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            Chapter Cognitive Dynamics for Construction Management Learning Tasks in Mixed Reality Environments

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            Author(s)
            Liu, Xuanchang
            Mutis, Ivan
            Language
            English
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            Abstract
            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
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/173448
            Keywords
            Electroencephalography (EEG); Dynamics of attention; Cognitive load; Cognitive processing; thema EDItEUR::U Computing and Information Technology
            DOI
            10.36253/979-12-215-0289-3.22
            ISBN
            9791221502893
            Publisher
            Firenze University Press
            Publisher website
            www.fupress.com/
            Publication date and place
            Florence, 2023
            Series
            Proceedings e report,
            Pages
            11
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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