Policy presence
University of Johannesburg has 2 source-backed public claims for policy presence; deterministic analysis status: unclear.
Johannesburg, South Africa
University of Johannesburg
University of Johannesburg is listed as QS 2026 rank =308. University of Johannesburg has 3 source-backed AI policy claim records from 3 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 Johannesburg is listed as QS 2026 rank =308. University of Johannesburg has 3 source-backed AI policy claim records from 3 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 Johannesburg as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 3 source-backed claims, including 3 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/university-of-johannesburg.json. The entity-level confidence is 93%. 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 Teaching claims.
- No specific AI service name is highlighted by the current public claim text.
- 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 Johannesburg has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
University of Johannesburg has 3 source-backed public claims for coursework; deterministic analysis status: required.
Exams
University of Johannesburg has 3 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 Johannesburg has 2 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
University of Johannesburg has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.
Named AI services
No source-backed public claim naming a specific AI service is present in this profile.
The current public tracker record does not contain claim evidence naming a specific AI service.
Teaching guidance
University of Johannesburg has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
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
3 reviewed evidence-backed public claim
Academic Integrity
UJ's practice note states that presenting the work of a generative AI tool, in whole or in part, as one's own is academic dishonesty, and says AI use should be acknowledged where used.
Review: Agent reviewed
Normalized value: ai_generated_work_presented_as_own_is_academic_dishonesty
Original evidence
Evidence 1To present the work of someone else or of a generative AI tool, in whole or in part, as one’s own, is academic dishonesty. To mitigate the risks of academic misconduct, in the context of generative AI, it is recommended that: students and researchers be transparent and sign a declaration that the work is their own.
Academic Integrity
UJ's student guide says generative AI use depends on course, department, faculty rules and UJ policy, and students should familiarise themselves with those requirements before producing assignments and assessments.
Review: Agent reviewed
Normalized value: students_must_check_course_and_policy_requirements
Original evidence
Evidence 1How you use generative AI depends on your course, department, or faculty rules, as well as UJ policy. Familiarise yourself with the rules and requirements before you produce assignments and assessments.
Teaching
UJ's staff guide frames appropriate generative AI use as including clear communication of institutional, departmental, and course regulations on generative AI, including referencing generated content.
Review: Agent reviewed
Normalized value: staff_guidance_clear_communication_of_ai_rules
Original evidence
Evidence 1Appropriate use of generative AI should apply the following parameters: Clear communication of the institutional/ departmental/ course regulations on the use of generative AI, including referencing generated content, developing proficiency in prompt generation, and harnessing the benefits of generative AI.
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
3 source attribution
Staff Guide: Generative Artificial Intelligence in Teaching, Learning and Research
uj.ac.za
UJ Practice Note: Generative Artificial Intelligence in Teaching, Learning and Research
uj.ac.za
UJ Quick Guide for Students: Using Generative Artificial Intelligence as a Learning Tool
uj.ac.za
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.