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Model Based Development of a Mental Workload Sensitivity Index for Subject Clustering

Fürstenau, Norbert and Radüntz, Thea and Mühlhausen, Thorsten (2020) Model Based Development of a Mental Workload Sensitivity Index for Subject Clustering. Theoretical Issues in Ergonomics Science. Taylor & Francis. doi: 10.1080/1463922X.2020.1711990. ISSN 1463-922X.

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Official URL: https://doi.org/10.1080/1463922X.2020.1711990


Considering individual differences in personality, personal characteristics, or abilities is common praxis in several areas of research. The clustering of subjects related to individual variables is particularly important in order to value identified content, recognize relationships, analyse and derive complex concepts as well as improve our understanding of potential issues. In this context, the concept of mental workload comprises a number of individual characteristics but is rarely used for subject clustering. In our article, we introduce an approach for the calculation of a workload-sensitivity index that can be used for such purpose. We present a two-parametric logistic model that predicts workload (WL) sensitivity parameters for sample means across participants. Together with a linear approximation it provides estimates for individuals. Thereby it takes into account cognitive resource limitation and the specific scale limits of WL-metrics as well as domain expert knowledge as prior information. Experimental evidence is provided by means of a human-in-the-loop simulation experiment with 21 air traffic controllers through measuring of the WL-effects under eight different task load levels (scenarios) realized by traffic flow n (aircraft/hour) and a non-nominal event using subjective Instanteneous Self Assessment (ISA) metrics. We analyse the ISA measures and show that the theoretically predicted ISA vs. n characteristic exhibits surprisingly good agreement with the experimental parameter estimates when based on the ISA scenario averages despite large inter-individual variance. To sum up, our model based subject clustering allows for defining subgroups of different WL-sensitivity based on a single dimensionless sensitivity index.

Item URL in elib:https://elib.dlr.de/134742/
Document Type:Article
Title:Model Based Development of a Mental Workload Sensitivity Index for Subject Clustering
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Fürstenau, NorbertUNSPECIFIEDhttps://orcid.org/0000-0003-4377-0032UNSPECIFIED
Mühlhausen, ThorstenUNSPECIFIEDhttps://orcid.org/0000-0002-5901-7275UNSPECIFIED
Date:25 January 2020
Journal or Publication Title:Theoretical Issues in Ergonomics Science
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
Publisher:Taylor & Francis
Series Name:Taylor & Francis: Behavioral Science and Public Health Titles
Keywords:workload; resource limitation; sensitivity index; instantaneous self assessment; logistic model; validation; subject clustering
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Human factors and safety in Aeronautics (old)
Location: Braunschweig
Institutes and Institutions:Institute of Flight Guidance
Institute of Flight Guidance > Controller Assistance
Institute of Flight Guidance > ATM-Simulation
Deposited By: Fürstenau, Dr.phil.nat. Norbert
Deposited On:07 Jul 2020 09:13
Last Modified:24 Oct 2023 11:25

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