Evolution Simulation Model — Matt Landis

Technology used: NetLogo
Course: BIOL0140 Ecology and Evolution
Learning objective: Allow students to experimentally investigate evolution through a computer simulation
Reason for using the technology: After using EcoBeaker in their labs for several years, Professor Matt Landis and his colleagues wanted to try a different simulation model. Because EcoBeaker is proprietary software, the instructors weren’t able to answer students’ questions about how the model worked. They also weren’t able to fix software bugs.  Using NetLogo allowed Matt to build and modify the model to directly address pedagogical needs.
Description: Matt used NetLogo, a free programmable modeling environment, to build a model of a finch population on Daphne Major, an island in the Galapagos.  Try it yourself here (works best with recent versions of Firefox).  Matt and the other BIOL0140 instructors have used this model for two years in a lab entitled “Computer Simulations and Evolution of Darwin’s Finches.”

The “Computer Simulations and Evolution of Darwin’s Finches” lab lasts for 3 weeks. In the first week, students form groups, familiarize themselves with the model and choose a topic. For example, they might decide to test how well genetically diverse populations withstand environmental variation. The students will develop a hypothesis, load the model on a computer, adjust the weather with a slider bar, and watch for changes in the population over hundreds of years. In the second week, the students meet with their instructors to refine their topics and review their results. In the third week, they present their findings to the rest of the class.

Matt learned NetLogo on his own. He worked from a model that he had created using other software, and he adapted the lab assignments from an EcoBeaker lab. The NetLogo site has a collection of samples that demonstrate other potential applications of the technology, including chemistry (polymer dynamics), political science (voting patterns), and public health (epidemiology).