Report on trends and policies and practices on the use of LLMs and generative AI in the partnership: Report 2

A tool gives students immediate AI-generated formative feedback on text assignments against criteria the instructor defines. Teachers add contextual material and set expectations for each task, and these elements are passed to the model through quality-secured prompts, which keeps the criteria in the teacher's hands while the response time falls to the student's.

A module on critical AI literacy for learning was offered to students from autumn 2025. Placing the subject inside a module rather than a workshop makes participation part of study rather than an optional addition to it.

A teacher describes artificial intelligence being applied as part of study modules while modules about artificial intelligence are offered to teachers and students alike, often using the technology itself as the starting point. The account records curriculum change from two directions at once: the technology enters existing modules and becomes the subject of new ones.

Operational practices introduced and expanded since October 2024 include AI-based early-warning systems for students, AI-assisted feedback, empathic conversational agents, pilots for automated assessment and personalised learning support. The range shows an institution moving from single tools to a portfolio held under one project.

Pilot projects at an institution the source does not name trial two institutional tools: a digital assistant intended to support students as a study companion, and a module writing assistant intended to support staff in creating and reworking content. The pairing repeats the pattern seen elsewhere, where the same institution builds one instrument for learners and another for the staff who design their learning.

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.

A workspace of materials on the basics of artificial intelligence in university work was published for teachers, researchers and support staff in 2025 and is updated as new material appears. A living workspace answers a difficulty that fixed guidance does not, since the tools change faster than documents are revised.

A framework introduced in 2025 provides internal guidelines for integrating AI across educational, administrative and support services, with the stated aim of turning the university into an AI-enabled institution. It answers the gap left a year earlier, when policy was still under discussion and the decision was delegated to individual teachers.

An AI committee was established alongside pilot tests of tools in learning design and IT support and seminars for staff, students and the general public. Extending the seminars beyond the university is unusual in the partnership and treats AI literacy as a public rather than an internal concern.

A working group was set up to develop an institution-wide AI policy and guidelines, with availability announced for 2026. Recording the group rather than the policy is itself the finding: in the second round the institution had teacher guidelines but no institutional instrument.

A library guide published in May 2025 proposes structures for making the use of AI tools transparent: which tools were used, for what purpose and to what extent. A related journal policy states that authorship cannot be attributed to AI, that its use is confined to improving language or readability, that it must be cited, and that authors remain responsible for the validity of what it generates.

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.

New assessment approaches aim to keep tasks robust to the use of AI while maintaining academic integrity and providing differentiated support for diverse needs. Staff capacity is developed through training on responsible use, ethics and inclusivity, with the institution reporting a shift from high-level guidance to concrete application.

A student reports that every university in the country now offers courses related to AI, and a teacher in the same round describes AI-related content being incorporated into curricula alongside the establishment of dedicated research centres. Two independent accounts describe the same national movement from different positions.

A support staff respondent reports that certificate programmes, associate degrees and undergraduate degrees in the field are available at universities, alongside a large number of scientific events each year. The account records provision at the level of qualifications rather than of individual courses.

A government action plan published in January 2025 sets out a roadmap for maximising the potential of AI across the country. Recorded as a change in nationwide practice rather than in policy, it marks the point at which the national conversation shifts from regulation towards deployment.

The conference of Spanish rectors published recommendations covering opportunities, risks, ethics and evaluation. The document is not law but guides the university system, and it explicitly delegates implementation to individual universities while proposing shared principles, competence definitions, internal discussion processes, equity of access and an assessment of ecological cost.

A draft law approved by the government in March 2025 aligns national provision with the EU AI Act. Its appearance in the second round is one of the clearest instances of European regulation propagating into national legislation during the observation period.

Material published in April 2025 by the national agency for education and the ministry gathers legislation and recommendations for 2025, prepared with practitioners, researchers and other stakeholders. The partner records the policies it contains as advisory rather than binding.

A national task force was established and seminars and workshops on generative AI and large language models in education were held. The pairing of a committee with public events is the shape national activity takes where no education-specific framework yet exists.

Guidelines for the confederation were published on 1 July 2025 and a report on AI in education followed a day later. In a partnership where the previous round recorded no national policy at all for this country, the appearance of two instruments within two days marks a distinct change of pace.

A central portal offers generative AI applications to all universities in North Rhine-Westphalia and is accessible to both staff and students. The arrangement answers procurement, access and cost at the level of a state system rather than leaving each university to negotiate separately.