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

Fürstenau, Norbert und Radüntz, Thea und 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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Offizielle URL: https://doi.org/10.1080/1463922X.2020.1711990

Kurzfassung

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.

elib-URL des Eintrags:https://elib.dlr.de/134742/
Dokumentart:Zeitschriftenbeitrag
Titel:Model Based Development of a Mental Workload Sensitivity Index for Subject Clustering
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Fürstenau, NorbertNorbert.Fuerstenau (at) dlr.dehttps://orcid.org/0000-0003-4377-0032NICHT SPEZIFIZIERT
Radüntz, Thearaduentz.thea (at) baua.bund.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Mühlhausen, Thorstenthorsten.muehlhausen (at) dlr.dehttps://orcid.org/0000-0002-5901-7275NICHT SPEZIFIZIERT
Datum:25 Januar 2020
Erschienen in:Theoretical Issues in Ergonomics Science
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
DOI:10.1080/1463922X.2020.1711990
Verlag:Taylor & Francis
Name der Reihe:Taylor & Francis: Behavioral Science and Public Health Titles
ISSN:1463-922X
Status:veröffentlicht
Stichwörter:workload; resource limitation; sensitivity index; instantaneous self assessment; logistic model; validation; subject clustering
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Luftfahrt
HGF - Programmthema:Luftverkehrsmanagement und Flugbetrieb
DLR - Schwerpunkt:Luftfahrt
DLR - Forschungsgebiet:L AO - Air Traffic Management and Operation
DLR - Teilgebiet (Projekt, Vorhaben):L - Faktor Mensch und Sicherheit in der Luftfahrt (alt)
Standort: Braunschweig
Institute & Einrichtungen:Institut für Flugführung
Institut für Flugführung > Lotsenassistenz
Institut für Flugführung > ATM-Simulation
Hinterlegt von: Fürstenau, Dr.phil.nat. Norbert
Hinterlegt am:07 Jul 2020 09:13
Letzte Änderung:24 Okt 2023 11:25

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