Appendix 2. The following lab activity example follows the CER framework and is designed to guide students through the
plant growth experiment. The lab can be modified for the soil respiration experiment. Example student answers are given in
italics. These examples are not the only possible responses but rather goal responses that have been crafted on the basis of real
middle school student responses. Modifications for the high school level could include asking students to first write a
hypothesis, then a prediction, and discuss the variability in the data (standard deviations).
Scenario: You are a farmer. A salesperson knocks on your door selling a new “miracle” soil additive that she claims will both
increase your crop yield and help the environment. After your discussion with the salesperson, you learn that the substance is
biochar. Biochar is made from organic waste such as wood chips or agricultural byproducts that are burned in the presence of
little or no oxygen.
The salesperson leaves you a small sample of the solid biochar so you can “see for yourself” the huge, amazing gains your
crops will make with biochar. After hearing the saleperson’s pitch, you decide to try this new “miracle substance” in a small plot
before you use it on your entire farm. You decide to conduct an experiment to test the effectiveness of the addition of biochar to
your mung bean crop.
Question to investigate: How does biochar affect plant growth in different soil types?
Prediction: Make a prediction about what will happen to the growth of your mung bean plants once biochar is added to the soil.
If biochar is added to the top soil (topsoil, potting soil, sand), then the mung beans will grow bigger than the mung beans in the
soil without biochar.
Initial explanation for prediction:
I think this will happen because
biochar increases how much water and nutrients is held by the soil, which helps plants grow.
Independent and dependent variables:
Independent variable: time, soil type, and amount of biochar
Dependent variable: plant growth (plant height, plant weight)
Create a line graph that plots the average height of plants over time. The independent variable (x-axis) is the day of growth. The
dependent variable (y-axis) is the plant height (mm). Include error bars that represent one standard deviation from the mean.
[An example of a student graph is given in Figure A2.]
local potting sand
n=5 n=6 n=5
Figure A1. Soil pH data collected by students during classroom plant growth experiments. Points represent
means. Error bars represent one standard deviation from the mean. Numbers above the points indicate sample
size. Here, biochar only meaningfully decreases soil pH in the sand.