Explicit engineering instruction
Use paper/cardboard, simulation, or another teacher-approved low-risk prototype.
Preserve raw test data before scoring the design. Multiple trials are stronger than one dramatic result.
Compare measured performance with the prediction and with each criterion, then record one revision.
Vocabulary: prototype; trial; performance metric; residual; iteration.
Worked example
A design predicts 50 units but repeated trials average 46. Residual is −4 and relative error is 8%.
Guided question
Which evidence should trigger a design revision: one outlier, repeated criterion failure, or both? Explain.
Independent work
- Preserve raw trial data.
- Calculate criterion metrics.
- Compare prediction with measurement.
- Revise one design feature and justify the change.
Design Investigation
Use safe materials or simulation only. Preserve raw trial data, model prediction, criterion scores, uncertainty, and revision.
Misconception check
Iteration should respond to evidence, not merely aesthetic preference.
Formative check
What makes a design revision evidence-based?
Reveal response
It targets a measured shortfall or model mismatch tied to criteria.
Mentor evidence conference
Ask Archaemenes to challenge criteria, weights, assumptions, and whether the evidence justifies the revision.
Teacher guidance
Foundation: Use supplied simulation data if needed.
Core: Complete prediction-test-revision loop.
Extended: Analyze repeatability and uncertainty.