In this game you are a predator figuring out which butterflies are non-poisonous. The butterflies morph over generations, so watch out! An interactive and engaging way to learn about Batesian mimicry.
Upcoming Release Dates
Desktop and Tablet: Spring 2018
Virtual Reality (Oculus Rift): Summer 2018
Interested in Beta releases? Contact us for more information.
Upon completion of this game, players will understand:
- The organism best suited to the environment survives the longest
- Environments change over time
- Organisms change over time
- Species’ survival occurs across several generations (e.g., Mimicry’s advantages emerge over time)
Teacher guide will be available near game release date – Coming soon!
Participants will be grade-school children at IMAX theaters within science museums. They begin with the 15-minute pretest composed of traditional MC (multiple choice) questions, and they play the game/test portion in the role of the predator. The MC questions will include a mixture of explicit questions that tap information presented directly in the movie and implicit questions that require inferences that go beyond information presented in the movie. Thus, both explicit examples from the movie and several mimicry examples NOT related to Batesian mimicry or specimens found in the Amazon are included. In addition, analyzing statistics about in-game processes and play decisions will offer more well-rounded profiles of the students’ prior science knowledge. After watching the movie, the children will take a post test consisting of the same MC questions and game play. Changes in the students’ mental models will be assessed from changes in MC performance and analyzing in-process game play choices.
The goal in the test version is to:
a) Assess what players know about natural selection BEFORE the intervention.
b) Assess what players know about natural selection AFTER the intervention.
This is a between subjects five-way design with over 250 4th through 6th graders.
System requirements to be posted near game release date.
This material is based upon work supported by the National Science Foundation under Grant No1020367. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.