Kinesiology data analysis
Open your materials, follow the steps, then turn in your work.
Analyze your motion data and write a CER about fatigue and range of motion.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
2. Start the work
Graph your force or angle versus trial number.
Show all 5 required steps
- Graph your force or angle versus trial number.
- Describe the trend and identify where fatigue changed performance.
- Complete the PLTW online analysis questions on kinesiology.
- Write a CER claiming how fatigue affected range of motion, using your data as evidence.
- Submit your labeled graph and data-based CER.
Lost your place? Lost your place? You are analyzing your motion data. Graph force or angle versus trial number, describe the trend and where fatigue hit, finish the PLTW kinesiology analysis questions, then write a CER using your own trial values as evidence.
Check your work before submitting
- You can graph and describe a fatigue trend.
- You can write a CER supported by your own data.
3. Turn in your work
DueCheck Schoology- Hand in
- Labeled graph of force or angle versus trial number plus a CER claiming how fatigue affected range of motion, citing specific data values.
How to submit and name your file
Submit graph and CER as a single combined document.
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.
Choose your Schoology section. Open only one assignment.
Check the section number beside Human Anatomy and Physiology in Schoology.
Assignment: Wk7 CER: Kinesiology data analysis
Link will not open? Open Schoology, choose your section, and find the assignment title above.
How this lesson connects
Keep using what you learned last class: A conclusion is only as good as the data under it, so you zero your sensor and run consistent trials in order to tell a real fatigue trend apart from a single noisy reading. Today: Graphing physiological data reveals a trend the raw table hides, so a CER that cites your specific trial values proves fatigue changed range of motion, while a general statement proves nothing.
Unit 1 guide: what to keep and use nextOptional: listen or watch a unit review▸
Need help? Warm-up, timing, and directions▸
💡 Big idea: Graphing physiological data reveals a trend the raw table hides, so a CER that cites your specific trial values proves fatigue changed , while a general statement proves nothing.
- 0-8Intro: graphing conventions and CER structure review
- 8-20Build labeled graph from Wednesday
- 20-40PLTW online analysis questions on
- 40-55Identify trend and fatigue-onset from graph
- 55-75Write data-based CER with specific trial numbers as evidence
- 75-80Submit labeled graph and CER; preview Friday evidence packet
- • Yesterday you collected raw numbers. Today you turn them into a story.
- • First you graph. Force or angle on the Y-axis, trial number on the X-axis. A proper graph has a title, labeled axes with units, and a scale that uses the full space.
- • Then you write a CER. Your claim names what happened to . Your evidence cites specific trial numbers from your table. Your reasoning connects the data to the physiology of fatigue.
- • A vague CER gets no credit. Use your numbers.
- • A line graph of force or angle versus trial number should show a plateau or decline as fatigue sets in; the slope of that decline quantifies fatigue rate.
- • is the study of human movement; (ROM) is the extent of movement at a measured in degrees.
- • A CER using collected data must cite specific trial numbers or values as evidence, not general statements about what usually happens.
PLTW connection and today's work
Complete the kinesiology data-analysis task in Project 1.2.6 Restoring ROM (Lesson 1.2 Muscles and Motion) on myPLTW; finish all analysis prompts before writing your CER.
Today's stopping point: Lab task is done; today the analysis task should show complete and your CER 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
- Project 1.2.6 Restoring ROM
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
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.
A conclusion is only as good as the data under it, so you zero your sensor and run consistent trials in order to tell a real fatigue trend apart from a single noisy reading.
Graphing physiological data reveals a trend the raw table hides, so a CER that cites your specific trial values proves fatigue changed , while a general statement proves nothing.
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 has 12 numbers in it. How does graphing them show you the exact moment fatigue changed your , and how steep that change was?
What you already know: A conclusion is only as good as the data under it, so you zero your sensor and run consistent trials in order to tell a real fatigue trend apart from a single noisy reading.
New idea: Graphing physiological data reveals a trend the raw table hides, so a CER that cites your specific trial values proves fatigue changed , while a general statement proves nothing.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Kinesiology data 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 analysis.
- 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 has 12 numbers in it. How does graphing them show you the exact moment fatigue changed your , and how steep that change was?
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 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.
- • fatigue: A state of physical or mental tiredness in which muscles or the body produce less force or focus and need rest to recover.
- • goniometer: Use the lesson context and glossary entry to explain goniometer in your own words.
- • 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.
Musculoskeletal function depends on the interaction of structure, force, joints, neural activation, and loading history, so one model or measurement captures only part of performance.
Limit: A classroom model or movement measure cannot diagnose an injury or prescribe .
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.
You can graph and describe a fatigue trend.
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
PLTW-HAP-2027-03-02 · Simulated classroom evidence scenario
Your role: anatomy and physiology consultant
Decision: Your team must decide what the evidence from data analysis supports before submitting the claim-evidence-reasoning response named on today's page.
- • Graph my own trial values and cite the specific numbers where my dropped.
- • Write in my CER that fatigue usually lowers performance, because that is what normally happens to muscles.
- • Add a rested control trial first, because my numbers alone cannot separate fatigue from technique changes.
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: Today's evidence supports a classroom claim about data analysis. It cannot prove causation, diagnose a real patient, or justify action outside this room.
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 write a CER that says fatigue 'usually lowers performance' and think that counts as evidence.. The trap: General statements about what normally happens are not evidence, because a data-based CER has to cite YOUR specific trial numbers or values, otherwise you are quoting common sense instead of your experiment.
Parallel scenario (not today's task): A test subject squeezed a hand dynamometer as hard as possible once every five seconds for eight trials while the grip force in kilograms was recorded. The question was whether fatigue changed the force output, when the change began, and how steep it was.\n\nGraph: a line graph with grip force (kilograms) on the y-axis and trial number on the x-axis, showing a flat plateau for the first few trials followed by a clear downward slope.\n\nClaim: Muscle fatigue reduced grip force output over the repeated squeezing trials.\n\nEvidence: The force stayed close to 44 kilograms for trials 1 through 3, then dropped to 40 kilograms at trial 4 and continued falling to 31 kilograms by trial 8, a total decline of about 13 kilograms. The steepest single drop, about 5 kilograms, happened between trial 4 and trial 5.\n\nReasoning: One low reading by itself could just be a bad squeeze or a measurement slip, but the steady downward slope from trial 4 onward shows a real trend rather than random error. As the muscle repeatedly contracted, its stores of ATP and phosphocreatine ran low and metabolic byproducts built up, so the fibers could no longer generate the same peak force. The graph pins the change to trial 4, where the plateau ends and the line begins to fall, and the sharp segment between trials 4 and 5 shows that is where fatigue set in fastest. This is why turning the numbers into a graph, instead of just reading the table, makes the exact moment and steepness of the change visible.
This model shows the level of evidence and organization needed to complete: A labeled graph of a measured variable versus trial number, plus a claim-evidence-reasoning argument that cites specific data values to explain how fatigue changed performance across repeated trials.
- 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 graph and CER as a single combined document.
- 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 Kinesiology data 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 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.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about data analysis. It cannot prove causation, diagnose a real patient, or justify action outside this room.
A classmate's CER says: 'Fatigue lowered my range of motion because muscles get tired during exercise.' What is wrong with the evidence, and how do you fix it?
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.
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.
Go 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.
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.
- 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.
This week
My Progress dashboard