Learning Evolution through Model-Based Inquiry

This project explores the use of computational, agent-based modeling activities in STEM classrooms (at all levels) as well as science museums. Its two main objectives are:

1. to develop new ways for students to learn core concepts of evolutionary biology, and
2. to explore innovative activity structures for student collaboration.

Our focus is researching how evolution can be thought of and learned as complex systems, by emphasizing the individual mechanics that lead to evolutionary processes like natural selection and genetic drift.

Our project combines the use of agent-based modeling with emerging interactive technologies (including multi-touch tabletop surfaces, networked simulations, and mobile devices).

PIs

• Uri Wilensky (PI)
• Michael Horn (Co-PI)
• Corey Brady (Co-PI)

Graduate Research Assistants

• Arthur Hjorth
• Aditi Wagh
• Elham Behesti
• Amartya Banerjee

Screenshots

An agent-based model showing genetic drift in a population of beetles		Learners take on the role of predators, and try to eat the bugs as fast as possible. Why do certain colors seem to make bugs more likely to survive?

This research is made possible by support from the National Science Foundation under NSF grant DRL-1109834.However, any opinions, findings, conclusions, and/or recommendations are those of the investigators and do not necessarily reflect the views of the Foundation.