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Evaluating gender-based effectiveness within multi-attribute task battery studies
Adeyemi, Esther Omotola Bommer, Sharon
Adeyemi, Esther Omotola
Bommer, Sharon
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Issue Date
2024-06
Type
Article
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Keywords
USAARL multi-attribute task battery,Cognitive abilities,Gender differences,Performance,Human factor
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Citation
Adeyemi, E. O., & Bommer, S. (2024). Evaluating gender-based effectiveness within multi-attribute task battery studies. Journal of Management & Engineering Integration, 17(1), 1-9. https://doi.org/10.62704/10057/28080
Abstract
The prevalent notion that females outperform males in multitasking is challenged by scrutinizing the cognitive abilities of each gender across various demand scenarios (Buser & Peter, 2012; Lui et al., 2020; Szameitat et al., 2015). Investigating cognitive performance at two levels of workload defined as high- and low-demand situations, this research delves into task-specific variations, cognitive strategies, and adaptability to multitasking challenges. Sixty participants in total, with thirty participants in each gender group, engaged in tasks encompassing resource management, tracking, monitoring, and communication using the U.S. Army Aeromedical Research Laboratory's Multi- Attribute Task Battery simulation software. Statistical variance analysis demonstrated notable task discrepancies across different difficulty levels (DL). However, the gender-based analysis indicated non-significant differences in given tasks, except communication tasks. Findings indicate that men tend to perform well in tasks requiring communication and target tracking, benefiting from auditory cues, while women excel in fuel management, displaying strong decision-making abilities. In assessments of visual and spatial perception, females outperformed males at low difficulty levels, whereas males showed greater proficiency at high difficulty levels. This paper advocates for a balanced understanding and approach of cognitive abilities in diverse scenarios.
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Description
Published in SOAR: Shocker Open Access Repository by the Wichita State University Libraries Technical Services, July 2024.
Publisher
Association for Industry, Engineering and Management Systems (AIEMS)
Journal
Book Title
Series
Journal of Management & Engineering Integration
v.17 no.1
v.17 no.1
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Archival Collection
PubMed ID
ISSN
1939-7984