Teach lesson
Can Boyle's law predict the pressure?
Use an initial real measurement to predict later pressures, then test those predictions against the same syringe run.
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Learning Outcomes
Use P1V1 = P2V2 to predict pressure at three later volumes.
Compare predictions with measurements using absolute and percentage error.
Evaluate a useful scientific model without demanding perfect agreement.
Student activity preview
Activity Content
Preview only. In a class session, students can fill in responses and submit their work to the teacher.
A model must make a testable prediction
7 min
A scientific model becomes more useful when it does not merely explain what already happened, but makes a prediction we can test. Boyle's law can do exactly that: from an initial pressure and volume, it predicts the pressure after compressing the same gas at approximately constant temperature.
Today you will not build two graphs or complete a long report. Use one initial measurement, make three numerical predictions, and compare them with measurements from the same real run.
Prediction model
P_1V_1=P_2V_2
\qquad
P_2=\frac{P_1V_1}{V_2}
P1 and V1 are the initial pressure and volume. V2 is the new volume, and P2 is the predicted pressure.
The ideal equation uses absolute pressure and the total volume occupied by the gas, with the same amount of gas at approximately constant temperature. The available lab source does not identify the LabQuest display as showing absolute or gauge pressure. In this activity, use the displayed pressure and syringe-scale volume consistently as working measurements. Gas in the tubing or sensor may add volume that is not shown on the syringe scale. This helps explain why the test is approximate rather than an exact match to the ideal equation.
What do you expect when predictions are compared with real measurements?
Measure the starting point and make predictions
16 min
Use the 60 mL syringe, trial 1. Open the lab and stop at the initial 60 mL reading. Save that pressure below and keep the lab tab open. Before continuing the video, calculate predicted pressures at 45, 30, and 20 mL.
Your starting point
Copy the large pressure number beside kPa; it appears red in the current interface. If it uses a decimal comma, use a decimal point in the numeric field.
Lab-screen note: the introduction may mention pressure and temperature. In this Boyle run, syringe volume changes, pressure is measured, and temperature is treated as approximately constant.
Open trial 1 and keep it open
Open the lab and select the 60 mL syringe, trial 1.
At the first pause, read
P1atV1 = 60 mL.Return to this activity without closing the lab tab.
Do not advance yet: complete all three table predictions first.
What initial pressure P1 did you observe at 60 mL?
For each row, calculate the predicted pressure using predicted P = P1 × 60 ÷ new volume. Keep the full calculator result for later comparison, but enter each prediction rounded to 0.1 kPa. Complete all three predictions before returning to the lab; do not edit them after seeing measurements.
Three predictions before measuring
Calculate and record all three predictions before continuing the video.
| New volume mL | Predicted pressure kPa |
|---|---|
Test the predictions with the run
12 min
Return to the lab tab you kept open. Continue the same run and record pressures at 45, 30, and 20 mL. Then complete absolute difference |predicted − observed| and percentage error in every row.
For this classroom test, call a prediction close when its percentage error is at most 5.0%. This relative criterion permits fairer comparison across different pressure levels. It is a transparent working rule, not a universal accuracy specification.
Continue without changing the trial
Use the same trial-1 sequence that began at 60 mL. Read the pressure before decreasing the volume again. If you closed the tab, reopen trial 1 from the previous section, restart at 60 mL, and follow the same sequence; do not switch to trial 2 or 3.
For each row, use your saved P1 to calculate P1 × 60 ÷ new volume again at full calculator precision. Do not change the rounded prediction you recorded above. Compare the full-precision prediction with the observed pressure to calculate absolute difference = |predicted − observed|, then calculate percentage error = absolute difference ÷ observed pressure × 100. Round only the values you report: the absolute difference to 0.1 kPa and the percentage error to 0.1%. Apply the 5.0% rule to the unrounded percentage.
Test the locked predictions
Use the predictions above without changing them. Add each observation, absolute difference, and percentage error.
| New volume mL | Observed pressure kPa | Absolute difference kPa | Percentage error % |
|---|---|---|---|
What is the largest percentage error? Enter its value and state the corresponding volume and absolute difference.
Which volume or volumes have the smallest percentage errors? Cite them, apply the 5.0% criterion, and compare them with the largest-error row you identified.
Judge the model, not one number
10 min
Do not expect all three predictions to agree equally well. In this activity, a prediction meets the criterion when its percentage error is ≤ 5.0%. A larger error does not by itself show that Boyle's law is false or reveal what caused the difference.
Possible explanations include:
- the resolution of a video reading or the sensor's response;
- a temperature change or a leak;
- gas in the tubing and sensor whose volume is not shown on the syringe scale.
With only one run, these explanations are hypotheses, not conclusions. If you propose one, use cautious wording such as “could be due to...”.
Count the rows in your table whose percentage error is ≤ 5.0%. How many are there? Choose the count that matches all three rows.
Write exactly five sentences, one for each item:
1. Equation: write the equation you used to calculate the predictions.
2. Check: choose one row and report its volume, predicted pressure, and observed pressure.
3. Comparison: report the smallest and largest percentage errors and the volume for each.
4. Hypothesis: propose one possible cause of a difference using cautious language such as “could”.
5. Verdict: state how many rows have error ≤ 5.0% and decide whether, in this run, the model was useful in all rows, only some rows, or none.