AI Quality Review Dashboard

Run the AI Quality Review Dashboard Fullscreen

Sample iframe reference

<iframe
   src="https://dmccreary.github.io/infographics/sims/ai-quality-review-dashboard/main.html"
   width="100%" height="650" scrolling="no">
</iframe>

About This MicroSim

This review dashboard teaches the editorial control workflow for AI-generated content. Three sample MicroSims of varying quality are available for practice — each with intentionally planted issues including factual errors, misaligned regions, missing metadata, and pedagogical fit problems.

Learners evaluate each sample against a structured checklist covering Factual Accuracy, Visual Alignment, Metadata Completeness, Responsiveness, and Pedagogical Fit. Failed items automatically generate specific findings with revision recommendations.

Lesson Plan

Learning Objective

Assess the quality of an AI-generated MicroSim by systematically reviewing its content, functionality, and pedagogical alignment using a structured review checklist.

Activities

1. Select the "Cell Biology (5 issues)" sample. Interact with the preview to test hover regions.
2. Work through the checklist categories, marking each item as Pass, Fail, or Not Reviewed.
3. Click Reveal Issues to see all planted problems. Compare with your findings.
4. Switch to "Network Architecture (7 issues)" for a harder challenge.
5. Discuss: What types of errors are hardest for AI to avoid? Why is human review essential?

References

• AI Content Quality Assurance — Principles of quality assurance applied to AI-generated content.