Mental Workload

Hancock, Gabriella M.; Longo, Luca; Young, Mark S.; Hancock, Peter A.

doi:10.1002/9781119636113.ch7

Cited by 36 publications

(21 citation statements)

References 138 publications

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“…It is widely understood that there are three main classes of measures of mental workload: self-report measures, physiological (and neurophysiological) measures, and primary task performance measures. A number of systematic reviews have been already published in this space, including (Kramer, 1991 ; Cain, 2007 ; Morris et al, 2007 ; Whelan, 2007 ; Antonenko et al, 2010 ; Byrne, 2011 ; Lean and Shan, 2012 ; Marquart et al, 2015 ; Young et al, 2015 ; Butmee et al, 2018 ; Orru and Longo, 2018 ; Charles and Nixon, 2019 ; Tao et al, 2019 ; Hancock et al, 2021 ; Marchand et al, 2021 ; Pagnotta et al, 2021 ). Therefore, conducting a new systematic review for mental workload measures not only is not feasible, but unnecessary.…”

Section: Measuring Mental Workloadmentioning

confidence: 99%

Human Mental Workload: A Survey and a Novel Inclusive Definition

et al. 2022

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Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics. Uncertainties exist in its characterization, motivating the design and development of computational models, thus recently and actively receiving support from the discipline of Computer Science. However, its role in human performance prediction is assured. This work is aimed at providing a synthesis of the current state of the art in human mental workload assessment through considerations, definitions, measurement techniques as well as applications, Findings suggest that, despite an increasing number of associated research works, a single, reliable and generally applicable framework for mental workload research does not yet appear fully established. One reason for this gap is the existence of a wide swath of operational definitions, built upon different theoretical assumptions which are rarely examined collectively. A second reason is that the three main classes of measures, which are self-report, task performance, and physiological indices, have been used in isolation or in pairs, but more rarely in conjunction all together. Multiple definitions complement each another and we propose a novel inclusive definition of mental workload to support the next generation of empirical-based research. Similarly, by comprehensively employing physiological, task-performance, and self-report measures, more robust assessments of mental workload can be achieved.

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Section: Measuring Mental Workloadmentioning

confidence: 99%

Human Mental Workload: A Survey and a Novel Inclusive Definition

et al. 2022

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“…More specifically, we refer to notions that like aspects of cognitive load, the term mental workload has similarly been used to investigate and thus describe cognitive demands of a task too (Miyake, 2001 ). Thus, as previously mentioned, the difference between mental workload and cognitive load appears to pertain to the use of mental effort and related processes, which could extend more greatly onto the use of intrinsic or germane load, given cognitive load theory publications appear to more readily incorporate those terms (Orru and Longo, 2019 ) when compared to others that focus solely on task demands alone (Hancock et al, 2021 ). On the other hand, other literature has suggested that cognitive load and mental workload are the same construct (Naismith et al, 2019 ).…”

Section: Related Workmentioning

confidence: 98%

Investigating Cognitive Load in Energy Network Control Rooms: Recommendations for Future Designs

et al. 2022

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This study analyzed and explored the cognitive load of Australian energy market operators managing one of the longest inter-connected electrical networks in the world. Each operator uses a workstation with seven screens in an active control room environment, with a large coordination screen to show information and enable collaboration between different control centers. Cognitive load was assessed during both training scenarios and regular control room operations via the integration of subjective and physiological measures. Eye-tracking glasses were also used to analyze the operators gaze behavior. Our results indicate that different events (normal or unexpected), different participants for the same session, and different periods of one session all have varying degrees of cognitive load. The system design was observed to be inefficient in some situations and to have an adverse affect on cognitive load. In critical situations for instance, operator collaboration was high and the coordination screen was used heavily when collaborating between two control centers, yet integration with the system could be improved. Eye tracking data analysis showed that the layout of applications across the seven screens was not optimal for many tasks. Improved layout strategies, potential combination of applications, redesigning of certain applications, and linked views are all recommended for further exploration in addition to improved integration of procedures and linking alarms to visual cues.

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“…Eine Übersicht weit verbreiteter physiologischer Messverfahren findet sich beispielsweise bei Hancock et al. ( 2021 ).…”

Section: Hintergrundunclassified

Design and validation of a computer-based task for the induction of a mental workload spectrum

et al. 2022

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ZusammenfassungIm Rahmen des vom BMBF geförderten Projekts Fahrerkabine 4.0 wird eine adaptive Mensch-Maschine-Schnittstelle für Landmaschinen entwickelt, die das aktuelle Beanspruchungslevel mit Hilfe physiologischer Daten detektiert. Zu diesem Zwecke wird in dieser Arbeit eine Experimentalaufgabe entwickelt und evaluiert, die ein psychisches Belastungsspektrum von wenig bis sehr stark anstrengend in Versuchspersonen induzieren kann. In drei Laborstudien wird psychische Belastung mit einer Überwachungstätigkeit erzeugt, deren Bearbeitungsgeschwindigkeit randomisiert variiert. Die Komplexität der Tätigkeit wird abschnittsweise durch eine visuelle und/oder eine auditive Nebenaufgabe erhöht. Von den Versuchspersonen empfundene psychische Beanspruchung wird mit Hilfe der Rating Scale Mental Effort, der Reaktionszeiten und der Fehlerrate bewertet. Die Studien mit jeweils N = 17, N = 8 bzw. N = 21 Probanden zeigen, dass eine dynamische Kombination von Haupt- und Nebenaufgaben signifikant unterschiedliche Belastungsgrade induzieren kann (F (2,40) = 54.834, p < 0,001).Praktische Relevanz: Mithilfe der entwickelten Experimentalaufgabe wird in zukünftigen Arbeiten ein Messsystem zur Klassifizierung psychischer Beanspruchungszustände für Landmaschinen entworfen und erprobt. In beanspruchungsarmen Situationen (z. B. automatisierte Ernte) sollen zusätzliche Handlungsempfehlungen vorgeschlagen werden. Während stark beanspruchenden Abschnitten soll eine Überforderung der Nutzenden vermieden werden, indem lediglich die für die Durchführung der Arbeitstätigkeit notwendigen Informationen angezeigt werden.

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Mental Workload

Cited by 36 publications

References 138 publications

Human Mental Workload: A Survey and a Novel Inclusive Definition

Human Mental Workload: A Survey and a Novel Inclusive Definition

Investigating Cognitive Load in Energy Network Control Rooms: Recommendations for Future Designs

Design and validation of a computer-based task for the induction of a mental workload spectrum

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