Messy Data, Real Science: Using Student Explanations for Variability in Weather Data to Support Scientific Thinking

Let us be honest …using real data in science class is hard. Data from the real world are often messy, and when students try to make sense of messy data, they make claims that are unexpected. Because of this, teachers are sometimes tempted to clean up the messiness in a data set so that the science learning goal is clearer to their students. However, the messiness and complexity of authentic data can actually support students’ engagement in science practices and increase their science content knowledge. In this paper, we show how teachers can leverage the messy variability in a data set to motivate a need for scientific ideas and explanations.