Recommendations for the use of generative artificial intelligence in teaching in youth education

Policy development
Practical measure/Initiative
Denmark
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Timeline
  • 2024Implementation
  • 2025Implementation
ID number
49480

Background

A brief overview of the context and rationale of the policy development, explaining why it is implemented or why it is important.

Many students in upper secondary schools and vocational programmes use generative artificial intelligence, including chatbots such as ChatGPT and Microsoft Copilot during teaching and in their schoolwork, however, not always in a well-reflected way. Students need to learn to use technology appropriately and learn to evaluate and qualify content produced by artificial intelligence. Also, teachers find it difficult to navigate the new technological developments and the influence on teaching.

Objectives

Goals and objectives of the policy development.

The purpose of the recommendations is to give school leaders and teachers the knowledge they need to organise teaching in light of technological developments, thereby promoting good use of generative AI for teaching and schoolwork, both as students and teachers.

Description

What/How/Who/For whom/When of the policy development in detail, explaining its activities and annual progress, main actors and target groups.

Together with experts and practitioners from the field of education, the National Agency for Teaching and Quality (STUK) has developed a list of recommendations for the use of generative AI in youth education (both in school and for homework). The specific recommendations for VET relate to the core subjects, such as mathematics, Danish etc. In the recommendations, the agency emphasises that school management should set a framework for the use of digital tools, so that students and teachers are not alone in assessing where it makes sense to use technology to strengthen students' learning and digital education.

Recommendations for upper secondary schools and VET institutions

School leadership ensures a common direction and clear framework for the appropriate and safe use of generative AI

  1. formulate an overall, shared direction for the use of generative AI;
  2. use solutions that the school leadership assesses to be in compliance with current GDPR regulations;
  3. define common and concrete guidelines and rules for teachers’ and students’ use of generative AI.

School leadership ensures that teachers are able to manage generative AI in teaching

  1. support dialogue and exchange of experiences among teachers about the possibilities and limitations of the technology;
  2. prioritise the development of teachers’ knowledge, skills, and didactic competences related to AI;

School leadership and teachers plan teaching in, with, and without generative...

Together with experts and practitioners from the field of education, the National Agency for Teaching and Quality (STUK) has developed a list of recommendations for the use of generative AI in youth education (both in school and for homework). The specific recommendations for VET relate to the core subjects, such as mathematics, Danish etc. In the recommendations, the agency emphasises that school management should set a framework for the use of digital tools, so that students and teachers are not alone in assessing where it makes sense to use technology to strengthen students' learning and digital education.

Recommendations for upper secondary schools and VET institutions

School leadership ensures a common direction and clear framework for the appropriate and safe use of generative AI

  1. formulate an overall, shared direction for the use of generative AI;
  2. use solutions that the school leadership assesses to be in compliance with current GDPR regulations;
  3. define common and concrete guidelines and rules for teachers’ and students’ use of generative AI.

School leadership ensures that teachers are able to manage generative AI in teaching

  1. support dialogue and exchange of experiences among teachers about the possibilities and limitations of the technology;
  2. prioritise the development of teachers’ knowledge, skills, and didactic competences related to AI;

School leadership and teachers plan teaching in, with, and without generative AI

  1. generative AI should only be used when it provides clear academic, didactic, and pedagogical value;
  2. explore the possibilities and limitations of the technology together with students in an open and curious way;
  3. discuss with students how, when, and for what purpose they can use generative AI in different subjects;
  4. design teaching that strengthens students’ critical and reflective use of the technology;
  5. plan written assignments and learning activities so that students learn to use generative AI to improve and qualify their working processes.
2024
Implementation

The recommendations were introduced by the National Agency for Teaching and Quality (STUK) in late fall of 2024.

2025
Implementation

The initiative was operational and ran as regular practice.

Bodies responsible

This section lists main bodies that are responsible for the implementation of the policy development or for its specific parts or activities, as indicated in the regulatory acts. The responsibilities are usually explained in its description.
  • Ministry of Children and Education
  • National Agency for Education and Quality (STUK)

Target groups

Those who are positively and directly affected by the measures of the policy development; those on the list are specifically defined in the EU VET policy documents. A policy development can be addressed to one or several target groups.

Learners

  • Learners in upper secondary, including apprentices
  • Young people (15-29 years old)

Education professionals

  • Teachers

Thematic categories

Thematic categories capture main aspects of the decision-making and operation of national VET and LLL systems. These broad areas represent key elements that all VET and LLL systems have to different extents and in different combinations, and which come into focus depending on the EU and national priorities. Thematic categories are further divided into thematic sub-categories. Based on their description, policy developments can be assigned to one or several thematic categories.

Modernising VET infrastructure

This thematic category looks at how VET schools and companies providing VET are supported to update and upgrade their physical infrastructure for teaching and learning, including digital and green technologies, so that learners in all VET programmes and specialities have access to state-of-the-art equipment and are able to acquire relevant and up-to-date vocational and technical skills and competences. Modernising infrastructure in remote and rural areas increases the inclusiveness of VET and LLL.

Improving digital infrastructure of VET provision

This thematic sub-category focuses on establishing and upgrading to state-of-the-art digital infrastructure, equipment and technology, such as computers, hardware, connectivity and good broadband speed that should ensure quality and inclusive VET provision, especially in blended and virtual modes. It also includes specific measures to remove the digital divide, e.g. supporting geographically remote or rural areas to ensure social inclusion through access to such infrastructure for learning and teaching. It also includes support measures for learners from socially disadvantaged backgrounds to acquire the necessary equipment.

Teachers, trainers and school leaders competences

Competent and motivated VET teachers in schools and trainers in companies are crucial to VET becoming innovative and relevant, agile, resilient, flexible, inclusive and lifelong.

This thematic category comprises policies and practices of initial training and continuing professional development approaches in a systemic and systematic manner. It also looks at measures aiming to update (entry) requirements and make teaching and training careers attractive and bring more young and talented individuals and business professionals into teaching and training. Supporting VET educators by equipping them with adequate competences, skills and tools for the green transition and digital teaching and learning are addressed in separate thematic sub-categories.

The measures in this category target teachers and school leaders, company trainers and mentors, adult educators and guidance practitioners.

Supporting teachers and trainers for and through digital

This thematic sub-category is in line with the EU policy focus on the digital transition, and refers to professional development and other measures to prepare and support teachers and trainers in teaching their learners digital skills and competences. It also covers measures and support for them to increase their own digital skills and competences, including for teaching in virtual environments, working with digital tools and applying digital pedagogies. Emergency measures taken during the COVID-19 pandemic also fall into this sub-category.

Subsystem

Part of the vocational education and training and lifelong learning systems the policy development applies to.
IVET

Further reading

Sources for further reading where readers can find more information on policy developments: links to official documents, dedicated websites, project pages. Some sources may only be available in national languages.
The use of generative artificial intelligence

Country

Denmark

Type of development

Policy developments are divided into three types: strategy/action plan; regulation/legislation; and practical measure/initiative.
Practical measure/Initiative
Cite as

Cedefop, & ReferNet. (2026). Recommendations for the use of generative artificial intelligence in teaching in youth education: Denmark. In Cedefop, & ReferNet. (2026). Timeline of VET policies in Europe (2025 update) [Online tool].

https://www.cedefop.europa.eu/en/tools/timeline-vet-policies-europe/search/49480