About the project
Building educators’ AI competence in designing Retrieval-Augmented Generation for teaching and learning in higher education — an Erasmus+ cooperation partnership.
Large language models are entering teaching and learning fast, but their use is often ad hoc, prompt-based and weakly anchored in educational knowledge. That raises real concerns about reliability, accuracy, bias, transparency and data protection.
Retrieval-Augmented Generation (RAG) combines generative AI with curated, domain-specific knowledge sources — lecture notes, slides, scientific publications, exams, lab materials — so that AI support in a course is more controllable, explainable and context-aware. Educators across Europe, however, currently lack the training, pedagogical frameworks and institutional support needed to design and run RAG-based solutions.
RAG4Edu closes that gap. It develops a competence-based RAG curriculum and a modular training programme with micro-learning modules, group-based learning activities, accessible tools, templates and worked examples that let educators create their own RAG applications without advanced AI skills. Cross-country pilots validate the programme, and a European Community of Practice carries it beyond the project.
The project promotes European, values-aligned AI — EU-based LLMs and EuroHPC infrastructure, open licences, GDPR-compliant design and alignment with the EU AI Act — contributing to a digitally competent and sovereign European higher-education sector.
Objectives
RAG4Edu strengthens the capacity of European higher-education institutions to design, implement and evaluate RAG for teaching and learning in a pedagogically grounded, responsible and sustainable way.
European AIPromote European AI technologies — EU-based LLMs such as EuroLLM, Mistral and Aleph Alpha, and EuroHPC infrastructure — with transparency, explainability, accountability and data sovereignty, in compliance with the AI Act.
PedagogyAnalyse the AI-in-education landscape, synthesise the state of RAG, and design the RAG4Edu Curriculum with competence levels, learning outcomes, instructional principles and micro-credentials.
ToolsBuild the RAG4Edu pipeline and framework, learner-aware augmentation, AI-supported group formation, and an authoring toolbox for multilingual educational chatbots on European LLMs.
TrainingDesign, pilot, evaluate and refine the RAG4Edu Training Programme in coordinated pilots across partner countries, generating evidence on effectiveness, usability and institutional feasibility.
CommunityRun the communication platform and a European Community of Practice, publish everything open access, and secure adoption through a sustainability and exploitation strategy, multiplier events and a final European workshop.
Project impact
These are the targets the partnership works towards and reports on. Evidence comes from the pilots, participant feedback and the use of the platform and results.
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