Reflection: Checks for Understanding DESIGN LAB: Nitrogen (1 of 4) - Section 3: EXPLORE: Inputs and outputs

 

The primary error that nearly every student group made in class was to not read the directions for the testing strips.  The two included classroom clips show a clear difference in group approaches. The "trial and error" group opens the bottle of testing trips and tests first and then reads directions. The "directions read" group has an ordered sequence of steps.  Such differences are rich learning opportunities for student groups.  Though some strips go to waste, by facilitating a dialogue between these two groups, important questions about the nature of data collection emerge.  How long should we wait for results? How do we check out colors? What do the numbers means? Why do we follow a standard procedure when using test strips? Can we trust data if everybody uses a different system to collect it?  Are there other sources of possible error that you can see?  For these particular groups, the "trial and error" groups quickly grasped the importance of reading directions and the idea that standard data collection methods results in useful data. This group was also able to point out that the "directions read" group should consider wearing gloves in order to avoid water contamination.  Students often believe that groups that read directions are beyond feedback; however, this is rarely true.  Even groups that use a "trial and error" approach have valuable voices that can improve the process of the "directions read" student groups.

  Checks for Understanding: Common mistakes and quick fixes with testing strips
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DESIGN LAB: Nitrogen (1 of 4)

Unit 5: Food (biosphere and geosphere)
Lesson 15 of 24

Objective: Students will be able to 1) explain the role of recycling in biogeochemical cycles; 2) use test strips to measure levels of ammonia, nitrate, and nitrite in various aquatic environments; and 3) predict how levels of ammonia, nitrate, and nitrite will change over time.

Big Idea: A functional nitrogen cycle is an essential part of healthy agricultural systems. How might we use models to help us understand how the nitrogen cycle becomes disrupted and what might be done to prevent disruption?

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