Certificate

PGCert Integrity and Generative AI (UK Dual Pathway)

Authorship, disclosure, and assessment in the generative-AI year—policy for dual pathway, not a coding bootcamp.

Online or on campus

9 months15 creditsEnglish (dual pathway: Edinburgh campus or tuition-free online; one academic standard)

PGCert Integrity and Generative AI (UK Dual Pathway)

Overview

Generative AI broke ‘submit a take-home essay and hope’. This PGCert starts with assessment design, disclosure, and oral confirmation—especially where identity-checked exams already exist. You will not be trained as a machine-learning engineer. UK higher education and qualifications-regulation literacy appear because complaints will cite both. Dual-pathway students must not face a harsher AI rule than campus students, or a laxer one. Faculty mark whether your policy is enforceable at 11 p.m. in a storm week. The award is not a coding certificate and not a detector-vendor partnership. Capstones are policy-and-task-design dossiers for a named programme. University of Brigant already runs identity-checked assessment; generative AI is treated as an authorship and task-design problem, not as a reason to buy humiliation software. Policies must be enforceable in a storm week. Ofqual-facing language appears in complaints literacy, not as a claim of regulator employment. Campus and online rules must be the same award, not two moralities. A policy that cannot be applied on a Sunday night in a rented room is not a policy. Staff marking load is part of the design, not an afterthought. PGCert Integrity and Generative AI (UK Dual Pathway) is taught as one award, not a list of unrelated modules. The published length is 9 months, and the credit total is 15. Students move from What a University Can Still Assess through What a University Can Still Assess; Disclosure, Permitted Use, and Grey Zones; Process Portfolios and In-Time Tasks; Allegations, Evidence, and Student Rights; Scottish and UK Sector Reference Points as Literacy, and finish on Scottish and UK Sector Reference Points as Literacy. Each course has a question, a method, and a submission. In this field, students define a measurable question, fit a method that can be checked, and report where it fails. Reading is a dataset description, a methods note, and one published evaluation. The artefact a marker expects is a project note with the question, the method, the result, and the limitation. The award is built so that a graduate can do the following in practice: Write an authorship and disclosure policy that can be applied Redesign tasks to assess the person under generative AI Align campus and online rules as one award Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.

Fifteen credits, nine months: authorship constructs, task design, conduct processes, and a supervised dossier. Dual pathway. No AI-vendor logos.

Who This Programme Is For

Module leaders and programme directors
Academic-conduct and quality officers
Learning technologists supporting dual pathway
Student-union education officers seeking policy literacy

How you can study

Recommended

Study online

100% tuition-free online

Online tuition is free. Online examinations are free. There is no exam fee for online study.

✦ Tuition: £0 / $0
✦ Examinations are free. There is no exam fee.
✦ Learn from anywhere · Live online seminars

Apply online →

On-campus study

Study at our campus

Prefer to learn at our Edinburgh campus? Campus tuition and campus examinations are charged. The published campus price is on each programme page.

✦ Tuition: £3,500 / US$4,500/year
✦ Location: 3 Lady Lawson St, Edinburgh EH3 9DS, United Kingdom
✦ Campus examinations are charged
✦ In-person seminars, library & student services

Apply for campus →

What You Will Learn

Write an authorship and disclosure policy that can be applied
Redesign tasks to assess the person under generative AI
Align campus and online rules as one award
Run conduct processes without detector worship
Refuse vendor-certificate and surveillance-product claims

Curriculum

Module 1: Authorship after generative models

Code	Course	Credits · hours
UOB901	What a University Can Still Assess What a University Can Still Assess (UOB901) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using What a University Can Still Assess as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. UOB901-M1 · The question, the unit of analysis, and data quality — What a University Can Still Assess UOB901-M2 · Features, baselines, and error — What a University Can Still Assess UOB901-M3 · Validation, leakage, and what the model must not decide — What a University Can Still Assess UOB901-M4 · Monitoring, drift, and human review — What a University Can Still Assess UOB901-M5 · Interpretation for a non-technical decision maker — What a University Can Still Assess UOB901-M6 · A supervised project with method, result, and limitation — What a University Can Still Assess	3 · 30 h
UOB902	Disclosure, Permitted Use, and Grey Zones Disclosure, Permitted Use, and Grey Zones (UOB902) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Disclosure, Permitted Use, and Grey Zones as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. UOB902-M1 · The question, the unit of analysis, and data quality — Disclosure, Permitted Use, and Grey Zones UOB902-M2 · Features, baselines, and error — Disclosure, Permitted Use, and Grey Zones UOB902-M3 · Validation, leakage, and what the model must not decide — Disclosure, Permitted Use, and Grey Zones UOB902-M4 · Monitoring, drift, and human review — Disclosure, Permitted Use, and Grey Zones UOB902-M5 · Interpretation for a non-technical decision maker — Disclosure, Permitted Use, and Grey Zones UOB902-M6 · A supervised project with method, result, and limitation — Disclosure, Permitted Use, and Grey Zones	3 · 30 h

Code

Course

Credits · hours

UOB901

What a University Can Still Assess

What a University Can Still Assess (UOB901) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using What a University Can Still Assess as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.

UOB901-M1 · The question, the unit of analysis, and data quality — What a University Can Still Assess
UOB901-M2 · Features, baselines, and error — What a University Can Still Assess
UOB901-M3 · Validation, leakage, and what the model must not decide — What a University Can Still Assess
UOB901-M4 · Monitoring, drift, and human review — What a University Can Still Assess
UOB901-M5 · Interpretation for a non-technical decision maker — What a University Can Still Assess
UOB901-M6 · A supervised project with method, result, and limitation — What a University Can Still Assess

3 · 30 h

UOB902

Disclosure, Permitted Use, and Grey Zones

Disclosure, Permitted Use, and Grey Zones (UOB902) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Disclosure, Permitted Use, and Grey Zones as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.

UOB902-M1 · The question, the unit of analysis, and data quality — Disclosure, Permitted Use, and Grey Zones
UOB902-M2 · Features, baselines, and error — Disclosure, Permitted Use, and Grey Zones
UOB902-M3 · Validation, leakage, and what the model must not decide — Disclosure, Permitted Use, and Grey Zones
UOB902-M4 · Monitoring, drift, and human review — Disclosure, Permitted Use, and Grey Zones
UOB902-M5 · Interpretation for a non-technical decision maker — Disclosure, Permitted Use, and Grey Zones
UOB902-M6 · A supervised project with method, result, and limitation — Disclosure, Permitted Use, and Grey Zones

3 · 30 h

Module 2: Task and oral design

Code	Course	Credits · hours
UOB905	Process Portfolios and In-Time Tasks Process Portfolios and In-Time Tasks (UOB905) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Process Portfolios and In-Time Tasks as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. UOB905-M1 · The question, the unit of analysis, and data quality — Process Portfolios and In-Time Tasks UOB905-M2 · Features, baselines, and error — Process Portfolios and In-Time Tasks UOB905-M3 · Validation, leakage, and what the model must not decide — Process Portfolios and In-Time Tasks UOB905-M4 · Monitoring, drift, and human review — Process Portfolios and In-Time Tasks UOB905-M5 · Interpretation for a non-technical decision maker — Process Portfolios and In-Time Tasks UOB905-M6 · A supervised project with method, result, and limitation — Process Portfolios and In-Time Tasks	3 · 30 h

Code

Course

Credits · hours

UOB905

Process Portfolios and In-Time Tasks

Process Portfolios and In-Time Tasks (UOB905) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Process Portfolios and In-Time Tasks as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.

UOB905-M1 · The question, the unit of analysis, and data quality — Process Portfolios and In-Time Tasks
UOB905-M2 · Features, baselines, and error — Process Portfolios and In-Time Tasks
UOB905-M3 · Validation, leakage, and what the model must not decide — Process Portfolios and In-Time Tasks
UOB905-M4 · Monitoring, drift, and human review — Process Portfolios and In-Time Tasks
UOB905-M5 · Interpretation for a non-technical decision maker — Process Portfolios and In-Time Tasks
UOB905-M6 · A supervised project with method, result, and limitation — Process Portfolios and In-Time Tasks

3 · 30 h

Module 3: Conduct and communication

Code	Course	Credits · hours
UOB909	Allegations, Evidence, and Student Rights Allegations, Evidence, and Student Rights (UOB909) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Allegations, Evidence, and Student Rights as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. UOB909-M1 · The question, the unit of analysis, and data quality — Allegations, Evidence, and Student Rights UOB909-M2 · Features, baselines, and error — Allegations, Evidence, and Student Rights UOB909-M3 · Validation, leakage, and what the model must not decide — Allegations, Evidence, and Student Rights UOB909-M4 · Monitoring, drift, and human review — Allegations, Evidence, and Student Rights UOB909-M5 · Interpretation for a non-technical decision maker — Allegations, Evidence, and Student Rights UOB909-M6 · A supervised project with method, result, and limitation — Allegations, Evidence, and Student Rights	3 · 30 h

Code

Course

Credits · hours

UOB909

Allegations, Evidence, and Student Rights

Allegations, Evidence, and Student Rights (UOB909) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Allegations, Evidence, and Student Rights as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.

UOB909-M1 · The question, the unit of analysis, and data quality — Allegations, Evidence, and Student Rights
UOB909-M2 · Features, baselines, and error — Allegations, Evidence, and Student Rights
UOB909-M3 · Validation, leakage, and what the model must not decide — Allegations, Evidence, and Student Rights
UOB909-M4 · Monitoring, drift, and human review — Allegations, Evidence, and Student Rights
UOB909-M5 · Interpretation for a non-technical decision maker — Allegations, Evidence, and Student Rights
UOB909-M6 · A supervised project with method, result, and limitation — Allegations, Evidence, and Student Rights

3 · 30 h

Module 4: Dossier

Code	Course	Credits · hours
UOB913	Scottish and UK Sector Reference Points as Literacy Scottish and UK Sector Reference Points as Literacy (UOB913) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Scottish and UK Sector Reference Points as Literacy as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. UOB913-M1 · The question, the unit of analysis, and data quality — Scottish and UK Sector Reference Points as Literacy UOB913-M2 · Features, baselines, and error — Scottish and UK Sector Reference Points as Literacy UOB913-M3 · Validation, leakage, and what the model must not decide — Scottish and UK Sector Reference Points as Literacy UOB913-M4 · Monitoring, drift, and human review — Scottish and UK Sector Reference Points as Literacy UOB913-M5 · Interpretation for a non-technical decision maker — Scottish and UK Sector Reference Points as Literacy UOB913-M6 · A supervised project with method, result, and limitation — Scottish and UK Sector Reference Points as Literacy	3 · 30 h

Code

Course

Credits · hours

UOB913

Scottish and UK Sector Reference Points as Literacy

Scottish and UK Sector Reference Points as Literacy (UOB913) is a 3-credit course on PGCert Integrity and Generative AI (UK Dual Pathway), with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Scottish and UK Sector Reference Points as Literacy as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.

UOB913-M1 · The question, the unit of analysis, and data quality — Scottish and UK Sector Reference Points as Literacy
UOB913-M2 · Features, baselines, and error — Scottish and UK Sector Reference Points as Literacy
UOB913-M3 · Validation, leakage, and what the model must not decide — Scottish and UK Sector Reference Points as Literacy
UOB913-M4 · Monitoring, drift, and human review — Scottish and UK Sector Reference Points as Literacy
UOB913-M5 · Interpretation for a non-technical decision maker — Scottish and UK Sector Reference Points as Literacy
UOB913-M6 · A supervised project with method, result, and limitation — Scottish and UK Sector Reference Points as Literacy

3 · 30 h

Career Paths

Academic integrity officer
Programme assessment lead
Quality officer (AI policy)
Learning design (assessment) specialist
Student conduct caseworker

Programme Highlights

Dual-pathway parity of AI rules
Assessment design over detector theatre
Nine months, 15 credits
Ofqual-facing literacy, not staff
No vendor logos

Assessment

Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.

Admission requirements

Academic entry

Bachelor's degree or three years of relevant professional experience
Identity document for remote identity-checked assessment
Preferred: work in teaching, assessment, quality, or academic conduct

English language

English proficiency: IELTS 5.5, TOEFL 46, or equivalent (waived for prior English-medium study). Dual-pathway applicants state Edinburgh campus or tuition-free online as primary mode without changing academic standards. Gaelic/Scots programmes may require additional language evidence as stated on the programme page.

Documents

Brief statement of interest (250 words)
CV or résumé

Programme questions

How long is the PGCert Integrity and Generative AI (UK Dual Pathway)?

The published duration is 9 months. Teaching language: English (dual pathway: Edinburgh campus or tuition-free online; one academic standard). Actual time-to-complete depends on mode and any recognised prior learning.

Can I study this from my country?

You may study this award fully online from your country, or — where published — on campus at Brigant. Online study does not require a student visa. Campus study may.

What does it cost?

Degree tuition for this award is published as £0 / tuition-free on the online pathway. Examination or administrative fees may apply at checkout — never an annual tuition invoice. Check the Fees page for any extras.

What are the entry requirements?

Requirements are grouped on this page (academic, English, documents). Equivalent qualifications are considered. English may be waived after prior English-medium study.

How is the programme assessed?

Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.

Will this award be recognised where I live?

Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. University of Brigant publishes verification pages for certificates. We do not claim automatic equivalence in every country.

How do I apply?

Start an application on this website. Progress is saved from the first step. Admissions: admissions@brigant.uk.

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