Predict, Observe, Explain...with Data!
By: Kristin Hunter-Thomson
THINKING AHEAD LIKE A SCIENTIST
You would be hard pressed to find a science classroom in the country where students are not making predictions (aka hypotheses) before they run experiments/demonstrations.
This is awesome!
In science we often have an idea of what we think we will find and what it will mean based off of previous knowledge about the topic area we are investigating.
But, would you be as successful in seeing students making predictions of what they actually are going to see in their data? Unfortunately, in my experience no.
This is a lost opportunity. Let's explore why through the work put forward by Kim Kastens and Ruth Krumhansl in their "Identifying Curriculum Design Patterns as a Strategy for Focusing Geoscience Education Research: A Proof of Concept Based on Teaching and Learning With Geoscience Data" article.
PREDICTING THE DATA FIRST
Having students stop and take time to think through what their data will look like - based on their understanding of the system, a conceptual model, a physical model, etc. - helps students explicitly make the connections between what they think broadly will come through in their results and actually what they will see in their data.
Additionally, this also helps the students think through more deeply what the relationships may be in the data and how they could observe those relationships via the data. This sets the students up to be successful in making sense of the data because they have a starting point or an idea of what to look for in the data.
Visual hypothesis of what students may think they will see in numbers of predators and prey as they relate to each other.
OBSERVING THE DATA
With that idea in their head of what they may find in the data, the students are off to the races to actually look at the data. Taking the time to really look at all of the data, not just individual data points, is easier when they have an idea of what kind of pattern or relationship they expect to see in the data.
Students can successfully find evidence to be able to answer prompts like:
-
"Explain how the data support or refute your predictions." rather than "Explain what the data show."
-
"Make a claim about what you see in the data with regards to the original question."
When they have an idea of what to look for, they have a starting place to go from to make sense of the data.
Actual data from an experiment looking at the number of black sea bass (a predator) and crabs (a prey).
EXPLAINING WHAT THEY SEE
The explanation piece gets a lot easier once they have made a prediction and observed the data to see if their prediction of the pattern or relationship in the data is present or absent.
You will find that getting your students to write their Reasoning statements in C-E-R will also come more easily if they are comparing the actual data against their prediction.
Another great benefit of this approach is that students begin to learn more clearly how the reality of the world (through the data) is not as clear, simple, or pretty as they would hope (or as the theory would predict). And this is a great seed to plant in our students in terms of the reality of variation in data and what uncertainty means in science.
OK, BUT WHERE CAN I SEE THIS IS ACTION?
Great question! Check out Kastens & Krumhansl's work.
Also, explore some of the data activities we have created that implement the Predict-Observe-Explain approach in the Polar-ICE Data Stories Series released in the 2017-18 academic year:
-
What are those whales doing? - Explore daily whale movements around Antarctica through Dr. Ari Friedlaender's research tracking whales
-
What drives patterns in ocean change? - Explore the high variability and movement of surface currents and what that means for the food web around a deep ocean canyon on the West Antarctic Peninsula through Dr. Josh Kohut's research
