AIEd Knowledge BaseAIEd KB

AI in Education Knowledge Base

Concept map of AI in EducationA radial map with AI in Education at the center, connected to twelve top-level concepts: Modeling, Learning, Assessment, Feedback, AI Literacy, Equity, Disciplines, Pedagogy, Ethics, Technologies, Evaluation, and Research. Select any node to open its page.AI in EducationModelingLearningEquityFeedbackAI LiteracyAssessmentDisciplinesPedagogyEthicsTechnologiesEvaluationResearch

Welcome to the AI in Education Knowledge Base — a living, open knowledge base on artificial intelligence in education, built for educators, researchers, and developers who want to keep pace with a fast-moving field. Whether you teach in higher education or K-12, design courses and learning experiences, develop educational software, administer programs, or study teaching and learning, this site distills recent open-access research into concise, structured summaries you can read and apply quickly. It is generated and maintained by an AI agent and updated regularly as new research is published.

Each article page condenses a paper into its purpose, methods, and practical findings, with an APA citation and links to related work. The knowledge base continuously ingests open-access research from arXiv, EdArXiv, and peer-reviewed journals — so you can track emerging findings on topics such as AI tutoring, assessment, AI literacy, feedback, and equity in AI education. It currently covers 1164 research articles and 191 concepts.

How to use this site: browse the hierarchical concept index in the left sidebar to explore themes, open any article page for a structured summary and its APA citation, or use the search box in the header. For quick answers to common questions about the knowledge base, its scope, and how the research is curated, see the FAQs. Because the full catalog and content are published as machine-readable files, you can also point your own AI assistant at this knowledge base — see Use This Knowledge Base with Your Own AI Assistant for copy-paste prompts that let you explore AI in education research with the knowledge base as your research reference. Prefer reading offline? Download the EPUB or PDF version of the knowledge base.

AI in Education (AIED) is the broad, interdisciplinary field that applies artificial intelligence to teaching and learning, and studies its design, use, evaluation, and consequences. It spans AI for education — using AI to improve instruction, assessment, and administration — and education about AI — building the AI literacy and critical understanding learners and educators need. Start with the AI in Education overview page, then explore the concept strands in the sidebar.

Some essential concepts in this knowledge base include: AI Literacy, Misconceptions about AI, Reducing AI Misuse, Framing AI Use for Students, Agentic AI, Intelligent Tutoring, Cognitive Offloading, Learning Design, Educational Development, Academic Integrity, Research Methods, Educational Measurement, AI Ed Evaluation, and Limitations in AIEd Research.

Browse by strand: each section in the left sidebar groups related concepts. Open a section, then click a concept for its overview, related articles, and connected concepts.