Policy presence
Kingston University, London has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Kingston upon Thames, United Kingdom
Kingston University, London
Record status
Review: Agent reviewed
Policy profile
Review: Machine candidate
AI disclosure
Kingston University, London has 3 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
Kingston University, London has 4 source-backed public claims for coursework; deterministic analysis status: required.
Exams
Kingston University, London has 4 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
Kingston University, London has 4 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
Kingston University, London has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.
Named AI services
Kingston University, London 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.
AI tools
No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.
Evidence-backed claims
5 reviewed evidence-backed public claim
Academic Integrity
Kingston University's 2025/26 Academic Integrity procedure defines unacceptable use of generative AI as presenting AI-generated content as one's own without proper acknowledgement, except when the assessment brief explicitly permits it.
Review: Agent reviewed
Normalized value: unacceptable_genai_presenting_ai_content_without_acknowledgement_unless_assessment_brief_permits
Original evidence
Evidence 1The University defines the unacceptable use of Generative Artificial Intelligence as the act of presenting content generated by artificial intelligence tools (such as text, media, tables etc - list not exhaustive), as one's own without proper acknowledgement, except where the nature of the assessment makes this permissible and is explicitly stated in the assessment brief.
Academic Integrity
Kingston University's AG2 guidance says that if generative AI is used as part of the editorial process, the student must acknowledge that use.
Review: Agent reviewed
Normalized value: generative_ai_editorial_process_use_must_be_acknowledged
Original evidence
Evidence 1Where a Generative AI has been used as part of the editorial process, then this must be acknowledged by the student.
Academic Integrity
Kingston University's 2025/26 Academic Integrity procedure says contributions by artificial intelligence tools must be properly acknowledged.
Review: Agent reviewed
Normalized value: ai_contributions_must_be_acknowledged
Original evidence
Evidence 1Contributions by artificial intelligence (AI) tools must also be properly acknowledged.
Ai Tool Treatment
Kingston University's AG2 editorial-help guidance covers software tools including generative AI when students use third-party help in draft or final assessment work.
Review: Agent reviewed
Normalized value: generative_ai_treated_as_possible_third_party_editorial_help
Original evidence
Evidence 1This guidance is for use when a student is considering whether to employ a third party such as a professional copy editing or proof-reading company or software tool (including generative artificial intelligence (GAI)) when producing work in draft or final version.
Source Status
Kingston University's 2025/26 regulation-change summary states that AR6 and AR7 introduced a formal definition of generative AI use within types of academic misconduct, and that AG2 became standalone guidance referencing AI and non-AI editorial help.
Review: Agent reviewed
Normalized value: 2025_26_genai_academic_integrity_definition_and_ag2_editorial_help_source_status
Original evidence
Evidence 1Introduction of a formal definition of use of generative artificial intelligence articulated within our current different types for academic misconduct. This guidance was previously published as an Annex within the Academic Integrity Procedures for Taught and Research degrees (AR6 and AR7) but has been reviewed as a new standalone document which references both AI and non-AI editorial help.
Candidate claims
0 machine or needs-review claim
Official sources
3 source attribution
Academic Guidance 2: Guidance on Editorial Help for Student Assessment 2025-2026
assets.kingston.ac.uk
Academic Integrity Taught Courses 2025-2026
assets.kingston.ac.uk
Policies and regulations - Summary of changes to regulations for 2025-2026
assets.kingston.ac.uk