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

Maior, Horia A. and Wilson, Max L. and Sharples, Sarah (2017) Workload alerts - using physiological measures of mental workload to provide feedback during tasks. ACM Transactions on Computer-Human Interaction, 1 (1). ISSN 1557-7325 (In Press)

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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.

Item Type: Article
Keywords: Mental Workload, FNIRS, Physiological computing, Feedback, Task Demand, Performance, Bio-feedback of Workload
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: 10.1145/3173380
Related URLs:
Depositing User: Maior, Horia
Date Deposited: 22 Jan 2018 10:46
Last Modified: 22 Feb 2018 18:32

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