Staff Guide: Assessing Student Generative-AI Use
A practical guide for teaching staff on reaching fair, consistent decisions when student AI use is suspected or disclosed.
Audience: Teaching staff, unit coordinators, integrity officers
Writing Samples
Writing samples that demonstrate translating research and policy into guidance people can actually use.
A practical guide for teaching staff on reaching fair, consistent decisions when student AI use is suspected or disclosed.
Audience: Teaching staff, unit coordinators, integrity officers
Plain-language guidance helping students use generative AI legitimately: check the rules, stay the author, verify everything, disclose honestly.
Audience: University students
A two-page-style brief for decision-makers on why detection-led responses fail and what a workable policy architecture contains.
Audience: University leadership, policy officers, quality agencies
A step-by-step SOP for collecting, archiving and version-controlling institutional policy documents for research use.
Audience: Research assistants, research students
How to write an honest, specific and proportionate AI-use declaration, with worked examples of good and poor disclosures.
Audience: Students, researchers, professional writers
Reference documentation for a policy-extraction API endpoint, demonstrating developer-facing technical writing.
Audience: Software developers
An end-user guide to recording policy coding decisions in the project's coding matrix, written for non-technical research staff.
Audience: Research assistants, coders
A short help-centre article answering a single student question in task-oriented steps.
Audience: Students using a learning management system
A methods guide walking research students through designing and running a defensible comparative policy analysis.
Audience: Research students, early-career researchers