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Human performance data collected in a virtual environment
This data article describes the experimental data used in the research article “Incorporating individual differences in human reliability analysis: an extension to the virtual experimental technique” (Musharraf et al., 2017) [1]. The article provides human performance data for 36 individuals collect...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633156/ https://www.ncbi.nlm.nih.gov/pubmed/29021999 http://dx.doi.org/10.1016/j.dib.2017.09.029 |
_version_ | 1783269832923283456 |
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author | Musharraf, Mashrura Smith, Jennifer Khan, Faisal Veitch, Brian MacKinnon, Scott |
author_facet | Musharraf, Mashrura Smith, Jennifer Khan, Faisal Veitch, Brian MacKinnon, Scott |
author_sort | Musharraf, Mashrura |
collection | PubMed |
description | This data article describes the experimental data used in the research article “Incorporating individual differences in human reliability analysis: an extension to the virtual experimental technique” (Musharraf et al., 2017) [1]. The article provides human performance data for 36 individuals collected using a virtual environment. Each participant was assigned to one of two groups for training: 1) G1: high level training and 2) G2: low level training. Participants’ performance was tested in 4 different virtual scenarios with different levels of visibility and complexity. Several performance metrics of the participants were recorded during each scenario. The metrics include: time to muster, time spent running, interaction with fire doors and watertight doors, interaction with hazards, and reporting at different muster locations. |
format | Online Article Text |
id | pubmed-5633156 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-56331562017-10-11 Human performance data collected in a virtual environment Musharraf, Mashrura Smith, Jennifer Khan, Faisal Veitch, Brian MacKinnon, Scott Data Brief Social Sciences This data article describes the experimental data used in the research article “Incorporating individual differences in human reliability analysis: an extension to the virtual experimental technique” (Musharraf et al., 2017) [1]. The article provides human performance data for 36 individuals collected using a virtual environment. Each participant was assigned to one of two groups for training: 1) G1: high level training and 2) G2: low level training. Participants’ performance was tested in 4 different virtual scenarios with different levels of visibility and complexity. Several performance metrics of the participants were recorded during each scenario. The metrics include: time to muster, time spent running, interaction with fire doors and watertight doors, interaction with hazards, and reporting at different muster locations. Elsevier 2017-09-22 /pmc/articles/PMC5633156/ /pubmed/29021999 http://dx.doi.org/10.1016/j.dib.2017.09.029 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Social Sciences Musharraf, Mashrura Smith, Jennifer Khan, Faisal Veitch, Brian MacKinnon, Scott Human performance data collected in a virtual environment |
title | Human performance data collected in a virtual environment |
title_full | Human performance data collected in a virtual environment |
title_fullStr | Human performance data collected in a virtual environment |
title_full_unstemmed | Human performance data collected in a virtual environment |
title_short | Human performance data collected in a virtual environment |
title_sort | human performance data collected in a virtual environment |
topic | Social Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633156/ https://www.ncbi.nlm.nih.gov/pubmed/29021999 http://dx.doi.org/10.1016/j.dib.2017.09.029 |
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