Here's an example of what's due today

Kinesiology data analysis

Tue, Mar 2, 2027 · Week 7 · Human Anatomy & Physiology (Human Body Systems)

Today's goal: Analyze your motion data and write a CER about fatigue and range of motion.

Learn first

What a finished product looks like

This is a model of the work you should turn in today. Use it to check your own: match the structure and the level of detail, do not copy it. Your data and wording should be your own.

Worked CER on a parallel case (grip-strength fatigue), modeling the graph plus claim-evidence-reasoning format without answering today's elbow range-of-motion prompt
Completes: 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.

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.

Line graph of joint angle versus trial number: nearly flat for the first three trials, then a steady downward slope from trial four onward marking fatigue onset.

Also due today: Submit graph and CER as a single combined document.

Check yourself

WebXam problem for today's skill

One exam-style question that uses exactly what you practiced today. Try it before you reveal the answer, then read why each choice is right or wrong.

WebXam-style domain: Evaluate Body SystemsSelf-check skill: Identifying a fatigue trend from a graph rather than a single point
On a graph of joint angle versus trial number, what pattern best indicates that muscle fatigue has set in?

Tap an answer to see the full explanation. Nothing is recorded or graded.