Spirometry data CER analysis
Do now
Students will analyze spirometry data and write a CER about respiratory function.
- Hand in
- Written CER analyzing spirometry data: claim about respiratory capacity, two specific measurement evidence entries compared to predicted values, reasoning linking alveolar structure to capacity, and one factor affecting vital capacity.
- 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.
Your measured came in below the value predicted for your height and age. Does that gap point to a real respiratory problem, or to something about how you measured, and what evidence lets you decide?
Students will analyze data and write a CER about respiratory function.
- • CER includes claim, evidence, and reasoning.
- • Data is compared to predicted reference values.
- Why can two people both have a of 3.5 liters, yet one is perfectly healthy and the other should see a doctor?
- Name one thing besides lung disease that could make a person's measured come out lower than predicted.
- 1Compare your lung volumes to predicted ranges.
- 2Make a claim about your respiratory capacity.
- 3Cite two measurements as evidence.
- 4Add reasoning linking alveolar surface area to capacity.
- 5Note one factor that could affect .
What did this day actually feel like?
Spirometry data CER analysis
A claim about respiratory capacity using my own numbers, compared to predicted values for height and age.
Analyzing data that came out of my own lungs is different from analyzing a dataset. I wanted the number to be good, which is exactly the bias the reference range exists to check.
AT HOME, THE NIGHT BEFORE THU APR 29 Submit respiratory evidence Gas exchange diagram, spirometry table, capacity CER, tracker.
Turned in: respiratory packet → recorded in Class Records
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.
A claim about respiratory capacity using my own numbers, compared to predicted values for height and age.
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.
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Tap a word in the lesson for a plain meaning and one example. Recycled into next week's Do-Now.
Do the work · 80-minute blockfirst 5 min = hook▸
💡 Big idea: Because a lung volume only has meaning against its predicted value, comparing measured to predicted lets you build an evidence-based claim about respiratory health instead of guessing from a raw number.
- 0-10Review predicted reference ranges; annotate your with above/below status
- 10-25Identify the most meaningful comparison in your data; decide on a specific claim
- 25-45Write full CER: claim, two measured-value evidence entries, reasoning linking structure to capacity
- 45-58Add one factor that could affect and explain the mechanism
- 58-70: check that reasoning names an alveolar or airway mechanism
- 70-80Revise and submit CER
- • Your data from yesterday is more than just numbers; it tells a physiological story.
- • Today you will analyze that story using the CER format, as a respiratory therapist would.
- • Comparing your values to predicted ranges is how clinicians identify patients who need further testing.
- • A complete CER with mechanistic reasoning is the highest-level thinking skill in this unit.
- • A measured significantly below predicted may suggest restrictive or obstructive lung disease.
- • Factors that reduce include height, age, smoking history, and chronic lung conditions.
- • CER reasoning must connect the measured deviation (or match) to the underlying alveolar or airway mechanism.
Unit 3.1 Gas Exchange: Respiratory anatomy, sheep pluck or virtual alternative, lung volumes, spirometry, expedition clearance. · data CER analysis
Day 4 of this lesson. Open this exact section in myPLTW (find it in Clever, Microsoft sign-in), then do the work below.
Do this: Complete the data-analysis or CER reflection prompt in Lesson 3.1 Cardiopulmonary Connection on myPLTW; finish it before of your CER.
Mark the analysis task complete in myPLTW after submitting your respiratory CER.
Lab task is done; today the analysis task should show complete and your CER should be submitted.
Screenshot or note of completion status for your tracker.
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.
Unit 3.1 Gas Exchange: Respiratory anatomy, sheep pluck or virtual alternative, lung volumes, spirometry, expedition clearance. · Spirometry data CER analysis
Complete the data-analysis or CER reflection prompt in Lesson 3.1 Cardiopulmonary Connection on myPLTW; finish it before of your CER.
Lab task is done; today the analysis task should show complete and your CER should be submitted.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Students will analyze data and write a CER about respiratory function.
- Compare your lung volumes to predicted ranges.
- Make a claim about your respiratory capacity.
- Cite two measurements as evidence.
- Add reasoning linking alveolar surface area to capacity.
- Note one factor that could affect .
CER: Written CER analyzing data: claim about respiratory capacity, two specific measurement evidence entries compared to predicted values, reasoning linking alveolar structure to capacity, and one factor affecting .
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 |
|---|---|
| Compare your lung volumes to predicted ranges. | _______ |
| Make a claim about your respiratory capacity. | _______ |
| Cite two measurements as evidence. | _______ |
| Add reasoning linking alveolar surface area to capacity. | _______ |
| Note one factor that could affect . | _______ |
Working solo? Put your own name in "Who" for every row.
- CER includes claim, evidence, and reasoning.
- Data is compared to predicted reference values.
- 1Do thisStudents will analyze spirometry data and write a CER about respiratory function.
- 2Use this resource
- 3Submit thisCER: Written CER analyzing spirometry data: claim about respiratory capacity, two specific measurement evidence entries compared to predicted values, reasoning linking alveolar structure to capacity, and one factor affecting vital capacity.
- 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. Human Anatomy & Physiology (Human Body Systems) › Unit 3.1 Gas Exchange: Respiratory anatomy, sheep pluck or virtual alternative, lung volumes, spirometry, expedition clearance. › CEROpen 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.
Because a spirometer turns breathing into measured liters, lung structure becomes numerical data, so a clinician can compare your value to your predicted value and catch disease you cannot feel yet.
Because a lung volume only has meaning against its predicted value, comparing measured to predicted lets you build an evidence-based claim about respiratory health instead of guessing from a raw number.
A mechanic studies a tool whose shape allows one job but limits another.
- Which feature makes the tool work?
- What changes if that feature bends or breaks?
- Which observation shows function rather than appearance?
Structure creates possibilities and limits for function.
Living tissues adapt and interact with other systems; a metal tool does not.
- • Tool shape maps to .
- • The job maps to physiological function.
- • Damage maps to a predicted functional change.
Driving question: Your measured came in below the value predicted for your height and age. Does that gap point to a real respiratory problem, or to something about how you measured, and what evidence lets you decide?
What you already know: Because a spirometer turns breathing into measured liters, lung structure becomes numerical data, so a clinician can compare your value to your predicted value and catch disease you cannot feel yet.
New idea: Because a lung volume only has meaning against its predicted value, comparing measured to predicted lets you build an evidence-based claim about respiratory health instead of guessing from a raw number.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Spirometry data CER analysis. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled structure, movement, or system relationship that connects form to function.
- Observe or measure the relevant feature in data CER analysis.
- Organize the observation with a stable evidence ID.
- Apply this rule: Structure creates possibilities and limits for function.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Your measured came in below the value predicted for your height and age. Does that gap point to a real respiratory problem, or to something about how you measured, and what evidence lets you decide?
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 tiny air sac at the end of an airway in the lung where oxygen enters the blood and carbon dioxide leaves it across a thin wall.
- • : The swapping of oxygen and carbon dioxide between air in the lungs and blood in the capillaries, driven by differences in gas concentration.
- • : The amount of air moved in or out of the lungs in one normal breath at rest, about 500 milliliters in an average adult.
- • : The largest amount of air a person can breathe out after taking the deepest possible breath in, measured to assess lung function.
- • : A breathing test that measures how much air a person can move in and out of the lungs and how fast, used to assess lung function.
- • : The percentage of in the blood that is carrying oxygen, normally about 95 to 100 percent in healthy people.
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 measured significantly below predicted may suggest restrictive or obstructive lung disease.
Limit: E1 supplies context or an observation; it does not by itself establish the explanation.
Because a lung volume only has meaning against its predicted value, comparing measured to predicted lets you build an evidence-based claim about respiratory health instead of guessing from a raw number.
Limit: E2 is a teaching statement or comparison and must be checked against the task evidence.
CER includes claim, evidence, and reasoning.
Limit: E3 supports only the result or product criterion named here; it cannot justify a broader clinical or causal claim.
PLTW-HAP-2027-04-28 · Simulated classroom evidence scenario
Your role: anatomy and physiology consultant
Decision: Your team must decide what the evidence from data CER analysis supports before submitting the claim-evidence-reasoning response named on the lesson page.
- • Select the option best supported by E1-E3.
- • Select a reasonable alternative and name the evidence it would require.
- • Delay the claim because the evidence does not distinguish the options.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the claim-evidence-reasoning response.
Claim ceiling: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about data CER analysis. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Reason for review: Your team must decide what the evidence from data CER analysis supports before submitting the claim-evidence-reasoning response named on the lesson page.
Context: A single measurement means nothing until you compare it to what was predicted; the gap between measured and predicted is what turns raw data into a claim about health.
- • T1: Compare your lung volumes to predicted ranges.
- • T2: Make a claim about your respiratory capacity.
- • T3: Cite two measurements as evidence.
- • T4: Add reasoning linking alveolar surface area to capacity.
- • T5: Note one factor that could affect .
- • E1: A measured significantly below predicted may suggest restrictive or obstructive lung disease.
- • E2: Because a lung volume only has meaning against its predicted value, comparing measured to predicted lets you build an evidence-based claim about respiratory health instead of guessing from a raw number.
- • E3: CER includes claim, evidence, and reasoning.
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 data CER analysis. Trace the labeled structure, movement, or system relationship that connects form to function. 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 data CER analysis.
- • 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 treat a below-predicted number as automatic proof of lung disease, jumping straight from a low reading to a diagnosis.. The trap: A low reading can come from a weak forced exhale, poor seal on the tube, or a single bad trial, not only from disease. The trap is skipping the reasoning step; a real CER connects the measured deviation to a plausible mechanism (like reduced alveolar surface) AND rules out measurement error, rather than declaring illness from one low liter count.
Claim: My resting heart rate is within a healthy range, sitting slightly above the middle of the predicted resting band rather than pointing to a heart problem.\n\nEvidence: I measured my resting heart rate twice after sitting quietly for five minutes. The first reading was 78 beats per minute and the second was 74 beats per minute, for an average of 76. A typical predicted resting range for a healthy teenager is about 60 to 100 beats per minute, so both readings fall inside that band.\n\nReasoning: Resting heart rate reflects how efficiently the heart pumps blood while the body is at rest. A strong, well-conditioned heart pushes out more blood with each beat, so it can meet the body's oxygen needs with fewer beats per minute. My average of 76 sits comfortably inside the predicted range, which means my heart is meeting my resting oxygen demand without straining. The 4-beat difference between my two readings is small and is best explained by normal measurement variation, such as still settling down or miscounting by one or two beats, rather than by a real change in heart function. A single count near the high end of the range does not by itself signal disease, because the predicted band is wide on purpose to cover healthy people.\n\nFactor that could affect resting heart rate: Recent caffeine intake would raise resting heart rate for a while, because caffeine is a stimulant that makes the heart beat faster and can push a reading toward the top of the range even when the heart is healthy. Measuring before drinking coffee or energy drinks gives a truer resting value.
This model shows the level of evidence and organization needed to complete: Models the CER format for physiological-data analysis: a claim, two personal measurements compared to a predicted value, structure-and-function reasoning, and one factor affecting the measurement, applied to resting heart rate instead of lung volumes so the spirometry task stays unspoiled.
- Write one defensible claim.
- Choose specific evidence that supports the claim.
- Explain the scientific rule that connects the evidence to the claim.
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 CER on the class site, or hand it to Mr. Mendoza in 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 Spirometry data CER analysis. 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.
Hand-picked readings, videos, and interactives for this lesson, all free and from authoritative open organizations (NIH, CDC, OpenStax, Khan Academy, PhET, HHMI, and more).
A fillable, Cornell-style notebook for Unit 3: Adventure Awaits. Type your notes, cues, and summaries right in the PDF, or print it and write by hand. Each lesson page has a cue column, a notes column, and a summary box, plus dated lab-record pages you can turn in.
HBS Unit 3 notebook: Adventure Awaits Fillable PDFCornell notes + lab recordsOpenVetted readings and references for this unit. Use them to prepare, to catch up if you were absent, or to go deeper on today's target.
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 data CER analysis. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
A student's measured vital capacity is well below predicted. Before concluding lung disease, name two non-disease explanations they must rule out.
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.
Go further and get help▸
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.
Today is individual work you can do from home: complete the same target above, then submit your CER.
Open the drop folderTurn 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:
MedlinePlus: Pulmonary function testsYou'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.