阿凡达
人机交互
虚拟现实
计算机科学
沉浸式(数学)
虚拟机
召回
学习效果
学习对象
多媒体
对象(语法)
忠诚
人工智能
心理学
认知心理学
微观经济学
经济
纯数学
操作系统
电信
数学
作者
María Murcia-López,Anthony Steed
标识
DOI:10.3389/fict.2016.00024
摘要
One potential application for virtual environments (VEs) is the training of spatial knowledge. A critical question is what features the VE should have in order to facilitate this training. Previous research has shown that people rely on environmental features, such as sockets and wall decorations, when learning object locations. The aim of this study is to explore the effect of varied environmental feature fidelity of VEs, the use of self-avatars and the level of immersion on object location learning and recall. Following a between-subjects experimental design, participants were asked to learn the location of three identical objects by navigating one of three environments: a physical laboratory, or low and high detail VE replicas of this laboratory. Participants who experienced the VEs could use either a head-mounted display (HMD) or a desktop computer. Half of the participants learning in the HMD and desktop systems were assigned a virtual body. Participants were then asked to place physical versions of the three objects in the physical laboratory in the same configuration. We tracked participant movement, measured object placement, and administered a questionnaire related to aspects of the experience. HMD learning resulted in statistically significant higher performance than desktop learning. Results indicate that, when learning in low detail VEs, there is no difference in performance between participants using HMD and desktop systems. Overall, providing the participant with a virtual body had a negative impact on performance. Preliminary inspection of navigation data indicates that spatial learning strategies are different in systems with varying levels of immersion.
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