Data-ethics debate
Do now
Debate the ethics of collecting and storing human physiological data.
- Hand in
- CER contribution arguing an ethical limit for physiological data collection and storage, plus two questions and a reflection connecting the argument to the Wednesday lab plan.
- 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.
Before your class straps a heart-rate or skin-response sensor to a classmate for Problem 2, where exactly should the line be on what you are allowed to collect, keep, and share?
Debate the ethics of collecting and storing human physiological data.
- • You can argue an ethical position on physiological data.
- • You can relate consent norms to your own study plan.
- Name one piece of physiological data a phone or watch already collects about you without you thinking about it.
- If a classmate wears your sensor for Problem 2, write one thing you think you must tell them before they say yes.
- 1Prepare two questions about consent and physiological data collection.
- 2Draft a CER position on an ethical limit for biometric data use.
- 3Debate with peers and record a counterargument.
- 4Connect the ethics to your own Problem 2 data plan.
- 5Submit two questions, one CER contribution, and a reflection.
What did this day actually feel like?
Data-ethics debate
ETHICS DAY Measuring classmates and then analyzing the results. Consent, and what happens to the data after.
It is easy to treat consent as a form when the subject is sitting next to you. The point is that it is easier to skip precisely then.
AT HOME, THE NIGHT BEFORE THU MAR 4 Experimental vs observational If you control the variable it is experimental. If you only watch, it is observational and you cannot claim cause.
Almost every claim I have ever repeated from the internet is observational reported as causal.
Turned in: pre-lab → 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.
Measuring classmates and then analyzing the results. Consent, and what happens to the data after.
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: Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
- 0-10Frame the debate: what does consent mean in a classroom physiology study?
- 10-25Debate prep: write two questions and draft your CER position on an ethical limit for biometric data use
- 25-55Structured debate: argue positions and record a counterargument
- 55-65Connect to your data plan: how does today's argument constrain how you will collect data Wednesday?
- 65-77Submit two questions, CER contribution, and reflection
- 77-80Pre-lab preview: review Wednesday's sensor protocol and note any questions
- • This week you will collect physiological data. Before you do, you need to think carefully about the ethics of doing so.
- • Biometric data -- heart rate, , skin response -- is personal. Who gets to collect it, and what happens to it afterward?
- • Today you debate an ethical limit and connect your argument to the plan you will execute in the lab on Wednesday.
- • Data ethics is woven into the Molecular and Genetic Technology strand on WebXam 072125.
- • What requires and why it applies to student physiology investigations.
- • How to argue a position on an ethical limit for biometric data collection using CER.
- • How the data-ethics debate connects to your own Problem 2 plan.
Experimental vs observational studies, sample size, graphing, mean, SD, t-test purpose. · Data-ethics debate
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 Problem 2 Exploring Human Physiology in your myPLTW course shell and locate the data-ethics debate or discussion activity to review the CER prompt.
Mark the data-ethics debate activity complete in your tracker after submitting your CER and reflection.
The Problem 2 research design ticket is done; by end of today the biometric-data ethics CER should be submitted and your pre-lab ready for Wednesday.
Two debate questions, one CER contribution on a biometric-data ethical limit, and a reflection connecting the argument to your Wednesday lab plan.
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.
Experimental vs observational studies, sample size, graphing, mean, SD, t-test purpose. · Data-ethics debate
Open Problem 2 Exploring Human Physiology in your myPLTW course shell and locate the data-ethics debate or discussion activity to review the CER prompt.
The Problem 2 research design ticket is done; by end of today the biometric-data ethics CER should be submitted and your pre-lab ready for Wednesday.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Debate the ethics of collecting and storing human physiological data.
- Prepare two questions about consent and physiological data collection.
- Draft a CER position on an ethical limit for biometric data use.
- Debate with peers and record a counterargument.
- Connect the ethics to your own Problem 2 data plan.
- Submit two questions, one CER contribution, and a reflection.
CER: CER contribution arguing an ethical limit for physiological data collection and storage, plus two questions and a reflection connecting the argument to the Wednesday lab plan.
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 |
|---|---|
| Prepare two questions about consent and physiological data collection. | _______ |
| Draft a CER position on an ethical limit for biometric data use. | _______ |
| Debate with peers and record a counterargument. | _______ |
| Connect the ethics to your own Problem 2 data plan. | _______ |
| Submit two questions, one CER contribution, and a reflection. | _______ |
Working solo? Put your own name in "Who" for every row.
- You can argue an ethical position on physiological data.
- You can relate consent norms to your own study plan.
- 1Do thisDebate the ethics of collecting and storing human physiological data.
- 2Use this resource
- 3Submit thisCER: CER contribution arguing an ethical limit for physiological data collection and storage, plus two questions and a reflection connecting the argument to the Wednesday lab plan.
- 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. Biotechnology for Health (Biomedical Innovations) › Experimental vs observational studies, sample size, graphing, mean, SD, t-test purpose. › 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.
Critiquing another study's flaws makes your own design safer, because every flaw you catch in their work becomes a requirement in yours, so you avoid their mistakes on paper instead of in your data.
Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
A bridge prototype is tested against a load limit, cost limit, and user need before revision.
- Which requirement is a criterion?
- Which limit is a constraint?
- What test result should trigger a redesign?
A design improves when evidence is compared with explicit criteria and constraints.
Biomedical designs also require , ethics, and biological validation beyond a physical prototype test.
- • Bridge requirements map to design criteria.
- • Load results map to E1-E3.
- • Revision maps to the next evidence-based iteration.
Driving question: Before your class straps a heart-rate or skin-response sensor to a classmate for Problem 2, where exactly should the line be on what you are allowed to collect, keep, and share?
What you already know: Critiquing another study's flaws makes your own design safer, because every flaw you catch in their work becomes a requirement in yours, so you avoid their mistakes on paper instead of in your data.
New idea: Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Data-ethics debate. 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 Data-ethics debate.
- Organize the observation with a stable evidence ID.
- Apply this rule: A design improves when evidence is compared with explicit criteria and constraints.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Before your class straps a heart-rate or skin-response sensor to a classmate for Problem 2, where exactly should the line be on what you are allowed to collect, keep, and share?
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.
- • : The number of subjects or observations in a study; larger samples give more reliable results and reduce the role of chance.
- • mean: The average of a set of numbers, found by adding all the values together and dividing by how many values there are.
- • : A number that measures how spread out data values are around the mean; a small value means values cluster tightly, a large value means they scatter.
- • t-test: A statistical test that compares the average values of two groups to judge whether their difference is likely real or just due to chance.
- • validity: How well a test or study actually measures what it claims to, so the conclusions truly reflect reality.
- • reliability: The degree to which a measurement, method, or person produces the same dependable result each time under the same conditions.
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.
What requires and why it applies to student physiology investigations.
Limit: E1 supplies context or an observation; it does not by itself establish the explanation.
Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
Limit: E2 is a teaching statement or comparison and must be checked against the task evidence.
You can argue an ethical position on physiological data.
Limit: E3 supports only the result or product criterion named here; it cannot justify a broader clinical or causal claim.
PLTW-BFH-2027-03-03 · Simulated classroom evidence scenario
Your role: biomedical design team member
Decision: Your team must decide what the evidence from Data-ethics debate 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-ethics debate. 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-ethics debate supports before submitting the claim-evidence-reasoning response named on the lesson page.
Context: Data from a human body is never just numbers, so consent, minimizing what you collect, and limiting how long you keep it are protections for a real person, not paperwork.
- • T1: Prepare two questions about consent and physiological data collection.
- • T2: Draft a CER position on an ethical limit for biometric data use.
- • T3: Debate with peers and record a counterargument.
- • T4: Connect the ethics to your own Problem 2 data plan.
- • T5: Submit two questions, one CER contribution, and a reflection.
- • E1: What requires and why it applies to student physiology investigations.
- • E2: Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
- • E3: You can argue an ethical position on physiological 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 Data-ethics debate. 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 Data-ethics debate.
- • 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 assume that if data is anonymous or has no name attached, there is no consent problem and nothing to protect.. The trap: Anonymous data is not automatically safe, because heart-rate patterns, skin response, and timing can often be linked back to one person when combined, so consent is about what the data can reveal, not just whether a name is stapled to it.
Worked CER on a parallel case (model only, different scenario)
This models the CER format for a DIFFERENT study so you can copy the structure, not the answer. Here the team runs a two-week fitness-tracker study that logs each volunteer's daily step count, and the ethical question is about sharing that data with an outside app, not about today's sensor plan.
Claim: A student step-count study should not share raw, name-linked activity data with any outside fitness app, and should share only aggregated, de-identified results (for example, the class average per day).
Evidence: Privacy standards for personal health information, such as informed-consent and purpose-limitation principles, say that data collected for one stated purpose should not be handed to a third party for a different purpose without fresh consent. Many free fitness apps also reserve the right to reuse uploaded data for advertising or resale.
Reasoning: A daily step log tied to a name can reveal patterns about a person's routine, health, and location over time. Sending that raw log to an outside app exposes volunteers to uses they never agreed to and that the study does not need. Sharing only an aggregated class average still lets the team report a result while keeping any single volunteer unidentifiable, so the benefit is kept and the risk is removed.
Link to my data plan: I will store step counts under codes (Volunteer 1, Volunteer 2), keep the code-to-name key on a separate sheet that only I hold, report results as group averages, and upload nothing to any external app.
Two questions:
1. Does a volunteer have the right to withdraw their data after the two weeks are over, and how would I remove it cleanly?
2. If a partner team asks for our raw numbers to combine with theirs, what would make that transfer acceptable?
Reflection: A teammate argued that uploading to a real fitness app would make our charts look more professional. I understand the appeal, but I think the volunteers only agreed to a class study, so reusing their data elsewhere would break that agreement. Aggregating first is what keeps the study honest.
This model shows the level of evidence and organization needed to complete: A parallel-case claim-evidence-reasoning argument that models the CER format and depth on a different physiological-data scenario (a fitness-tracker step-count study), with a link to a data plan, two questions, and a reflection, so students can mirror the structure without seeing today's answer.
- 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: Reply to one classmate and submit your questions, CER, and reflection on the class site, or hand it to Mr. Mendoza in class by end of period.
- 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 Data-ethics debate. 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 Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:physiology, research design. Score 142. 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 Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:physiology, research design. Score 142. 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 Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/00_Problem-Overview; keywords:physiology, research design. Score 138. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
How to get there: open Clever and sign in with your Microsoft (district) account. Both myPLTW and Schoology are in Clever. Do the activity in myPLTW. Turn the work in on this site or hand it to Mr. Mendoza, because that is the step that counts as submitted. Schoology only shows your report-card grade later.
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-ethics debate. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
A group wants to record classmates' heart rates during a stressful quiz and keep the raw files 'in case we need them later.' Name the two ethics rules this most likely breaks and why.
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.
Post a written CER contribution on an ethical limit for collecting and storing human physiological data, then reply to one classmate.
Then 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 Statistics and Probability- 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.