By Roland P. Stout, PhD, Univ. of North Carolina at Pembroke
For several semesters I have had my freshman chemistry students monitor our campus water feature on a weekly basis using most of the Water Quality Index measurements. The water feature is an artificial pond, roughly two hectares in area and a meter deep. It has two fountains, an amphitheater, and a picturesque bridge that is good for hanging probes into the water. The pond is lined with black rubber, leading to considerable solar heating.
This past year I added a new wrinkle to the experiment, which yielded a powerful teaching moment. I had two students take dissolved oxygen (DO) measurements using the Vernier Optical DO Probe and record both the mg/L and percent saturation values. As I suspected, the percent saturation was typically near 100% (98–100%), but the mg/L values varied throughout the spring. Near the end of the semester, we placed the entire semester’s readings on the board and discussed patterns we saw. Nearly everyone noticed that the percent saturation was always near 100%, while the mg/L values decreased significantly through the semester. None of the students knew what to make of that. I asked them to compare this pattern with other patterns in the measurements. One student finally noticed that the mg/L values decreased as the water temperature increased. I then had them look up gas solubility in their lecture texts, which confirmed the relationship observed by the students.
I challenged students to determine the mathematical relationship for solubility vs. temperature using the data we collected. After they kicked around several ideas, the students realized that since all but one of the DO readings were essentially 100%, the mg/L values must represent the saturation limit. Using Logger Pro, they plotted mg/L vs. temperature and obtained the expected solubility curve.
Carefully prompting my students along the way, rather than just telling them the relationships, gave the students ownership in the process. As their confidence grew, they began to see and work out explanations for several other correlations present in the data. Needless to say, it was rewarding to sit back and listen to my students figure it out for themselves.