

Normalized value: public_official_genai_teaching_guidance_available

Original evidence

Evidence 1
The following guidance and resources are available for University of Guelph faculty, instructors, staff, and teaching assistants as they navigate the impact of Generative AI on teaching and learning.

Teaching

The University of Guelph library student guide tells students to check the syllabus or ask the instructor before using generative AI for coursework.

Review: Agent reviewedConfidence89%

Normalized value: students_check_syllabus_or_instructor_before_coursework_genai_use

Original evidence

Evidence 1
Always check the course syllabus or check with your instructor before using gen AI in for your course work. At the U of G acceptable use of AI is determined by the course instructor and may vary across disciplines, programs, and types of assessments.

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

5 source attribution

Information Security Guidelines for the Use of Generative Artificial Intelligence

ithelp.uoguelph.ca

Snapshot hash
323605fcca67b9e499316b9fa76fdb9586133fc0ee9acead7b31b1f69d88389a

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.

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

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.

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