ABSTRACT

Remote virtual training for tasks that involve intensive human motor participation is gaining popularity in the emerging education 4.0 era. However, the user experience and the underlying cognitive characteristics while facing the state-of-the-art training platform are less understood. This paper implements a robot-assisted virtual reality training system for welding training. The virtual reality system creates an immersive environment, and the robotic device provides the necessary physical interaction. A total of 28 participants who had no prior welding experience were recruited to learn welding skills. The participants were trained under the conventional training condition, visual guidance condition, and haptic guidance condition. Participants’ pupillary response and subjective feedback were evaluated to investigate the user experience and the cognitive characteristics’ differences while being trained under different conditions. The results showed that participants felt easier when learning with conventional learning method, while pupillary response showed learning with visual and haptic feedback reduced the cognitive load. By showing the complexity of evaluating user experience, this study encourages training designers to evaluate the use of new technology with more dimensions.

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Go to Construction Research Congress 2024
Construction Research Congress 2024
Pages: 99 - 108

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Published online: Mar 18, 2024

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Yang Ye, S.M.ASCE [email protected]
1Informatics, Cobots, and Intelligent Construction (ICIC) Laboratory, Dept. of Civil and Coastal Engineering, Univ. of Florida. Email: [email protected]
Thanakon Uthai, S.M.ASCE [email protected]
2Informatics, Cobots, and Intelligent Construction (ICIC) Laboratory, Dept. of Civil and Coastal Engineering, Univ. of Florida. Email: [email protected]
Pengxiang Xia, S.M.ASCE [email protected]
3Informatics, Cobots, and Intelligent Construction (ICIC) Laboratory, Dept. of Civil and Coastal Engineering, Univ. of Florida. Email: [email protected]
Tianyu Zhou, S.M.ASCE [email protected]
4Informatics, Cobots, and Intelligent Construction (ICIC) Laboratory, Dept. of Civil and Coastal Engineering, Univ. of Florida. Email: [email protected]
Jing Du, Ph.D., M.ASCE [email protected]
5Associate Professor, Informatics, Cobots, and Intelligent Construction (ICIC) Laboratory, Dept. of Civil and Coastal Engineering, Univ. of Florida, Gainesville, FL. Email: [email protected]

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