Teaching the techniques to collect and analyze data on wild populations presents many obstacles. Capturing, identifying, and collecting data from wildlife has many safety-related and logistical challenges. Pokémon GO, a relatively new, smartphone-based augmented reality game, provides a new landscape for simulating wildlife ecology research. The world of Pokémon GO is overlaid onto the physical world and is populated with a variety of species, each having biologically relevant characteristics. Each individual Pokémon also has unique morphometric data. These features of the game provide a platform for data collection and analysis that mimics real-world practices, while eliminating many logistical and safety-related constraints. Additionally, little to no training is involved to begin data collection, allowing more time to plan and execute simulated wildlife ecology projects and activities. The availability of this new virtual wildlife community provides a widely accessible, freely obtained resource for data collection that has directly relevant applications for wildlife ecology education.

In this paper, we present an augmented reality learning system that uses the input of a depth camera to interactively teach anatomy to high school students. The objective is to exemplify human anatomy by displaying 3D models over the body of a person in real time, using the Microsoft Kinect depth camera. The users can see how bones, muscles, or organs are distributed in their bodies without the use of targets for tracking.