Policy presence
Monash University has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Melbourne, Australia
Monash University
Monash University has 9 source-backed AI policy claims from 9 official source attributions. Review state: agent reviewed; 9 reviewed claims. Last checked May 10, 2026.
Monash University AI policy short answer
v1 public contract
Monash University has 9 source-backed AI policy claims from 9 official source attributions, including 9 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 10, 2026. Discovery context: Monash University is listed as QS 2026 rank =36.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Monash University as an agent-reviewed AI policy record last checked on May 10, 2026 and last changed on May 10, 2026. The record contains 9 source-backed claims, including 9 reviewed claims, from 9 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/monash.json. The entity-level confidence is 98%. 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.
- Evidence includes Research claims.
- Evidence includes Privacy claims.
- Evidence includes AI tool treatment claims.
- Named AI services detected in public claims: ChatGPT, 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
Monash University has 2 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
Monash University has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Monash University has 5 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
Monash University has 3 source-backed public claims for privacy and data entry; deterministic analysis status: blocked.
Academic integrity
Monash University has 2 source-backed public claims for academic integrity; deterministic analysis status: restricted.
Approved tools
Monash University has 4 source-backed public claims for approved tools; deterministic analysis status: blocked.
Named AI services
Monash University has 5 source-backed public claims for named ai services; deterministic analysis status: blocked.
Teaching guidance
Monash University has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
Monash University has 2 source-backed public claims for research guidance; deterministic analysis status: restricted.
Security and procurement
Monash University has 1 source-backed public claim for security and procurement; deterministic analysis status: recommended.
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
9 reviewed evidence-backed public claim
Academic Integrity
When allowed or required to use AI in an assessment, students must follow all instructions and restrictions on its use, clearly document the type of AI used and how it contributed, and provide written acknowledgment of the use of AI and its extent.
Review: Agent reviewed
Normalized value: ai_acknowledgement_requirements
Evidence originale
Evidence 1Whenever you are allowed or required to use AI in an assessment, you must also: Follow all instructions and restrictions on its use; Clearly document the type of AI used and how it contributed to the assessment; Provide written acknowledgment of the use of AI and its extent; and When necessary, cite and reference using the closest source types in the style being used.
Teaching
Chief Examiners have overarching responsibility for designing and setting assessment conditions, including communicating and verifying the responsible use of AI within assessment tasks.
Review: Agent reviewed
Normalized value: chief_examiner_responsible_for_ai_assessment_conditions
Evidence originale
Evidence 1Chief Examiners have overarching responsibility for designing and setting assessment conditions, including communicating and verifying the responsible use of AI within assessment tasks.
Research
Thesis examiners are not permitted to use Generative AI technologies (such as ChatGPT) during the thesis examination process to support, prepare, or write their examiners' report.
Review: Agent reviewed
Normalized value: examiners_prohibited_from_genai_in_examination
Evidence originale
Evidence 1To preserve the confidentiality of thesis examination, examiners are not permitted to use Generative AI technologies (such as ChatGPT) during the thesis examination process to support, prepare or write their examiners' report.
Academic Integrity
Using AI in a way not permitted in an assessment, or failing to acknowledge its use correctly, may breach assessment conditions under the Student Academic Integrity Procedure.
Review: Agent reviewed
Normalized value: unauthorized_ai_use_breach_of_integrity
Evidence originale
Evidence 1It is important that you follow assessment instructions regarding the use of AI. If you don't, you may breach assessment conditions (Student Academic Integrity Procedure, 2022). This occurs when you use AI in a way that is not permitted in an assessment, or fail to acknowledge its use correctly.
Privacy
Students should not upload personal, sensitive, copyrighted, or licensed material to AI tools, as many AI tools cannot guarantee privacy, strong data security, or the protection of intellectual property.
Review: Agent reviewed
Normalized value: do_not_upload_sensitive_data_to_ai
Evidence originale
Evidence 1When uploading personal, sensitive, copyrighted, or licensed material: Many AI tools cannot guarantee privacy, strong data security, or the protection of intellectual property (IP).
Privacy
Monash enterprise systems such as Copilot have enterprise data protections identified under the green shield in Monash Copilot. Students should use their Monash email address to access Microsoft Copilot which provides data protection for Monash.
Review: Agent reviewed
Normalized value: copilot_enterprise_data_protection
Evidence originale
Evidence 1Monash enterprise systems such as Copilot have enterprise data protections identified under the green shield in Monash Copilot. To be safe, you can use your Monash email address to access Microsoft Copilot which provides data protection for Monash.
Ai Tool Treatment
Monash's AI responsible use principles include community benefit, education and research excellence, fairness, transparency, integrity and accountability, and data security and privacy.
Review: Agent reviewed
Normalized value: monash_ai_responsible_use_principles
Evidence originale
Evidence 1Monash AI responsible use principles: Community benefit, education and research excellence; Fairness; Transparency; Integrity and accountability; Data security and privacy.
Teaching
Responsible use of AI should be explainable in terms of what AI was used, which AI tools assisted in producing the work, how many versions and drafts were produced, and how outputs were adapted.
Review: Agent reviewed
Normalized value: ai_use_must_be_explainable
Evidence originale
Evidence 1Responsible use of AI should be explainable in terms of: What AI was used; Which AI tools assisted in producing the work, how many versions and drafts were produced; How outputs were adapted.
Ai Tool Treatment
Microsoft Copilot is a generative AI program that has capabilities to generate text and images in response to user prompts. Monash recommends logging in using Monash credentials to ensure data is more protected.
Review: Agent reviewed
Normalized value: copilot_capabilities_and_login_recommendation
Evidence originale
Evidence 1Microsoft Copilot is a generative artificial intelligence (GenAI) program that has capabilities to generate text and images in response to user prompts. Make sure to log in using your Monash credentials before accessing Copilot. This ensures that your data is more protected.
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
9 source attribution
Acknowledging the use of AI - Student Academic Success
monash.edu
AI and assessment - Learning and Teaching - Monash University
monash.edu
AI and assessments - Student Academic Success - Monash University
monash.edu
AI Policies and Guidelines - Artificial intelligence at Monash
monash.edu
AI statements - Learning and Teaching: Teach HQ - Monash University
monash.edu
Guidance on Generative AI - Graduate Research - Monash University
monash.edu
Microsoft Copilot - Student Academic Success
monash.edu
Responsible and ethical use of AI - Student Academic Success
monash.edu
Responsible use of AI in education at Monash - Learning and Teaching
monash.edu
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.