AI Standards for K-12
Strategic Overview
Practical, human-centered guardrails for safe, effective, and equitable AI use in schools. These standards provide a comprehensive framework for K-12 institutions to implement AI responsibly while maintaining educational excellence.
Core Standards Framework
Governance & Policy
Establish a board-approved AI policy, define data stewardship, and set transparent decision rights for procurement, use, and review.
Privacy, Safety, & Compliance
Protect student data (FERPA, state regs), ensure model/provider vetting, and implement risk and incident response procedures.
Instructional Quality
Align AI use with pedagogy, accessibility, and MTSS/UDL; require evidence of learning impact and continuous improvement.
Equity & Bias Mitigation
Audit content and outputs for bias, provide human-in-the-loop review, and monitor usage patterns across student groups.
Security & Infrastructure
Harden identity, logging, and API access; isolate workloads; and document data flows between SIS/LMS and AI services.
Professional Learning
Role-based training for executives, instructional leaders, and staff that emphasizes judgment, ethics, and effective practice.
Implementation Strategy
Implementation Notes
Start small with tightly scoped pilots, publish success criteria, and iterate using stakeholder feedback. Pair technical controls with change management.
AI Curriculum Tracks
Executive Functions Track (8 Weeks)
Instructional Track (12 Weeks)
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