TAICo Cases

Explore our cases here and discover how AI is transforming teaching and learning across Europe.

MAI: A Metacognitive AI Agent

MAI supports teachers by monitoring collaborative learning groups and identifying key “trigger moments”, instances when students need to recognize and regulate their own learning. By doing so, MAI allows teachers to focus on providing deeper, content-specific guidance and helping students develop more advanced learning strategies. It also enhances teachers’ own awareness and skills in fostering self-regulated learning.

Education Level

Secondary School

Subject Area

Science Education

Challenges
Collaborative Regulation
Teacher Relevance

Metacognitive Empowerment

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Collaborative Problem Solving

Teachers will gain tools and strategies to design and orchestrate collaborative problem-solving lessons that foster both individual learning progress and productive collaboration. The case aims to strengthen teachers’ situation-specific skills, their ability to notice, interpret, and respond to students’ learning processes with the support of AI-informed feedback.

Education Level

Secondary school

Subject Area

Mathematics, English as a foreign language

Challenges
Collaborative Blindness
Teacher Relevance

Instructional Awareness

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Collaboration analytics for supporting students and teachers in higher education

A showcase of teacher-AI complementarity where AI as an synergistic partner, augmenting teachers’ perception and action spaces to enhance students’ collaboration and regulation of learning in real-world small-group higher education collaborative context.

Education Level

Higher Education

Subject Area

Educational Technology

Challenges
Collaborative Regulation
Teacher Relevance

Instructional Awareness

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Curriculum Adaptivity

In this case, primary school teachers in the Netherlands plan differentiated mathematics lessons using an AI-supported curriculum adaptivity tool embedded in a widely used commercial Adaptive Learning Technology. Where the underlying system already adapts within learning goals, curriculum adaptivity extends this across learning goals: drawing on student progress data and historical learning patterns, the AI recommends lesson objectives and student groupings across lesson types (instruction, independent practice, review, enrichment), so that pupils progress through the curriculum at different rates. Teachers review the AI's proposals, interrogate the underlying data, and adjust, override, or accept them before finalising the lesson.

Education Level

Primary schools

Subject Area

Mathematics

Challenges
Verifying AI suggestions
Teacher Relevance

Planning curriculum adaptive lessons

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Support Practitioners to Author Learning Activities with AI

Within this case, teachers co-design with researchers a set of AI-powered tools to support them in designing and authoring learning activities. By incorporating teachers' voices and evidence-informed pedagogical best practices from research into these AI-powered tools, the TAICo case aims to foster effective teacher-AI collaboration. Based on the evaluation of the tools' usage, the case's further objective is to support the development of guidelines for the design and implementation of AI-based tools that assist teachers in conceptualizing and authoring high-quality learning activities.

Education Level

Higher Education

Subject Area

Adaptive Grouping

Challenges
AI Literacy
Teacher Relevance

Professional Development

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Promoting teachers ability to provide adaptive support for students basic skill development in math with an ITS

Teachers face increasing workloads due to large class sizes, teacher shortages, and rising student heterogeneity, particularly in early education. Investigating ways to support their professional needs is essential to enhance instructional quality and promote equitable learning outcomes.

Education Level

Primary Schools

Subject Area

Math

Challenges
Implementation Barriers
Teacher Relevance

Professional Growth

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GenAI for feedback design

This case explores the use of Generative Artificial Intelligence (GenAI) to support teachers in the design and delivery of formative feedback. Formative feedback plays a central role in learning, yet it is often challenging to provide in a timely, personalized, and pedagogically meaningful way.

Education Level

Secondary school

Subject Area

Instructional Design, Project-based assignments

Challenges
Complexity
Teacher Relevance

Professional development, Feedback design/awareness

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