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AECT 2022 Convention Page
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This proposal reports a CAVE (Cave Automatic Virtual Environment) VR-based learning system that focuses on providing an immersive, collaborative, and interactive learning experience expected to help students learn abstract topics such as how conveyor belts in the atmosphere are used to explain the transport of air and the formation of different meteorological phenomena. This study contributes empirical evidence and experience in how to design and implement an immersive CAVE VR learning environment for STEM students.
Contributor: Xinhao Xu, University of Missouri
Contributor: Fang Wang, University of Missouri-Columbia
Contributor: Eric Aldrich, University of Missouri System
Contributor: Shangman Li, University of Missouri-Columbia
Contributor: Isaac Schroeder, University of Missouri System
Contributor: Hao He, University of Missouri Columbia
Contributor: Scott Dean Murrell, University of Missouri