Change log

Université de Montpellier

Tracker history: 0 release records.

Change summary

Current public record freshness and review state.

6 current claims; 3 official sources.

This page combines all public release diffs for Université de Montpellier. Individual release snapshots remain available from their release-specific URLs.

No recorded updates are available in this tracker history.

This tracker 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.

Newly extracted claims are tracker additions and are not necessarily newly published by the university. Source snapshot changes show hash changes for the same source URL and are not by themselves policy changes.

Diff categories

Semantic classification for this release diff.

Tracker claim text0Newly extracted0Evidence0Source snapshots0Source text0Source added0Source removed0

Recorded text comparisons

Only recorded comparisons with an exact Claim ID match are shown.

No recorded updates are available in this tracker history.

Release history

Tracker history: 0 release records.

Current claim records

Current claim records: 6.

teaching

UM's official AI hub says it offers multiple pathways to help teachers, researchers, staff, and students discover and appropriate AI uses, including AI tools/platforms, resources, self-training, and student acculturation.

Review: Agent reviewedConfidence84%Evidence1Languagesfr

ai_tool_treatment

UM's digital-services guidance says the university provides institutional Microsoft Copilot access through A1 and A3 licences for staff and students, with data-protection advantages.

Review: Agent reviewedConfidence88%Evidence1Languagesfr

academic_integrity

UM's AI-in-training principles say student AI use should respect university regulations, rules for each teaching activity, and assessment-specific instructions; expectations should be clarified in course and assessment materials.

Review: Agent reviewedConfidence93%Evidence1Languagesfr

privacy

UM's AI-in-training principles say confidentiality, privacy, personal data, and intellectual property protections should be guaranteed, and no nominative, confidential, or sensitive data should be used in a public AI tool.

Review: Agent reviewedConfidence95%Evidence1Languagesfr

teaching

UM's AI-in-training principles say decisions to use or address AI in training activities rest with teaching staff and should align with learning objectives.

Review: Agent reviewedConfidence92%Evidence1Languagesfr

source_status

Universite de Montpellier has official AI-in-training principles, but this staged crawl found no separate central binding AI policy page.

Review: Agent reviewedConfidence90%Evidence1Languagesfr

Source snapshots

Official source records: 3.