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THE EFFECT OF TIME PRESSURE ON THE PERFORMANCE OF DEXTEROUS OPERATIONS

Part of: Human Behaviour and Design

Published online by Cambridge University Press:  11 June 2020

M. Pooripanyakun ,
A. Wodehouse  and
J. Mehnen
M. Pooripanyakun*
Affiliation:
University of Strathclyde, United Kingdom
A. Wodehouse
Affiliation:
University of Strathclyde, United Kingdom
J. Mehnen
Affiliation:
University of Strathclyde, United Kingdom
*
*[email protected]

Abstract

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This study explores the effects of time pressure in dexterous operations on two types of interface: the fixed interface and the moving interface. Results show that the accuracy of finger movement is decreased, the information processing on the sense of sequence, position and direction is worsened by the psychological disturbance. The findings indicate that a fixed interface is more robust to performance and participants can learn and perform tasks quicker than a moving interface. Finally, the researchers give some practices on both fixed and moving interface design.

Keywords

design cognitionperformance indicatorsdesign guidelines
Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 1521 - 1530
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2020. Published by Cambridge University Press

References

Bakker, S. et al. (2016), “Introduction: Framing Peripheral Interaction”, In: Bakker, S. (Ed.), Peripheral Interaction, Human–Computer Interaction Series, Springer, Switzerland, pp. 1–10. https://doi.org/10.1007/978-3-319-29523-7_1CrossRefGoogle Scholar
Csikszentmihalyi, M. (1997), Finding flow: the psychology of engagement with everyday life, Basic Books, New York.Google Scholar
Ehrlich, K. (1996), “Applied mental models in human-computer interaction”, In: Johnson-Laird, P.N., Oakhill, J. and Garnham, A. (Eds.), Mental models in cognitive science, Psychology Press, East Sussex, pp. 223–245.Google Scholar
Hong, J.C. et al. (2012), “Effects of cognitive style on digital jigsaw puzzle performance: A GridWare analysis”, Computers in Human Behavior, Vol. 28 No. 3, pp. 920–928. https://doi.org/10.1016/j.chb.2011.12.012CrossRefGoogle Scholar
Hughes, L.E. and Babski-Reeves, K. (2005), “Time pressure and mental workload effects on perceived workload and key strike force during typing”, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, SAGE, Los Angeles, CA, pp. 1390–1394. https://doi.org/10.1177/154193120504901427Google Scholar
Illera, C. et al. (2010), “NO_PANIC. “Escape and Panic in Buildings”—Architectural Basic Research in the Context of Security and Safety Research”, In: Klingsch, W., Rogsch, C., Schadschneider, A. and Schreckenberg, M. (Eds.), Pedestrian and Evacuation Dynamics 2008, Springer, Berlin, Heidelberg, pp. 733–742. https://doi.org/10.1007/978-3-642-04504-2_71CrossRefGoogle Scholar
Norman, D.A. (1983), “Some observations on mental models”, In: Gentner, D. and Stevens, A. (Eds.), Mental models, Lawrence Erlbaum Associates, New Jersey, pp. 7–14.Google Scholar
Norman, D.A. (1984), “Stages and levels in human-machine interaction”, International Journal of Man-Machine Studies, Vol. 21 No. 4, pp. 365–375. https://doi.org/10.1016/S0020-7373(84)80054-1CrossRefGoogle Scholar
Probst, K. et al. (2016), “Peripheral interaction in desktop computing: why it's worth stepping beyond traditional mouse and keyboard”, In: Bakker, S. (Ed.), Peripheral Interaction, Human–Computer Interaction Series, Springer, Switzerland, pp. 183–205. https://doi.org/10.1007/978-3-319-29523-7_9Google Scholar
Proctor, R.W. and Vu, K.L. (2016), “Principles for Designing Interfaces Compatible with Human Information Processing”, International Journal of Human-Computer Interaction, Vol. 32 No. 1, pp. 2–22. https://doi.org/10.1080/10447318.2016.1105009CrossRefGoogle Scholar
Rasmussen, J. and Vicente, K.J. (1989), “Coping with human errors through system design: implications for ecological interface design”, International Journal of Man-Machine Studies, Vol. 31 No. 5, pp. 517–534. https://doi.org/10.1016/0020-7373(89)90014-XCrossRefGoogle Scholar
Richardson, J.T. and Vecchi, T. (2002), “A jigsaw-puzzle imagery task for assessing active visuospatial processes in old and young people”, Behavior Research Methods, Instruments, & Computers: A Journal of the Psychonomic Society, Vol. 34 No. 1, pp. 69–82.10.3758/BF03195425CrossRefGoogle ScholarPubMed
Wu, L. et al. (2016), “Influence of information overload on operator's user experience of human–machine interface in LED manufacturing systems”, Cognition, Technology & Work, Vol. 18 No. 1, pp. 161–173. https://doi.org/10.1007/s10111-015-0352-0CrossRefGoogle Scholar
Young, M.S. et al. (2015), “State of science: mental workload in ergonomics”, Ergonomics, Vol. 58 No. 1, pp. 1–17. https://doi.org/10.1080/00140139.2014.956151CrossRefGoogle ScholarPubMed
Young, R.M. (1983), “Surrogates and Mappings: Two kinds of conceptual models for interactive devices”, In: Gentner, D. and Stevens, A. (Eds.), Mental models, Lawrence Erlbaum Associates, New Jersey, pp. 35–52.Google Scholar
Zeidner, M. and Matthews, G. (2011), Anxiety 101, Springer Pub. Co, New York.Google Scholar