The Problem:

<aside> πŸ–ŠοΈ Our view of the world is very human-centric, limiting our understanding of the earth to the human experience. Animals, on the other hand, perceive the world in a fundamentally different way. Most often, this kind of knowledge is taught in classroom settings with through textbooks or other forms of more passive learning. So how can we translate this information into an engaging educational tool that could help us see the world as it is seen by animals?

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Our Solution:

<aside> πŸ–ŠοΈ Anivision is a virtual reality platform that lets users explore and compare their experiences to that of animals with extreme adaptations β€” like the tarsier's night-vision eyes or the honey bee's ultraviolet sight. In the VR world, users can toggle between a human and animal view as they explore different habitats, encouraging a self-motivated learning experience. Paired with educational materials to facilitate the activity, Anivision brings classroom concepts into the context of personal experience, forming a fully immersive learning experience.

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The Impact:

<aside> πŸ–ŠοΈ Anivision expands our understanding of the world to include non-human-centric experiences, provides a novel, immersive, and engaging platform for learning, and provokes exploration of the world from different perspectives.

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News

In the Winter of 2020, DALI project Tarsier Vision Virtual Reality Experience was selected to be a part of the lab portion of Dartmouth class Biology 14 (Physiology). The experience was piloted in a real classroom with students who were learning about optics and vision perception.

β€œMany of us learn about how evolution has produced adaptations in visual perception, but it is difficult to communicate why that all matters. By bringing our project to the Leakey Foundation, we have the opportunity to show how design and modern technology can be bridged to science education and how science can be brought to a personal level of understanding and relevance.” – Sam Gochman β€˜18

Moving forward, the team will be working on creating simulations of the ways other animals perceive the world.

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Supported by the National Science Foundation under Award ID 1917002