K-12 AI Education — AI Ed Wiki

K-12 AI education — the use of artificial intelligence in primary and secondary education, spanning AI literacy curricula, AI tutoring, teacher support, and safety considerations unique to younger learners.

Distinctive K-12 considerations

Safety and guardrailing: K-12 AI use demands stronger Pedagogical Safety protections. EduZone, EduGuard, and tutor harm research specifically address child-safe AI interaction.

AI literacy curricula: K-12 AI literacy modules and policy frameworks develop age-appropriate AI understanding. The vibe coding framework empowers teachers to create their own AI tools.

Evidence base: The K-12 AI evidence base aggregates what works at scale, with Transfer Of Learning as the critical open question about whether AI-assisted gains persist.

Tutoring at grade level: K-12 personalized companions and correct answer trap research examine tutoring effectiveness for younger students.

Developmental appropriateness: Child safety research and Special Education considerations address the needs of diverse K-12 populations.

Scale and equity

K-12 AI deployment operates at societal scale — millions of students, compulsory education, and significant equity implications. Equity and K 12 research examines whether AI widens or narrows opportunity gaps.

Connections

K-12 connects to Pedagogical Safety (child protection), AI Literacy (student competency), Teacher Role (K-12 teacher transformation), Equity (access gaps), and Special Education (diverse learner needs).