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Generalizability of Mental Workload Prediction Using VACP Scales in Different Fields

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Engineering Psychology and Cognitive Ergonomics (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14017))

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Abstract

Mental workload prediction plays an important role in product design, work organization, task design and assignment in many fields since only with an appropriate mental workload level, could an operator maintain satisfactory task performance. The VACP method was developed for prediction of mental workload that would be induced by a task by calculating a sum score of four independent ratings from visual, auditory, cognitive and psychomotor dimensions, respectively, based on a table of workload component scales. This study aimed to explore the relationship between mental workload scores obtained by the VACP method and NASA-TLX subjective workload ratings, so as to explore the validity of the VACP method applied in different fields. The data with detailed experimental task description and NASA-TLX rating scores were collected from the existing publications, and the predicted mental workload scores were obtained by applying the VACP method for each task described in the publications. By correlation analysis, the results showed that there was a significant correlation between VACP scores and subjective workload ratings. According to the regression models between VACP scores and NASA-TLX ratings in different data groups, there was a significant linear correlation between VACP score and NASA-TLX ratings in most cases. The explicit model of VACP scores and NASA-TLX ratings would contribute to the control of mental workload for different domains and tasks in both product design and operation phases.

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Authors and Affiliations

  1. Department of Industrial Engineering, Tsinghua University, Beijing, China

    Yanrong Huang & Zhizhong Li

  2. Beijing Aerospace Control Center, Beijing, China

    Nanxi Zhang

Authors
  1. Yanrong Huang
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  2. Nanxi Zhang
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  3. Zhizhong Li
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Correspondence to Zhizhong Li .

Editor information

Editors and Affiliations

  1. Coventry University, Coventry, UK

    Don Harris

  2. Cranfield University, Cranfield, UK

    Wen-Chin Li

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Huang, Y., Zhang, N., Li, Z. (2023). Generalizability of Mental Workload Prediction Using VACP Scales in Different Fields. In: Harris, D., Li, WC. (eds) Engineering Psychology and Cognitive Ergonomics. HCII 2023. Lecture Notes in Computer Science(), vol 14017. Springer, Cham. https://doi.org/10.1007/978-3-031-35392-5_6

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  • DOI: https://doi.org/10.1007/978-3-031-35392-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35391-8

  • Online ISBN: 978-3-031-35392-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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