Educational AI Policy

Educational AI policy — the formal and informal rules governing AI use in educational institutions, from national legislation to classroom guidelines. Policy research in the wiki spans institutional governance, curriculum mandates, and teacher preparation requirements.

Policy levels

Institutional policy: Institutional policy analysis compares how universities develop AI policies. Institutional change frameworks provide models for policy development.

Government policy: State teacher AI policy and lifelong learning policy examine regulatory approaches at national and regional levels.

K-12 policy: The Brookings AI students report and Stanford evidence reviews inform K-12 AI policy.

Assessment policy: Assessment reform policies and Authentic Assessment frameworks represent policy-level responses to AI-enabled cheating.

Policy maturity gap

The wiki documents that institutional AI policies lag behind actual AI use. Faculty Development programs, Teacher AI Competency frameworks, and Regulation all require coherent policy foundations.

Connections

Educational AI policy connects to Regulation (legal framework), AI Governance Education (institutional implementation), Faculty Development (policy implementation through training), Equity (policy impacts on access), and Higher Ed / K 12 (context-specific policy).