Device and model testing lab
Safety gate · before any work
- Handle scissors and any cutting tools with blade pointed away from the body.
- Do not modify model materials beyond the SOP: unauthorized changes invalidate the trial data.
- Keep adhesives and solvents (if any) capped when not in use; avoid skin contact.
Do now
Students build and test a device or vessel model, collecting data to evaluate performance.
- Hand in
- Completed data table with at least three trial measurements, labeled independent and dependent variables, an average performance calculation, one measurement error source, and one test-setup limitation.
- Where
- Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
You get two school days for every day you were absent, so this deadline moves with you.
Students build and test a device or vessel model, collecting data to evaluate performance.
Students build and test a device or vessel model, collecting data to evaluate performance.
- • Collect repeated-trial performance data following the SOP.
- • Identify all variables and state one procedural limitation.
- What do you already know about Device and model testing lab?
- What would you need to find out to answer today's question?
- 1Record the SOP for assembling and testing the model.
- 2Identify the independent, dependent, and controlled variables for the test.
- 3Build the CAD-based or physical model to specification.
- 4Run repeated trials and record performance data in a table.
- 5Note measurement error and one limitation of the test setup.
What did this day actually feel like?
Device and model testing lab
LAB We built a model and tested it, identifying independent, dependent, and controlled variables, and running at least three trials.
Three trials is the rule and I finally understand why. One trial is a measurement. Three trials let you see spread, and the spread tells you whether your result is real or noise. That is the same idea as the standard deviation lesson in week two, arriving again fourteen weeks later in a context where I needed it.
Our first build failed on trial one. We had not controlled a variable we did not realize was a variable. Rebuilding cost us twenty minutes and the second version held.
Turned in: data table with three trials → Data Tables folder
Fiction. There is no such student. The lessons, labs and dates are the real planned course; the student, the classmates and the conversations are invented.
The same day, drawn.
Our first build failed on trial one. We had not controlled a variable we did not know was a variable. One trial is a measurement. Three trials are evidence.
Fiction. There is no such student. The lessons, labs and dates are the real planned course; the student, the classmates and the conversations are invented.
🛠 Get unstuck · pick your level
Lab day: Tier 1 is the whole class at the bench. No extension today.
Do the work · 80-minute blockfirst 5 min = hook▸
💡 Big idea: Performance data only means something if you controlled the variables and ran enough trials: one trial is a measurement, three trials are evidence.
- 0-8 minRecord the assembly and testing SOP; verify all materials are present at your station.
- 8-15 minIdentify and record independent, dependent, and controlled variables.
- 15-40 minAssemble the device or vessel model to specification following the SOP.
- 40-62 minRun at least three repeated trials; record performance data in a labeled after each trial.
- 62-72 minCalculate the average performance across trials; note one measurement error source.
- 72-80 minState one test-setup limitation; begin organizing data for Thursday CER.
- • Today you are the test engineer: your job is to produce clean, repeatable data from a physical model.
- • Read the SOP before you touch any material: the SOP order exists for accuracy and reasons.
- • WebXam 072110 strand 5 (Handling/Preparation/Storage/Disposal) is assessed today: procedure discipline matters.
- • Three trials minimum: if trial 3 is very different from trials 1 and 2, you have a problem worth noting.
- • The is what you deliberately change; the is what you measure as a result.
- • Controlled variables are held constant across all trials so that only the causes outcome differences.
- • Measurement error can come from tool precision, assembler technique, or environmental variability: name the source, not just the effect.
Innovation, Inc.: designing and testing a biomedical device · Device and model testing lab
Day 3 of this lesson. Open this exact section in myPLTW (find it in Clever, Microsoft sign-in), then do the work below.
Do this: Open myPLTW and locate the Lesson 4.1 Designing the Future device testing lab activity. Use the platform rubric or data-table template to structure your results.
Submit test-result responses or the in myPLTW before leaving.
Platform data submission completed by end of the lab period.
Handwritten with three-trial data plus platform submission.
The official PLTW activity stays inside myPLTW. If myPLTW will not open, use F1 and E1-E3 on this page to complete today's local evidence decision, then make up the official activity when access returns. Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
Check things off as you work, then submit. This tells Mr. Mendoza how you're doing so he can help the class. It does not replace turning in your producible through the submission route shown below.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
Innovation, Inc.: designing and testing a biomedical device · Device and model testing lab
Open myPLTW and locate the Lesson 4.1 Designing the Future device testing lab activity. Use the platform rubric or data-table template to structure your results.
Platform data submission completed by end of the lab period.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Students build and test a device or vessel model, collecting data to evaluate performance.
- Record the SOP for assembling and testing the model.
- Identify the independent, dependent, and controlled variables for the test.
- Build the CAD-based or physical model to specification.
- Run repeated trials and record performance data in a table.
- Note measurement error and one limitation of the test setup.
Data table: Completed with at least three trial measurements, labeled independent and dependent variables, an average performance calculation, one measurement error source, and one test-setup limitation.
Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not. Use the checklist just below and upload by 11:29 PM for full credit. Absent with an excused absence? You get two school days for every day you were absent, so this deadline moves with you.
| Task | Who |
|---|---|
| Record the SOP for assembling and testing the model. | _______ |
| Identify the independent, dependent, and controlled variables for the test. | _______ |
| Build the CAD-based or physical model to specification. | _______ |
| Run repeated trials and record performance data in a table. | _______ |
| Note measurement error and one limitation of the test setup. | _______ |
Working solo? Put your own name in "Who" for every row.
- Collect repeated-trial performance data following the SOP.
- Identify all variables and state one procedural limitation.
- 1Do thisStudents build and test a device or vessel model, collecting data to evaluate performance.
- 2Use this resource
- 3Submit thisData table: Completed data table with at least three trial measurements, labeled independent and dependent variables, an average performance calculation, one measurement error source, and one test-setup limitation.
- 4Submit it here
- 1Open the drop folder.
- 2Sign in with your district Microsoft account, not a personal one.
- 3Upload the file, named Lastname_Firstname__Assignment Title.
- 4Your own upload panel says Uploaded with a green check: that is your receipt.
Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not. Principles of Biomedical Technology (Principles of Biomedical Science) › Innovation, Inc.: designing and testing a biomedical device › Data tableOpen the drop folder
Learn it · deck, reading, 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.
Speed to market and depth of testing exist in direct tension: more testing protects patients but delays access for those who are suffering now.
Performance data only means something if you controlled the variables and ran enough trials: one trial is a measurement, three trials are evidence.
A smoke alarm detects signs of fire but can also react to burnt toast.
- What does the alarm detect?
- What creates a false alarm?
- What evidence is needed before declaring a fire?
A screening signal changes what to investigate next; it does not automatically prove the cause.
Biomedical tests have measured performance and biological sampling limits that a household alarm does not capture.
- • Alarm signal maps to a test result.
- • Burnt toast maps to a .
- • Inspection maps to confirmation or the next test.
Driving question: Students build and test a device or vessel model, collecting data to evaluate performance.
What you already know: Speed to market and depth of testing exist in direct tension: more testing protects patients but delays access for those who are suffering now.
New idea: Performance data only means something if you controlled the variables and ran enough trials: one trial is a measurement, three trials are evidence.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Device and model testing lab. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled observation or evidence sequence before choosing an explanation.
- Observe or measure the relevant feature in Device and model testing lab.
- Organize the observation with a stable evidence ID.
- Apply this rule: A screening signal changes what to investigate next; it does not automatically prove the cause.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Students build and test a device or vessel model, collecting data to evaluate performance.
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.
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.
The is what you deliberately change; the is what you measure as a result.
Limit: E1 supplies context or an observation; it does not by itself establish the explanation.
Performance data only means something if you controlled the variables and ran enough trials: one trial is a measurement, three trials are evidence.
Limit: E2 is a teaching statement or comparison and must be checked against the task evidence.
Collect repeated-trial performance data following the SOP.
Limit: E3 supports only the result or product criterion named here; it cannot justify a broader clinical or causal claim.
PLTW-PBT-2026-12-10 · Simulated classroom evidence scenario
Your role: biomedical investigator
Decision: Your team must decide what the evidence from Device and model testing lab supports before submitting the labeled and result claim named on the lesson page.
- • Choose the strongest supported explanation.
- • Choose the next evidence to collect.
- • Hold the decision because the evidence is insufficient.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the labeled and result claim.
Claim ceiling: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about Device and model testing lab. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
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 Device and model testing lab.
- • 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
SOP recorded: assemble the model to spec, run the same test three times, record each result, then average.
Variables:
- Independent variable: pore size of the filter (what we deliberately changed between designs).
- Dependent variable: flow rate in mL/min (what we measured).
- Controlled variables: same liquid, same volume, same temperature, same timer, held constant across all trials.
Design goal: flow rate of at least 12 mL/min.
Results: Trial 1 = 11.0, Trial 2 = 11.6, Trial 3 = 11.3 mL/min. Average = (11.0 + 11.6 + 11.3) / 3 = 11.3 mL/min.
Measurement error source: the stopwatch was started by hand, so reaction time could add or subtract a fraction of a second each trial. That is a tool-and-technique error, named at the source, not just 'human error.'
Test-setup limitation: we ran only three trials, so an unusual single result would pull the average noticeably. More trials would make the average more trustworthy.
| Trial | Pore size (independent) | Flow rate mL/min (dependent) |
|---|---|---|
| 1 | Medium | 11.0 |
| 2 | Medium | 11.6 |
| 3 | Medium | 11.3 |
| Average | Medium | 11.3 |
This model shows the level of evidence and organization needed to complete: Completes the testing lab: a data table with at least three trials, labeled variables, an average, one measurement-error source, and one setup limitation.
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
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 your data table on the class site, or hand it to Mr. Mendoza in class before leaving.
- 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.
Hand-picked readings and interactives for this lesson, from authoritative open organizations and PLTW's own public course outline.
Check yourself · commit, then reveal▸
Claim ceiling for this check: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about Device and model testing lab. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Go further and get help▸
I can name the procedure's purpose and the evidence I will record. I can identify each named hazard and the control that reduces it: Handle scissors and any cutting tools with blade pointed away from the body. My data table is ready before materials are handled.
Finish the checklist before you handle any material.
- • Handle scissors and any cutting tools with blade pointed away from the body.
- • Do not modify model materials beyond the SOP: unauthorized changes invalidate the trial data.
- • Keep adhesives and solvents (if any) capped when not in use; avoid skin contact.
- • Clean up all loose model scraps and dispose in the designated waste bin before leaving the station.
- • Wash hands after handling any lab materials.
- 1Before materials are handled, identify the purpose, variables or comparison, controls, measurement units, and stop-work condition.
- 2Record the SOP for assembling and testing the model.
- 3Identify the independent, dependent, and controlled variables for the test.
- 4Build the CAD-based or physical model to specification.
- 5Run repeated trials and record performance data in a table.
- 6Note measurement error and one limitation of the test setup.
- 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.
Hands-on testing lab: assemble the device or vessel model, run repeated trials against the SOP, and record performance data with controlled variables.
PhET: Interactive SimulationsThen submit your Data table. Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
PhET: simulations for engineering and physical testingYou'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.
- SubmittedTurned in the right way, on the class site or handed to Mr. Mendoza in class, and confirmed. Not in Schoology: that is where the report-card grade appears later.
- 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.