Bioethics: wearable data privacy
Do now
Debate whether employers should access workers' wearable motion and fatigue data, then post a CER.
- Hand in
- One-paragraph CER taking a position on whether employers should access wearable physiological data from workers.
- 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.
Should a warehouse or factory be allowed to read the muscle-fatigue readings off a worker's fitness wearable to decide when that worker is 'too tired' to keep going?
Debate whether employers should access workers' wearable motion and fatigue data, then post a CER.
- • You can take a position on employer access to wearable data.
- • You can balance a benefit against a privacy harm.
- Name one piece of data your phone or watch already collects about your body without you thinking about it.
- If your job could see that data, write one reason that could help you and one reason that could hurt you.
- 1Read the prompt: should a company see the muscle-fatigue data from an employee's fitness wearable?
- 2List two benefits and two privacy harms of employer access.
- 3Choose a side and write a one-sentence claim with your reasoning.
- 4Debate in your John Carroll bioethics group and note the strongest counterpoint.
- 5Post a CER response balancing worker and data privacy.
What did this day actually feel like?
Bioethics: wearable data privacy
ETHICS DAY Should an employer be allowed to see the data from a wellness wearable they paid for? The wearable is a gift with a sensor in it.
Nobody in the room said yes. What we argued about was where the line is, because health insurance already prices risk and a wearable is just a faster way to learn the same thing. I wrote that the problem is not the data, it is that consent given for wellness gets reused for employment.
AT HOME, THE NIGHT BEFORE MON MAR 1 Muscle fatigue and EMG basics Electromyography. Muscles produce a measurable electrical signal when they fire, and as they fatigue the signal changes in a predictable way.
We had to sketch a prediction of what the EMG trace would look like across repeated trials before measuring anything. Predicting first, then measuring, is a different feeling than measuring and then explaining whatever happened.
Turned in: labeled prediction sketch → 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.
Should an employer be allowed to see the data from a wellness wearable they paid for? The wearable is a gift with a sensor in it.
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
🔑 Today's words · 5
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: Wearables read your body's data outside a clinic, so the rules that would protect that data at a doctor's office often do not apply, leaving privacy and workplace in direct tension.
- 0-5Intro: what wearable motion sensors actually collect
- 5-20Independent reading and -benefit/privacy-harm list
- 20-40John Carroll bioethics debate
- 40-55Draft claim and evidence
- 55-75Write and post CER
- 75-80Class share: most persuasive vs privacy arguments
- • This week you collect real physiological data using sensors. Before we do that, here is the question the technology raises.
- • Wearable devices can tell an employer exactly when your muscles are fatiguing. Should they be allowed to look?
- • Build your CER around one specific position: either employers should have access with conditions you name, or they should not.
- • The EMG vocabulary in the reading today will show up again Tuesday when we learn what the signal actually measures.
- • Wearable sensors can collect EMG (electromyography), heart rate, and range-of-motion data in real time outside a clinical setting.
- • Personal health information is protected by HIPAA in clinical contexts, but workplace wearables occupy a legal gray zone.
- • The bioethical tension is between using data to prevent injury (employer benefit) and the right not to share your body's data with an employer (worker autonomy).
Unit 1.2 Motion Data: Muscle strength, fatigue, physiology sensors, range of motion, joint testing, kinesiology taping. · Bioethics: wearable data privacy
Day 1 of this lesson. Open this exact section in myPLTW (find it in Clever, Microsoft sign-in), then do the work below.
Do this: Open Lesson 1.2 Muscles and Motion in myPLTW and complete the introductory motion-and-fatigue task; use a fact from it in your wearable-data-privacy CER.
Mark the introductory task complete after posting your CER.
You finished muscle- content last week; this week focuses on motion data within Lesson 1.2, and the task should be checked off today.
myPLTW completion status plus CER screenshot.
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 1.2 Motion Data: Muscle strength, fatigue, physiology sensors, range of motion, joint testing, kinesiology taping. · Bioethics: wearable data privacy
Open Lesson 1.2 Muscles and Motion in myPLTW and complete the introductory motion-and-fatigue task; use a fact from it in your wearable-data-privacy CER.
You finished muscle- content last week; this week focuses on motion data within Lesson 1.2, and the task should be checked off today.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Debate whether employers should access workers' wearable motion and fatigue data, then post a CER.
- Read the prompt: should a company see the muscle-fatigue data from an employee's fitness wearable?
- List two benefits and two privacy harms of employer access.
- Choose a side and write a one-sentence claim with your reasoning.
- Debate in your John Carroll bioethics group and note the strongest counterpoint.
- Post a CER response balancing worker and data privacy.
CER: One-paragraph CER taking a position on whether employers should access wearable physiological data from workers.
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 |
|---|---|
| Read the prompt: should a company see the muscle-fatigue data from an employee's fitness wearable? | _______ |
| List two benefits and two privacy harms of employer access. | _______ |
| Choose a side and write a one-sentence claim with your reasoning. | _______ |
| Debate in your John Carroll bioethics group and note the strongest counterpoint. | _______ |
| Post a CER response balancing worker and data privacy. | _______ |
Working solo? Put your own name in "Who" for every row.
- You can take a position on employer access to wearable data.
- You can balance a benefit against a privacy harm.
- 1Do thisDebate whether employers should access workers' wearable motion and fatigue data, then post a CER.
- 2Use this resource
- 3Submit thisCER: One-paragraph CER taking a position on whether employers should access wearable physiological data from workers.
- 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 1.2 Motion Data: Muscle strength, fatigue, physiology sensors, range of motion, joint testing, kinesiology taping. › 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 muscle can only pull, controlled movement needs an agonist that contracts and an antagonist that relaxes, so a strength imbalance between the pair invites overuse injury.
Wearables read your body's data outside a clinic, so the rules that would protect that data at a doctor's office often do not apply, leaving privacy and workplace in direct tension.
A pilot uses a preflight checklist before the aircraft moves.
- Which checks happen before action?
- Which hazard does each check control?
- What happens if a familiar step is skipped?
A routine works when each action controls a named hazard before exposure begins.
A laboratory hazard can change during a procedure, so students must keep monitoring conditions after the checklist.
- • Preflight checks map to PPE and setup.
- • Aircraft hazards map to chemical, biological, heat, or sharps hazards.
- • Go or no-go maps to the pre-lab readiness decision.
Driving question: Should a warehouse or factory be allowed to read the muscle-fatigue readings off a worker's fitness wearable to decide when that worker is 'too tired' to keep going?
What you already know: Because a muscle can only pull, controlled movement needs an agonist that contracts and an antagonist that relaxes, so a strength imbalance between the pair invites overuse injury.
New idea: Wearables read your body's data outside a clinic, so the rules that would protect that data at a doctor's office often do not apply, leaving privacy and workplace in direct tension.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Bioethics: wearable data privacy. 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 Bioethics: wearable data privacy.
- Organize the observation with a stable evidence ID.
- Apply this rule: A routine works when each action controls a named hazard before exposure begins.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Should a warehouse or factory be allowed to read the muscle-fatigue readings off a worker's fitness wearable to decide when that worker is 'too tired' to keep going?
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.
- • fatigue: A state of physical or mental tiredness in which muscles or the body produce less force or focus and need rest to recover.
- • EMG: Electromyography, a test that records the electrical signals muscles produce when they contract, used to study muscle and nerve function.
- • : The full distance and direction a can move, measured in degrees from its fully bent to its fully straightened position.
- • : Bending a so the angle between two body parts decreases, such as curling the forearm toward the shoulder.
- • extension: A movement that increases the angle of a and straightens a body part, such as opening the arm to straighten the elbow.
- • biomechanics: The study of how forces, motion, and structure act on living bodies, applying physics to muscles, bones, and joints.
- • : The scientific study of human movement, including how muscles, bones, and the nervous system work together to produce motion.
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.
Wearable sensors can collect EMG (electromyography), heart rate, and range-of-motion data in real time outside a clinical setting.
Limit: E1 supplies context or an observation; it does not by itself establish the explanation.
Wearables read your body's data outside a clinic, so the rules that would protect that data at a doctor's office often do not apply, leaving privacy and workplace in direct tension.
Limit: E2 is a teaching statement or comparison and must be checked against the task evidence.
You can take a position on employer access to wearable data.
Limit: E3 supports only the result or product criterion named here; it cannot justify a broader clinical or causal claim.
PLTW-HAP-2027-02-25 · Simulated classroom evidence scenario
Your role: anatomy and physiology consultant
Decision: Your team must decide what the evidence from Bioethics: wearable data privacy 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 Bioethics: wearable data privacy. 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 Bioethics: wearable data privacy supports before submitting the claim-evidence-reasoning response named on the lesson page.
Context: Physiological data is deeply personal, so whether it protects you or exposes you depends entirely on who controls it and why they want it.
- • T1: Read the prompt: should a company see the muscle-fatigue data from an employee's fitness wearable?
- • T2: List two benefits and two privacy harms of employer access.
- • T3: Choose a side and write a one-sentence claim with your reasoning.
- • T4: Debate in your John Carroll bioethics group and note the strongest counterpoint.
- • T5: Post a CER response balancing worker and data privacy.
- • E1: Wearable sensors can collect EMG (electromyography), heart rate, and range-of-motion data in real time outside a clinical setting.
- • E2: Wearables read your body's data outside a clinic, so the rules that would protect that data at a doctor's office often do not apply, leaving privacy and workplace in direct tension.
- • E3: You can take a position on employer access to wearable data.
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 Bioethics: wearable data privacy. 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.
Students often think Students assume that if data is collected to keep someone safe, sharing it with an employer must be fine.. The trap: Good intentions do not erase the privacy cost, because the same fatigue reading that prevents an injury can also be used to cut hours, deny a raise, or push someone out, and the worker rarely gets to say no.
Claim: A school should not require students to wear a district-issued fitness tracker in gym class and share their step and heart-rate data unless students and families give clear, informed, and revocable consent.\nEvidence: A fitness tracker records heart rate, step counts, and activity levels continuously, which together can reveal a student's fitness level and even signs of a health condition. Under FERPA, a school must protect student education records, but data streamed from a personal-style wearable falls into an unsettled area where those protections are not clearly applied.\nReasoning: Tracker data could support a real benefit, such as helping a PE teacher set fair activity goals or notice a student who is struggling. Requiring the device without consent, though, creates a real privacy harm and a risk of misuse, such as tying a grade to a body metric or sharing the data beyond the gym. Because the student carries the privacy cost while the school gains the data, consent should stay with the student and family, and any health goals can be supported through voluntary opt-in use.\nCounter-argument I heard and my response: A classmate argued that a required tracker would make grading more objective and keep everyone active. I agree that fairness and activity matter, which is why a fair system can make the tracker optional, grade on effort rather than raw numbers, and use only aggregate class data, protecting both the learning goal and each student's privacy.
This model shows the level of evidence and organization needed to complete: A parallel-model claim-evidence-reasoning post that shows the CER format and depth on a different consent-and-body-data case, so it guides students without answering today's own prompt.
- 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: Post to the class board and screenshot for your evidence packet.
- 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 Bioethics: wearable data privacy. 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 1: Road to Rehabilitation. 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 1 notebook: Road to Rehabilitation 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 Bioethics: wearable data privacy. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Why do workplace wearables sit in a 'legal gray zone' when the same heart-rate data at a doctor's office is strictly protected?
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.
Read the linked overview on personal health records, then post a written CER on whether employers should access wearable fatigue data, citing one fact from the resource.
MedlinePlus: Personal health recordsThen submit your CER. 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:
Khan Academy: Joints and Movement- 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.