The curated records of Task 2.2. The account view reads them grouped by level and domain; the database view opens the same records for filtering, sorting and downloading.
Resources developed for educators and learners include a course on AI in teaching hosted in the learning management system, an experimentation environment, and a regional hub whose materials teachers can integrate into their own courses. Delivering staff development inside the same system staff already teach in removes one barrier to participation.
The university maintains a set of instruments that are revised regularly: an AI guide, recommendations for action, a service agreement on the use of AI systems, and a register of processing activities. The combination places advisory guidance and data protection documentation in the same institutional package.
The institution updated its AI guidelines in April 2025 and its recommendations for action in July 2025, both advisory in character, while an overarching AI strategy and guidelines for AI in examinations were under development. Alongside them the university maintains a mandatory internal regulation of learning analytics to ensure data privacy, which is the one binding instrument in the set.
The university runs experimental environments that bring a feedback centre, automated grading, personalised support and an immersive collaboration hub together with access to various models for testing. The arrangement gives staff a bounded space in which tools can be trialled before any decision about institutional deployment.