 Preview - Intro To Learning With Computational Models

## Systematically investigating spread of wildfire

Let's investigate how the density of the tree affect the spread of wildfire.

We will first generate some data using the model and then represent it using another computational tool called CODAP.

Let's follow an experimental design that is described below.

Research Question: How does density of tress in a forest affect spread of wildfire?

Hypothesis: As the density of trees in the forest increases, percentage of forest burned will increase linearly. That means, if density of trees doubles, the percentage of forest burned will also double.

Let's test our hypothesis.

Change the values of density systematically. Record the value of 'percentage forest burned' in the data table. Make sure that you press 'setup' button every time you run an experiment.

Run each experiment twice. Make sure you record values for each experimental trial.

The software will plot average of the two values that you will record.

### Questions

Describe your observations of the graph of 'density' vs 'percentage burned'.

Do you think that evidence that we gathered with our experiment support our hypothesis?

Spread of wildfire is an emergent phenomenon. Below certain density the fire does not spread much, however when the density crosses a 'tipping point' or threshold, the fire engulfs almost all the forest.

Tipping point in this model falls within which of the following ranges?

Between 30 and 40
Between 40 and 50
Between 50 and 60
Between 60 and 70

Can you give an example of another such phenomenon with a tipping point?

### Notes

These notes will appear on every page in this lesson so feel free to put anything here you'd like to keep track of.