Safety, ethics and evidence boundary
Capstone work must remain low-risk and teacher/parent approved. No human-subject research, personal health/genetic data, biological culturing, animal manipulation, hazardous chemicals, mains electricity, weapons, or procedural gene editing. Public sources must be cited; private or sensitive locations/data must not be exposed.
Explicit science instruction
A capstone quantitative model can be a budget, rate equation, population projection, diversity index, risk matrix, energy/material balance or multi-criteria score. The model should define variables, units, source values and sensitivity to uncertain inputs.
Precision should match evidence quality; avoid false decimals that imply more certainty than the data support.
Worked example with reasoning
A restoration design estimates native-plant survival = planted individuals × survival rate. 200 plants × 0.70 = 140 expected survivors. If survival plausibly ranges .55–.80, expected range is 110–160. Reporting 140.000 is false precision.
Guided question
Why is a range often more useful than one precise-looking capstone forecast?
Independent work
- Define variables and units.
- Build one quantitative comparison among options.
- Calculate a central estimate and plausible range.
- Identify the most sensitive assumption.
Misconception check
A model output is conditional on assumptions; it is not a promise of what will happen.
Formative understanding check
What is sensitivity analysis used for?
Worked response
To see which uncertain inputs most affect the result and whether conclusions remain stable.
Open-book formative practice only; not an official mastery attempt or grade.
Mentor evidence conference
Ask Archaemenes to challenge the evidence, stakeholder assumptions, quantitative model, tradeoffs, and revision criteria.
Open ArchaemenesTeacher guidance
Foundation: use a simple spreadsheet/table model. Core: include uncertainty and units. Extended: perform one-variable and scenario sensitivity analyses.
Preserve learning evidence
Keep data, design choices, corrections, stakeholder reasoning, and uncertainty in the matching Week 35 evidence field.