Sibel Kaçar
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2025 · Learning Analytics · Explainable AI · Disaster Education · Interactive Learning · Performance Insights

Afet Akademi: Disaster Education Learning Analytics Platform

Explainable AI & Learning Analytics for Disaster Preparedness Education

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Problem

Traditional disaster education often lacks measurable assessment and adaptive instructional feedback. Static curricula do not account for learner behavior, cognitive states, or contextual transfer in high-stakes scenarios such as natural disaster response.

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Approach

Afet Akademi is an integrated learning analytics ecosystem that uses explainable AI (XAI) to model student performance across 48 defined learning outcomes tailored to K-12 disaster education standards. The platform combines interactive educational games with analytics dashboards, transparent learner insights, and contextual performance tracking to provide educators and learners with evidence-based interpretation of disaster preparedness skills.

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Outcome

Afet Akademi provides a structured environment where learners engage with interactive educational content while underlying analytics track progress, explain performance factors, and support adaptive learning goals. The system bridges immersive activities with measurable outcomes, enhancing understanding of disaster risks and decision-making behaviors.

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Technology Stack

Next.js App Router (SSR)Tailwind CSSTypeScriptMongoDBLearning Analytics EngineExplainable AI (XAI) components

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