Literature DB >> 8244409

Experimental evaluation of a model of mental workload.

P A Hancock1, J K Caird.   

Abstract

This study was designed to test predictions from a model of mental workload. The model predicts that mental workload grows as perceived distance from a task goal increases and the effective time for action decreases. Decreases in workload can be achieved by actions that bring the task goal into the region of acceptable time/distance constraints for successful resolution. We reported an experiment that tested these assertions using the Timepools performance task. Timepools generates a spatial representation of a shrinking temporal target to assess the effects of path length (i.e., the number of sequential targets to be acquired) and shrink rate (i.e., elapsed time during which the circle is halved in area) on reaction time (RT), movement time (MT), error rate, and the subjective perception of workload. Data from the experiment indicated systematic effects for task-related factors across performance and workload measures. Path length and shrink rate had differential effects on both RT and MT, which were also reflected in the components of the individual workload scales. The results support a general form of the workload model which may help researchers and practitioners in the difficult task of workload prediction.

Mesh:

Year:  1993        PMID: 8244409     DOI: 10.1177/001872089303500303

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  4 in total

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Authors:  Luca Longo; Christoper D Wickens; Gabriella Hancock; Peter A Hancock
Journal:  Front Psychol       Date:  2022-06-02

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Authors:  Stéphane Perrey
Journal:  Sports (Basel)       Date:  2022-04-08

3.  Multi-Scale Heart Beat Entropy Measures for Mental Workload Assessment of Ambulant Users.

Authors:  Abhishek Tiwari; Isabela Albuquerque; Mark Parent; Jean-François Gagnon; Daniel Lafond; Sébastien Tremblay; Tiago H Falk
Journal:  Entropy (Basel)       Date:  2019-08-10       Impact factor: 2.524

4.  Applications of EEG indices for the quantification of human cognitive performance: A systematic review and bibliometric analysis.

Authors:  Lina Elsherif Ismail; Waldemar Karwowski
Journal:  PLoS One       Date:  2020-12-04       Impact factor: 3.240

  4 in total

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