On 16 February 2026, the European Schoolnet Academy hosted its 6th thematic seminar, bringing together teacher educators, researchers, policymakers and school leaders to explore a question that is becoming increasingly difficult to ignore: How do we recognise teacher learning when the evidence we have relied on for years is changing?

The seminar also marked the launch of the new report, Assessing Teacher Learning in the age of AI, which examines how teacher education systems across Europe are evaluating teacher learning in the context of generative AI becoming embedded in professional practice. The report considers current assessment approaches in both initial teacher education and continuing professional development, the new knowledge, skills, and attitudes that AI demands of teachers, and how assessment methods and tools are adapting in response. Rather than pointing to a single solution, discussions throughout the afternoon reflected a shared sense that this is a moment of transition; one where organisations are revisiting the knowledge, skills, and dispositions they prioritise, and how best to support teacher development.

Re-thinking evidence of teacher learning

For many years, portfolios and assignments have played a central role in documenting professional growth. These remain important, but they no longer tell the whole story. As Professor Mary Richardson (UCL Institute of Education) noted during the seminar, assessment shapes what is seen and valued in learning. When digital tools can support the production of text, attention naturally shifts towards the learning process itself: how teachers make decisions, respond to feedback, and adapt their practice over time.

In response, many teacher education programmes are broadening the kinds of evidence they use. Observation, mentoring conversations, and professional dialogue are increasingly combined with written work to build a fuller picture of teacher learning. Rather than replacing existing approaches, these methods place written assignments within a wider view of professional growth.

The report also highlights how the current moment is pushing organisations to clarify their intentions. What do we want evidence of when we assess teacher learning? What does meaningful professional growth look like in practice? For Professor Jo Tondeur (Vrije Universiteit Brussel), this shift is encouraging teacher educators to return to core questions about learning goals and purpose. Starting with these questions helps keep assessment focused on its purpose rather than on the tools being used and highlights the importance of assessment literacy for those designing and leading professional development.

AI as a catalyst for re-examining assessment

At the same time, AI was discussed not only as a challenge but also as a catalyst for rethinking assessment. Postdoctoral researcher Tim Fütterer (University of Tübingen) referred to emerging research on AI-supported classroom observation and analytics that can provide feedback on teaching patterns, as well as the use of AI in training simulations and professional learning environments. Such tools may offer new ways to support reflection and feedback, but their value depends on trust and clarity around data use. Doctoral researcher Ev Abbott (UCL Institute of Education) emphasised, the focus should not be on detecting AI use in outputs alone, but on designing assessment in ways that make learning visible throughout the process. This perspective resonated with many participants, particularly those working directly with teachers who are already experimenting with digital tools in their day-to-day practice.

The keynote and thematic report also outlined key recommendations for policymakers, teacher educators, and school leaders on adopting assessment methods that effectively meet the needs of an AI-enhanced educational environment. These included strengthening both assessment literacy and AI literacy, ensuring that human judgement remains central in AI-supported assessment processes, and addressing ethical and equity considerations such as data protection, access to infrastructure and transparency around data use. Speakers also emphasised the importance of approaching AI and assessment as a long-term shift rather than a quick fix, and of creating supportive environments where teachers can experiment with new tools while maintaining meaningful professional dialogue.

The report brings together perspectives and examples from across Europe and offers practical insights and examples from different systems, inviting readers to continue this reflection in their own contexts.

Read the full report and revisit the seminar recording.

If these questions connect with your work, we also welcome your feedback to help shape future European Schoolnet Academy thematic seminars.