9791221502893_22.pdf

Technologies to communicate construction project information (engineering designs, schedules) have evolved into a wider range of innovative ecosystems for engineering practices (e.g., cloud-based 3D representations and advanced immersive environments). There is a lack of exploration of effective use...

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Γλώσσα:English
Έκδοση: Firenze University Press 2024
Διαθέσιμο Online:https://books.fupress.com/doi/capitoli/979-12-215-0289-3_22
id oapen-20.500.12657-89110
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spelling oapen-20.500.12657-891102024-04-03T02:23:39Z Chapter Cognitive Dynamics for Construction Management Learning Tasks in Mixed Reality Environments Liu, Xuanchang Mutis, Ivan Electroencephalography (EEG) Dynamics of attention Cognitive load Cognitive processing thema EDItEUR::U Computing and Information Technology Technologies to communicate construction project information (engineering designs, schedules) have evolved into a wider range of innovative ecosystems for engineering practices (e.g., cloud-based 3D representations and advanced immersive environments). There is a lack of exploration of effective user interaction for learning and training in relation to how presented information influences cognition in these ecosystems. The presented research investigates the users’ cognitive and attentional differences using the interactive capabilities of Mixed reality (MX) technology. The enhanced user-situation interactions are analyzed by measuring cognitive dynamics with an emphasis on two processes (attentional focus and cognitive load) in relation to the challenge of the engineering learning task— defined by its complexity (limited time frame for observations of the situations, number of required observations) and nature (episodic). Cognitive dynamics were measured using an electroencephalography (EEG) device that senses electrical activity in response to changing levels of cognitive stimuli via electrodes placed on the scalp. Measuring fluctuations in cognitive processing (related to the intensity of various task demands) allows associating efforts on semantic information processing for learning and training tasks (e.g., walkthroughs for safety checks in job site in MX). The approach enhances opportunities to design technology that best adapts to the user needs for engineering practices with an efficient comprehensive performance assessment 2024-04-02T15:46:50Z 2024-04-02T15:46:50Z 2023 chapter ONIX_20240402_9791221502893_79 2704-5846 9791221502893 https://library.oapen.org/handle/20.500.12657/89110 eng Proceedings e report application/pdf n/a 9791221502893_22.pdf https://books.fupress.com/doi/capitoli/979-12-215-0289-3_22 Firenze University Press 10.36253/979-12-215-0289-3.22 10.36253/979-12-215-0289-3.22 bf65d21a-78e5-4ba2-983a-dbfa90962870 9791221502893 137 11 Florence open access
institution OAPEN
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language English
description Technologies to communicate construction project information (engineering designs, schedules) have evolved into a wider range of innovative ecosystems for engineering practices (e.g., cloud-based 3D representations and advanced immersive environments). There is a lack of exploration of effective user interaction for learning and training in relation to how presented information influences cognition in these ecosystems. The presented research investigates the users’ cognitive and attentional differences using the interactive capabilities of Mixed reality (MX) technology. The enhanced user-situation interactions are analyzed by measuring cognitive dynamics with an emphasis on two processes (attentional focus and cognitive load) in relation to the challenge of the engineering learning task— defined by its complexity (limited time frame for observations of the situations, number of required observations) and nature (episodic). Cognitive dynamics were measured using an electroencephalography (EEG) device that senses electrical activity in response to changing levels of cognitive stimuli via electrodes placed on the scalp. Measuring fluctuations in cognitive processing (related to the intensity of various task demands) allows associating efforts on semantic information processing for learning and training tasks (e.g., walkthroughs for safety checks in job site in MX). The approach enhances opportunities to design technology that best adapts to the user needs for engineering practices with an efficient comprehensive performance assessment
title 9791221502893_22.pdf
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title_full 9791221502893_22.pdf
title_fullStr 9791221502893_22.pdf
title_full_unstemmed 9791221502893_22.pdf
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publisher Firenze University Press
publishDate 2024
url https://books.fupress.com/doi/capitoli/979-12-215-0289-3_22
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