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"AAB AI Education Case Registry Dataset v1.0"

Winnie Han, Lei Xu

Year
2026
Citations
2

Abstract

"This dataset provides a structured registry of documented AI education cases collected and organized under the AI Assessment Board (AAB) evidence registry framework. The dataset is designed to support comparative research, standards development, public-interest documentation, and evidence preservation in AI education and AI literacy.Each case record represents a documented AI education implementation, program, classroom activity, community initiative, research-based intervention, afterschool program, teacher professional development activity, workforce training activity, or physical AI \/ robotics-enabled learning experience. Records may include information such as case ID, country or region, implementing organization type, education setting, learner age group, AI education focus, pedagogy, AI tool role, session format, evidence type, safeguards, observed outcomes, limitations, source references, and provisional Evidence Maturity Index (EMI) classification where applicable.The dataset is intended to help researchers, educators, policymakers, and standards developers compare AI education practices across settings and identify recurring implementation patterns, documentation gaps, evidence signals, and emerging areas for further research.This dataset does not contain raw student data, personally identifiable learner information, private assessment records, or confidential institutional data. Inclusion of a case in the dataset does not imply endorsement, certification, ranking, accreditation, or product recommendation by AAB. The purpose of the dataset is to preserve structured public evidence and support transparent, evidence-informed development of AI education and AI literacy standards."

Keywords

DocumentationWorkforceWorkforce developmentConfidentialitySession (web analytics)Raw dataInclusion (mineral)Literacy

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