🔬 ScienceGrade 6Lesson 34
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Prototype and Test Improvements

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What you will learn

  • 1Explain why a low-fidelity prototype is built before a final build
  • 2Plan a fair test that changes only one variable at a time
  • 3Explain how a baseline and a data table show whether a change helped
  • 4Iterate on the design by keeping what worked and fixing what failed
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Mini Lesson

A prototype is a rough first version of a design — built quickly, tested honestly, and improved on purpose. Real engineers never trust a first draft. They build, test, learn, and rebuild. In this lesson you will plan a prototype, test it fairly, record what happens, and iterate. The goal is not a perfect first try; the goal is to fail forward — to learn something useful from every attempt.

Low fidelity vs high fidelity

  • Low fidelity: cheap, fast, made of paper, tape, cardboard, or sticks. The job is to test the BIG idea, not the looks. Build it in minutes, not hours.
  • High fidelity: closer to the real product. Better materials, more careful build, longer to make. Only worth doing AFTER the low-fidelity test proves the idea is worth it.
  • Fidelity = how close the prototype is to the real thing. Start low, raise fidelity only as questions get more specific.

Why we test

A design that has not been tested is just a guess. Testing turns a guess into evidence. We test to find out: does it work, how well does it work, and what breaks first? A failed prototype is not a wasted prototype — every failure points to the next improvement. That is what fail forward means: keep moving, but learn from each fall.

Setting up a fair test

  1. Pick one variable to change (the independent variable). Example: ramp height.
  2. Pick one variable to measure (the dependent variable). Example: distance the car rolls.
  3. Keep everything else the same (controls). Same car, same floor, same release method.
  4. Run each test more than once and average the results — one trial can lie.

Baseline first

Before you change anything, record a baseline — how the prototype performs in its starting form. Without a baseline, you cannot tell whether your change was an improvement, no change, or a step backward. The baseline is your "before" picture.

Recording observations

  • Use a simple data table: trial number, what you changed, what you measured, what you noticed.
  • Write what actually happened, not what you wanted to happen. Honest data is the only data worth having.
  • Photos and quick sketches count as observations — capture before, during, and after.

The iteration cycle

  1. Build a low-fidelity prototype.
  2. Test it and record the baseline.
  3. Identify one thing that worked and one thing that failed.
  4. Change ONE thing to fix the failure — keep what worked.
  5. Test again. Compare to the baseline. Repeat.

Words to know

prototype

A rough first version of a design, built to be tested and improved.

test

A planned trial that produces measurable evidence about how a design performs.

iterate

To improve a design through repeated cycles of build, test, and adjust.

fail forward

To treat each failure as useful information that guides the next improvement.

fidelity

How close a prototype is to the final product; low fidelity is rough, high fidelity is polished.

baseline

The starting performance of a prototype, recorded before any changes are made.

The Iteration CycleFour nodes around a central REPEAT label - Build, Test, Learn, Improve - connected by clockwise arrows on a dashed ring.The Iteration CycleBuild, test, learn, improve - then repeat.BUILDlow fidelityTESTfair testLEARNfail forwardIMPROVEiterateREPEATEach loop changes ONE thing. Keep what worked, fix what failed.
Build, test, learn, improve, repeat.
Baseline vs IterationBar chart comparing a baseline paper airplane flight of 80 cm to an improved iteration of 110 cm, a 30 cm gain.Baseline vs IterationPaper airplane flight distance (cm).050100cm80 cmBaseline110 cmIteration+30 cm gainAlways compare a new trial against the recorded baseline.
Baseline measurement vs improved iteration.
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Tip: when you change two things at once and the result improves, you do not know which change helped. One change per round. Slower at first, faster in the end.

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← Lesson 33: Design a Solution to a Local ProblemLesson 35: Analyze Failures and Iterate →