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Success Criteria Validation Workflow

This interactive flowchart illustrates the systematic process for validating a MicroSim against its defined success criteria. The workflow ensures thorough testing and provides clear paths for both approval and iterative refinement.

About This MicroSim

The workflow demonstrates a quality assurance process with four types of steps:

  1. Testing Steps (Blue) - Actions for verifying MicroSim behavior against specifications
  2. Decision Points (Yellow) - Evaluation checkpoints that determine the next action
  3. Success Outcomes (Green) - Positive results and final approval states
  4. Iteration Paths (Orange) - Feedback loops that return to the AI for refinement

Interactions:

  • Hover over any node to see a brief description of that step
  • Click a node to lock the description panel for detailed reading
  • Click again or elsewhere to deselect

Fullscreen

Workflow Steps Explained

Step Type Description
1. MicroSim Generated Start AI has produced a working MicroSim from your specification
2. Load Success Criteria Checklist Process Open the specification document to the success criteria section
3. Test Functional Criterion #1 Process Manually verify each functional requirement one at a time
4. Criterion Met? Decision Evaluate if the MicroSim behavior matches the specification exactly
5a. Document Pass Process Check off the criterion and note any observations
5b. Document Failure Details Process Record exactly how behavior differs from specification
6. More Criteria? Decision Check if there are additional criteria remaining to test
7. All Criteria Passed? Decision Review the overall results after testing all criteria
8a. MicroSim Approved End MicroSim is ready for deployment or the next phase
8b. Create Refinement Request Process Document specific issues for AI to address in the next iteration

Key Insights

  • Systematic testing prevents oversights - Testing each criterion individually ensures comprehensive validation
  • Documentation is essential - Recording both passes and failures creates an audit trail and helps with future refinements
  • Iteration is expected - The workflow includes explicit paths back to the generation step, acknowledging that refinement is normal
  • Specific feedback improves results - Documenting exactly how behavior differs from specification helps AI make targeted improvements

Use Cases

This workflow applies to validating:

  • Interactive educational simulations
  • Data visualizations
  • User interface components
  • Algorithm demonstrations
  • Any specification-driven generated content

Lesson Plan

Grade Level: Professional Development / Graduate

Duration: 20 minutes

Bloom's Taxonomy Level: Evaluate

Learning Objectives:

  • Understand the systematic process for validating MicroSims against success criteria
  • Identify decision points in the quality assurance workflow
  • Recognize when to approve vs. iterate on generated content

Activities:

  1. Explore the Workflow (5 min) - Click through each node to understand the validation process
  2. Trace the Happy Path (3 min) - Follow the path from generation through approval
  3. Trace the Iteration Path (3 min) - Follow what happens when criteria fail
  4. Discussion (5 min) - What makes good success criteria? How specific should failure documentation be?
  5. Practice (4 min) - Write 3 success criteria for a simple MicroSim concept

References