Language Education in an AI-Driven World: Reflections from the ECML Coordinators’ Meeting

On April 29–30, I had the opportunity to attend the project coordinators’ meeting at the European Centre for Modern Languages (ECML) in Graz,¹ Austria, in my capacity as the coordinator of the Artificial Intelligence in Language Education (AI Lang) project. This post offers a behind-the-scenes look at our work, introduces our team, and shares our evolving vision for teaching and learning languages in the age of AI.

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Setting the Stage: The ECML Project Coordinators’ Meeting

The ECML is currently supporting eight innovative projects addressing a wide range of topics in language education, from Pluriliteracies to Content and Language Integrated Learning.

These regular meetings bring project coordinators together to align procedures, share tools, and ensure the timely, high-quality delivery of outputs. They also provide an invaluable opportunity to identify overlaps and potential synergies across projects, contributing to a more cohesive vision of language education in Europe.

Amid this rich collaborative environment, the AI Lang project has now been running for just over a year, making this a great moment to share what we’ve been working on.

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Meet the AI Lang Team

None of this would be possible without the expertise and dedication of an extraordinary team:

• Elisabeth (Lis) PÖLZLEITNER is a veteran English language educator with more than 30 years of experience. She leads our online presence and designs our digital learning resources.
• Anne-Laure DUBRAC, Associate Professor at Université Paris-Est Créteil, brings deep pedagogical insight and is responsible for translating our materials into French to ensure multilingual access.
• Aleksandra LJALIKOVA, from Tallinn University, joined the team recently and contributes valuable expertise in educational technology and digital dissemination.

Working with us are four associate members:

• Jérémie Séror (University of Ottawa),
• Stephen Scott Brewer (Université Paris-Est Créteil),
• Merilyn Meristo (Tallinn University), and
• Konstandina Alevizou, who has the unenviable task of supporting me.

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What Is AI Lang All About?

Despite the title, Artificial Intelligence in Language Education isn’t just about exploring new AI tools or figuring out how to use them in the classroom. Our vision is broader: we aim to rethink what language education looks like in a world increasingly shaped by AI.

The goals of the project are the following:

• Understand how teachers and learners are already engaging with AI in language education.
• Develop a framework of guidelines to support the responsible and effective use of AI.
• Create professional learning resources (primarily a Moodle course) to support teacher development.

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Developing Guidelines for Using AI in Language Education

A key deliverable of our project is a structured set of guidelines for using AI in language teaching and learning. While there is no shortage of policy documents on AI ethics, such as the UNESCO Recommendation on the Ethics of Artificial Intelligence or the EU Guidelines on AI and Data in Education, our framework is unique in its focus on the specific needs of language educators.

To make the guidelines practical and easy to apply, we’ve structured them hierarchically:

1. Core principles, or foundational values for AI in language education.
2. Operational guidelines, or specific, actionable recommendations.
3. Competences and associated descriptors, or illustrative examples of what responsible practice might look like in different contexts.

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Our Six Core Principles

At the heart of our framework are six guiding principles,² which outline how the use of AI in language education should be. These are the following:

1. AI use in language education should be safe

AI use must comply with relevant legislation, especially regarding data protection (e.g. GDPR). Teachers and learners should understand both what data they provide intentionally and what is collected in the background.

2. AI use in language education should be ethical

AI should support teaching and learning in ways that respect rights, avoid harm, and promote well-being.

3. AI use in language education should be meaningful

AI tools should add genuine value to language learning. For example, it should enable tasks that would otherwise be impossible or too time-consuming.

4. AI use in language education should be effective

AI use should align with sound pedagogical principles and foster communicative, skills-balanced language development.

5. AI use in language education should be reflective

Teachers should thoughtfully evaluate the impact of AI on their learners and remain central decision-makers in the learning process.

6. AI use in language education should be critical

AI must be used to support equitable, inclusive, and socially just education. This includes resisting de-professionalisation and promoting linguistic diversity.

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Competences and Descriptors: Balancing Fixed and Flexible

The next layer of the framework is currently under development. These competence descriptors will provide more concrete illustrations of how educators can implement each guideline in practice.

One of the intellectual challenges we face is designing something that remains relevant in a rapidly evolving field. To address this, our framework draws inspiration from post-method pedagogy, distinguishing between fixed values and context-sensitive practices. While principles like “AI should be safe” are non-negotiable, how this is achieved will depend on local contexts, available technologies, and evolving risks.

For instance, today’s guidance might stress the importance of teaching learners about the risks of sharing personal data with chatbots. Tomorrow, if data harvesting is curbed through regulation, that guidance may evolve; but the principle of safety will remain.

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Supporting Professional Development: Our Moodle Course

One area where we’ve made significant headway is our online course for teachers. Built on Moodle, it’s designed to support self-directed learning and professional development for educators looking to build their AI literacy.

The course is fully functional and we’re actively improving its content and usability. We warmly invite all teachers and teacher educators to register, explore, and give feedback. We are particularly keen on learning which activities you find most helpful, if there are any important content areas that we may have overlooked, and even if there are technical issues that need our attention. Your input will help shape the final product so that is is relevant to your needs and as user-friendly as possible!

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Save the Date: The AI Lang Workshop

Lastly, we’re excited to announce our upcoming AI Lang workshop, taking place at the ECML in Graz on 25–26 November 2025. This event will bring together educators from across the Council of Europe member-states to share insights, try out our resources, and help shape the future of AI in language education.

More information, including how to apply and details about funding, will be shared soon. Participant selection will be managed by national nominating authorities, so please contact your country’s authority if you’re interested.

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Final Thoughts

As AI reshapes our educational landscape, it’s essential that language education evolves with care, thoughtfulness, and creativity. Through AI Lang, we hope to offer a roadmap that supports teachers in navigating this change confidently and responsibly.

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Notes

1. Incidentally, Graz was my academic home between 2015 and 2018, although I worked at the Karl-Franzens Universität Graz, rather than the ECML. ↩︎
2. I’ll admit, I tried (and failed) to turn these into a clever acronym. The best I came up with was spelling CREMES backwards—Semerc. Suggestions are welcome! ↩︎

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