Validation plan
Open your materials, follow the steps, then turn in your work.
Design a test plan that defines the metrics needed to validate your prototype.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
2. Start the work
State the specific claim your prototype is supposed to satisfy.
Show all 5 required steps
- State the specific claim your prototype is supposed to satisfy.
- Choose two measurable validation metrics with units.
- Describe the test procedure, including what counts as a pass or fail.
- Identify a control or baseline for comparison.
- List one source of error and how you would reduce it.
Lost your place? Lost your place? Check that you have written the exact claim (Step 1). If yes, pick two metrics with units (Step 2), then define your pass/fail procedure and control in Steps 3 and 4.
Check your work before submitting
- Your plan names two measurable metrics with pass/fail thresholds.
- You included a control and one error-reduction step.
Before lab work: read the safety rules
- Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start.
- Human samples and data stay private: label with a code, never a name, and dispose of materials in the correct waste container, then wash your hands.
3. Turn in your work
DueCheck Schoology- Hand in
- Validation plan with prototype claim, two measurable metrics with units and pass/fail thresholds, a control, a test procedure, and one error-reduction step.
How to submit and name your file
Use the submission route shown on today's today's page.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
PDF upload helpYou get two school days for every day you were absent, so this deadline moves with you.
How this lesson connects
Keep using what you learned last class: You weight each criterion by how much it matters so that the winning option is chosen by an auditable score, not by whichever design you liked first. Today: You define a metric with units, a control, and a pass/fail line so that a result can be traced to the prototype rather than to chance or wishful thinking.
Optional: listen or watch a unit review▸
Need help? Warm-up, timing, and directions▸
💡 Big idea: You define a metric with units, a control, and a pass/fail line so that a result can be traced to the prototype rather than to chance or wishful thinking.
- 0-5 minWarm-up: what would count as proof that your prototype does what you claim?
- 5-20 minState your prototype claim and choose two measurable metrics with units
- 20-40 minWrite the test procedure with pass/fail thresholds
- 40-55 minAdd a control or baseline and identify one error source
- 55-70 min: can your partner run your test from your written plan alone?
- 70-80 minExit ticket: name your two metrics and their pass thresholds
- • A prototype that works is still just a prototype until you can prove it works with data.
- • Today you'll write the validation plan that turns your design claim into a testable experiment.
- • We'll focus on two things: what you measure and what counts as good enough.
- • This plan is the document your teacher and future engineers would use to run the test.
- • A validation metric must have units and a numeric threshold to be testable.
- • A control gives you a baseline so you know whether the prototype is the cause of any result.
- • Identifying error sources in advance is a Lab SOP expectation.
PLTW connection and today's work
Open Problem 3 in your myPLTW course shell and navigate to the current activity, then write a validation plan that defines measurable metrics for your prototype.
Today's stopping point: The decision matrix is done; by end of today your validation plan with two measurable metrics, a control, and one error-reduction step should be submitted.
PLTW activity titles identify the course connection. If your account will not open, use the posted materials for today and tell Mr. Mendoza. Do not mark an online activity complete unless you completed it.
Course connection
- Problem 3.1.3 Design Innovations
Use the turn-in directions at the top of this page. Do not create a second submission unless your teacher asks for one.
Show another explanation or a smaller first step
Need help? Choose a starting point
Finish the assigned lab safely before starting extra practice.
Lesson resources: reading, slides, and vocabulary▸
The deck carries the prior idea forward, lets you inspect an analogy, maps the rule to biology, and ends with the same evidence decision and exit ticket used on this page.
Generated from this lesson's canonical data with a red-team citation check.
You weight each criterion by how much it matters so that the winning option is chosen by an auditable score, not by whichever design you liked first.
You define a metric with units, a control, and a pass/fail line so that a result can be traced to the prototype rather than to chance or wishful thinking.
A research team lays out its question, variables, controls, sampling plan, measurement record, and analysis before deciding what the data support.
- Which variable is changed or compared?
- Which conditions and measurements must stay consistent?
- Which conclusion is inside the study's evidence boundary?
Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
A well-organized classroom study can still be limited by , measurement quality, confounding, and the population represented.
- • Question and variable cards map to the study design.
- • Control and measurement cards map to fair, reproducible data collection.
- • The conclusion card maps to a bounded claim supported by the analysis.
Driving question: Your prototype is supposed to do something specific. What exact number, measured against what baseline, would let you honestly say it passed or failed?
What you already know: You weight each criterion by how much it matters so that the winning option is chosen by an auditable score, not by whichever design you liked first.
New idea: You define a metric with units, a control, and a pass/fail line so that a result can be traced to the prototype rather than to chance or wishful thinking.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Validation plan. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled system, test, or design relationship and identify which evidence should trigger revision.
- Observe or measure the relevant feature in validation plan.
- Organize the observation with a stable evidence ID.
- Apply this rule: Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Your prototype is supposed to do something specific. What exact number, measured against what baseline, would let you honestly say it passed or failed?
What the evidence supports: E1-E3 and F1 support the daily take-home when the response meets the stated success criteria.
What it cannot prove: The package does not support claims beyond this lesson's or any real patient diagnosis.
- • : A careful summary and analysis of existing published research on a topic, used to find what is known and where gaps remain.
- • : The process where independent experts evaluate a research study for quality and accuracy before it is published.
- • : A scoring table that rates each option against the same set of criteria so the best choice can be picked with evidence rather than guesswork.
- • validation: Confirming through testing and evidence that a method, device, or result actually does what it claims and gives accurate, repeatable outcomes.
- • metric: A standard measurement used to track or compare something, such as growth rate, concentration, or survival, giving data a clear number.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
A biomedical design advances when test evidence is compared with explicit user needs, criteria, constraints, risks, and failure modes, then used to justify a documented revision.
Limit: A classroom prototype, , presentation, or does not establish clinical , effectiveness, manufacturing quality, or regulatory clearance.
Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
Limit: A well-organized classroom study can still be limited by , measurement quality, confounding, and the population represented.
Your plan names two measurable metrics with pass/fail thresholds.
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
PLTW-BFH-2027-04-05 · Simulated classroom evidence scenario
Your role: biomedical design team member
Decision: Your team must decide what the evidence from validation plan supports before submitting the pre-lab readiness record named on today's page.
- • Wait until two testers score the same trial separately, because no one has checked whether they land on the same number.
- • Define each metric with units, a control, and a pass line set before testing, so the prototype can actually fail.
- • Test whether users feel better with the prototype, since an improvement people notice is proof enough that it works.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the pre-lab readiness record.
Claim ceiling: Today's evidence supports a classroom claim about validation plan. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Reason for review: Your team must decide what the evidence from validation plan supports before submitting the pre-lab readiness record named on today's page.
Context: Validation needs a measurable metric, a control, and a set pass/fail line, because without all three you cannot show the prototype (and not chance) caused the result.
- • T1: State the specific claim your prototype is supposed to satisfy.
- • T2: Choose two measurable validation metrics with units.
- • T3: Describe the test procedure, including what counts as a pass or fail.
- • T4: Identify a control or baseline for comparison.
- • T5: List one source of error and how you would reduce it.
- • E1: A biomedical design advances when test evidence is compared with explicit user needs, criteria, constraints, risks, and failure modes, then used to justify a documented revision.
- • E2: Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
- • E3: Your plan names two measurable metrics with pass/fail thresholds.
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Figure finding: Teaching diagram for Validation plan. Trace the labeled system, test, or design relationship and identify which evidence should trigger revision. This is a teaching model, not patient or experimental data.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Mean = sum of values / number of values. Median = middle ordered value. Range = maximum - minimum.
For 2, 4, 4, and 10: mean = 20 / 4 = 5, median = 4, and range = 10 - 2 = 8.
Mean, median, and range keep the measurement unit. Order the values before finding the median.
Calculate the requested summary for today's supplied values, then write what it reveals and what it hides.
- • The solution must address the stated need in validation plan.
- • The decision must be supported by E1-E3.
- • The final product must make the success criteria visible.
- • Complete the work inside the 80-minute block.
- • Use only supplied or teacher-approved materials and evidence.
- • Do not trade , accessibility, or privacy for speed.
- • and evidence quality: must pass before scoring other criteria.
- • User need and effectiveness: highest scored criterion.
- • Time, cost, and ease of use: compare only after and effectiveness pass.
Test evidence: For each option, record the E1-E3 result that supports or fails each criterion. Do not assign a score without a named observation.
- Version or option tested
- Criterion met or missed
- Evidence ID and result
- Revision made
- Reason for the revision
- Need and user
- Criteria and constraints
- Chosen option and evidence
- Test result
- Revision and reason
Students often think Students often think a metric like 'it works better' or 'patients feel better' is measurable enough to validate a prototype.. The trap: 'Better' is not a metric because it has no units and no threshold, so two people could measure the same test and disagree. The trap is a claim you cannot fail. A real metric has units and a numeric pass line set in advance (for example, 'reduces cited pain from 7 to 4 or lower on a 0-10 scale').
Prototype claim: My reminder device gets users to take medication within 15 minutes of the scheduled time.
Metric 1: On-time dosing rate, in percent. Pass threshold: at least 80 percent of doses taken within 15 minutes of schedule.
Metric 2: Time-to-response, in minutes. Pass threshold: average response under 5 minutes after the alert.
Procedure: Run 10 scheduled reminders per test user over one week. Log whether each dose was taken within the 15-minute window and the response time. A user passes if both thresholds are met.
Control: A baseline week with no reminder device, so I can tell whether the device, not memory alone, caused any improvement.
Error source and reduction: Users might forget to log their own doses (recording error). I reduce this by having the device auto-timestamp each acknowledged alert instead of relying on a paper log.
This model shows the level of evidence and organization needed to complete: Completes the Problem 3 validation-plan step: a testable plan with the prototype claim, two measurable metrics with units and pass/fail thresholds, a control, a procedure, and one error-reduction step.
- Identify the purpose, hazards, and required controls.
- Write the procedure in a usable order.
- Confirm materials, measurements, and waste handling before starting.
Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.
Also due today: Submit the validation plan on Schoology before the end of class.
- CER:
- Claim, Evidence, Reasoning: make a claim, back it with evidence, explain your reasoning.
- SOP:
- Standard Operating Procedure, the exact steps to follow (especially in a lab).
- Tracker:
- Your PLTW progress log where you record completed evidence.
- myPLTW:
- The PLTW course site where you do the online activities. Find it in Clever with your Microsoft sign-in, right next to Schoology.
Tap the speaker to hear a term. Add two of these to your notebook glossary with a definition and an example in your own words.
Pick just 2 or 3 words from today and make them yours: write what each one means in your own words, name the context clue or evidence that helped, then give one example from what you actually did in Validation plan. Try your own words first; the glossary is there if you get stuck. This is voluntary and counts as extra credit, so keep it short.
Saved on this device. Show Mr. Mendoza or add these to your notebook glossary to claim the extra credit.
Classroom documents for this lesson are posted in Schoology. Open Clever, then Schoology, and find each one by the name shown on its card.
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Prototype validation and evidence audit by path:Biomedical-Innovations/Problem-3_Medical-Innovation/3.1_Medical-Innovation; keywords:rubric. Score 134. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Prototype validation and evidence audit by path:Biomedical-Innovations/Problem-3_Medical-Innovation/3.1_Medical-Innovation; keywords:rubric. Score 130. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Open this when the class reaches this activity and use it to complete the required lesson artifact.
Placement rationale
Matched Prototype validation and evidence audit by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology. Score 126. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Sign in to Clever with your district Microsoft account to open Schoology or myPLTW. Follow today's posted steps. If myPLTW will not open, use the posted alternative and tell Mr. Mendoza. Turn in your completed work through the Schoology assignment.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about validation plan. It cannot prove causation, diagnose a real patient, or justify action outside this room.
A student writes this validation metric: 'The prototype should make the patient healthier.' What is wrong with it, and how would you rewrite it so it is actually testable?
Write an answer and pick a confidence to unlock the key.
Fast retrieval with instant answers, not the commit-then-reveal check above. Try each from memory first: write what you remember about the earlier units, then check yourself here.
Missed class or ready for more?▸
Run this before you touch the bench. It is built from the real lab procedure, so the decisions you make here are the ones you will make with the equipment in your hands. This lesson has more than one, and they cover different skills.
I can name the procedure's purpose and the evidence I will record. I can state today's specific hazards and the control for each. If this deck does not name them, I ask Mr. Mendoza before I touch anything. My data table is ready before materials are handled.
Finish the checklist before you handle any material.
- • Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start.
- • Human samples and data stay private: label with a code, never a name, and dispose of materials in the correct waste container, then wash your hands.
- 1Before materials are handled, identify the purpose, variables or comparison, controls, measurement units, and stop-work condition.
- 2State the specific claim your prototype is supposed to satisfy.
- 3Choose two measurable validation metrics with units.
- 4Describe the test procedure, including what counts as a pass or fail.
- 5Identify a control or baseline for comparison.
- 6List one source of error and how you would reduce it.
- 7Record each result in the prepared table before interpreting it. Mark missing, repeated, or invalid results truthfully.
- 8Complete the named cleanup and waste route, remove PPE safely, wash hands when required, and confirm the station is ready for the next group.
| Trial or sample ID | Independent condition | Measured result with units | Observation before interpretation | Quality-control note |
|---|---|---|---|---|
Before the procedure, predict the result and cite the rule behind the prediction.
After the procedure, compare the result with the prediction and name one limitation or source of uncertainty.
What today's skills lead to. These are real health-science careers this course builds toward. Tap one to see, on the US Department of Labor's O*NET site, what the job actually involves, what it pays, and how fast it is growing.
Complete a simulated validation run: enter sample readings into the provided test-plan template and compute whether the prototype passes each metric.
PhET: simulation-based testingUse the submission route shown on today's today's page.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
Khan Academy: scientific method and experiment designYou've passed Unit 2, so the optional extra-credit track is open. Complete reserved-unit work from home, including virtual labs, for extra credit. Each item shows its correct submission route.
Open the extra-credit track- CompleteEvery required part of the artifact is present, nothing left blank.
- AccurateThe science and the data are correct and match the evidence.
- Scientific reasoningYou explain your claim with evidence and reasoning (CER), not just an answer.
- Professional communicationClear, organized, labeled, and written the way a clinician or scientist would.
- SubmittedGo to Schoology to turn this in. Submit one PDF. Put your first and last name in the document header. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
- Error analysis and method · counts doubleName a specific limit of the method and how it moved your result, and compare what you predicted to what happened. "Human error" does not count; say what about the procedure or instrument caused it.
This week
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