Last week in my graduate class I spent part of the class speaking about strategies for data analysis.  I found myself having the same conversation with my student teacher today trying to discuss using inquiry strategies as a method for analysis.  Many lab activities can have large quantities of data for examination.  The challenge, I think, is helping students discover their own inner voice for determining what to do with all of it.

Sure, I can precisely say what I expect them to do, but then I impose my values and attitudes, not to mention removing the critical thinking necessary to determine what is needed.  For example, this week my students are going to conduct an enzyme catalysis lab where they examine different environmental factors which influence enzyme activity over time, specifically: concentration, pH, and temperature.  Each group takes data every thirty seconds for 10 minutes (20 points per condition, ~8 conditions per group, ~ 10 groups = ~ 1600 data points)  Wow,  considering class data, that’s an awful lot of data.  But there is true value in it.  Over the years, students have consistently found the proper enzyme activity trends.

The challenge is determining what to do.  Students could certainly graph every point – but that would probably be a waste of time. Aren’t graphs supposed to show trends and summarize results?  Seeing everything probably would be of little value.  Ultimately, though I want my students to determine what is of value to them so they can draw the conclusions necessary to understand the scientific concepts.  Giving them the autonomy to make their own decisions ultimately gives the power to control their learning.

I think that’s a worthy goal!