The effect of presentation position and multichannel approach on learning performance in the use of an augmented reality–head worn display interface for train-driving training

增强现实 接口(物质) 介绍(产科) 计算机科学 人机交互 培训(气象学) 平视显示器 主管(地质) 职位(财务) 多媒体 模拟 人工智能 医学 物理 气泡 财务 地貌学 最大气泡压力法 并行计算 气象学 经济 放射科 地质学
作者
Dongyu Yu,Xing Yao,Kaidi Yu,Dandan Du,Jinyi Zhi,Chunhui Jing
出处
期刊:Interactive Learning Environments [Taylor & Francis]
卷期号:: 1-16 被引量:2
标识
DOI:10.1080/10494820.2022.2124426
摘要

The objective of this study was to determine the differential effects of the presentation position of the augmented reality–head worn display (AR-HWD) interface and the audiovisual-dominant multimodal learning material on learning performance and cognitive load across different learning tasks in training for high-speed train driving. We selected 48 participants to conduct an AR driving training experiment for high-speed trains. The results indicated that whether or not the AR interface was presented next to the learning target did not significantly affect learning performance and cognitive load. In complex learning tasks, such as learning to operate the controller of a high-speed train and to remember the steps of swapping the front and tail of the train, the auditory-led AR learning materials were effective in improving learning performance and reducing cognitive load compared with the visual-led AR learning materials. In the simple task of icon recognition, the visual-led AR learning materials performed better in terms of learning performance and cognitive load. The results of this study can guide the design of AR-HWD interfaces for different learning tasks in training for high-speed train driving, which can improve learning performance and reduce cognitive load during the learning process. HIGHLIGHTSWe studied the position of AR interface presentation and AR multichannel learning for high-speed train-driving training.Whether or not the AR interface was presented next to the target did not have a significant effect on learning performance for that target.Auditory-dominant interfaces outperformed visual-dominant interfaces in complex learning tasks.Visual-dominant interfaces outperformed auditory-dominant interfaces in simple recognition tasks.
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