Report

Practice Matrix

Rows are practice domains, columns are the level at which the practice is enacted: micro for classroom and learning design, meso for institutional governance, macro for national policy. Each cell reports how many documented practices were found and opens the underlying entries.

Practice Matrix
DomainMicroClassroom and learning designMesoInstitutional governanceMacroNational policy
Curriculum and Learning Design1Design work entering the single course3A complete qualification built on the technology3Expanding provision and a design framework
Teaching Practice3Verification, self-assessment and a configured tool—Not documented—Not documented
Assessment and Academic Integrity2Feedback against teacher-set criteria and verification before submission4Declaration forms and boundaries at the assessment event1A national body generating examination items
Student Support and Guidance—Not documented4Assistants ranging from rule-based systems to a project portfolio—Not documented
AI Literacy and Professional Development4Two instruments and the competence acquired without them4The most developed institutional response1A national platform rather than a national rule
Governance, Strategy and Policy—Not documented7From delegated discretion to institutional frameworks10European regulation beneath uneven national instruments
Ethical Frameworks and Responsible Use1Declaration in the absence of a form2Permission with conditions, and authorship refused2Advisory guidance reaching universities by two routes
Data Protection, Privacy and Security1The rule that operates at the point of entry2Controlling the setting in which the interaction occurs—Not documented
Equity, Inclusion and Accessibility—Not documented1Inclusion addressed through assessment design—A recommendation rather than an instrument
Infrastructure, Tools and Procurement—Not documented3Experimental environments preceding services2Shared provision at system level
Quality Assurance, Monitoring and Evaluation—Not documented—Not documented2Quality assurance and a single binding prohibition
Partnership, Networks and Transferability—Not documented—Not documented1Curriculum as a route into the sector
Densityfewer → more

Table 1. The number in a cell is the count of practices documented at that domain and level. Colour intensity is scaled to the highest value in the matrix rather than to an absolute count, so the tones show relative weight across domains. An empty cell is a finding rather than an omission: no documented practice was found at that intersection.

Figure 1

The three levels: who decides, what the instrument looks like, what counts as evidence

MicroClassroom and learning design
Who decides
The teacher and the student, inside a single learning encounter
What the instrument looks like
A habit, a task instruction, a criterion written for one assignment
What evidence looks like
An account given by the person who did it; nothing is filed anywhere
MesoInstitutional governance
Who decides
A rectorate, a vice-rectorate, a committee, a faculty office
What the instrument looks like
A policy, a guideline, a form, a licence, a training programme
What evidence looks like
A document that can be opened, dated and compared between years
MacroNational policy
Who decides
A ministry, a higher education authority, a quality agency, a legislature
What the instrument looks like
A strategy, an ethical guide, a regulation, a funding rule, an action plan
What evidence looks like
A published instrument, with its force stated or left unstated

Figure 1. The diagram sets out the rule by which every record in this report was assigned to a level. A level is determined by where the decision constituting the practice is taken and not by who is affected by it. Accordingly, a national guide addressed to researchers remains at the macro level, while a centrally provided tool configured course by course is assigned to the micro level. Reading the three bands from the bottom upwards also accounts for the density of the matrix, in that the two lower bands operate through instruments that can be inspected and counted, whereas the upper band operates through practices that exist only where a respondent reports them.

Figure 2

Force of instruments, from advisory to binding

AdvisoryBinding
MacroNational ethical guide on generative AI in research
the partner states: all advisory
MacroNational material gathering legislation and recommendations
advisory rather than binding
MesoInstitutional AI guidelines, second version April 2025
advisory in character
MesoInformation security guideline prescribing device, account and tool
force not stated in the source; placed conservatively
MesoProhibition during examinations, permission in assignments
the boundary is the assessment event
MesoInternal regulation of learning analytics
the institution calls it mandatory
MesoDeclaration form signed as a condition of thesis submission
a required document
MacroProhibition on generative tools in research funding assessment
explicitly prohibited

Figure 2. Position on the axis is derived from what the source states about the instrument rather than from an assessment of its apparent importance. Where a partner records that guidance is advisory, or that a regulation is mandatory, the wording determines the position; where binding force is left unstated the instrument is placed conservatively. Read from left to right, the axis represents the central asymmetry identified in this report: the numerous instruments are located on the advisory side, while the few that bind are institutional and narrow in scope, with one national exception that binds evaluators rather than those being evaluated.

Practice Domains

The rows of the matrix. Opening a domain shows its reading across the three levels, together with its practices and figures.

Curriculum and Learning Design7

Where generative AI enters programme outcomes, course structure, learning activities and materials.

Teaching Practice3

Classroom and online delivery: how teaching staff use generative AI while teaching and how students use it while learning.

Assessment and Academic Integrity7

Assessment redesign, disclosure requirements, detection practices and integrity regulation.

Student Support and Guidance4

Advising, tutoring, accessibility support and student-facing AI services beyond the course itself.

AI Literacy and Professional Development9

Training, certification and capacity building for students, teaching staff and administrators.

Governance, Strategy and Policy17

Institutional strategy, formal policy instruments, committees, decision rights and national regulation.

Ethical Frameworks and Responsible Use5

Codes of conduct, ethical principles, human oversight requirements and responsible use guidance.

Data Protection, Privacy and Security3

GDPR compliance, data processing agreements, consent, retention and information security.

Equity, Inclusion and Accessibility1

Unequal access to tools, language and disability accommodation, and the distributive effects of AI adoption.

Infrastructure, Tools and Procurement5

Licensing, institutional deployments, integration with the virtual learning environment and vendor arrangements.

Quality Assurance, Monitoring and Evaluation2

Evidence collection, pilot evaluation, indicators, accreditation expectations and accountability mechanisms.

Partnership, Networks and Transferability1

Cross-institutional collaboration, sector networks, and the conditions under which a practice transfers to another context.