Synthèse
AI tools are arriving in schools faster than research can evaluate them. Teachers are experimenting with new tools and districts are writing policies, all while students are already using AI both inside and outside the classroom. But for many education leaders, a basic question remains: What does rigorous research actually say about how AI affects teaching and learning? To help answer that question, we released a new report: The Evidence Base on AI in K-12: A 2026 Review. The report reviews the current research, focusing specifically on studies that convincingly estimate causal impact, meaning studies that can tell us whether an AI tool changed outcomes for students or educators.
AI tools are arriving in schools faster than research can evaluate them. Teachers are experimenting with new tools and districts are writing policies, all while students are already using AI both inside and outside the classroom. But for many education leaders, a basic question remains: What does rigorous research actually say about how AI affects teaching and learning? To help answer that question, we released a new report: The Evidence Base on AI in K-12: A 2026 Review. The report reviews the current research, focusing specifically on studies that convincingly estimate causal impact, meaning studies that can tell us whether an AI tool changed outcomes for students or educators.
Source originale
scale.stanford.edu
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