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

Maior, Horia, Wilson, M.L. and Sharples, S. (2018) Workload alerts-using physiological measures of mental workload to provide feedback during tasks. ACM Transactions on Computer-Human Interaction, 25 (2). ISSN 1073-0516

Full content URL: http://doi.org/10.1145/3173380

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Item Type:Article
Item Status:Live Archive

Abstract

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 article, 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.

Additional Information:cited By 4
Divisions:College of Science > School of Computer Science
ID Code:39505
Deposited On:17 Jan 2020 09:01

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