Practice Matrix · Micro

Teaching Practice

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

Back to the matrix

practices

Who

—

Where

Source report

The reading of this intersection

The count in the cell shows density; what the intersection says is carried by the reading below.

What this intersection documents is a set of disciplines rather than a tool. Teachers report subjecting every output to a check for academic precision, pedagogical alignment and ethical standards before it reaches a student, while students report requesting direction and an assessment of work already completed rather than the completion of the work itself. The third report identifies augmentation rather than replacement as the framing that covers the majority of responses concerning use, and this framing recurs across stakeholder groups and purposes.

A third record moves one stage earlier in the process. A teacher reports assigning a voice to the model, constructing separate agents for separate areas of expertise, and selecting models that reflect a personal teaching style. In this instance the tool is not adopted as delivered but configured, and the configuration expresses a pedagogical preference rather than a technical one.

All three records depend on nothing supplied by an institution. This constitutes both their strength and their limitation: they require no licence, no committee and no platform, and they equally leave no record that an institution might evaluate, transfer or require. Two of the three levels represented in this matrix operate through instruments that can be inspected, whereas this level operates through practices that can only be reported.

Who, and where

The actors carrying out the practice and where they are. Where a source does not name the institution, no attribution is made.

Institutions and actors

The source does not name the institution

Countries

Multiple countries

Context

Higher education

How it was done

Each record stands with its imprint, its short reading and the sentence found in the source. Quotations are not shortened, so that a reader can check the inference.

Configuring the model to a teaching style through voice and specialised agents

A teacher reports assigning a voice to the model, creating several agents specialised in different areas of expertise, and selecting models that reflect a personal teaching style. The tool is not adopted as delivered but configured, and the configuration expresses a pedagogical preference rather than a technical one.

Institution: not stated in the source
Country: Multiple countries
Delivery model: not stated in the source
Context: Higher education
Contributed by: not stated in the source
Year: 2026
Maturity: Piloted
Scalability: Emerging
Transferability: Established
Source report: R3

Evidence

A verbatim teacher account given under the theme on increased awareness and caution, where the respondent sets out the configuration alongside a more deliberate approach to prompting.

I have assigned a voice to the AI and created several agents specialising in different areas of expertise. I use models that reflect my teaching style.

R3, p. 3.2.5

Human-in-the-loop checking of every AI output before use in teaching

Teachers describe subjecting every AI output to a check for academic precision, pedagogical alignment and ethical standards before use, and describe the tool as a partner for refining ideas rather than an author. The framing that dominates the third round is augmentation rather than replacement, and it recurs regardless of the purpose of use.

Institution: not stated in the source
Country: Multiple countries
Delivery model: not stated in the source
Context: Higher education
Contributed by: not stated in the source
Year: 2026
Maturity: Established
Scalability: Piloted
Transferability: Embedded
Source report: R3

Evidence

The report identifies this as the theme covering most answers to the question on use, and supports it with quotations from several stakeholder groups.

Rather than using the raw output, I always apply a 'human-in-the-loop' approach to ensure the final content meets professional standards.

R3, p. 3.3.3

Students using AI for self-assessment instead of task completion

Students describe using the tool to obtain direction, to get help with parts they do not understand and to identify the strengths and weaknesses of work they have already done, rather than to have the work done for them. The practice is located within the learning situation and depends on nothing other than the student's own decision as to what to ask.

Institution: not stated in the source
Country: Multiple countries
Delivery model: not stated in the source
Context: Higher education
Contributed by: not stated in the source
Year: 2026
Maturity: Piloted
Scalability: Piloted
Transferability: Embedded
Source report: R3

Evidence

Reported through student quotations under the theme covering most answers on use; no institutional instrument mediates the practice, which is why it is recorded at the micro level.

Instead of having AI do my homework for me, I use it to ask for ideas that can guide me in the right direction

R3, p. 3.3.3