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Research Brief

Published datasetIEEE DataportDOI 10.21227/z095-8k08

AI Education Case Registry Dataset

Research brief for the IEEE Dataport AI education case registry dataset

Summary

This brief introduces the case registry dataset as a curated evidence base for real-world AI education practices, including implementation settings, learner audiences, evidence fields, and source trace.

Key evidence signals

  • Case records help researchers study implementation patterns across K-12, higher education, community, workforce, and informal learning contexts.
  • The dataset is strongest for descriptive registry analysis and evidence mapping; impact claims require record-level source review.
  • Case completeness, source quality, and publication status should be considered when selecting records for synthesis.

Dataset source and citation

This AAB brief links to the dataset record hosted on IEEE Dataport. The publication host is named in text rather than represented with IEEE marks or logos.

Open Dataport recordOpen DOI
Suggested citation

AI Assessment Board. (2026). AI Education Case Registry Dataset. IEEE Dataport. https://doi.org/10.21227/z095-8k08

Recommendations

  1. Use case records to identify practice patterns, recurring implementation constraints, and evidence gaps.
  2. Preserve case IDs, source links, setting fields, and evidence notes in downstream analysis.
  3. Do not treat registry inclusion as AAB endorsement of a tool, provider, or instructional approach.