The AIEOU Collab Labs

Where global questions turn into collective action.

Built on our shared research agenda, each Lab brings together researchers, educators, policymakers, and industry partners to explore one critical domain of AI in education. These are not discussion groups. They are working spaces designed to develop research, pilot ideas, and generate evidence that can inform real decisions in classrooms, institutions, and policy.

Across the year, Labs move from co-design to experimentation to dissemination, producing outputs such as co-authored papers, pilot studies, datasets, and policy briefings. The aim is not only to understand AI in education, but to shape how it is designed, governed, and experienced in practice.

Each Lab is interdisciplinary, international, and participatory by design. Together, they form a living research infrastructure that connects insight with action, and global perspectives with local realities.

The 10 Collab Labs

Human-centred Education and Human Flourishing

This Lab explores one central question: how do we ensure AI serves human development rather than displacing it? Work focuses on wellbeing, relationships, identity, and the broader purposes of education, examining how AI can support human flourishing in ways that are ethical, relational, and developmentally grounded.

Teaching, Learning, and Pedagogy

This Lab investigates how AI is reshaping classroom practice. It brings together educators and researchers to explore emerging pedagogical models, curriculum design, and the evolving role of the teacher, with a focus on maintaining rigour while adapting to new technological realities.

Cognition, Metacognition, and Learning Sciences

This Lab examines how AI is changing the way we think and learn. It focuses on attention, memory, reasoning, and metacognition, asking when AI supports deeper learning and when it risks undermining productive struggle and intellectual development.

Equity, Inclusion, and Global Justice

This Lab centres questions of access, fairness, and representation. It explores who benefits from AI in education, who is excluded, and how systems can be designed to address structural inequalities across diverse global contexts.

Ethics, Safety, and Integrity

This Lab addresses the moral and societal challenges of AI in education. It focuses on issues such as data privacy, bias, accountability, and academic integrity, working towards frameworks that support safe, transparent, and responsible use.

Agency, Autonomy, and Participation

This Lab explores how AI shapes human agency. It examines whether learners and educators retain control, voice, and decision-making power in AI-mediated environments, and how systems can be designed to support meaningful participation.

Assessment, Feedback, and Academic Integrity

This Lab rethinks how learning is evaluated in an AI-rich world. It explores new forms of assessment, the role of AI-generated feedback, and how institutions can uphold academic integrity while adapting to technological change.

AI Literacy and Professional Capacity

This Lab focuses on building the knowledge and skills needed to engage with AI critically and confidently. It explores what meaningful AI literacy looks like for teachers, students, leaders, and policymakers, and how it can be embedded across systems.

Future of Education, Work, and Institutions

This Lab takes a forward-looking perspective, exploring how AI may reshape education systems, professions, and pathways into work. It considers what should change, what should be preserved, and what futures education should actively work towards.

Governance, Policy, and Systems Design

This Lab addresses the structural conditions shaping AI in education. It focuses on regulation, procurement, data governance, and institutional readiness, aiming to develop evidence-informed approaches that operate across local, national, and global levels.