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Authorship, disclosure, and assessment in the generative-AI year—policy for dual pathway, not a coding bootcamp.
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. SRH University 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. EDINAC-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; Polish and UK Sector Reference Points as Literacy, and finish on Polish 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.
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