Workload alerts - using physiological measures of mental workload to provide feedback during tasks

Feedback is valuable for allowing us to improve on tasks. While retrospective feedback can help us improve for next time, feedback “in action” can allow us to improve the outcome of on-going tasks. In this paper, we use data from functional Near InfraRed Spectroscopy to provide participants with fee...

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Main Authors: Maior, Horia A., Wilson, Max L., Sharples, Sarah
Format: Article
Language:English
English
Published: Association for Computing Machinery 2018
Subjects:
Online Access:https://eprints.nottingham.ac.uk/49196/
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author Maior, Horia A.
Wilson, Max L.
Sharples, Sarah
author_facet Maior, Horia A.
Wilson, Max L.
Sharples, Sarah
author_sort Maior, Horia A.
building Nottingham Research Data Repository
collection Online Access
description Feedback is valuable for allowing us to improve on tasks. While retrospective feedback can help us improve for next time, feedback “in action” can allow us to improve the outcome of on-going tasks. In this paper, we use data from functional Near InfraRed Spectroscopy to provide participants with feedback about their Mental Workload levels during high-workload tasks. We evaluate the impact of this feedback on task performance and perceived task performance, in comparison to industry standard mid-task self assessments, and explore participants’ perceptions of this feedback. In line with previous work, we confirm that deploying self-reporting methods affect both perceived and actual performance. Conversely, we conclude that our objective concurrent feedback correlated more closely with task demand, supported reflection in action, and did not negatively affect performance. Future work, however, should focus on the design of this feedback and the potential behaviour changes that will result.
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spelling nottingham-491962018-06-10T14:07:32Z https://eprints.nottingham.ac.uk/49196/ Workload alerts - using physiological measures of mental workload to provide feedback during tasks Maior, Horia A. Wilson, Max L. Sharples, Sarah Feedback is valuable for allowing us to improve on tasks. While retrospective feedback can help us improve for next time, feedback “in action” can allow us to improve the outcome of on-going tasks. In this paper, we use data from functional Near InfraRed Spectroscopy to provide participants with feedback about their Mental Workload levels during high-workload tasks. We evaluate the impact of this feedback on task performance and perceived task performance, in comparison to industry standard mid-task self assessments, and explore participants’ perceptions of this feedback. In line with previous work, we confirm that deploying self-reporting methods affect both perceived and actual performance. Conversely, we conclude that our objective concurrent feedback correlated more closely with task demand, supported reflection in action, and did not negatively affect performance. Future work, however, should focus on the design of this feedback and the potential behaviour changes that will result. Association for Computing Machinery 2018-04-16 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/49196/8/a9-maior.pdf application/pdf en https://eprints.nottingham.ac.uk/49196/1/Feedback.pdf Maior, Horia A., Wilson, Max L. and Sharples, Sarah (2018) Workload alerts - using physiological measures of mental workload to provide feedback during tasks. ACM Transactions on Computer-Human Interaction, 25 (2). 9:1-9:30. ISSN 1557-7325 Mental Workload FNIRS Physiological computing Feedback Task Demand Performance Bio-feedback of Workload https://dl.acm.org/citation.cfm?doid=3200181.3173380 doi:10.1145/3173380 doi:10.1145/3173380
spellingShingle Mental Workload
FNIRS
Physiological computing
Feedback
Task Demand
Performance
Bio-feedback of Workload
Maior, Horia A.
Wilson, Max L.
Sharples, Sarah
Workload alerts - using physiological measures of mental workload to provide feedback during tasks
title Workload alerts - using physiological measures of mental workload to provide feedback during tasks
title_full Workload alerts - using physiological measures of mental workload to provide feedback during tasks
title_fullStr Workload alerts - using physiological measures of mental workload to provide feedback during tasks
title_full_unstemmed Workload alerts - using physiological measures of mental workload to provide feedback during tasks
title_short Workload alerts - using physiological measures of mental workload to provide feedback during tasks
title_sort workload alerts - using physiological measures of mental workload to provide feedback during tasks
topic Mental Workload
FNIRS
Physiological computing
Feedback
Task Demand
Performance
Bio-feedback of Workload
url https://eprints.nottingham.ac.uk/49196/
https://eprints.nottingham.ac.uk/49196/
https://eprints.nottingham.ac.uk/49196/