This book presents a human-first vision of education where pedagogy leads and AI serves. It shows how educational technology can amplify progressive ideas without replacing the relationships, judgment and creativity that make learning meaningful.

The Learnlab Methodology

Learning is dynamic and iterative. Building on the Learnlab model (Activate, Explore, Deepen, Concretize and Reflect), students cycle through inquiry and revision in a hermeneutic spiral. Phases overlap in real classrooms, with Deepen, Concretize and Reflect often looping as understanding grows. Thoughtful AI integration strengthens each phase and supports ambitious pedagogy amid rising demands on schools.

Two roles for AI

1. Efficiency & offloading: Drafting plans, materials, and assessments; giving immediate, differentiated feedback; compiling insights from class contributions so teachers can spend more time with students.
2. Intelligence augmentation: Scaling best practices, personalizing support (language, level, interests), and informing decisions with data—making learning more inclusive and effective.

Platform in practice

Learnlab tools operationalize the model: plan and assess; activate prior knowledge; guide exploration; deepen with targeted feedback; produce authentic multimodal work; and reflect with AI-assisted summaries and prompts.

AI for assessment

The book proposes continuous competence assessment that moves beyond one-size tests:

1. Tailored content aligned to goals and learner needs.
2. Differentiated feedback on a six-point scale.
3. Progression insight via engagement tracking, model-text comparison and metacognitive prompts.
4. Adapted assessments generated from each student’s own work to evidence genuine understanding.

Benefits include holistic evaluation of higher-order skills, reduced test anxiety, real-time feedback, personalized pathways and proof of competence through reflection.