Recommendations for lecturers

Recommendations for action

AI tools can support lecturers in the creation of materials, enrich learning processes and encourage students to engage in critical and reflective dialogue. At the same time, they place new demands on transparency, examination formats, data protection and academic integrity.

The following recommendations for action provide lecturers with a compact overview of how AI systems can be used in teaching in a responsible, educational and legally compliant manner. They are based on the checklist for the legally compliant use of AI and the AI traffic light system for the examination context.

Create transparency

Communicate at an early stage whether and how AI may be used at your event. Use the AI traffic light systemto clearly define the permissible scope and communicate it transparently to students.
Record the rules for using AI in writing, e.g. in the assignment, in the accompanying OLAT course, in the exam organisation record in KLIPS or in the first session. Formulation modules for the respective traffic light colour can be found in the KI traffic light system.
Set a good example: Label AI-generated content in your own teaching and learning materials, for example with AI-generated images in the slide set (see Art. 50 AI Regulation).

Integrating AI into teaching in a meaningful way

Make generative AI the subject of teaching, e.g. by analysing strengths, weaknesses, bias, hallucinations or the role of training data.
Before designing examination services, reflect on the learning objectives you are pursuing and whether AI supports or counteracts them. The Key questions in the AI traffic light system help you with the categorisation.
Encourage students to use AI competently and reflectively. You will find an overview of target group-specific offers for acquiring AI competences here.

Strengthening independence and academic integrity

Emphasise the students' responsibility for the correctness and comprehensibility of their work. Their own contribution in terms of content and design must represent the main part of their examination performance.
Set students to the colour that matches the selected traffic light colour. Declaration of independence ready. Sample declarations of independence can be found in the KI traffic light system.
Make it clear that the use of AI in the Appendix on the use of AI tools must be documented (tool used, purpose, sections affected, critical examination). Determine whether a prompt/output minutes must also be attached.
Point out that unauthorised or unmarked AI use can be considered an attempt to cheat in accordance with the examination regulations framework.

Observe data protection and copyright

Point out that no personal or confidential data may be entered into open AI systems.
Point out that copyrighted works of third parties (e.g. textbooks, journal articles) may not be entered into AI systems without the consent of the copyright holder.
Recommend the use of AI services provided by the university. You can find an overview on the page AI systems & tools.
If you have any questions about data protection, please contact Information Security and Data Protection Unit.
A compact overview of all legal requirements before, during and after the use of AI services - including data protection, copyright and the AI Regulation - is provided by the Checklist for the legally compliant use of AI.

Regulating AI in the audit context

Use the AI traffic light system For each examination performance, determine whether the use of generative AI is not permitted (red), partially permitted (yellow) or permitted (green). The key questions in the traffic light system will help you to categorise them.
Communicate and justify the chosen traffic light colour at an early stage, e.g. in the assignment, in the OLAT course or in KLIPS. Formulation modules for each traffic light colour can be found in the KI traffic light system.
Design tasks in such a way that the independent performance remains recognisable - for example by including reflection, justification, case reference or personal positioning.

Promoting AI competences and accompanying learning processes

Help students to classify AI results professionally and critically - for example by jointly analysing AI outputs in the course.
Encourage a culture of experimental learning: openly dealing with the possibilities and limitations of AI promotes a reflective development of expertise.
Please note that the acquisition of AI competences is mandatory according to Art. 4 of the European AI Regulation.
If required, use the Koblenz AI competence model as an orientation framework for competence development.

Monitor developments

Bear in mind that AI systems are developing rapidly and that their functional scope, risks and performance can change at short notice.
Stay informed about internal university developments, new services and updated recommendations. All important information is published on the central Service page on AI at the University of Koblenz bundled.
If you have any questions, uncertainties or need clarification, please contact the authorised representative for artificial intelligence.

At a glance

Create transparency: Communicate rules on AI use clearly and at an early stage.

Integrating AI into teaching: Use AI as an object of teaching and reflect on learning objectives.

Strengthen integrity: Require a declaration of independence and documentation of the use of AI.

Observe data protection and copyright: Do not enter any personal, confidential or protected content into AI systems.

Regulate AI in the audit context: Select traffic light colour, give reasons and design tasks in a competence-oriented way.

Promoting AI competences: Critical categorisation of AI results.

Observe developments: Stay informed; the AI authorised representative provides support with questions.

Examinations and AI

An AI traffic light system for the use of generative AI in examination settings, featuring guiding questions, phrasing templates, and sample declarations of originality for lecturers

Data protection, copyright, and the AI Act

A checklist for using generative AI services in compliance with the law

Further information

Learning path "Using AI constructively in teaching" for lecturers (Interdisciplinary Centre for Teaching)

The learning path "Using AI constructively in teaching" is aimed at all lecturers at our university. The learning path consists of impulse workshops and in-depth workshops and was designed by the Interdisciplinary Centre for Teaching based on the European DigCompEdu competence framework. The learning path offers a changing, target group-orientated range of courses that address current topics and lecturers' needs.

Click here for the learning path