What Communities of Practice are
Communities of Practice (CoPs) are structured spaces where teachers from different disciplines, school leaders and, in some cases, students work together around a common educational challenge. In AI-DL, that challenge is clear: making data literacy meaningful across subjects in a world where GenAI is already influencing how information is produced, selected and evaluated.
AI-DL is already working with around 40 European schools. These schools are not only recipients of project resources; they are helping to co-design the core activities and make sure they are realistic for classrooms, subjects and national contexts.
What schools are and will be doing
- Giving feedback on the AI-DL Framework so it reflects classroom realities and the questions teachers actually face.
- Helping develop concrete examples that can be included in the next version of the framework and used in training.
- Reviewing training-module outlines and proposed content, so activities are better aligned with teachers’ needs, students’ experiences and school priorities.
- Preparing for the next phase, where teachers will test, adapt and reflect on AI-DL activities with their students.
Why it matters
Data literacy cannot be built by one subject alone. GenAI raises questions for science, languages, humanities, social sciences, arts and vocational learning: Where did this data come from? What is missing? What assumptions are built into the output? How should students use, challenge and communicate AI-supported information?
By bringing colleagues together, CoPs help schools move from isolated experimentation to a shared strategy. Teachers can compare needs, share examples, discuss difficulties and agree on common priorities. This makes data literacy less of an external project objective and more of a living part of school culture.
From Framework to Training kit
The training kit is the bridge between the AI-DL Framework and classroom experimentation. It is being designed to help teachers explore key issues in data literacy and GenAI, and then translate them into learning activities for students.
What you’ll find inside
- Three training modules connected to the AI-DL Framework competences.
- Activities and reflection tasks that help teachers examine GenAI outputs, data use, reliability, bias, privacy, ethics and participation.
- Practical examples that can be adapted across subjects and national contexts.
- Support for designing classroom activities where students do more than use AI tools: they question them, interpret them and make responsible decisions about them.
The first full version of the training kit is planned by the end of 2026. Teacher training and classroom implementation will follow in 2027, with feedback from schools used to refine the resources further.
The AI-DL Framework groups data literacy in the GenAI era into four interconnected areas.
From local experience to European impact
Each participating school contributes to a wider European effort. Local classroom experiences will help shape resources, recommendations and examples that can support other teachers and schools across Europe.
This is the AI-DL pathway from policy to practice: from European and national priorities on digital education, to a shared competence framework, to teacher training, to classroom experimentation, and finally to open resources for the wider educational community.
School participation makes this pathway concrete. It supports the development of students who are not only able to use AI tools, but also able to question them, understand the role of data, identify risks and opportunities, and act as critical, ethical and responsible citizens in a digital society.
